Volume 16, Issue 2

ollision C

Volume 16 Issue 2

The International Compendium for Crash Research

Crash Data & Images Available After Automotive Repair with Airbag Control Module Replacement

Crashology Impact Severity

CRASHCON22

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The Lost Energy

of Planar Impact Mechanics

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Contents

Volume 16 Issue 2

inside 3

Content Information

4

Letter from the Editor

5

Collision Magazine Info and Advertiser Index

12

features 6

Crash·ol·o·gy - Impact Severity: A function of vehicle closing speed or vehicle impact speed (ground speed)?

by Wesley Vandiver, Robert Anderson, Michelle Hoffman, David Hallman, Billy Cox

12

50

CRASHCON22: The Value of In-Person Conferences and Live Crash Testing

by Billy Cox and Robert Anderson

38

Vehicles, VIN's, Certification Labels, and parts What “Model Year” is it??

by Daniel W. Vomhof III

46

My Turn At The Wheel: What Is "30" How And Why Should We Use It?

66

by Richard C. Rinker

50

Nissan Automobile EDR Recording Characteristics

by David M. Hallman, Billy S. Cox, Jr., Robert D. Anderson

66

The Lost Energy of Planar Impact Mechanics

82

Utilizing EDR Data To Determine The Effects Of Hard Braking On Delta-V Calculations In Low-To-Moderate Speed Impacts

by Micky Marine

92

by Shannon Crowley, Camila Marrero Torres, Alex Kazmierczak, Christopher J. Furbish and Bryan Randles and Justin Brink

92

Crash Data and Images Available After Automotive Repair with Airbag Control Module Replacement

by Robert Anderson www.collisionpublishing.com

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letter from the editor As another year comes to a close we finish Volume 16 of Collision Magazine full of original work by a number of authors. We also bring to a close the current ownership of Collision Magazine (a very difficult and emotional decision). Due to the expansion of Crash Data Group being a distributor for Bosch, GIT and Tesla (and those EDR brands expanding), along with the new YouTube Series EDR Tech (see below) we simply can't give Collision Magazine the attention it deserves. Beginning with the next issue, Volume 17, Issue 1, Collision Magazine will be under new ownership.

Be assured Crash Data Group is working closely with this new company to make this transition seemless. We will also be working together to disseminate crash research in various media outlets.

Back to this issue. One aspect is the addition of crash testing data and information which is planned to continue into future issues going forward. Being able to share crash test data from researchers looking into cutting edge issues and topics is what made Collision unique when we started and something we’re planning to continue in future issues.

While on the subject of taking advantage of new technology, last August Crash Data Group launched a new monthly video series on their YouTube Channel named "EDR Tech". Each month a new EDR Tech video is released and is free to watch on the CDG YouTube Channel.

In this issue, there is a short article about Toyota Techstream data which ties into a more complete explanation of Toyota Techstream Vehicle Control

History data, which can be seen on Crash Data Group’s YouTube channel as “EDR Tech Edition 4: Toyota Techstream Vehicle Control History Data” with guest speaker, David Hallman. https://www.youtube.com/@crashdatagroup There are other presentations with Q&A including “Understanding the CDR Tool Vehicle and Cable Lookup,” a look at the CDR 500 adapter, an overview of the Hyundai and Kia CDR Tool and a new cable release video. The last one, of course, raises the issue of cables not being available from Bosch…yet. Be assured Bosch is working on the release of additional cables and are hopeful that the backlog of cables not yet released will break loose and we will see some of the most recent cables released in the next couple quarters.

And while we’re being hopeful for the coming year, plans are in the works for the return of the EDR Summit at a new location mid-year 2023.

The company taking the reigns of Collision Magazine will also be running the EDR Summit going forward. Stay tuned for more details as plans and speakers are finalized. Current potential topics include a deep dive into the GM Front Camera Module with case problem examples, An in-depth look at Tesla CAN Bus data with an explanation of element translations and applications, and, of course, more on the growing application of Toyota Techstream data, as well as other topics.

So, a lot going on in the EDR world. It has been a highlight of my life running Collision Magazine for the past 16 years along with the ARC-CSI Crash Conferences and EDR Summits. During that time we have seen an incredible evolution of the EDR technology and what it means to crash investigation. I am excited to see what the EDR future brings.

Scott Baker Managing Editor

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ADVERTISER INDEX

Crash Data Group Inc PO Box 892885, Temecula, CA 92589 Toll Free: 800-280-7940 E-mail: sbaker@crashdatagroup.com www.collisionmagazine.com ISSN: 1934-8681

COLLISION STAFF Scott Baker Sean Haight Tonya Baker

Owner, Managing Editor Senior Editor Advertising Manager

4N6XPRT Systems Bosch CDR Tool (CDG) Collision Magazine Collision Safety Institute (CSI) Crash Hub Engineering Dynamics GIT EDR Tools (CDG) Leica Geosystems Lightpoint Tesla Virtual Crash We Buy Key Fobs

PAGE Inside Back Cover 96 76 91 80-81 Inside Front Cover Back Cover 2 1 45 65 37

SUBMIT AN ARTICLE If you would like to submit an article to be published in Collision please use the following link:

www.collisionmagazine.com/submit BACK ISSUES All back issues of Collision Magazine are now available in digital format - please visit:

https://crashdatagroup.com/collections/ collision-magazine-back-issues All rights reserved, © 2022 Crash Data Group Inc. The opinions and conclusions expressed in this publication and any associated data and throughout the articles attributed to specific authors are the opinions and conclusions of the authors noted and not necessarily the editorial staff or anyone else for that matter. While some articles have been reviewed for content, the accuracy of reprinted models or equations cannot be fully guaranteed. It is the responsibility of the reader to apply critical thinking to an individual review of the content and make their own personal judgements as to its value to them, individually.

At the end of the day, facts belong to everybody, any other opinions to us. The distinction is yours to draw...otherwise, the opinions expressed herein are not necessarily those of any employer, not necessarily ours and probably not necessary.

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crash·ol·o·gy THE SCIENCE OF CRASHES Wesley Vandiver

Robert Anderson

Collision Forensics

Michelle Hoffman Forensic Injury Analysis

Biomechanics Analysis

David Hallman Hallman Engineering

Billy Cox

Billy Cox Group

Impact Severity: A function of vehicle closing speed or vehicle impact speed (ground speed)?

A

persistent misconception in vehicle crash analyses is that collision severity and injury potential are related to a vehicle’s ground speed at impact rather than to its closing speed and the Delta V experienced. That is, claims are often made that if a struck vehicle has a higher impact speed (over-the-ground speed) at impact, this inherently means that it experiences a more severe impact. Actually, impact severity is related to a vehicle’s change in velocity (Delta V) during the impact, which is a function of its closing speed, which may or may not be equal to its impact speed (ground speed).

This misconception was described by Schmidt, et al., (1998), who surveyed practicing reconstructionists at a crash conference and received several different misconceived explanations from the respondents with widely varying backgrounds, education and training. [1] Schmidt, et al., found that the given reasons for this misconception varied, but two reasons predominated, “the absolute energy notion” and the “absolute momentum notion” (Schmidt, 1998). A theoretical analysis of the fundamental physics as to why these two notions are incorrect can be found in the paper by Schmidt, et al.

An example of this misconception would be the thinking that during a vehicle-to-vehicle rear-end impact: if the struck vehicle is traveling at some speed, rather than stationary at impact, then it somehow experiences a more severe impact. That is, if Vehicle A was traveling 20 mph and was struck from behind by Vehicle B traveling 30 mph (closing speed of 10 mph), some have the misconception

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that this impact would be more severe than if Vehicle A was stationary and struck by Vehicle B traveling 10 mph (closing speed of 10 mph).

An analogy to demonstrate this principle follows. Person A is on a jet airplane that is flying at 400 mph relative to the earth’s surface. They walk down the aisle of the airplane at 2 mph and accidentally bump into Person B, who is standing in the aisle of the airplane. Relative to the earth’s surface, Person A is traveling 402 mph and Person B is traveling 400 mph. Is this impact more severe for either party than if Person B was standing on the earth’s surface and Person A walked into him/her at 2 mph? The answer is no. The severity is the same in both scenarios, because it is the speed of the people relative to each other, not their speed relative to the earth’s surface that is important.

This principle was also demonstrated with crash testing conducted at the 2022 SATAI Crash Conference. A series of two tests were performed. In Test 1, a 2007 Chevrolet Impala (silver) was traveling 34 mph when it impacted the back of a 2006 Chevrolet Impala (white) that was traveling 21 mph. In Test 2, the 2007 Impala was stationary when it was struck from behind by the 2006 Impala that was traveling 13 mph. Thus, even though the bullet vehicle was traveling 34 mph in Test 1 and only 13 mph in Test 2, the closing speed in both tests was 13 mph.

Both vehicles were instrumented with accelerometers. In addition to the accelerations and Delta Vs of each vehicle, impact speeds were measured using Racelogic VBOX

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Impact Speed mph TEST 1 BULLET - 2007 silver Impala (vehicle #4) TARGET - 2006 white Impala (vehicle #3) TEST 2 BULLET - 2006 white Impala (vehicle #3) TARGET - 2007 silver Impala (vehicle #4)

Closing Speed mph 13

Delta V mph

34 21

-7.8 7.7 13

13 0

-10 7.6

Table 1: Vehicle ground speeds, closing speeds and Delta Vs for Tests 1 and 2. equipment. As seen in Table 1, the impact speed relative to the ground for the bullet vehicle was 34 mph in Test 1 and 13 mph in Test 2, yet the closing velocity between the vehicles was 13 mph in each test. It is also clear from Table 1 that the Delta V experienced by the target vehicle in Test 1 (7.7 mph) was equal to the Delta V experienced by the target vehicle in Test 2 (7.6 mph).

The bullet vehicle’s Delta V in Test 2 (-10mph) was 2.2 mph greater than the bullet vehicle’s Delta V in Test 1 (-7.8 mph). This is attributed to braking of the bullet vehicle during impact in Test 2. As discussed in the previous Crashology article, “Event Data Recorder Delta V: The Effect of Tire Friction,” bullet vehicle braking can inflate the measured Delta V of the bullet vehicle. [2] Figure 2 shows the Delta Vs of the bullet vehicles for Tests 1 and 2.

BULLET – Driver TARGET – Driver

Age Years 62 55

Still images from video of the vehicles at maximum engagement during impact for Test 1 and Test 2 are shown below in Figures 3 and 4, respectively.

These still images demonstrate that the dynamic crush of the bullet vehicle at maximum engagement is very similar.

The bullet vehicle demonstrates slightly more dynamic deflection of the lower bumper cover during Test 2 than in Test 1; however, there was no noticeable difference in the static residual deformation after the collisions.

A single human volunteer served as the driver of the target vehicle in each test, while a second human volunteer served as the driver of the bullet vehicle for each test. The magnitude of the impacts was controlled to be within the established tolerable range for volunteers. Information on the volunteers is shown below in Table 2.

Gender M M

Height Inches 73 67

Sitting Height Inches 36 36

Weight Pounds 230 200

Table 2: Information on human volunteer drivers.

Peak Head Accel Peak Thorax Accel Peak Lumbar Accel Shoulder Belt Load Lap Belt Load g's g's g's lbsf lbfs TEST 1 BULLET - Driver TARGET - Driver TEST 2 BULLET - Driver TARGET - Driver

4.8 9.0

6.0 7.1

8.9 5.4

275.5 87.4

29.2

6.3 11.6

8.3 9.3

8.5 6.9

319.4 84.1

34.7

Table 3: Volunteer driver experienced accelerations and seat belt loads. www.collisionpublishing.com

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Figure 1: The Delta V of the target vehicle in Test 1 is almost identical to the target vehicle Delta V in Test 2.

Figure 2: The Delta V of the bullet vehicle in Test 2 is slightly greater than Test 1 from braking during impact in Test 2.

Both volunteers were instrumented with head, thorax and lumbar accelerometers. Seat belt load cells were used to measure the shoulder belt loads for each driver and the lap belt load for the target driver. Table 3 below includes the peak resultant head, thorax and lumbar loads for the volunteer drivers in each test, as well as their seat belt loads.

It is clear from viewing the data in Table 3 above that the head, thorax and lumbar accelerations, as well as the lap and shoulder belt loads for the target vehicles’ driver 8 Collision Magazine - Volume 16 Issue 2

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were very similar between Tests 1 and 2. Likewise, Table 3 shows these values were also similar for the bullet driver between Test 1 and Test 2.

The similarity of these values for the target vehicles’ driver is further demonstrated in Figures 5-9 below, which show the target driver’s head acceleration (Figure 5), thorax acceleration (Figure 6), lumbar acceleration (Figure 7), shoulder belt loads (Figure 8), and lap belt loads (Figure 9) in Tests 1 and 2.

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Figure 3: Still image of vehicles at maximum engagement during Test 1.

Figure 4: Still image of vehicles at maximum engagement during Test 2.

Figure 5: Target driver head accelerations for Tests 1 and 2. www.collisionpublishing.com

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The vehicle damage and the vehicle and occupant data from this test series demonstrate that in terms of vehicle damage and impact severity, Test 1 and Test 2 are indistinguishable. In other words, one cannot determine in which impact both vehicles were moving versus the one vehicle stopped impact by studying the vehicle accelerations, Delta V, vehicle damage, and/or the occupant kinematics.

Therefore, this test series serves as a demonstration of the principle that collision severity is a function of the closing speed between the vehicles, and not directly a function of

the speed of either vehicle relative to the ground at the time of impact.

References 1. Schmidt BF, Haight WR, Szabo TJ and Welcher JB, “System-Based Energy and Momentum Analysis of Collisions,” SAE#980026, Society of Automotive Engineers, 1998.

Figure 6: Target driver thorax accelerations for Tests 1 and 2.

Figure 7: Target driver lumbar accelerations for Tests 1 and 2.

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2.

Vandiver W and Anderson R, “Event Data Recorder Delta V: The effect of Tire Friction,” Crashology: The Science of Crashes, Collision: The International Compendium for Crash Research, 16(1):96-98, 2022.

Figure 8: Target driver shoulder belt loads for Tests 1 and 2.

Figure 9: Target driver lap belt loads for Tests 1 and 2.

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CRASHCON22:

The Value of In-Person Conferences and Live Billy S. Cox, Jr Crash Testing Billy Cox Group

I

f you’re like me, you are tired of the “Covid Emergency” that radically changed our travel habits and the way we did business over the last couple of years.

Shortly after the close of the EDR Summit in Houston in March of 2020, the world shut down. Perhaps the most obvious casualty was the in-person conference. While there have been a few in-person conferences with crash testing, i.e. SCARS 2021 and 2022 held in July in Charleston, SC, MATAI 2021 held in Des Moines, IA and SATAI 2022 held in Glendale, AZ in January 2022, they haven’t necessarily been well-attended.

Finally, we may have turned the corner on the moratorium on in-person training. One of the most obvious recent examples occurred in May 2022. The Barczyk Biomechanics Institute organized CrashCon22 in New Orleans, Louisiana that was attended by up to 150 people from a variety of professions. About two-thirds of the attendees represented the Reconstructionist and Biomechanists private sector and law enforcement communities and about one-third were members of the chiropractic community. The stated purpose of the conference was to “Help determine injury mechanism to scientifically support an objective causation opinion” and “understanding the injury mechanism and human tissue response.”

Robert “Bob” Anderson Biomechanics Analysis

chael Rosenfield and Daniel Vomhoff III, performed a series of twelve crash tests, with the first one going off at about 9:00 a.m. and the last at about 3:15 p.m. The test series made up ten low-speed tests with human volunteers, plus two remote driven high speed tests.

We also utilized two Anthropomorphic Test Devices (ATDs) in eleven of the tests. Overall, more than 70 channels of data were collected in each two vehicle collisions. More than 750 data channels were collected in 12 total tests. There were up to 12 video camera angles, plus drone video for each test and up to 70 photograph images.

This conference organizer David J. Barczyk, D.C., a practicing Louisiana chiropractor for 20 years. Dr. Barczyk has the distinction of being the only treating doctor in Louisiana that has been qualified to testify as an expert in motor vehicle crash biomechanics. While his training is somewhat novel, there is a trend for chiropractic practitioners to seek and obtain training in crash reconstruction.

Crash testing occurred on Friday. The team compiled all of the data on Saturday and presented the data to the attendees on Sunday before the close of the conference. Because of the short turnaround between testing and presentation and the volume of data collected, conference attendees were provided with a DropBox link to all processed data about seven days after the conference concluded.

The crash team consisting of Robert (Bob) Anderson, Christopher Furbish, David Hallman, Bryan Randles, Mi-

The vehicles we acquired to perform the tests are as follows:

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V1: 2007 Chevrolet Suburban, VIN# 3GNFC16JX7G305199 (EDR Support, D2M Cable 02003320 with Hitch). Weight as tested, 5580 lbs, plus occupant if applicable.

V2: 2004 Chevrolet Suburban, VIN# 3GNEC16Z04G135478 (EDR Support, D2M Cable 02003003, NO Hitch). Weight as tested, 5350 lbs, plus occupant if applicable.

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V3: 2014 Ford Focus, VIN# 1FADP3F22EL227516 (EDR Support, D2M Cable F00K108597). Weight as tested, 2890 lbs, plus occupant if applicable.

of muscle tone. Similarly, anthropomorphic dummies are designed to approximate human movement in potentially injurious impacts and to be durable in repeated high speed collisions, but they have been shown to be inappropriate for replicating human occupant motions in low speed collisions.

Currently, the adequacy and applicability of mathematical models to simulate occupant motions in low speed impacts have yet to be demonstrated. [1,2,3,4,5,6] As such, until there is sufficient improvement in the low speed performance of anthropomorphic dummies and/or mathematical models in replicating live human motion, actual live human subjects continue to be a desirable and appropriate form of surrogate for humans in low speed impacts.

V4: 2010 Nissan Altima, VIN# 1N4AL2APXAN473398 (No EDR Support). Weight as tested, 3120 lbs, plus occupant if applicable.

V5: 2014 Mazda 5 Sport, VIN# JM1CW2BL3E0169838 (EDR Support, D2M Cable F00K108778). Weight as tested, 3,480 lbs, plus occupant if applicable.

In the design, evaluation and improvement of automobile safety, the use of human surrogates, such as anthropomorphic dummies and cadavers, has over the years been and continues to be a valuable tool. However, in low speed collisions the utility of cadavers is limited due to their lack 14 Collision Magazine - Volume 16 Issue 2

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It is paramount that researchers ensure that live human exposures pose, at most, “minimal risk,” defined as, “the risk of harm anticipated in the proposed research are not greater, considering probability and magnitude, than those ordinarily encountered in daily life or during the performance of routine physical or psychological examination or tests.” [7,8] This is primarily accomplished by limiting the magnitude of the vehicle velocity change during the impact testing so that the body motions and forces are commensurate with those of everyday activities and events.

It is for this reason that the vast majority of human subject exposures to rear-end impacts has generally been limited to vehicle velocity changes of less than 11 mph, [9] with many conducted below 8 mph [10,11,12,13] lateral impacts have generally been limited to vehicle velocity changes of less than 10 mph [14,15,16] and frontal impacts have been generally limited to 20 mph vehicle velocity changes.

[17,18,19] For each volunteer, we obtained informed consent wherein each person was interviewed and told what to expect.

Each volunteer was informed they would be subjected to up to three crash exposures with increasing magnitude.

Each volunteer viewed a three minute video compilation showing rear and side impacts. For the rear impact video examples, speed changes ranged from 2.5 mph to 7.0 mph.

The lateral impact video examples had speed changes of 3.0 to 6.0 mph. All of our volunteer testing was at or below these thresholds.

Each volunteer was told they could opt out at any time, before, during or after any test. One female volunteer opted out after two rear impacts. One male volunteer declined to participate in lateral tests altogether after he observed our first few tests in person. The vital statistics on each volunteer is provided in Table One.

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Volunteer Test 1A-1C

Gender Female

Height 5’ 10”

Weight 150 lbs.

Test 1D-1F

Male

6’ 3”

214 lbs.

Test 3A and 3B

Female

5’ 4”

135 lbs.

Test 3C and 3D

Male

5’ 7”

168 lbs.

Age Notes 20 Prior left knee surgery. Reported transient posterior head tenderness after third test. Follow up after 24-hours, no symptoms.

24 No prior orthopedic surgeries. Follow up after 24-hours, no symptoms.

21 No prior orthopedic surgeries. Follow up after 24-hours, no symptoms.

24 No prior orthopedic surgeries. Follow up after 24-hours, “I’m doing well, thank you.”

Table 1: Statistics on each volunteer Data was collected using IST accelerometers and Diversified Technical Systems (DTS) TDAS Pro or SLICE data acquisition systems. DTS data acquisition systems and sensors set the standard for occupant safety, R&D, and Euro NCAP testing worldwide. We have used the TDAS and TDAS Pro systems in testing since 1997.

The vehicles were fitted with a tri-axial block of ICS 3031050 (50g) accelerometers screwed to the floor near the center of gravity. An angular rate sensor which measured the vehicle roll, pitch, and yaw was mounted on top of the accelerometer. Acceleration data was collected at 10,000 Hz. Vehicle acceleration data filtered with an SAE Class 180 filter. Vehicle changes in velocity were calculated by integrating the area under the acceleration curve. All axis systems were in accordance with SAE J211 recommended practice with the X, Y, and Z axes directed forward, to the right, and downward, respectively.

Each volunteer was fitted with a nine-channel head array consisting of three-axis accelerometer mounted on the right, left and front (See Figure 1).

Figure 1: Nine channel head array.

Each volunteer was also fitted with a triaxial accelerometer affixed at the sternal notch with two-sided adhesive (See Figure 2).

Figure 2: Accelerometer at sternal notch (thorax).

Finally, each volunteer was also fitted a triaxial accelerometer in the area of the L5-S1, plus an additional single axis accelerometer, oriented on the X-axis at about the L1-L2 level. The purpose of this additional accelerometer was to measure the acceleration of the lumbar spine at two levels and compare the data (See Figure 3).

Figure 3: Accelerometer at L5-S1 and location for L1-L2 accelerometer.

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All human subject data was sampled at 10,000 Hz. Head, thorax, and lumbar data acceleration was filtered with an SAE Class 1000 filter. Data analysis was limited to the sagittal plane, thus, only the longitudinal (x-axis) acceleration was analyzed. Peak amplitude and time to peak amplitude were determined for the crash pulse. The volunteers were subjected to changes in velocity ranging from 2.2 mph to 5.2 mph. These exposure levels are at or below those approved by various institutional review boards for previous research [McConnell 1993 [20], 1995 [21], Siegmund 1997 [22] and Kiefer 2005 [23]].

The crash tests were carried out according to plan, more or less. As is typical, when performing tests in a harsh environment (in this case, extreme heat and humidity) and when relying on electronic instrumentation, you have to be somewhat flexible.

Our first test series involved six tests. In the first three tests (Test 1A-1C), the V1-Suburban with a stiff bumper struck the rear of the V2-Suburban with a stiff bumper with the hitch assembly removed. There was a 20-year old female volunteer in the target vehicle and this test series went off without a hitch (see what I did there?). The closing speed was increased in order to observe the damage that resulted, changes in the collision duration and the biomechanical response. The volunteer experienced three exposures with increasing magnitude.

For the next three tests in this series (Test 1D-1F), the Suburban positions were switched. The V2-Suburban with a stiff bumper became the bullet vehicle and the V1-Suburban equipped with a rear hitch in place became the target.

This test series also went off as planned. Again, this was a three test series, with increasing speed in order to measure the damage that occurred, changes in the collision duration and the biomechanical response. A 24-year old male volunteer occupied the target vehicle and sat for three exposures, each with increasing magnitude.

Recording Characteristics Of The Event Data Recorders (Edr) We did not see a new EDR event after every test. In test 1A, the target V2-Suburban recorded a non-deployment event with an EDR-reported delta-V of zero. The delta-V of zero should not come as a surprise. GM vehicles of this vintage will only record a delta-V that is below zero, i.e., frontal collisions. Figure 4 shows the point where separation between the vehicles starts to occur.

Our measured closing speed was 3.2 mph. The instrument recorded delta-V for the bullet V1-Suburban was -2.5 mph. There was no EDR event for the bullet V1-Suburban. The instrumentation package on the V2-Suburban recorded delta-V was 2.24 mph at about 114 msec. Figure

Figure 4: Test 1A, EDR recorded delta-V of zero on the target vehicle.

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5 is the, ”System Status at Non-Deployment” for the target V2-Suburban showing a delta-V of zero.

In Test 1D, the bullet V2-Suburban recorded a frontal crash event. Our measured closing speed was 4.8 mph, while the “Vehicle Speed” of the bullet V2-Suburban was reported as 4.0 mph at -1.0 second. The EDR recorded delta-V was -2.6 mph, while the instrument recorded delta-V was -3.6 mph. The impact-induced delta-V for the

bullet vehicle was under reported. The ”System Status at Non-Deployment” for the bullet V2-Suburban (See Figure 6).

Notice that Test 1D data overwrote the Test1A data in the bullet V2-Suburban. A quick review of the “Data Limitations” explains the capabilities of the EDR in this vehicle.

“There are two types of Recorded crash events. The first is the Non-Deployment Event. A Non-Deployment Event re-

Figure 5: Non-deployment event for the target V2-Suburban, Test 1A.

Figure 6: EDR data from the V2-2004 Chevrolet Suburban, VIN# 3GNEC16Z04G135478 after Test 1D. www.collisionpublishing.com

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cords data but does not deploy the air bags(s).

It contains Pre-Crash and Crash data. The SDM can store up to one Non-Deployment Event. This event may be overwritten by another non-Deployment Event.”

In Test Two we planned a high-speed, GPS guided, two vehicle intersection collision. The V4-Nissan Altima and V5-2014 Mazda 5 Sport were selected for this test. Each vehicle was controlled by Phantom Driver, a remote control steering device that can be programmed with GPS coordinates to steer to a precise location (See Figure 8).

Both events occurred on the same key cycle (36,281) because we did not cycle the key after each test.

In the sixth test in this series (Test 1F), we set another EDR event. In this test, the bullet V2-Suburban recorded a frontal crash event, overwriting the data we obtained after Test 1D. The image of the EDR again occurred on key cycle 36,281.

As noted previously in the Data Limitations, “This event may be overwritten by another non-Deployment Event.”

Our measured closing speed was 7.0 mph.

The “Vehicle Speed” -1.0 second in the EDR data was also 7.0 mph. The instrument recorded delta-V was -4.4 mph, while the EDR recorded delta-V was –4.04 mph. In this test, the instrument closing speed and delta-V were in agreement with the EDR data (See Figure 7).

Figure 8: Phantom Driver installed in the V5-Mazda 5 Sport.

Figure 7: EDR data from the V2-2004 Chevrolet Suburban, VIN# 3GNEC16Z04G135478 after Test 1F. 18 Collision Magazine - Volume 16 Issue 2

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Alas, the electronic gremlins showed up and the V4-Nissan Altima decided to ignore its GPS guided programming.

When it became clear that the intersection collision was not going to happen, we lined up the vehicles opposing each other and ran a two-vehicle, Phantom Driver headon collision. Each vehicle was accelerated and steered remotely by an operator using a joy stick controller. The clos-

ing speed was about 40 mph. Using our instrumentation, the delta-V of the V4-Nissan Altima was determined to be -22.5 mph and the delta-V of the V5 Mazda 5 Sport was determined to be -20.5 mph. The collision sequence is represented in Table Two with images captured from the drone video.

Test Two Impact Orientation.

Test Two Maximum Engagement.

Test Two Separation.

Test Two Final Rest.

Table 2: Images of Test Two captured from the drone video

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There were several interesting observations regarding EDR data and the writing order for the EDR of the V5-2014 Mazda 5 Sport. Prior to testing, we performed a baseline image of the EDR on all supported vehicles. We recovered two events on the V5-2014 Mazda 5 Sport baseline image.

Baseline Event Record 1 was a non-deployment event at ignition cycle 767. It is interesting to note that this vehicle showed a lateral and longitudinal delta-V of zero with a speed of 35 mph at 0.0 sec (See Figure 9).

Event Record 2 was non-deployment event at ignition cycle 4238. Interestingly, the V5-2014 Mazda 5 Sport showed a lateral and longitudinal delta-V of zero on this event record with a speed of 0.0 for all pre-crash data points (See Figure 10).

Following test two, the EDR on the V5-2014 Mazda 5 Sport was imaged revealing two new Event Records. The new events overwrote the unlocked, non-deployment events that were recovered in the baseline download. The new Event Record 1 was a deployment event at ignition cycle 5286. The EDR recorded longitudinal delta-V was 21.7 mph and lateral delta-V of 2.5 mph, both positive values (See Figure 11).

Given that test two was a frontal crash that resulted in a deployment command, one would expect the polarity of the longitudinal delta-V to be negative. Obviously, the polarity is wrong for the longitudinal data set from the V5-2014 Mazda 5 Sport. The graph of the longitudinal delta-V shows a negative slope consistent with the frontal crash (See Figure 12).

Figure 9: Event Record 1, baseline image of EDR for the V5-Mazda 5 Sport.

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Figure 10: Event Record 2, baseline image of EDR for the V5-Mazda 5 Sport.

The V5-2014 Mazda 5 Sport rotated clockwise initially. As such, one would expect a negative value for the longitudinal delta-V, assuming that standard SAE sign convention was followed in the RCM programming. It appears that the polarity may be wrong for the lateral data set as well.

The graph of the lateral delta-V shows a negative slope consistent with a clockwise rotation (See Figure 13).

The new Event Record 2 imaged on the V5-2014 Mazda 5 Sport after this test was a non-deployment event, also at ignition cycle 5286. There were 0.2 seconds between Event Record 1 and Event Record 2. The pre-crash data was identical for Event Record 1 and Event Record 2. Each recorded a speed of 20 mph at 0.0 mph. Event Record

2 showed a longitudinal delta-V of 0.0 mph and lateral delta-V of 4.3 mph (See Figure 14).

Our third test series involved the V4-Ford Focus with a typical passenger vehicle bumper consisting of a bumper cover, energy absorber and bumper reinforcement bar striking the rear hitch on the V1-Suburban. A 21-year old female volunteer occupied the target vehicle. This was planned for a three test series, with increasing speed in order to measure the damage that occurred, changes in the collision duration and the biomechanical response. However, our volunteer opted out after test 3B. In our baseline download for the V4-Ford Focus, there were no events.

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Figure 11: EDR event for Test Two, deployment event V5Mazda 5 Sport.

Figure 12: Longitudinal delta-V graph for the V5-2014 Mazda 5 Sport after Test Two. 22 Collision Magazine - Volume 16 Issue 2

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Figure 13: Lateral delta-V graph for the V5-Mazda 5 Sport after Test Two.

Figure 14: Event Record 2 for Test Two, V5-Mazda 5 Sport.

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In Test 3A, our measured closing speed was 7.9 mph. The EDR was imaged on both vehicles and a non-deployment event was recorded as Event Record 1 for the bullet V4Ford Focus. The “Speed, Vehicle Indicated” was 8.0 mph at 0.0 seconds in the EDR data (See Figure 15).

The instrument recorded delta-V was -6.9 mph, while the EDR recorded delta-V was –5.6 mph for the bullet V4Ford Focus. The instrument recorded delta-V was 2.9 mph for the target V2-Suburban. There was no EDR record for

the V2-Suburban in this crash test. Figure 16 shows the vehicle positions after the collision.

In test 3B, our instrument measured closing speed was about 10 mph. The EDR was imaged on both vehicles and a new non-deployment event was recorded as Event Record 2 for the bullet V4-Ford Focus. The “Speed, Vehicle Indicated” was 10.3 mph at 0.0 seconds in the EDR data.

Figure 17 shows the Pre-Crash Data for the bullet V4-Ford Focus record as the second event record.

Figure 15: Pre-Crash data from the V4-Ford Focus (bullet) after test 3A.

Figure 16: Post-crash, Test 3A. 24 Collision Magazine - Volume 16 Issue 2

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The instrument recorded delta-V was -8.23 mph compared with an EDR recorded delta-V –8.2 mph for the bullet V4-Ford Focus. The instrument recorded delta-V was 3.5 mph for the target V2-Suburban. There was no EDR record for the V2-Suburban in this crash test. Figure 18 shows the vehicle positions after the collision.

in Test 3D. The EDR was imaged on both vehicles. There was no EDR record for the bullet V1-Suburban in either test. The EDR was not imaged on the target V4-Ford Focus after either test.

The fourth and final test was a three vehicle, inline collision wherein the V2-Suburban was remotely driven into Test 3C and 3D was a two-test lateral impact series. The the rear the stationary V1-Suburban. The V1-Suburban target vehicle was struck on the right rear. The closing was propelled forward into the rear of the V4-Ford Focus. speed was measured at 5.4 mph in Test 3C and 6.34 mph

Figure 17: Pre-Crash data from the V4-Ford Focus (bullet) after test 3B.

Figure 18: Post-crash, Test 3B. www.collisionpublishing.com

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The closing speed of the bullet V2-Suburban was recorded as 38.5 mph using the Video VBox HD. In this test, a Deployment level event was recorded in the bullet V2-Suburban. The EDR event recorded in Test 1F (non-Deployment) was retained in the record. The “Vehicle Speed” in the Deployment record was 31 mph at -1.0 seconds prior to Algorithm Enable. It should be noted that the throttle was at 100 percent for the -3 to -1 “Seconds Before AE” data points. The V1-Suburban was accelerated at 100 percent throttle up the point of impact. Figure 19 shows the Pre-Crash Data for the bullet V2-Suburban.

Our instrument recorded delta-V was -24.6 mph compared with an EDR recorded delta-V –21.07 mph for the bullet V2-Chevrolet Suburban.

For the center target V1-Suburban, the instrument recorded delta-V was 21.5 mph f in the initial impact, followed by a delta-V of -10.5 mph when it struck the third vehicle in line (V4-Ford Fusion). The EDR recorded delta-V was 19.9 mph when it was struck from behind.

The graphical display of the recorded delta-V captured the rear collision and the frontal collision even though the EDR captured no frontal event. The delta-V shows to be about 19.9 mph at around 140 msec. The acceleration curve flattens thereafter until about 190 msec, then begins to decline. The delta-V graph drops to about -9.5 mph at 270 msec. Thus, the frontal delta-V, graphically depicted, would be about -10.4 mph.

The graphed data agrees with the instrument measured data for the subsequent frontal impact. The EDR did not

Figure 19: Pre-Crash data for the Deployment event recorded in the V2Suburbran (bullet) after test Four.

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Figure 20: Longitudinal delta-V of the center V1-Suburban for Test Four.

Biomechanical Implications

Prasad and Mertz set forth a risk curve for severe, AIS ≥4, head or brain injury as a function of HIC. NHTSA later expanded the risk curves for all AIS levels. [25] A head injury with symptoms of headache or dizziness is classified as an AIS 1 injury. A head injury with a loss of consciousness of less than one hour is classified as an AIS 2 injury. [26]

With respect to the biomechanical implications in the various crash tests, the Head Injury Criteria (HIC), Neck Injury Criteria (NIC) and various other parameters were evaluated. The head acceleration and thorax acceleration was measured and the HIC and NIC values were calculated.

Volunteer studies are routinely conducted in a range that produce HIC’s below 50 without consequence. All of the HIC values in the volunteer tests we conducted at CrashCon22 were well below 50. Below 50 there is effectively no chance of even the most minor (AIS 1 or 2) head injury (See Figure 22). [27]

The HIC is based upon the linear resultant head center of gravity acceleration. The HIC is the maximum calculated value over a time frame where t2 – t1 = 15 or 36 msec using the formula shown in Figure 21.

In Test 1A, a rigid bumper vehicle striking another vehicle bumper vehicle, the peak vehicle acceleration was 2.5g wherein the collision duration was 89 msec. The peak acceleration of the head of the volunteer was 2.1 g at 179 msec. The delta-V was 2.2 mph.

see two non-deployment events even though it captured data from the initial rear crash and the subsequent front crash in the graph. Figure 20 shows the graphical data from Test Four.

Figure 21: Head Injury Criterion The Abbreviated Injury Scale [24] or AIS, is a standardized system to describe injury severity that ranges from AIS 1 to AIS 6, representing minor through fatal/untreatable injury.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 2.0 g at 112 msec and the peak lumbar acceleration at L1-L2 was 2.2 g at 118 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1A is shown in Figure 23.

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Figure 22: Ryan et al, Probability of Head Injury Severity as a function of HIC

Figure 23: Lumbar acceleration vs. Vehicle acceleration, Test 1B, CrashCon22.

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In Test 1B, a rigid bumper vehicle striking another vehicle bumper vehicle, the peak vehicle acceleration was 6.06 g at 89 msec. The peak acceleration of the head of the volunteer was 4.34 g at 148 msec. The delta-V was 3.72 mph Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 4.2 g at 80 msec and the peak lumbar acceleration at L1-L2 was 4.5 g 74 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1B is shown in Figure 24.

of her head where the headband was fastened over her hair braids.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 6.4 g at 69 msec and the peak lumbar acceleration at L1-L2 was 6.8 g at 73 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1C is shown in Figure 25.

In Test 1D, a rigid bumper vehicle striking another vehicle bumper vehicle with a protruding, frame mounted hitch, Test 1C was our most robust test at CrashCon22. The vol- the peak vehicle acceleration was 5.4 g wherein the colliunteer head acceleration peaked at 12 g at 123 msec vs. sion duration was 105 msec. The peak acceleration of the the vehicle peak acceleration of 11.38 g at 39 msec. The head of the volunteer was 3.0 g. The delta-V was 3.3 mph. delta-V was 5.2 mph. With the exception of this female volunteer following this test (her third exposure, none of Both lumbar accelerometers recorded peak accelerations the volunteers reported any symptom of injury or pain im- that were well below the peak acceleration of the vehicle mediately following the tests or in the days following. This and the lumbar acceleration at L5-S1 modeled the accelvolunteer reported some transient minor pain to the back eration at L1-L2 modeled each other. The peak lumbar ac-

Figure 24: Lumbar acceleration vs. Vehicle acceleration, Test 1B, CrashCon22. www.collisionpublishing.com

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Figure 25: Lumbar acceleration vs. Vehicle acceleration, Test 1C, CrashCon22 celeration at L5-S1 was 2.9 g at 73 msec and the peak lumbar acceleration at L1-L2 was 2.8 g at 81 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1D is shown in Figure 26.

In Test 1E, a rigid bumper vehicle striking another vehicle bumper vehicle with a protruding, frame mounted hitch, the peak vehicle acceleration was 5.4g wherein the collision duration was 105 msec. The peak acceleration of the head of the volunteer was 7.0g. The delta-V was 4.26 mph.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 3.6 g at 73 msec and the peak lumbar acceleration at L1-L2 was 3.5 at 93 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1E is shown in Figure 27.

In Test 1F, a rigid bumper vehicle striking another vehicle bumper vehicle with a protruding, frame mounted hitch, the peak vehicle acceleration was 6.2 g wherein the colli30 Collision Magazine - Volume 16 Issue 2

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sion duration was 119 msec. The peak acceleration of the head of the volunteer was 6.4g. The delta-V was 4.5 mph.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 3.2 g at 88 msec and the peak lumbar acceleration at L1-L2 was 3.6 g at 113 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 1F is shown in Figure 28.

In Test 3A, the V4-Ford Focus with a typical passenger vehicle bumper consisting of a bumper cover, energy absorber and bumper reinforcement bar struck the rear hitch on the V1-Suburban. The peak vehicle acceleration was 3.1g and the collision duration was 162 msec. The peak acceleration of the head of the volunteer was 4.2 g. The delta-V was 2.9 mph.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the accel-

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Figure 26: Lumbar acceleration vs. Vehicle acceleration, Test 1D, CrashCon22.

Figure 27: Lumbar acceleration vs. Vehicle acceleration, Test 1E, CrashCon22. www.collisionpublishing.com

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Figure 28: Lumbar acceleration vs. Vehicle acceleration, Test 1F, CrashCon22. eration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 1.9g at 156 msec and the peak lumbar acceleration at L1-L2 was 2.2 g at 167 msec. A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 3A is shown in Figure 29.

In Test 3B, the V4-Ford Focus with a typical passenger vehicle bumper consisting of a bumper cover, energy absorber and bumper reinforcement bar struck the rear hitch on the V1-Suburban. The peak vehicle acceleration was 3.6 g. The crash duration was 218 msec. The peak acceleration of the head of the volunteer was 4.2 g. The delta-V was 3.8 mph.

Both lumbar accelerometers recorded peak accelerations that were well below the peak acceleration of the vehicle and the lumbar acceleration at L5-S1 modeled the acceleration at L1-L2 modeled each other. The peak lumbar acceleration at L5-S1 was 2.4 g at 193 msec and the peak lumbar acceleration at L1-L2 was 2.45 g 200 msec.

A graphic representation of the lumbar acceleration vs. the vehicle acceleration from Test 3B is shown in Figure 30.

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Table Three shows the results of the biomechanical data from all front to rear crash tests.

In the rear crash tests, all of the data in this series confirmed that the lumbar spine is well supported by the seat back and the seat material absorbs collision energy as observed

by Lam. With respect to head or neck injury, the HIC and NIC values were well below the established minimum threshold for head (HIC <50) or cervical injury (NIC <15 m2/sec2) in five of six tests.

In Test 1C, the NIC was 24 m2/sec2. With a crash pulse of about 80 msec, compared to the first test with a duration of 114 msec, this impact was much stiffer as bumper to bumper tests go. This was the third in the series of stiff bumper to stiff bumper impacts. It is apparent that there was more yielding of the bumper system in the first test, compared with the third test. The volunteer reported no symptoms of cervical injury following the test series, after three exposures. [29,30]

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Figure 29: Lumbar acceleration vs. Vehicle acceleration, Test 3A, CrashCon22.

Figure 30: Lumbar acceleration vs. Vehicle acceleration, Test 3B, CrashCon22. www.collisionpublishing.com

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Volunteer Gender

Age

Height Weight

Test 1A Test 1B Test 1C Test 1D Test 1E Test 1F Test 3A Test 3B

20 20 20 24 24 24 21 21

5’ 10” 5’ 10” 5’ 10” 6’ 3” 6’ 3” 6’ 3” 5’ 4” 5’ 4”

Female Female Female Male Male Male Female Female

150 lbs.

150 lbs.

150 lbs.

214 lbs.

214 lbs.

214 lbs.

135 lbs.

135 lbs.

Delta-V (mph) 2.2 3.72 5.2 3.3 4.26 4.5 2.9 3.8

HIC

NIC

0.093 0.505 6.5 0.2 0.6 1.2 .176 .485

.51 m2/sec2 6.2 m2/sec2 24 m2/sec2 4.9 m2/sec2 8.6 m2/sec2 6.4 m2/sec2 .072 m2/sec2 1.1 m2/sec2

Peak Shldr Belt Load (lbs) 6.86 13.04 48.9 6.92 14.8 20.2 6.3 3.66

Peak Lap Belt Load (lbs) 2.15 2.56 4.65 6.3 8.59 13.19 2.74 2.06

Table 3: Results of the biomechanical data from all front to rear crash tests Two lateral crash tests were performed wherein the volunteer was subjected to two, far side impacts. In Test 3C, the V4-Ford Focus was struck on the right rear side by the V1Suburban. The centerline of the V1-Suburban was aligned with the center of the rear axle on the V4-Ford Focus. The closing speed was about 5.4 mph. The peak vehicle acceleration was -2.9 g on the Y-axis and +1.5 g on the X-axis.

The crash duration was 97 msec on the Y-axis.

The peak acceleration of the head of the volunteer was 2.9g with a HIC score of 0.205. The acceleration was -2.9g on the lumbar spine, Y-axis. The delta-V on the Y-axis was -2.08 mph and +0.57mph on the X-axis, yielding a resultant delta-V of 2.15 mph. Figure 31-34 is a photo series from the crash test depicting the impact orientation, maximum occupant excursion and final rest of vehicles.

In Test 3D, the V4-Ford Focus was left in its post-collision position following Test 3C. The closing speed was about 6.34 mph. The peak vehicle acceleration was -3.0 g on the Y-axis and -1.8g on the X-axis. The crash duration was 92 msec on the Y-axis.

The peak acceleration of the head of the volunteer was 2.6 g with a HIC score of 0.16. The acceleration was -2.6 g on the lumbar spine, Y-axis. The delta-V on the Y-axis was -2.6 mph and -0.63 mph on the X-axis, yielding a resultant delta-V of 2.67 mph. Figure 35-38 is a photo series from the crash test depicting the impact orientation, maximum occupant excursion and final rest of vehicles.

We have been involved in lateral impact volunteer crash tests for at least 25 years. [31,32,33] There were no surprises in the lateral crash test series. The changes in velocity for the lateral impact series fell below levels commonly endured by human volunteers participating in crash test research, as outlined in the literature. Our volunteer experienced no symptom of injury in the two test series. Bailey, et al., [34] conducted several lateral vehicle-to-vehicle col34 Collision Magazine - Volume 16 Issue 2

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lisions in which volunteers were subjected to repeated impacts with velocity changes ranging from 0.4 to 4.2 mph.

Neither of Bailey’s subjects complained of any symptoms following the tests.

Furbish, et al [35] performed lateral, far-side vehicle-tovehicle collisions in which volunteers were subjected to repeated impacts with velocity changes ranging from 3.9 km/hr to 9.3 km/hr (2.4 to 5.77 mph), primarily through the lateral CG of the vehicle. They also performed later impacts with rear oblique configuration, similar to the CrashCon22 test with velocity changes of 5.6 km/hr and 4.4 km/hr (3.47 to 2.73 mph), respectively. The results of our lateral tests reasonably modeled the results observed in this scholarly publication.

Having been involved in conference crash testing for over 25 years, I can say with confidence that we always learn something while performing tests at in-person conferences.

CrashCon22 was no different. The in-person conference with live crash testing always provides a great value for the price of tuition, based on the value of the data each attendee receives alone. This article is intended to provide an overview of the testing protocols, instrumentation packages and the observations in general from CrashCon22.

A crash conference wherein you run 12 fully instrumented crash tests, on time, within a 6-hour window and present the data a day and a half later is truly a team effort. I would like to acknowledge the contributions of my colleagues, Christopher Furbish and Bryan Randles, Aperture, LLC, David Hallman of Hallman Engineering, Robert “Bob” Anderson of Biomechanics Analysis, Michael Rosenfield of RSR Engineering, and Daniel “DV3” Vomhof III of 4N6XPRT Systems. I would also like to thank David Barczyk and the Barczyk Biomechanics Institute for entrusting us to develop and execute the crash test plan for CrashCon22.

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Figure 31: Test 3C, impact orientation.

Figure 32: Test 3C, mid-collision. Maximum excursion of the occupant.

Figure 33: Test 3C, mid-collision. Maximum excursion of the occupant.

Figure 34: Test 3C, final rest position.

Figure 35: Test 3D, impact orientation.

Figure 36: Test 3D, mid-collision. Maximum excursion of the occupant.

Figure 37: Test 3D, mid-collision. Maximum excursion of the occupant.

Figure 38: Test 3D, mid-collision. Maximum excursion of the occupant.

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References 1.

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Szabo TJ and Welcher JB, “Human Subject Kinematics and Electromyographic Activity During Low Speed Rear Impacts,” SAE paper 962432, Proceedings of the 40th Stapp Car Crash Conference, Albuquerque, NM, November 1996.

Szabo TJ, Welcher JB, Anderson RD, Rice MM, Ward JA, Paulo LR and Carpenter NJ, “Human Occupant Kinematic Response to Low Speed Rear-end Impacts,” SAE paper 940532, in Occupant Containment and Methods of Assessing Occupant Protection in the Crash Environment (SP-1045), Society of Automotive Engineers, Inc., Warrendale, PA, 1994.

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13. Meyer S, Weber M, Castro W, Schilgen M and Peuker C, “The Minimal Collision Velocity for Whiplash,” in Whiplash Injuries: Current Concepts in Prevention, Diagnosis and Treatment of Cervical Whiplash Syndrome, Robert Gunzberg and Marek Szpalski, ed., Lippencott-Raven, Philadelphia, 1998.

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Szabo TJ and Welcher JB, “Human Subject Responses to Various Acceleration Fields,” Presented at the Low Speed Collision TOPTEC”, Society of Automotive Engineers, Vancouver, BC, August 1996.

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10. Wilson LA & Haight S, ”Kinematics of Braced, Un-braced, and Out-of-Position Occupants in Low-Speed Bumper-toBumper Rear Impacts,” Collision-The International Compendium for Crash Research, Vol 12, Issue 2, 2015.

11. Ruberte LM, Cox BS & Lantz S, “The Older Lady Versus the Younger Lady: Female Occupant Kinematics in LowSpeed Rear-End Collisions,” Collision-The International Compendium for Crash Research, Vol 11, Issue 1, 2016.

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17. Wagner R, “A 30 mph Front/Rear Crash with Human Test Persons,” SAE Paper 791028, Proceedings of 23rd Stapp Car Crash Conference, Society of Automotive Engineers, 1979.

18. Vandiver W & Anderson RD, “Analysis of Crash Data from a 2012 Hyundai Genesis Coupe Event Data Recorder,” Society of Automotive Engineers, Paper 2021-01-0905.

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20. McConnell, Whitman E., et al. “Analysis of Human Test Subject Kinematic Responses to Low Velocity Rear End Impacts, Society of Automotive Engineers 930889 Warrendale, PA. 1993.

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22. Siegmund, Gunter P., et al. “Head/Neck Kinematic Response of Human Subjects in Low-Speed Rear-End Collisions.” Society of Automotive Engineers, 973341, Warrendale, PA. 1997.

23. Kelfer OP, Layson PD and Reckamp BC, “The Effects of Seated Position on Occupant Kinematics in Low-speed

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rear-end Impacts,” SAE Paper 2005-01-1204, in Accident Reconstruction 2005 (SP-1930), Society of Automotive Engineers, Inc., Warrendale, PA, 2005.

24. Biomechanics, Principles and Applications, Second Edition, Peterson DR and Bronzino JD editors, ISBN-13: 9780849385346, CRC Press, 2007.

30. Wheeler, Jeffrey B., Smith, Terry A., et al. “Validation of the Neck Injury Criterion (NIC) Using Kinematic and Clinical Results From Human Subjects in Rear-End Collisions.”

ITCOBI Conference – Goteborg, September 1998.

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25. Abbreviated Injury Scale, Association for the Advancement of Automotive Medicine, Des Plaines, IL 2005.

32. Independent Crash Test, T241-04. “Nissan 240 SX striking Honda Prelude.” February 25, 1999.

26. Pike, Jeffrey A., “Automotive Safety: Anatomy, Injury, Testing & Regulation.” 1990 Society of Automobile Engineers, Inc.

33. Independent Crash Test,T241-05. “Nissan 240 SX striking Honda Prelude.” February 25, 1999.

27. NHTSA, Injury Risk Curves and Protection Reference Values,” Final Economic Assessment, FMVSS No. 201, Upper Interior Head Protection, June 1995.

28. Lam, Tak, Ivarsson, B.J., “Vehicle Rear Impacts and Spinal Disc Herniations in Occupants: Is there a Basis for Causation. Society of Automotive Engineers 217-01-1458 Warrendale, PA, 03/28/2017.

29. Svensson, M.Y., Bostrom, O., et al. “Neck Injuries in Car Collisions – A Review Covering a Possible Injury Mechanism and the Development of a New Rear Impact Dummy.” WAD ’99 Compendium/Traffic Safety and Auto Engineering.

34. Bailey, M. N. et al. “Data and Methods for Estimating the Severity of Minor Impacts”, Accident Reconstruction: Technology and Animation V, Society of Automotive Engineers Special Publication SP-1083, pp. 139-175, February 1995.

35. Furbish, Christopher and Welcher, Judson, et al. “Occupant Kinematics and Loading in Low Speed Lateral Impacts. Society of Automotive Engineers Special Publication 2019-01-1027, Published 02, Apr 2019.

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Vehicles, VIN's, Certification Labels, and parts

What “Model Year” is it??

Daniel W. Vomhof III 4N6XPRT Systems

T

his article is a result of some recent discussions and research by individuals on the Crash Forum (www.crashforum.info) with respect to, for example which direct-to-module CDR Tool cable is needed for a download based on the “model year.” As such, this will concentrate on the model year portion of the VIN (and other vehicle labels) trying to answer the question of “What model year is it, and which equipment/part/cable is therefore needed?” Please keep in mind that every time we think we have a system, the automotive industry finds a way .... so please don’t shoot the messenger.

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Background One of the original purposes of the VIN system was to enhance public safety by deterring vehicle theft based on the assumption that drivers of stolen vehicles are more likely to operate those vehicles unsafely and thus be involved in vehicle crashes. The current 17-character VIN

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system embodied in 49CFR565 (“part 565”) continues to serve this purpose and, as stated in Part 565, also serves…

1. “to increase the accuracy and efficiency of vehicle recall campaigns.”

2. The VIN has also become the key identifier in data systems that track such things as: 2.1 compliance with federal importation regulations, 2.2 vehicle registrations, 2.3 insurance coverage, and 2.4 motor vehicle crashes.

Within the automotive industry, the vehicle model year is nominally the “vehicle design” year specifications to which

the vehicle is built. The VIN indicates a “Design” model year with character ten of the VIN in combination with (since 2010 when the Year Code reset to “A”) character 7.

Per NHTSA’s Final Rule on Vehicle Identification Number Requirements, as of 2010, it is required that VIN position 7 be alphabetic for passenger cars and multipurpose passenger vehicles and trucks with a gross vehicle weight rating of 4536 kg (10,000 lbs) or less (prior to 2010 this position must be numeric for these vehicles, while either an alphabetic or numeric character can be used in this position for other vehicles covered by the standard).

From 49CFR565.12 (m): “… Model year means the year used to designate a discrete vehicle model, irrespective of the calendar year in which the vehicle was actually produced, provided that the production period does not exceed 24 months. …”

While for a short period of time the CFR required/stated that it was meaning 2 calendar years, they reverted to the

24 month time period irrespective of calendar year due in part to a January 7, 2005 letter from General Motors which stated in part it is common practice for a manufacturer to use a model year designation for the production of a vehicle that spans over three calendar years, particularly when a manufacturer introduces a substantial design change for a vehicle model. This practice allows the manufacturer to “obtain early experience with the performance of a new model and to correct problems, including potential safety defects, before a large volume of vehicles has been delivered to dealers and customers.”

Orientation While the VIN may be found in several places on a vehicle, the two most common places I look for a VIN is on the driver’s side front dash near the lower corner of the front window (Figure 1), and on the certification label that is usually (A) on the driver’s side A pillar covered by the front door, (B) on the driver’s door below the window level on the B pillar side, or ( C ) on the B pillar covered by the driver’s door below the side window level (Figure 2). While most of the vehicles have the certification label in one of these three places, on select vehicles you can also find the

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Figure 1: VIN plate on the driver’s side front dash near the lower corner of the front window

Figure 2: Certification label that is usually (A) on the driver’s side A pillar covered by the front door, (B) on the driver’s door below the window level on the B pillar side, or ( C ) on the B pillar covered by the driver’s door below the side window level 40 Collision Magazine - Volume 16 Issue 2

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certification label on the inside of the trunk lid (i.e.: 2002 Buick Century) and on the inside of the glove compartment door (1990's era Toyotas). It doesn’t happen often, if you don’t see the label in locations A-C (Figure 2), check these two additional locations.

The 10th character of the VIN indicates the model year, in this case, N=2022 (Figure 3). On the Certification Label example seen as Figure 4, it can be seen that the manufacture date is 12/21. So, this vehicle was manufactured in 2021, but, assigned a 2022 model year code. Not uncommon at all. In fact, for most manufacturers, the change over from one model year to the next has historically been in September. However, that is slowly changing where the new model year is coming out earlier and earlier in the year and some manufacturers have adopted what is effectively a quarterly new or change over model release schedule. Add to that the oddities such as Toyota which from time to time has had a “.5" model year (note, there is no way to represent this in the VIN). You also have Tesla which sets their new model year per no certain schedule, or so it has been related to me although we should probably assume that it complies with 49CFR565.

From time to time, you also have a manufacturer come out with the new model year vehicle that is a total redesign as early as February, and then sell it side by side with the carry over design from the previous model year. While this occurs most commonly with pickups, another example is where a manufacturer might change the production location or make other changes to a vehicle line. As an example, you could see for a given model both a 2022 and a 2023 model year vehicle on a new dealer lot in March of 2022. So model year DOES NOT necessarily mean and has no specific, direct connection to the CALENDAR year of manufacture.

Who Decides The Model Year?

After repeated readings of the Code of Federal Regulations, the only thing set in stone is that a given model year applied to a given model vehicle has to be applied within a 24 month period around the production date.

In 49CFR565.12(m) we find where NHTSA has specified: “… Model year means the year used to designate a discrete vehicle model, irrespective of the calendar year in which the vehicle was actually produced, provided that the production period does not exceed 24 months. …”

And the VIN is assigned by the manufacturer (per 49CFR 565.12(n) where we find: “… Plant of manufacture means the plant where the manufacturer affixes the VIN. …”

Beyond that, when a model year starts, when it ends, and how long it is applied is totally up to the manufacturer within the limits of 49CFR565.12(m). That bears repeating. The manufacturer determines the model year. The model year is NOT set by the DMV. The model year is NOT set by the calendar year of manufacture. The manufacturer determines and sets the model year of the vehicle.

Model Year Implications With Regards To Equipment For those who remember the Souplantation/Sweet Tomatoes chain of salad buffet restaurants, they would have several new soups that came for a period of about a month before they transitioned to the next “special” soup. Their transition period, however, was not a sharp line of demarcation, but rather one of a day or two depending upon how fast, or slow, the ingredients for one soup were used up and how soon the next soups ingredients came in. When look-

Figure 3: 10th character of the VIN indicates the model year www.collisionpublishing.com

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VIN - The Rest Of The Story So, we have dealt with the model year portion of the VIN, what do the rest of the characters indicate? When looking at passenger cars, MPV/ SUV’s, or Trucks with a GVWR of 10,000 or less that were manufactured with the intention of being sold within the United States, and with a model year of 2010 or later, the following applies: Characters 1-3 are referred to as the “WMI” or World Manufacturer Identifier. They indicate in broad brush terms Country of Manufacture, the country the manufacturer is based in, and possibly vehicle type or division. The company division and/or vehicle type (i.e. - passenger car, MPV, Pickup, etc.) was a definite part of the WMI in the early years of the VIN (1980-2000).

Due to a fear that if this practice continued, the available characters would be “used up” and thus the 17-character VIN would have to have more characters, the division and/or vehicle type now often has to be determined through a combination of characters 1-8 instead of just 1-3. If the third character is a 9, that indicates the manufacturer is a low volume manufacturer and thus is identified in characters 12-14.

Figure 4: Certification Label example ing at equipment and parts that go into a vehicle during a production run, you almost have to look at things the same way - especially when the vehicle build date is close to the model year transition.

With the understanding that a part/plug, adapter, etc. will work as intended regardless of the assigned model year. Did the assembly plant have a surplus of the old model year parts to be used up? Did they use up the previous model year’s parts early and so grabbed from the next model year’s parts bin for the last few to few hundred vehicles in a production run? Was there a last-minute design change applicable to assembly that never made it into the “design notes?”

For this reason, one should take the model year designation for a vehicle as a “guide” to the vehicle dimensions and other information, not a hard and fast requirement for those same dimensions nor for what equipment, CDR Tool cables, connectors, etc. are on or to be used for a specific, given vehicle.

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On this point, specific to the Bosch CDR Tool, the WMI should not be confused with the “Market Code” found in the CDR Tool software Help file. While the Market Codes listed in the Help file might seem to correspond to the WMI that’s not the case. In Figure 5, we see the Market Code list from the Bosch CDR Tool Help file and note that Market Code 1, is for the “USA and Canada.” Similarly, a “1” in the WMI would indicate “North America” and the US WMI would be a “1,” “4” or “5” indicator digit as part of that WMI. Canada’s specific WMI indicator is “2” which, as part of the Market Code list is specifically the “USA.” In short then, it should be clear that the CDR Tool Market Codes are specific to the Bosch CDR Tool and should not be confused with some sort of correlation to the VIN WMI. Characters 4-8 may be used to identify the vehicle attributes such as model, drive wheels, number of doors, restraints, and GVWR, to name a few. For many of the manufacturers, the eighth character identifies the engine, however depending on the manufacturer and the year, final en-

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Character 10 is the Model Year for the vehicle as, again, assigned by the manufacturer. If Character 7 is a number, the model year is in the range of 1980-2009.

If character 7 is an Alpha character, the model year is in the range of 2010-2039.

Character 11 is the Assembly Plant code.

Plant of Manufacture means the plant where the manufacturer affixes the VIN (49CFR565.12 (b)).

Figure 5: Market Code list from the Bosch CDR Tool Help file gine determination may have to be made through a combination of the WMI and some or all of characters 4-8.

Character 9 is what is referred to as a “Check digit”. The value of the ninth character is 0-9 or X. It is calculated based on the other 16 characters in the VIN. For the method of calculating the check digit refer to 49 CFR Part 565.15 (c) (1) through (4). The purpose of the check digit is to provide a means for verifying the accuracy of any VIN transcription.

Characters 12-17 are the Sequential Production characters (i.e.: the unique serial number) for the vehicle. If the manufacturer is deemed to be a low production (i.e. - below 1000 vehicles per year) manufacturer, characters 12-14 are assigned to that manufacturer as part of the WMI. If the manufacturer is a high-volume manufacturer, all of the characters are used to identify the sequence that the vehicle comes off of the assembly line. Note that the sequential production number does not necessarily reset at the beginning of each model year, nor does it necessarily start at 000001. Where it starts and when it “resets” is, as with the Model Year designation, up to the manufacturer, as long as there are no two vehicles within the 60 year range of 1980-2039 with the exact same 17 character sequence.

An Example An example of multiple or changing production lines and which has resulted in some VIN indicated model year confusion is the Volkswagen Tiguan. The generation

Figure 6: Examples of the certification sticker production date to designated MY for the Tiguan www.collisionpublishing.com

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1 Tiguan was built at one of two plants in Germany from 2008 to 2018. A second generation Tiguan with a longer wheelbase went into production at VW’s Mexico plant around June 2016 and so, for a time, the Tiguan designated as a MY 2017 (VIN character H) and MY 2018 (VIN character J) had overlapping production dates. In the case of the Tiguan, a careful examination of the VIN will reveal which "model" it is by the WMI and by the Plant code.

Unfortunately, this will not always be the case with "overlapping models" with the same model year code." While we can identify the plant through the VIN, the model year designation may still be something of a “moving target.”

The MY 2017 Tiguan could have been built during the period 5/2016 through 11/2017 and the MY 2018 could have a production date between 4/2017 and 9/2018. As you can see, during a large part of calendar year 2017 production dates, the specific vehicle, depending mainly on the production plant at that point, could be designated a MY 17 or MY18. This production “anomaly” caried over for majority of production dates in 2018 where a Tiguan could have been designated as MY 2018 or MY 2019 as seen in the VIN MY digit. A review of some 300 randomly selected VW Tiguans by VIN and certificaton sticker for model years 2017- through 2020 developed a pattern such that the build calendar date from the certification stickers fell within the appropriate 2 year period, however, many fell outside the production calendar date. Ultimately, depending on where the Tiguan was built or its generation… a 2017 (H) Tiguan could have a production date between 5/2016 and 11/17 •

a 2018 (J) Tiguan could have a production date between 4/2017 and 9/18

•

a 2019 (K) Tiguan could have a production date between 1/2018 and 8/19

•

a 2020 (L) Tiguan could have a production date between 8/2019 and 9/20

Examples of the certification sticker production date to designated MY for the Tiguan are seen in Figure 6.

the individual looking to download data having to make sure they have more than one direct to module cable on hand since the model year indicator may not be the deciding factor when it comes to identifying the right cable.

In Summary Since 1981, the Vehicle Identification Number (VIN) has been structured with 17 characters, some of the positions and values being mandated, but most being left “up to” the manufacturer to a greater or lesser extent.

The 10th character identifies the manufacturer designated Model Year of the vehicle. Model Year means the year used to designate a discrete vehicle model, irrespective of the calendar year in which the vehicle was actually produced, provided that the production period does not exceed 24 months. (49CFR565.12 (b)) If you are relying upon the VIN designated MODEL YEAR to identify the cable(s) that will be needed to complete a download, you might want to make sure you have the cables for the immediately preceding and following Model Years on hand as well to make sure you don’t get out to the vehicle and experience an unwelcome production date related “surprise.” This is the unfortunate reality of the industry in which we are “playing.”

For Additional Reading and Reference 1. https://www.ecfr.gov/current/title-49/subtitle-B/ chapter-V/part-565 2. NHTSA Letter of Explanation as to “Model Year” -https://www.nhtsa.gov/interpretations/modelyearjoneslet4 3. Rescind determination of “calendar year” as part of the “model year” statement - https://www.federalregister. gov/documents/2005/05/06/05-9140/vehicle-identification-number-requirements-technical-amendment 4. WMI, Country Codes, etc - https://en.wikipedia.org/ wiki/Vehicle_identification_number

As it might relate to, for example, direct-to-module cables for the Bosch CDR Tool, there is an airbag control module changeover suggested for this period which would leave

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Tesla EDR Tool Kit

EDR Data can be retrieved from all Tesla Model S, Model X, Model 3, and Model Y vehicles. Tesla Roadster, which was produced from 2008 to 2012, is equipped with a RCM but does not have an EDR.

The EDR Retrieval Hardware Kit for Tesla vehicles contains all the hardware required to download the Event Data Recorder (EDR) data that may be stored in all Tesla Model 3, Model S, Model X, and Model Y vehicles. This is the only kit that contains genuine Tesla EDR cables.

Available at Crash Data Group www.crashdatagroup.com (800) 280-7940 crash@crashdatagroup.com

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MY

RN TU

AT

E TH

L EE WH

WHAT IS "30" how and why should we use it?

Richard C. Rinker

I

recently had the pleasure of flying from Dallas, Texas to Ontario, California. I was seated between a gentleman who explained the benefits of Ivermectin in the current health situation and a woman traveling with a 3-year-old child who loudly protested the effect of changes of air pressure on his ears. She apparently failed to grasp the value of a therapeutic dose of a fine Kentucky Bourbon in such a situation. In self-defense I allowed my mind to ponder my favorite number, 30, and its place in the grand scheme of life. By “30” of course, I refer to the value with which we are all familiar, the basic Slide to Stop skid speed formula. At least those of us residing in the U.S. We are all familiar with the Slide to Stop formula S=√30df where S=Speed in units of Miles Per Hour (MPH), d = distance of the slide in feet, f = coefficient of friction, and 30 = what? Most of us have been taught 30 is a constant derived from the combination of Kinetic and Work Energy formulas, such that Energy = Energy, so Kinetic Energy (KE) = ½MV² = work energy = Fd (Lofgren, M. (1993) IPTM, Pg 11-13).

I’m not going to derive the entire formula here. We should have all seen it at one time or another, but as a reminder, mass = weight/gravity, and, in Earth based collisions, gravity ≈ 32.2 FPS/S. We call it a constant because, well, it’s constant. It does not vary from California to Alaska to Maine to Hawaii.

maintains 30 is a constant. Why? Because it is consistent on Earth and that’s what everyone calls it. This may come from the landmark decision People v. Herman, 20 NYS 2nd, 149 (1940) in which the court recognized 30 to be a mathematical constant. The court held in Herman: “30 = The gravitational constant, 32.2 feet per second per second, doubled and multiplied by a factor, (3600/5280)2 which transforms the miles per hour in V2 to feet per second” However, to truly be a constant, it must be the same universally. Gravity, however, is not a constant universally (other than Einstein’s Gravitational Constant, but that’s for another discussion. On Earth, the acceleration of gravity is generally held as 32.2 FPS². On the Moon, it is 0.16 FPS. On Mars it is 3.71 FPS². Yes, I realize it will be a very long time before we need to work a collision on any of these celestial bodies. That is not the point. The point is, if a value, any value, varies from place to place or situation to situation, it cannot be considered a constant. But as long as we maintain our frame of reference as operating on the Earth, we can probably get away with calling it a constant, for our purposes.

The other school of thought holds that 30 is really a derived conversion factor which changes measurements of the change of distance with respect to time from units of feet per second (FPS) to miles per hour (MPH). As we follow the derivation of the slide to stop formula, we get to a point where we have a term, 2g, expressed as 2x32.22 But is it really a math- = 64.4 FPS² which we need to divide by (5280 feet/3600 ematical Constant? seconds)² to convert a value from FPS to MPH or as we There are two are more familiar with it, 1.467²= 2.15, 64.4/2.15, which schools of equals approximately 29.95 depending on how one hanthought on dles decimals. We then, of course round up to get the this. One “30” with which we are all familiar. This shows “30” to be school a derived conversion factor changing velocity in Feet per Second to speed in Miles per Hour. We call it a “factor”

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because it is a number by which we multiply other numbers. This is also the answer to the question how does S=√30df which contains variables of distance in feet and friction with no obvious units of measure but no units of speed or velocity provide the user with an answer in MPH? Thus, regardless of which school one follows, Constant or Conversion Factor, 30 is a derived value which comes from the conversion of FPS to MPH. The units of measure of the rate of change of distance with respect to time expressed in units of MPH is hidden in the derivation of the number 30. The fact that the court in Herman specifically analyzed the use of the number 30 to the exclusion of all other numbers suggests that only 30 is the tested and accepted value to be used in this application.

This brings me to the actual use of the slide to stop formula. We use the formula to estimate the minimum speed of a vehicle sliding with all wheels locked. At this point, I am not including adjustments for vehicles with defective brakes, grades or other adjustment needed to handle special conditions. We will get to that shortly. We are taught the ideal method to estimate speed of a skidding vehicle is to track the movement of the center of mass of the vehicle in question. In a perfect world involving a vehicle skidding with locked tires, we should measure all tire marks, plot them on a scale diagram, locate the center of mass of the vehicle, track its’ movement during the skid, measure the distance the center of mass moves, determine the average drag factor affecting the center of mass of the involved vehicle, apply the appropriate average drag factor or deceleration rate over the measured distance and estimate the initial speed of the vehicle based upon the average deceleration over the given distance.

This method works for a vehicle skidding in a straight line on one consistent surface.

Now let us consider a special condition in which a vehicle skids with all tires locked from one surface onto a second surface, sequentially, with a different drag factor, or a third, or fourth, etc. To deal with this situation, we typically track the movement of the center of mass to determine the speed loss of the vehicle on each surface individually and combine them using Pythagoras’ gift to Accident Reconstruction, the Pythagorean Theory, a2+b2=c2. We could also solve the problem by treating it as an acceleration problem, solving for V0 (Fricke, Northwestern University (1990) page 60-8) if we know the acceleration rate and distance. If we want to show off, we could even solve it using vectors and right triangles. But one variable we need to use in all the methods is we need to determine the average drag factor (or acceleration rate) acting on the center of mass of the vehicle.

Now, consider another special case where we have a vehicle skidding on two surfaces having dissimilar drag factors at the same time, say, right side on wet, muddy concrete and the left side on clean, dry asphalt. In this case, I am ignoring, for the moment, rotation of the vehicle caused by the unbalanced drag factors. We will discuss that complication later.

Once again, I find two schools of thought in finding the resolution to the problem of determining the minimum estimated speed of the vehicle leaving the skid marks. One school says the investigator should measure each skid, plot them on a diagram, determine the distance of the movement of the center of mass of the vehicle, then determine the drag factor for the left side and right side independently, add the respective drag factors and divide by two to determine the average drag factor acting on the center of mass of the vehicle. We then use the traditional slide to stop formula to estimate the speed. In practical application, this would look like S=√30dfa where fa is the average f acting on the center of mass of the vehicle. A modification of the traditional formula would be S=√(30d ((f1+f2)/2)).

In the real world, both formulas are the same thing, just written differently. This formula has two advantages. First, it makes use of the distributive property of division, that is it divides two drag factors using the average f acting on the vehicle over the distance traveled by the center of mass. Second, it maintains the derived value, “30” unaltered.

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The second method I have found divides 30 by 2 and looks like this √(15d(f1+f2)) (Parkka, D. IPTM, (1996) page 126 and Daily, Shigemura and Daily, IPTM, (2006) page 352). A very valid question at this point could be “So what?”. Each method provides the same answer. Both methods provide the correct answer to the question. Ok, so what? There are probably at least 10 methods which will all provide the correct answer. For instance, Howell, IPTM, (1994) (page 58 and 63 – 68) provides 7 apparently different formulas to estimate the same original speed value as either MPH or FPS. I say apparently because they are really all the same formula, with different names applied to the same variables and expressed differently.

The answer to the question “So what?” takes us back to the original question of what is “30”? As has been discussed, as long as we restrict our investigations to Earth based collisions, we can call “30” a derived constant. But, if it’s a derived constant, how do we justify modifying it and changing it to “15”? If we call it a conversion factor which converts the term 2g from FPS to MPH, how do we justify saying that for the same circumstances, a vehicle skidding with all tires locked, we don’t really have 2g in the derivation, but only 1g? We could claim we are making use of the distributive property of division to divide 30 by 2 rather than taking the average of two drag factors. But if “30” is either a derived value or a derived constant, it should be held inviolate and not subject to the whims of convenience to solve a simple problem.

At this point, we may now consider the effect of rotation of the vehicle caused by dissimilar drag factors. If the dissimilar surfaces have f values which are sufficiently different, greater than about 0.20 or so, there will be rotation as the sides slow at different rates. As the vehicle rotates, it may either rotate about the vertical axis or it may both rotate and change direction. Either way with rotation comes a difference in the distance traveled by the respective tires and sides of the vehicle which means the formula using “15” and a common skid distance value is no longer valid unless one adjusts also the left and right-side skid distances which only complicates matters. This situation raises additional problems for the expert. Consider 40-foot commuter bus having a 30-foot wheelbase, skidding on two dissimilar surfaces simultaneously. Due to the dissimilar surfaces and resulting different drag factors, the bus will rotate toward the higher f value surface. Let us say left side has a 0.80, on clean dry concrete, and the right side is in mud, with an f value of 0.60.

As the bus rotates counterclockwise, the left side wheels will skid continuously on the surface with the higher resistance. If the tires do not fully lock, but enter an ABS braking event, as the bus rotates, the right front tire will depart the contaminated surface and skid a considerable distance on the dry surface while the right rear wheel assembly continues to skid on the contaminated surface. Imagine the arcs left by the vehicle similar to yaw marks. Again, I understand it is not leaving a yaw mark per se, the turn is caused by the drag factor, not a turn by the driver, and there is significant braking occurring, but it is rotating and leaving marks which superficially resemble yaws. The arc lengths will be different, with the outside arc being longer than the inside arc. Therefore, the d value will be different, invalidating the formula √(15d(f1+f2)).

For some not insignificant distance we have the left side at f = 0.80, the right side right starting at f = 0.60, then transitions to f= 0.80 and the right rear at f = 0.60 prior to departing the contaminated surface further complicating the calculation.

And what if the outside rear wheel assembly never leaves the contaminated surface?

An argument could be raised that we cannot alter the drag factor affecting the op-

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posite sides of the vehicle. This is not a valid argument.

We adjust drag factors for grade and brake loss often. By taking the average f values left and right, we are actually calculating the drag factor affecting the center of mass of the vehicle as a whole. I think I’d rather sit between those two airplane seatmates again than think about this aspect.

All this came up as I watched a hapless collision investigation expert for a local Police Department, names withheld to protect the innocent and ill prepared, testify to just such a situation. He was asked by opposing counsel to justify using “15” in his formula. He was unable to do so. He was asked what Accident Investigation or Reconstruction classes teach using 15. He was unable to do so, other than to quote a couple of published books showing S=√(15d(f1+f2)) as the solution to the problem.

After watching the Officer being shredded on the stand, his reputation, analysis, and opinion left in tatters, I began researching his technique. I understand what he did.

I have found the formula using “15” has been published in two separate derivation manuals (Parrka, (1996) pg 126 and Daily, Shigemura and Daily, IPTM, (2006) page 352). In researching this article, I asked several respected colleagues in the academic world if they were aware of any training institutions which teach the use of “15” to address this special condition. I have found only one program which teaches using S=√(15d(f1+f2)) , the US Department of Transportation, in their Advanced Problems in Bus Collision Investigation (APBCI) (Advanced Problems in Bus Collision Investigation, Formula Book, formula #7).

They choose to teach this formula, using “15” as the constant in a classroom environment to familiarize the students with a method to combine simultaneous skids on multiple surfaces. The problem with teaching this is that should a student be faced with a real-world situation which likely would include vehicle rotation as a result of dissimilar drag factors, they may believe this formula actually works. While it may work in a very narrow range of classroom situations, if the real-world collision differs, this formula will not work, and the student will not understand why. Further complicating the matter students are taught that while possible, f values above 1.0 are rare.

However using √(15d(f1+f2)) reasonable drag factors of 0.75 and 0.55 provide an f value of 1.30. This could lead to further confusion for students. They are also told “30” is a “constant” with no justification for reducing it to 15 to fit a particular situation.

To resolve this issue, and hopefully prevent any colleagues from experiencing the stressful situation the officer faced on the witness stand, I have the following recommendations: 1. The recommended explanation for the use of “30” is that it is a derived conversion factor which converts units of speed from FPS to MPH. 2. In a situation in which a vehicle skids on two surfaces simultaneously, left side and right side, the recommended formula to use is S=√(30((D1f1)+(D2f2))…)

References 1. Fundamentals of Traffic Crash Reconstruction, Daily, Shigemura, Daily, (2006) 2. University of North Florida, Institute of Police Technology 3. Handbook for the Accident Reconstructionist, M. Lofgren, University of North Florida, Institute of Police Technology 4. Equation Directory for the Reconstructionist, (1996), Daniel J. Parkka, University of North Florida, Institute of Police Technology 5. Derivations Manual for Formulas Used in Traffic Accident Investigation and Reconstruction. Wiley L. Howell, (1994) pg 58 and 62 through 68. University of North Florida, Institute of Police Technology 6. Formula Workbook Traffic Crash Investigation and reconstruction, 2nd Edition, Gary L. Stephens, (2019) pg 56. University of North Florida, Institute of Police Technology 7. Traffic Accident Reconstruction, Volume 2, Fricke, Lynn, (1990) Page 60-8. Northwestern University Traffic Institute 8. Accident Formulas, Traffic Management and Accident Investigation, United States Air Force Military Training Center, 3280 Technical Training Group, Lackland Air Force Base, Texas (1984).

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Nissan Automobile EDR Recording Characteristics David M. Hallman M.S., P.E. Billy S. Cox, Jr. Robert D. Anderson, M.S.

A

bstract In our prior work entitled, “Nissan SUV EDR Recording Characteristics.” [1] first published in Volume 14 Issue 1 of Collision Magazine, we reported on our research where we developed and executed a repeatable test method for determining Nissan’s non-deployment trigger threshold. We also evaluated/confirmed 50 Collision Magazine - Volume 16 Issue 2

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the published [2] non-deployment event recording order.

The purpose of additional testing outlined in this paper was to further evaluate the Nissan non-deployment trigger threshold, to compare the recording behavior of the previously tested Nissan SUV (Pathfinder) to Nissan passenger cars (Versa) and to further verify the Nissan recording order.

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During the prior testing with the subject 2013 Nissan Pathfinder, the event record did not include up to 45 msec of the initial crash pulse during low-speed frontal non-deployment crashes, whether the target was a second vehicle or fixed a barrier. Further, we observed that the event record missed up to 15 msec of the crash pulse in low-speed, rear event threshold crash events.

The testing conducted in this study revealed that the recording time offset found in the Nissan SUV is also exhibited in the tested passenger car. The testing conducted in this study also determined that the recording threshold for non-deployment events is 1g in less than 30msec. We verified that the tested passenger car recorded non-deployment events in the same order as the Nissan SUV evaluated during the prior testing.

Introduction Our prior published work was based on the results from a single vehicle test series using a Nissan Pathfinder SUV. At the conclusion of that testing, we pondered whether the same behavior would be observed in Nissan passenger cars. The testing described here was performed utilizing Nissan Versa passenger cars.

The prior testing also raised questions as to whether the observed recording threshold behavior is influenced by off-longitudinal axis or roll axis acceleration as all the prior test impacts were essentially aligned with the vehicle x-axis resulting in purely longitudinal accelerations.

Some of the tests described here were performed at 30 degrees and 45 degrees to the barrier.

Materials and Test Equipment The tests that are the focus of this study were conducted on two separate occasions. The first set of tests was performed in August of 2020 in Whitehall Texas. The second set of tests was conducted in advance of the 2021 SATAI crash program in Glendale Arizona in February 2021. The test vehicle in both test sets was a 2014 Nissan Versa, VIN 3N1CN7AP2EL811198, which was purchased as a used vehicle. In addition, a 2020 Nissan Versa, VIN 3N1CN8EVXLL882581, was subjected to a single car-to-car impact during the Texas test series.

A total of nine low-speed crash tests were conducted in August 2020 in Texas and ten low-speed crash tests were conducted in Arizona. The 2014 Nissan Versa was occupied by an instrumented human volunteer for all tests.

In keeping with the concept that live humans can safely be subjected rear-end and broadside impacts with deltaVs up to about 10 mph [3-15] and 20 mph delta-V frontal impacts [16, 17] all tests were planned and conducted to produce less than 10 mph delta-Vs. www.collisionpublishing.com

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In the Texas series, five tests were conducted wherein the stationary 2014 Nissan Versa was struck from behind by a moving Ford Crown Victoria. One test was a right-side impact to the Nissan Versa by the Ford Crown Victoria.

Two tests were conducted with a head-on configuration with the stationary Ford Crown Victoria being struck by the Nissan Versa. Finally, the 2020 Nissan Versa was rearended by the Ford.

In the Arizona series, three tests were conducted wherein the Nissan Versa was driven straight into a fixed barrier in the forward direction. Two tests were conducted wherein the Nissan Versa approached the barrier at 45 degrees in the forward direction with the left front making contact.

One test was conducted wherein the Nissan Versa approached the barrier at 45 degrees to barrier in the forward direction with the right front making contact.

One test was conducted wherein the Nissan Versa approached the barrier at 30 degrees to barrier in the forward direction with the right front making contact. Two tests were conducted wherein the Nissan Versa approached the barrier at 30 degrees to the barrier with the left front making contact. The final test was a vehicle-to-vehicle test wherein the subject Nissan Versa backed into the front of a stationary Chevrolet Suburban with the front bumper removed.

The same instrument package was used in all these tests.

The Nissan Versa was fitted with a tri-axial block of ICS 3031-050 (50g) accelerometers mounted to the floor near the center of gravity of the vehicle, vehicle acceleration data was collected at 10,000 Hz and filtered with an SAE Class 60 filter. Vehicle changes in velocity were calculated by integrating the area under the acceleration curve, with vehicle acceleration data filtered with an SAE Class 180 filter. All axis systems were in accordance with SAE J211 recommended practice with the X, Y, and Z axes directed forward to the right, and downward, respectively.

The volunteer was fitted with a nine-channel head array with a three-axis accelerometer mounted on the right, left and front. The volunteer was also fitted with a triaxial accelerometer affixed at the sternal notch and in the area of the L5-S1 with two-sided adhesive. Each triaxial accelerometer collected acceleration data on the X, Y, and Z axis.

All data was sampled at 10,000 Hz. Head, thorax and lumbar acceleration was filtered with an SAE 211 Class 1000 filter. Peak amplitude and time to peak amplitude were determined for the crash pulse. These data were collected with the Diversified Technical Systems (DTS) Tiny Data Acquisition System (TDAS) Pro.

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Although the biomechanical aspects of this test series were not the focus, the biomechanical response of the volunteer was captured with instrumentation. Other than receiving a bruise on his low back from the accelerometer in the last test of the Arizona series, a 7.6 mph delta-V, the volunteer (61-year-old male) reported no symptom of cervical or upper thoracic injury following the test series.

We also utilized the Racelogic Video VBOX, an IST EDR 3C – 10 G, Slam Stick S, a DTS speed trap on the ground, Garmin Virb, Garmin Virb Elite and Garmin Virb XE Action cameras. Externally, High Speed Video Cameras, DSLR Still Cameras, and various other video and still cameras were used to record each test. The ACM was imaged through the data link connecter (DLC) with the Bosch Crash Data Retrieval (CDR) kit with CDR software version 21.0 after every test to determine if an event was stored.

Tests Conducted Texas Series The first five tests were vehicle to vehicle tests conducted with the Ford Crown Victoria moving forward into the rear of the Nissan Versa. Figure 1 shows the test set-up.

The Ford Crown Victoria was driven into the rear of the Nissan Versa at increasing speeds for these five tests. The results from this testing are found in Figure 8, Chart 1. No events were stored during tests one through five.

The next test was a vehicle-to-vehicle side impact test where the Nissan Versa was struck by the Ford Crown Victoria on the right side. Figure 2 shows the test set-up.

The Ford Crown Victoria was driven into the right side of the Nissan Versa for this test. The result from this test is found in Figure 8, Chart 1. No event was stored during test six.

The next two tests were vehicle to vehicle tests conducted with the Nissan Versa moving forward into the front of the stationary Ford Crown Victoria. Figure 3 shows the test set-up.

The Nissan Versa was driven into the front of the Ford Crown Victoria at two different speeds for these two tests.

The results from this testing are found in Figure 8, Chart 1.

One non-deployment event was stored during test seven.

In test X1 the Ford Crown Victoria driven into the rear of a 2020 Nissan Versa similarly equipped to the 2014 Nissan Versa utilized for the rest of the testing described here.

This test produced a 4.1 mph delta-V but did not result in the ACM storing an event.

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Figure 1: Texas Series Test Set-up, Tests 1 through 5.

Figure 2: Texas Series Test Set-up, Test 6. www.collisionpublishing.com

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Figure 3: Texas Series Test Set-up, Tests 7 and 8. are found in Figure 9, Chart 2. Test 3 resulted in a stored non-deployment event.

Arizona Series

The first three tests were vehicle to concrete barrier tests conducted with the Nissan Versa moving forward. The The next three tests (Tests 4 through 6) were angled vehicle Nissan Versa was idled into a concrete barrier. Figure 4 to concrete barrier tests in the forward direction and 45 shows the test set-up. degrees to the barrier. The Nissan Versa was idled into a stationary concrete barrier. Figure 5 shows an angled barThe Nissan Versa was allowed to roll in at idle from in- rier test set-up. creasing distance from the barrier and therefore increasing speeds for these three tests. The results from this testing

Figure 4: Arizona Series Test Set-up, Tests 1 through 3.

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Figure 5: Arizona Series Test Set-up, Tests 4 through 6.

Figure 6: Arizona Series Test Set-up, Tests 7 through 9.

The Nissan Versa rolled in at idle from increasing distance from the barrier for these tests. The accelerator was not applied. Some of the results from this testing are found in Figure 9, Chart 2. None of these tests resulted in stored events.

The next three tests (Tests 7 through 9) were also vehicle to barrier tests, in the forward direction and 30 degrees to the barrier. The Nissan Versa was idled into the stationary concrete barrier. The photo in Figure 6 shows the test set-up.

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The Nissan Versa rolled in at idle from increasing distance for these tests. The results from this testing are found in Figure 9, Chart 2. Test 9 resulted in a stored non-deployment event.

of this article. The maximum longitudinal acceleration reported is the Class 180 filtered peak from the accelerometer connected to the TDAS. The longitudinal delta-V was calculated from the filtered TDAS acceleration data and the EDR delta-V was reported directly from the imaged The final test (Test 10) was a vehicle-to-vehicle test. The data as listed in the System Status at Event Chart in each Nissan Versa was driven into a stationary Chevrolet Sub- EDR report. urban in reverse. The front bumper had been removed from the Suburban for a prior test. The photo in Figure 7 Results shows the test set-up.

Texas Series The Nissan Versa was driven into the front of the Suburban in reverse for this test. The Nissan Versa was placed This series resulting in a single non-deployment event on a curb to align the bumper of the Nissan Versa with which occurred during test 7. This test is highlighted in the bumper supports on the front of the Suburban. The Figure 8, Chart 1 below. As this was the first time an event results from this test are found in Figure 9, Chart 2. Test was stored in this vehicle, it was stored in Event Record 1.

10 resulted in a stored non-deployment event.

Methods Vehicle speed reported in the Arizona Series is the approach speed of the Nissan Versa measured with a speed trap placed on the ground immediately prior to the impact with the barrier or the front of the Chevrolet Suburban.

Vehicle speed reported in the Texas series is either of the Ford Crown Victoria or the Nissan Versa depending on the test. This is detailed in the Tests Conducted section

In test 7, the EDR-reported longitudinal delta-V was -6 mph but the calculated longitudinal delta-V from the acceleration data was -6.8 mph.

Arizona Series The first three tests resulted in a single non-deployment event which occurred during Test 3. This test is highlighted in yellow in the Figure 9, Chart 2. As this was the second event stored in this vehicle, it was stored in Event Record 2.

Figure 7: Arizona Series Test Set-up, Test 10.

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Figure 8: Chart 1, Texas Series Test Results, Tests 1 through 8 and X1.

Figure 9: Chart 2, Arizona Series Test Results, Tests 1 through 10.

In test 3, the EDR-reported longitudinal delta-V was -4 mph but the calculated longitudinal delta-V from the acceleration data was -5.5 mph.

Analysis

Tests 4 through 10 resulted in a two non-deployment events which occurred during Tests 9 and 10. These tests are highlighted in yellow in Figure 9, Chart 2.

Test 7, Non-deployment Event 1 in this series

In Test 9, the EDR-reported longitudinal delta-V was -4 mph, the reported lateral delta-V was 1 mph and the calculated delta-Vs from the IST acceleration data were -5.3 mph and -0.9 mph. The test 9 event overwrote the Texas Series Test 7 event in Event Record 1.

In Test 10, which was conducted in reverse, the EDR-reported delta-V was 6 mph and the calculated delta-V was 7.6 mph. The Test 10 event overwrote the Arizona Series Test 3 event in Event Record 2.

Texas Series

Test 7 was the only non-deployment event which was recorded during the Texas test series. This test was part of the crash series of the Nissan Versa straight into the Ford Crown Victoria. As there were no stored events, the event data was written in Event Record 1 in the ACM. The maximum EDR-reported longitudinal delta-V from this event was -6 mph. The longitudinal delta-V calculated from the IST measured and filtered acceleration was -6.8 mph. In reviewing the individual acceleration data points in the EDR data (Figure 10) with a sample rate of 10 Hz, the first recorded data point was found to be at -3 G as opposed to zero.

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When the EDR acceleration data from Test 7, Event 1 is compared to the measured acceleration data (Figure 11) there is an offset of approximately 53 msec between the start of the crash as recorded by the IST accelerometers and the start of the recorded EDR acceleration. This offset was determined by finding the location in the IST acceleration data which matched the first ACM recorded acceleration data. This offset accounts for the difference between the EDR-reported delta-V and the calculated delta-V. The offset resulted in an EDR-reported delta-V below the 5 mph 49CFR563 trigger threshold, when the actual vehicle delta-V was greater than the part 563 trigger threshold at -6.8 mph.

Arizona Series Test 3, Non-deployment Event 1 in this series Test 3 was the first non-deployment event which was recorded during the Arizona test series. This test was part of the crash series of the Nissan Versa straight into the concrete barrier. Due to a pre-existing stored event which occurred during the Texas series of tests, the event data was written in Event Record 2 in the ACM. The maximum EDR-reported delta-V from this event was -4 mph.

The delta-V calculated from the IST measured and filtered

acceleration was -5.3 mph. In reviewing the individual acceleration data points in the EDR data (Figure 12) sampled at 10 Hz, the first recorded data point was found to be at -3 G as opposed to zero.

When the EDR acceleration data from Test 3, Event 1 is compared to the measured acceleration data (Figure 13) there is an offset of approximately 57 msec between the start of the crash as recorded by the IST accelerometers and the start of the recorded EDR acceleration. This offset was determined by finding the location in the IST acceleration data which matched the first ACM recorded acceleration data. This offset accounts for the difference between the EDR-reported delta-V and the calculated delta-V. The offset resulted in an EDR-reported delta-V below the 5 mph 49CFR563 trigger threshold, when the actual vehicle delta-V was greater than the part 563 trigger threshold at -5.3 mph.

Test 9, Non-deployment Event 2 Test 9 was the second non-deployment event which was recorded during the Arizona test series. This test was part of the angled Nissan Versa front end to barrier series. The event data for Test 9 was written into Event Record 1 in the ACM, overwriting the first event recorded in the Texas

Figure 10: Texas Test 7, Event 1 EDR Longitudinal Acceleration.

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Figure 11: Texas Test 7, Event 1 EDR Acceleration Data Offset.

Figure 12: Arizona Test 3, Event 1 EDR Longitudinal Acceleration www.collisionpublishing.com

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Figure 13: Arizona Test 3, Event 1, EDR Acceleration Data Offset.

series Test 7. The event generated in Test 3 was still present in Location 2. The maximum EDR-reported longitudinal delta-V from the Test 9 event was -4 mph. and the lateral was 1 mph. The longitudinal delta-V calculated from the IST measured and filtered acceleration for Test 9 was -5.3 mph and the lateral was -0.9 mph. In reviewing the individual acceleration data points in the EDR data for Test 9, the first EDR recorded acceleration data point was found to be at -4.5 G as opposed to zero.

When the EDR acceleration data from Test 9, Event 2, is compared to the measured acceleration data (Figure 14), there is an approximately 40 msec offset between the start of the crash as recorded by the IST and the start of the recorded EDR data meaning that the ACM did not record the first 40 msec. Again, this accounts for the difference between the EDR delta-V and the delta-V calculated from the filtered and processed accelerometer data.

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A comparison of the first 30 msec of IST recorded longitudinal acceleration data for Test 8 and Test 9 (Figure 15) shows that the difference between setting and not setting a non-deployment event. The Test 8 longitudinal acceleration does not get to 1 G in the first 30 msec of the crash.

The Test 9 longitudinal acceleration exceeds 1 G at approximately 29 msec. Test 8 did not set a non-deployment event and Test 9 did. Based on this test, it appears that the Nissan Versa needs to exceed 1 G in the first 30 msec of the crash to set a non-deployment event.

It is important to note that the data in Figure 15 represents IST data and not EDR recorded acceleration data. This would appear to indicate that the determination whether or not to record is made prior to any actual recording by the ACM in the lag time which has been documented through this testing.

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Figure 14: Arizona Test 9, Event 2, EDR Acceleration Data Offset.

Figure 15: Comparison of Acceleration Data from Arizona Test 8 and Test 9. www.collisionpublishing.com

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Test 10, Non-deployment Event 3 Test 10 was the third and final non-deployment event which was recorded during the Arizona test series. This test was a vehicle-to-vehicle test with the Nissan Versa backing into a Suburban. The non-deployment event data was written into Event Record 2 in the ACM and replaced the non-deployment event data from Arizona Series Test 3.

The maximum EDR-reported longitudinal delta-V from this event was 6 mph. The delta-V calculated from the IST acceleration was 7.6 mph. In reviewing the individual acceleration data points in the EDR data sampled at 10 Hz, the first recorded data point was found to be at 11 G as opposed to zero.

explains the difference between the EDR-reported longitudinal delta-V of 6 mph, and the 7.6 mph longitudinal delta-V calculated from the accelerometer recorded value.

The time duration of the missed data for Test 10, Event 3 is less than the forward crashes. This is reasonable as the EDR measured acceleration at algorithm enable was 11 Gs as opposed to the 3.5 or 5G that were seen in the nondeployment events set in the forward direction. The higher accelerations were due to several factors regarding this crash. The vehicle approach speed was higher than prior tests at 7.9 mph and the rear of this vehicle was found to have a higher stiffness than the front of the vehicle. The acceleration from the rearward impact increased more rapidly due to the combination of the higher speed and increased vehicle stiffness.

When the EDR acceleration data from Test 10, Event 3 is compared to the measured acceleration data (Figure 16), there is an approximately 17 msec offset between the start Conclusions of the crash as recorded by the IST accelerometer and the start of the recorded EDR data. The ACM did not re- The initial purpose of testing in “Nissan SUV EDR Record roughly 17 msec of the initial acceleration data. This cording Characteristics” was to determine the minimum non-deployment event recording threshold for Nissan

Figure 16: Arizona Test 10, Event 3, EDR Acceleration Data Offset.

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vehicles. Based on previously collected case related EDR data, this threshold appeared to be less than the 5 mph or 8 kph described in 49CFR563. In the subsequent research, two non-deployment events were stored with an EDRreported longitudinal delta-V of -4 mph. However, those events were found to have an on-board accelerometer measured and calculated longitudinal delta-V of -5.5 mph and -5.3 mph. Based on that data and the testing described here, the minimum event recording threshold still appears to be 5 mph or 8 kph on the longitudinal axis in both the forward and reverse direction for this vehicle. Therefore, the longitudinal accelerations and resulting delta Vs seem to be under reported. During this continued testing, no non-deployment events with zero acceleration or zero delta-V were stored. The testing in this analysis included longitudinal and angled testing at 30 degrees and 45 degrees.

that would reach a Delta V of 5 mph. In other words, predictive, just like airbag deployments.

The testing in this research also revealed that, in order to record an event, the tested Nissan Versa had to be subjected to a minimum of 1 G acceleration within the first 30 msec of the crash pulse. If that threshold is not met, no event is stored by the ACM.

Glossary

During the testing conducted for this research, it was confirmed that the event recording order for Nissan Passenger cars is the same as the previously tested Nissan SUV and follows the data limitations in the EDR report. The oldest event is overwritten by a new event. If an event is stored as “Event Record 1” and “Event Record 2” is more recent, “Event Record 1” is overwritten by a new non-deployment event. In the Texas series, Test 7 was recorded as “Event Record 1” and in the Arizona series, Test 3 was recorded as “Event Record 2”. Arizona Test 9, the third event to meet the recording threshold, became “Event Record 1” overwriting Texas Test 6 and Arizona Test 10, the fourth event to meet the recording threshold, became “Event Record 2” overwriting Arizona Test 3.

Also, as seen in the prior testing with the Nissan Pathfinder, it was also observed in this testing that the ACM does not record the start of the crash pulse during a low-speed non-deployment event. In the longitudinal and angled low-speed frontal non-deployment event setting crashes into a second vehicle and into a barrier, the ACM did not record up to 57 msec of the crash pulse and in low-speed rear non-deployment event setting crash the ACM did not record 17 msec of the crash pulse.

The behavior of the Nissan EDR function in both testing and case work is consistent with a system that does not record an event based upon reaching a 5 mph Delta V, but rather one that records an event when the first detected but unreported accelerations are consistent with an impact

This, coupled with the fact that some of the initial accelerations are unreported, could provide an explanation for why we observe the 0 DV events in practice, but we have not yet been able to replicate in testing. It could also provide an explanation for the correlation between event recording and how quickly the crash pulse reaches a particular level.

Acknowledgements The authors wish to thank SATAI for providing a location for this testing and Wesley Vandiver, Michael Rosenfield and Michelle Hoffman for their assistance during testing.

Thanks also to any others whom the authors may have missed in these acknowledgements.

ACM – Airbag Control Module CDR – (the) Crash Data Retrieval (Tool) delta-V – Vehicle velocity change during impact EDR – Event Data Recorder SATAI – Southwestern Association of Technical Accident Investigators SUV – Sports Utility Vehicle TDAS – Tiny Data Acquisition System by DTS VBOX – Noncontact speed data collector by Racelogic DLC – Data Link Connector DTS – Diversified Technical Systems SAE – Society of Automotive Engineers TDAS – Tiny Data Acquisition System IST – Instrumented Sensor Technology (Accelerometers) VIN – Vehicle Identification Number References 1. Hallman DM & Cox BS, “Nissan SUV EDR Recording Characteristics,” Collision-The International Compendium for Crash Research, Vol 14, Issue 1, 2020.

2. Nissan Data Limitations, Bosch CDR Report

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3. Szabo TJ and Welcher JB, “Human Subject Kinematics and Electromyographic Activity During LowSpeed Rear Impacts,” SAE paper 962432, Proceedings of the 40th Stapp Car Crash Conference, Albuquerque, NM, November 1996.

4. McConnell WE, Howard RP, Poppel JV, Krause R, Guzman HM, Bomar JB, Raddin JH, Benedict JV, and Hatsel CP, “Human Head and Neck Kinematics After Low Velocity Rear-End Impacts - Understanding ‘Whiplash’,” SAE Paper 952724, Proceedings of the 39th Stapp Car Crash Conference, San Diego, CA, November 1995.

5. West DH, Gough JP and Harper GTK, “Low Speed Rear-end Collision Testing Using Human Subjects,” Accident Reconstruction Journal, May/June 1993.

6. Szabo TJ and Welcher JB, “Human Subject Responses to Various Acceleration Fields,” Presented at the LowSpeed Collision TOPTEC”, Society of Automotive Engineers, Vancouver, BC, August 1996.

7. Meyer S, Weber M, Castro W, Schilgen M and Peuker C, “The Minimal Collision Velocity for Whiplash,” in Whiplash Injuries: Current Concepts in Prevention, Diagnosis and Treatment of Cervical Whiplash Syndrome, Robert Gunzberg and Marek Szpalski, ed., Lippencott-Raven, Philadelphia, 1998.

8. Mills D & Carty G, “Comparative Analysis of LowSpeed Live Occupant Crash Test Results in Current Literature,” Proceedings of the Canadian Multidisciplinary Road Safety Conference XIV; June 27-30, 2004; Ottawa, Ontario.

ings of the 8th Stapp Car Crash and Field Demonstration Conference, October 1964.

13. Zaborowski AV, "Lateral Impact Studies - Lap Belt Shoulder Harness Investigations," SAE Number 650955, Proceedings of the 9th Stapp Car Crash and Field Demonstration Conference, 1965.

14. Ewing JL, Thomas DJ, Lustik L, Muzzy WH, Willems GC and Majewski P, "Dynamic Response of the Human Head and Neck to +Gy Impact Acceleration," SAE Number 770928, Proceedings of the 21st Stapp Car Crash Conference, 1977.

15. Furbish C., Welcher J., Brink J., Jones B., Swinford S & Anderson RD, “Occupant Kinematics and Loading in Low-Speed Lateral Impacts,” SAE Technical Paper 2019-01-1027, 2019, doi:10.4271/2019-01-1027.

16. Wagner R, “A 30 mph Front/Rear Crash with Human Test Persons,” SAE Paper 791028, Proceedings of 23rd Stapp Car Crash Conference, Society of Automotive Engineers, 1979.

17. Vandiver W & Anderson RD, “Analysis of Crash Data from a 2012 Hyundai Genesis Coupe Event Data Recorder,” Society of Automotive Engineers, Paper 2021-01-0905.

18. Anderson RD & Vandiver W, “Analysis of the Event Data Recorder Information Obtained in Crash Testing of Supported and Pre-Supported Hyundai Vehicles: a 2015 Elantra Sedan and a 2012 Genesis Coupe,” Collision-The International Compendium for Crash Research, Vol 16, Issue 1, 2022.

9. Haight, W. R., Szabo, T. J., Collision Reconstruction for the Medical Practitioner, Texas A&M University, Texas Engineering Extension Service (TEEX), 19982000 10. Lam, T. and Ivarsson, B., "Vehicle Rear Impacts and Spinal Disc Herniations in Occupants: Is there a Basis for Causation?" SAE Paper 2017-01-1458, 2017, doi:10.4271/2017-01-1458.

11. Cormier J, Gwin L, Rienhart L, Wood R & Bain C, “A Comprehensive Review of Low-Speed Rear Impact Volunteer Studies and a Comparison to Real-World Outcomes,” Spine, DOI: 10.1097, PMID 29489567, ISSN 0362-2436, Feb 2018.

12. Zaborowski AV, "Human Tolerance to Lateral Impact with Lap Belt Only," SAE Number 640843, Proceed-

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The Lost Energy of Planar Impact Mechanics Micky Marine SSi Phoenix, Inc.

P

lanar impact mechanics (PIM), as applied to automobile accident reconstruction, comprises a number of various formulations that have been presented in the open literature (Brach [1], Woolley [2], Ishikawa [3], Smith [4], Steffan & Moser [5], etc.).

PIM formulations have an appeal to accident analysts in that they provide algebraic solutions to non-collinear and eccentric automobile impact configurations. There has been an ongoing interest in breaking down the energy loss that can be calculated within PIM methods to terms that relate to crush energy (volume strain) and energy dissipation due to sliding, shearing, entanglement, etc. Brach has presented equations that separate energy loss into normal 66 Collision Magazine - Volume 16 Issue 2

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and tangential contributions, and Carpenter & Welcher [6] have expanded on this, presenting equations, for what they call isotropic conditions, that further separate the energy loss into volume strain and surface sliding categories. In this article, we will delve into PIM energy loss by examining what constitutes isotropic and anisotropic conditions, presenting examples of each in impulse space and relative velocity-impulse component diagrams. Additionally, the derivation of various forms of energy loss equations that can be derived from the PIM formulations are evaluated with an eye toward the effects Newton’s kinematic and Poisson’s kinetic restitution hypotheses have on them.

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Assumptions and Energy Loss Equations The assumptions that underly the PIM formulations typically used in automobile accident reconstruction are: •

PIM is based on rigid-body mechanics – vehicle masses and moments of inertia do not change

•

The distributed forces acting on the respective vehicles in the contact region are resolved to an impulse acting at a single point (herein called the impulse center (IC) – see Figure 1)

•

The impulse acting on each vehicle occurs instantaneously

•

Due to the instantaneously applied impulses, changes in vehicle velocities are discontinuous

•

The impulses induce negligible displacement and rotation of the involved vehicles (i.e., the IC is fixed relative to the respective vehicles)

•

Deformation of the respective vehicles is not modeled and is considered negligible

•

Tire forces and other external forces are assumed to be negligible

In addition to the above assumptions, two constraint relationships are necessary in order to solve the set of PIM equations that result from the derivation of the equations of motion. These constraints are typically in the form of a restitution constraint (εN) along a normal axis and a constraint applied orthogonal to the normal axis (a tangent axis), often in the form of an impulse ratio (µ), a slip ratio (σ) or a tangential restitution (εT).

Figure 1: Planar Impact Mechanics Diagram www.collisionpublishing.com

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Figure 2: Planar Impact Mechanics Conceptualization The orientation of the normal-tangent axis is selected by the analyst. Conceptually, PIM models reduce the complex, time-varying interaction that occurs in the contact region of an automobile collision (left panel of Figure 2) to a single point of instantaneous impulse exchange between rigid, non-deformable bodies like that of the right panel of Figure 2.

The various forms of the energy loss equation that can be derived from PIM are based on the fundamental conservation of energy concept where work done on the system due to vehicle interaction is equal to the difference between the pre- and post-impact kinetic energies. This well-understood equation is shown in Equation (1) where pre-impact values are designated by upper-case and post-impact values by lower-case: Equation (1):

Using Equation (1) and various algebraic relationships that are part of PIM formulations, energy loss can be expressed in a number of different ways. One of which is (using Brach’s nomenclature): Equation (2):

This is a rather cryptic-looking version of the energy loss equation with mass/inertia terms and IC location terms concealed within the various parameters. It nonetheless illustrates that IC constraint values (here a normal restitution and an impulse ratio) figure prominently in the determination of energy loss.

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(a2 – b2) = (a + b)(a – b), and applying it to Equation (1) leads to the derivation of Equation (3). Equation (4) contains rewrites of Equation (3) using IC constraint values; Newton’s kinematic restitution in both cases and a slip ratio in one case with Ishikawa’s tangential restitution in the other. Equation (3) was presented by Brach et al [8], [9] and discussed in regard to correlating normal and tangential energy contributions to physical work processes where normal energy loss contributions were related to crush energy normal to vehicle surfaces, and tangential energy loss contributions were related to forces developed from sliding, shearing, and entanglement of vehicle components.

Brach et al. [9] explained, however, that “The energy partitioning process…, is intuitive, and does not follow directly from any principle in mechanics,” and also noted in reference [1] that energy is not a vector that can be split out into discrete components, but as an approximation, the normal and tangential energy loss contributions can be apportioned as “normal effects” and “tangential effects.”

Equation (3):

Equation (4):

Equation (5) was developed by Carpenter & Welcher [6] starting with Brach’s energy partitioning equation and employing various algebraic PIM relationships to arrive at a partitioning equation based on initial relative velocities and impulse and slip velocities at “termination of closure” (i.e., maximum compression). Carpenter and Welcher identify the first term as being specifically due to volume strain energy dissipation (plastic deformation) and the second term due to surface sliding energy dissipation. In Equation (5),

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a “C” in the subscript indicates values calculated at maximum compression: Equation (5):

Yet another form of the energy loss equation is shown in Equation (6). An inspection of this equation reveals that, for a given energy loss value, it forms an ellipse in impulse space. Because of the PNPT cross-term, this ellipse is a skewed ellipse, meaning that the major axis is not generally parallel with either the PN or PT axis. For a given collision configuration and impulse ratio, concentric ellipses representing particular energy loss values can be formed with larger energy losses represented by smaller ellipses.

The limit to this is that the maximum energy loss for a given impact configuration is the point at the center of the concentric ellipses. This maximum-energy-loss point occurs when the coefficient of restitution is zero and there is no sliding velocity present at the end of the collision (i.e., where the impulse ratio is Brach’s critical value, and both the slip ratio and tangential restitution are zero).

Equation (6):

Impulse Space At this point, a brief review of diagramming PIM solutions in impulse space will be helpful. For additional discussion on impulse space the reader is directed to reference [10].

A useful set of equations for plotting solutions in impulse space are those that can be derived from each of the various PIM models discussed herein. They are, using Brach’s nomenclature: Equation (7):

mental lines that can be defined in impulse space from these equations are the Maximum Compression Line and the No Sliding Line. The Maximum Compression line is defined by setting the post-impact relative normal velocity at the IC to zero in Equation (7), and the No Sliding Line is defined by setting the post-impact sliding velocity at the IC to zero in Equation (8). The intersection of these two fundamental lines defines the impulse space solution where a common velocity exists at the IC (i.e., there is no relative velocity at the IC in either the normal or tangential direction). This common velocity solution is depicted as Point A in Figure 3 and is the maximum energy loss solution discussed above. Also indicated in Figure 3 are the effects of the IC normal and tangential constraint values. For instance, a solution with a positive-valued normal restitution, and a positive-valued slip ratio (or a negative-valued tangential restitution) will place the solution in the upper left quadrant of the figure where the PIM result includes a rebound velocity in the normal direction and continued sliding (i.e., same direction as initial sliding velocity) in the tangential direction at the end of impact.

Carpenter & Welcher [6] stated that their energy loss analysis was limited to only isotropic solutions where the normal and tangential restitution are the same, and that anisotropic PIM energy loss analyses were open for further study. To this author’s knowledge, this is the first known reference to distinctions between isotropic and anisotropic PIM solutions and warrants a further look. In the formulation presented by Carpenter & Welcher there are two designated PIM approaches based on whether an impact configuration is deemed non-sliding (synonymous with the PC-Crash Full-Impact [5]) or sliding (PC-Crash has one of these too). In the non-sliding PIM model, there is no relative velocity present between the two vehicles in either the normal or tangential direction at the IC at maximum compression. As discussed in reference [11], there is a characteristic impulse ratio that defines the non-sliding impact configuration, and, if used with the sliding model, will provide the same solution as that of the non-sliding model. This is expressed in Brach’s nomenclature [1] as: Equation (9):

Equation (8):

These equations define lines in impulse space, the intersection of which identifies the solution for a given set of initial velocity and impact configuration inputs. Funda-

Ishikawa [3] formulated a PIM solution through the use of a tangential restitution value which could take on values different than the normal restitution value; hence, this formulation was classified as anisotropic by Carpenter & Welcher. An impulse ratio was derived in terms of the nor-

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Figure 3: Impulse Space Features. mal and tangential restitution values, expressed in Ishikawa’s nomenclature, as: Equation (10):

This was reformulated in Brach’s nomenclature in reference [11] as: Equation (11):

We can see in Equation (11) that if the tangential restitution is set to zero (i.e., no sliding at the end of impulse), the equation reduces directly to Brach’s critical impulse ratio [1]. Furthermore, if the normal and tangential restitu-

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tion coefficients are both zero, or are made equal to one another, the restitution terms will cancel and we end up with the same impulse ratio as that of Equation (9). As it happens, Ishikawa went through this very exercise and called the resulting impulse ratio a Generalized Impulse Ratio (GIR). Carpenter & Welcher state that isotropic restitution is “where a single restitution coefficient applies to both the normal and tangential directions,” and “Satisfying Eq. (6a) and Eq. (6b) simultaneously corresponds with isotropic restitution.” Where Equation (6a) in reference [6] is Ishikawa’s tangential restitution and Equation (6b) is Newton’s kinematic normal restitution. Therefore, according to this definition, for a given impact configuration, it is the GIR that serves as the limiting boundary for the non-sliding/PC-Crash Full-Impact solution (Virtual CRASH employs this boundary as well [12]) that defines the line containing the PIM isotropic solution locus.

Back to Energy Loss For PIM formulations typically used in automobile accident reconstruction, Newton’s restitution hypothesis ap-

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plied in the normal direction leads directly to Poisson’s restitution hypothesis applied to both the normal and tangent impulse components (see Appendix A). Though a Poisson restitution hypothesis is applied to both the normal and tangential impulses, this does not constitute an isotropic PIM condition. A constraint on the relative velocities along the tangent axis is still needed to determine a PIM solution, and it is this constraint (e.g., a tangential restitution, etc.) that determines whether a PIM configuration is isotropic or anisotropic in the Carpenter-Welcher definition.

With the isotropic solution space having been defined to simply be a line in impulse space, with anisotropic solutions everywhere else, we can see that the PIM formulations commonly used in accident reconstruction analyses ([1], [3], [4], [5]), other than the PC-Crash Full Impact (Carpenter & Welcher non-sliding), include anisotropic solution space. For a given impact configuration, it is only for a set of specific IC constraints that isotropic solutions are found; which all of the PIM formulations mentioned herein can accommodate. The non-sliding/PC-Crash Full-Impact/Virtual CRASH bounded formulations are

really “stick”-and-reversed-slide solutions along the GIR Line that disallow solutions for impulse ratios greater in magnitude that the GIR - i.e., they do not allow solutions in which sliding ceases prior to maximum compression.

Example solutions on an isotropic locus line are presented in Figure 4. This example is based on the PIM analysis for NHTSA test #4363 discussed by Rose et al, [13] and then

by Marine [10]. The four solutions indicated in this figure (red diamonds) demonstrate the changing locations along the GIR Line (isotropic locus) for increasing restitution (0.0 to 0.3). Also included in the chart is a listing of the effects of “walking up” the GIR Line. As the restitution is increased, the solution moves up the GIR Line, the energy ellipses become larger indicating decreasing total energy loss, and the reversed sliding velocity becomes larger. Importantly, for every solution that lies on the GIR Line, the sliding velocity at maximum compression is zero and, according to the Carpenter-Welcher formulation, all energy loss is attributed to volume strain dissipation.

For examples of anisotropic solutions, we again use the PIM analysis of NHTSA Test #4363. In Figure 5, three

Figure 4: Solutions Along the GIR Line. www.collisionpublishing.com

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Resultant Impulse Circle (RIC) solutions discussed in reference [10] are plotted in impulse space. As discussed in reference [10], each of these solutions is based on the same impact configuration and IC location, and provide identical solutions in terms of post-impact velocities, yaw rates, resultant impulse vector, and total energy loss. The only difference between the three solutions is the normaltangent axis orientation and the restitution and tangent constraint values necessary to produce the identical postimpact results. The baseline solution, provided in reference [13], is the “55 Degrees” solution indicated in Figure 5. The other two solutions indicated in the figure are for normal-tangent axis orientation changes of ± 10 degrees.

The Maximum Compression, No Sliding , and GIR Lines for each solution are indicated (shortened to minimize clutter in the figure) by the blue, green, and orange lines,

respectively. The total energy loss ellipses for each solution are also indicated in Figure 5, and, since each solution results in the same total energy loss, the ellipses are similarlyshaped. While the total energy loss is the same for each of the three RIC solutions (274,140 ft-lbf ), the Carpenter & Welcher total volume strain dissipated energy and sliding dissipated energy values for the three solutions are different for each of the normal-tangent axis orientations. For example, the total volume strain dissipation energy loss was approximately 262,500 ft-lbf, 254,200 ft-lbf, and 243,400 ft-lbf, for the 45 Degrees, 55 Degrees, and 65 Degrees orientations, respectively. For a given vehicle collision, the actual total volume strain (crush energy) resulting from that collision is, of course, indifferent to an analyst’s selection of a normal-tangent axis orientation.

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Of additional note in Figure 5 is the location of the solutions (red diamonds) relative to the respective No Sliding Lines. The 55 Degree solution, being based on the critical impulse, lies on the No Sliding Line whereas the 45 Degree solution lies on the reversed-sliding side of the No Sliding Line and the 65 Degree solution on the continuedsliding side of the No Sliding Line. Including the GIR Line solutions described above, we have four potential solution cases: •

Case A: No sliding at maximum compression; reversed sliding at end of impulse (GIR Line)

•

Case B: Sliding at maximum compression; reversed sliding at end of impulse

•

Case C: Sliding at maximum compression; no sliding at end of impulse (No Sliding Line)

•

Case D: Sliding at maximum compression; continued sliding at end of impulse

An example of the regions in impulse space for each solution case is shown in Figure 6. The solution space for Case A is along the GIR Line; the solution space for Case B is the region between the GIR Line and the No Sliding Line (not including either of the lines); the solution space for Case C is the No Sliding Line (critical impulse solutions); and the solution space for Case D is the region on the continued-sliding side of the No Sliding Line (not including this line) and above, and including, the Maximum Compression Line.

Examples of these four solution cases are depicted in the velocity-impulse (V-P) space diagram of Figure 7 where the normal and tangential sliding velocities are plotted against their respective impulses. The energy loss for each case is simply the sum of the areas under each line. The derivation of the energy loss equation for Case D is provided in Appendix B. The dashed line in Figure 7 identifies the location of maximum compression for the normal impulse as a reference for the tangential V-P space diagrams. Keep in mind, when looking at Figure 7, that though a finite elapsed time to progress from the initial relative velocity

Figure 6: Four Solution Cases in Impulse Space www.collisionpublishing.com

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Figure 7: Relative Velocity vs. Impulse Diagrams state to the final relative velocity state might be inferred, this is not the case. A fundamental assumption in PIM formulations is that changes from the initial velocity state to the final velocity state occur instantaneously (i.e., discontinuously) in the time domain.

The resulting equation from the Appendix B derivation for Case D is: Equation (12):

This is the energy loss equation developed by Carpenter & Welcher with the first term as their volume strain dissipated energy, and the second term their surface sliding dissipated energy (Equations (21) and (20), respectively, in reference [6]). It is a relatively straightforward exercise to show that Equation (12) is valid for all four solution cases.

The only relevant distinction between “isotropic” and “anisotropic” restitution then is simply that, for solutions along the GIR Line, the maximum compression sliding velocity is always zero and the energy loss equation simplifies to: Equation (13):

It is interesting to note that if we plot the surface sliding energy loss term of Equation (12) on a V-P diagram for Case B it comprises Area 2 and Area 3 (left panel of Figure 8). Area 3, however, is not a region that resides under the sliding line and must be subtracted out for an energy loss

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calculation. Additionally, due to the sign of vrT for this case, Area 4 is a “negative area” and is effectively subtracted out as well. Through algebraic rearrangement, and the fact that Poisson’s restitution acts on the tangential impulse, the calculation for Area 3 and Area 4 combined can be made to have an εN2 factor and it is then collected in the so-called volume strain dissipated energy term of Equation (12). We end up with the Carpenter-Welcher tangential volume strain energy loss calculated as Area 1 minus Area 3 minus Area 4, and the surface sliding energy loss as Area 2 plus Area 3 (right panel of Figure 8). Therefore, not only is the reversed-sliding area (Area 4) designated as a volume strain energy restoration, so is the virtual area (Area 3). Consequently, to arrive at Equation (12), an area not under the sliding line is added to one term and subtracted from another. An inspection of the tangent V-P diagrams of Figure 8 reveals that this situation also exists for Cases C and D, and arises as a matter of algebraic semantics rather than the effect of a particular physical process.

While deriving equations, and laying out impulse-space and V-P diagrams is both fun and interesting, what are we dealing with in a practical sense (refer to both Appendix A and B to see what additional interesting fun can be had using a tangential restitution)? In Figure 9 the tangential V-P diagram (left panel) for two fairly similar PIM solutions (impulse vectors shown in the right panel of Figure 9) for the same impact configuration are plotted to scale. One of the solutions is a GIR Line solution with a coefficient of restitution set to zero (a Case A solution), while the other solution is based on the critical impulse ratio (a Case C solution). At the end of impulse, the initial sliding velocity of 42.7 mph is brought to zero for both solutions. In this example, the GIR Line solution dissipates approximately 87,000 ft-lb of tangential energy with all of it attributed to volume strain dissipated energy (Equation (13)). The

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Figure 8: Area Sections for the Case B Tangential Energy Loss Calculation

Figure 9: V-P Diagram and Impulse Vectors for Comparison Solutions critical impulse solution dissipates approximately 88,000 ft lb of tangential energy with 82% of that attributed to volume strain and the remaining 18% attributed to surface sliding dissipated energy (Equation (12)). This is a rather significant difference in energy loss allocation for two PIM solutions in which the same initial sliding velocity is brought to rest with similar, instantaneously applied, tangent impulses.

The above example tells us one of two things: Either (1) PIM formulations have within them a remarkable capability to discern specific energy loss mechanisms; or (2) they don’t. Whereas much non-accident reconstruction literature related to planar impact mechanics considers deformations to be small and local to the IC, in accident reconstruction-related applications, it is the complex inter-vehicular interaction occurring in larger-scale crush regions that is reduced to impulses acting instantaneously at a single point that is fixed relative to the respective vehicles.

The coefficient of restitution is employed in PIM formula-

tions as a simplifying constraint parameter applied at that point. In the formulations typically used in accident reconstruction, Newton’s kinematic hypothesis and Poisson’s kinetic hypothesis (applied to the resultant impulse vector), are, as shown in Appendix A, a complementary set – to invoke one leads to the other. Does this then mean that, by virtue of invoking a relative velocity constraint in the normal direction, we get the added benefit of being able to discern whether energy loss due to tangent impulse work is of a particular physical process? This would be exceptionally fortuitous, and highly unlikely. While the coefficient of restitution is a simplifying parameter that has proven useful in facilitating analytical impact solutions, it has nonetheless been noted to be of “questionable” and “doubtful” fundamental significance [14], [15]. Engineering judgement is in the mind of the beholder, of course, and the reader may well disagree, but to expect algebraic PIM formulations to accurately determine automobile collision energy loss due to specific physical processes, vis-

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à-vis the application of a coefficient of restitution, is to ascribe them more sophistication than they possess.

References

13. Rose, N., Fenton, S., and Beauchamp, G., “Restitution Modeling for Crush Analysis: Theory and Validation,” Society of Automotive Engineers Paper No. 2006-01-0908, 2006.

1. Brach, R. & Brach, M., “Vehicle Accident Analysis and Reconstruction Methods,” Society of Automotive Engineers, Warrendale, PA, 2005.

14. Goldsmith, W., “Impact: The Theory and Physical Behavior of Colliding Solids,” Edward Arnold Publishers, Ltd., London, 1960.

2. Woolley, R., “The ‘IMPAC’ Program for Collision Analysis,” Society of Automotive Engineers Paper No. 870046, 1987.

15. Chatterjee, A., “Rigid Body Collisions: Some General Considerations, New Collision Laws, and Some Experimental Data,” PhD Thesis, Cornell University, January, 1997.

3. Ishikawa, H., “Impact Model for Accident Reconstruction – Normal and Tangential Restitution Coefficients,” Society of Automotive Engineers Paper No. 930654, 1993 4. Smith, G., “Conservation of Momentum Analysis of Two-Dimensional Colliding Bodies, With or Without Trailers,” Society of Automotive Engineers Paper No. 940566, 1994.

5. Steffan, H. & Moser, A., “The Collision and Trajectory Models of PC-CRASH,” Society of Automotive Engineers Paper No., 960886, 1996.

6. Carpenter, N. & Welcher, J., “Inter-Vehicular Sliding Friction and Crush Energy Losses in Impulse Momentum Planar Collision,” Society of Automotive Engineers Paper No. 2019-01-0422, 2019.

16. Emori, R., “Vehicle Mechanics of Intersection Collision Impact,” Society of Automotive Engineers Paper No., 700177, 1970.

17. Wang, Y., & Mason, M., “Two-Dimensional RigidBody Collisions with Friction,” Journal of Applied Mechanics, Vol. 59, September 1992.

18. Lankarani, H., “A Poisson-Based Formulation for Frictional Impact Analysis of Multibody Mechanical Systems with Open or Closed Kinematic Chains,” ASME Journal of Mechanical Design, Vol. 122, December 2000.

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7. Thomson, W. & Tait, P., “Treatise on Natural Philosophy,” Cambridge University Press, Cambridge, UK, 1879.

8. Brach, M., & Brach, R., “Crush Energy and Planar Impact Mechanics for Accident Reconstruction,” Society of Automotive Engineers Paper No. 980025, 1998.

9. Brach, R., Welsh, K., and Brach, M., “Residual Crush Energy Partitioning, Normal and Tangential Energy Losses,” Society of Automotive Engineers Paper No. 2007-01-0737, 2007.

10. Marine, M., “Restitution, Impulse Space, and Orientations,” Collision Magazine, Volume 16, Issue 1, 2022.

11. Marine, M., “On the Concept of Inter-Vehicle Friction and its Application in Automobile Accident Reconstruction,” Society of Automotive Engineers Paper No. 2007-01-0744, 2007.

12. Virtual Crash User’s Guide, Appendix 1 – Single Body Collision Physics Model, 2020

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Appendix A – The Newton and Poisson Restitution Hypotheses Complement Starting with Equation (7) of the main text and substituting Newton’s restitution coefficient (εN) we get:

If, instead, we work with Equation (8) of the main text (the sliding line equation) and apply a tangential restitution value we get: Equation (A6):

Equation (A1):

At maximum compression, this equation is written as: Equation (A2):

Here the tangential restitution is defined as by Ishikawa [4]: Equation (A7):

Using Equation (A6) and working through a similar process as above for the normal restitution, and using the impulse condition at the No Sliding Line, we can get a tangential restitution relationship (subscript “S” indicates impulse values at the No Sliding Line):

Rearranging to solve for VrN we get: Equation (A3):

Equations (A8): Substituting Equation (A3) into Equation (A1) and algebraically rearranging: Equation (A4):

The solution to this equation, by inspection or by invoking the impulse ratio, leads us to Poisson’s restitution hypothesis applied to both the normal and tangential impulse (i.e., to the resultant impulse vector):

Similar to the normal restitution coefficient, invoking a kinematic tangential restitution leads directly to a set of Poisson-looking tangential restitution equations. Note that the normal restitution is still employed and Equations (A5) and (A8) exist simultaneously, and neither dictates an isotropic condition.

Appendix B – Derivation of Energy Loss Equations From V-P Diagrams

Equations (A5):

Beginning with the top left panel of Figure B1, the energy loss due to the normal impulse is found by determining the area under the relative normal velocity line: Similarly, if we start with Poisson’s hypothesis applied to both impulse components, applying Equations (A5) to Equation (7) of the main text, and working through some algebra with Equation (A2), will lead directly to Newton’s restitution hypothesis. This is not the case, though, in formulations where Poisson’s restitution hypothesis is applied to only the normal impulse, as other researchers have presented ([16], [17], [18]).

The Poisson/Ishikawa tangential restitution complement:

Equation (B1):

To determine the energy loss due to the tangential impulse, we go about it the same way by determining the area under the sliding velocity line:

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Equation (B2):

under the sliding velocity line of the upper left panel of Figure B2: Equation (B8):

By noting similar triangles in the lower left panel of Figure B1 and because we have a Poisson restitution relationship for the tangential impulse (i.e., PT = (1 + εN)PTC), we can find a relationship for the velocities along the sliding velocity line: Equation (B3):

This allows us, along with the mathematical expedient of 1 = 2 – 1, to rearrange Equation (B2) as follows:

By noting similar triangles in the upper left panel of Figure B2, and because we have a Poisson restitution relationship for the normal impulse in Equations (A8) (i.e., PN = (1 + ετ)PNS), we can find a relationship for the velocities along the relative normal velocity line: Equation (B9):

Equation (B4): This allows us, once again along with the mathematical expedient of 1 = 2 – 1, to rearrange Equation (B8) as follows: Therefore, the total energy loss equation is found to be:

Equation (B10):

Equation (B5):

We can go about finding the energy loss for the other three cases described in the main text in a similar manner and discover that Equation (B5) is valid for each of the them.

For Case A solutions, VrTC is always zero and the energy loss equation reduces to:

Therefore, the total energy loss equation is now found to be: Equation (B11):

Equation (B6):

Energy loss through Ishikawa’s tangential restitution: Working with the V-P Diagram of the lower left panel of Figure B2 and Equations (A7) and (A8) we get: Equation (B7):

Here we have a sister equation to that of Equation (B5).

Both are derived through the use of the respective kinematic-kinetic restitution complements that are, in turn, derived through the respective impulse-space fundamental lines; and both result in energy restorative-looking terms (i.e., εN2 and εT2). Additionally, along the GIR Line, where εT = εN; PTS = PTC; and PNS = PNC, Equation (B11) reduces identically to Equation (B6). Whether this suggests the components of Equation (B11) represent energy loss due to specific mechanical processes is left to the reader’s technical appraisal.

To determine the energy loss due to the normal impulse, we again go about it the same way by determining the area

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Figure B1: Case D V-P Diagram and Impulse Space Diagram

Figure B2: Tangential Restitution-Based V-P Diagram and Impulse Space Diagram

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Utilizing EDR data to determine the effects of hard braking on Delta-V calculations in low-tomoderate speed impacts Shannon CrowlEy, Camila Marrero Torres, Alex Kazmierczak, Christopher J. Furbish and Bryan Randles Aperture Justin Brink Forensic Science and Biomechanics

A

bstract Four instrumented low-speed collinear impacts were conducted to study the effects of bullet vehicle hard braking in tests with Delta-Vs ranging from 5.0 to 12.4 mph. The bullet vehicle’s deceleration from hard braking was used to determine the effective bullet vehicle Delta-V for momentum analysis when applied to the target vehicle. In all tests, the bullet vehicle had maximally applied braking prior to and throughout the duration of the impact. Several methods for analyzing EDR data to determine bullet vehicle deceleration and impact durations are presented. The deceleration was used to calculate the effective bullet vehicle Delta-V and was then compared to the reference Delta-V from the instrumentation mounted within the vehicle. In all test impacts, the EDR-reported Delta-V overestimated the bullet vehicle effective Delta-V. The methods presented in this paper allow for a more accurate calculation of the target vehicle’s Delta-V for cases where bullet vehicle hard braking is evident and EDR data in the target vehicle are unavailable. When performing a simple momentum analysis of an impact where the impacting vehicle exhibits hard braking, using the EDR-reported Delta-V may result in an artificially high Delta-V on the corresponding vehicle, based on our testing 1.1-1.8 mph, up to 48%.

Literature Review The accuracy of Event Data Recorder (EDR) data has been well documented, however the effects of hard braking on Delta-V have been less robustly studied. [1,2,3] For example, there is known error in reported speed due to wheel slip during deceleration due to hard braking.

A study of late model General Motors (GM) vehicles found that braking at lower levels that did not activate the ABS system underreported the vehicle speed, and in cases where the ABS system was activated, the vehicle speed was underreported by approximately 8-18%. [4] An analysis of the accuracy of EDR-reported data during braking in a 2010 Ford Flex found that in all test cases, the EDR-reported speed 82 Collision Magazine - Volume 16 Issue 2

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In collisions with evidence of hard braking, the use of EDR-reported Delta-V can lead to an over-estimation of the calculated Delta-V on the target vehicle.

A recent publication by Vandiver and Anderson examined two crash tests and the effects of tire friction from the bullet vehicles. It was found that the Delta-V from tire friction resulted in the same speed change from skidding over a tenth of a second, 1⅔ mph. [8] The present study aims to provide methods to calculate the bullet vehicle effective Delta-V for use in momentum analysis for more accurately determining the resulting target vehicle Delta-V. Theoretical Calculations In low-speed impacts, hard braking can account for a substantial portion of the vehicle's deceleration and thus, overreport the Delta-V as a result of the collision. As a consequence, use of the bullet's EDR-reported Delta-V to examine the severity of the impact experienced by the target vehicle can result in an overrepresentation, or overcalculated DeltaV. In order to more accurately calculate the Delta-V experienced by the target vehicle, when utilizing EDR data obtained from the bullet vehicle, the effective Delta-V needs to be determined for use in a momentum and restitution equation. The total Delta-V of the bullet vehicle is the sum of the Delta-V due to the collision, or the effective Delta-V

(∆VEffective), and the Delta-V component due to hard braking (VL). [8] Equation 1: ∆VTotal=∆VEffective+∆VL The Delta-V component due to hard braking (VL) can be calculated using the drag factor (µ), acceleration of gravity (g) and impact duration (t), according to the formula below.

Equation 2: ∆VL=µ×g×t For cases where there is no EDR or pre-crash data available, the Delta-V component due to hard braking (VL) can be calculated theoretically and applied as long as there is evidence of hard braking. In these cases, a range of deceleration can be used. The theoretical VL due to hard braking was calculated using the above formula based on a range of impact duration (90-150 ms) and deceleration (0.5-0.9 g). This range of deceleration was determined by referring to Ruth et al. [4] However, the deceleration for high performance ABS could be as high as 1.2. [9] Deceleration (g) Crash pulse duration (ms)

was less than the speed reported by GPS. [5] An analysis of the 2010 and 2011 Toyota Camry during braking attributed positive differences between GPS and EDR data to speed data refresh rates and negative differences due to wheel slip as expected during braking. [6] Ruth et. al offers a method to calculate the range of speed at impact based on EDR pre-crash data. The article provides an outline to calculate speed loss from the last reliable data point. [7]

90 100 110 120 130 140 150

0.5

0.6

0.7

0.8

0.9

0.99 1.10 1.21 1.32 1.43 1.54 1.65

1.19 1.32 1.45 1.58 1.71 1.84 1.98

1.38 1.54 1.69 1.84 2.00 2.15 2.31

1.58 1.76 1.93 2.11 2.28 2.46 2.63

1.78 1.98 2.17 2.37 2.57 2.77 2.96

Table 1: Delta-V Component due to Hard Braking, VL (mph) In cases where pre-crash EDR data is available, there are various methods that can be used to find the effective Delta-V of the bullet vehicle, using the impact duration and deceleration.

1. Find the impact duration. Three methods of finding the impact duration from the EDR report were compared (Table 4). First, the EDRreported time of maximum Delta-V. Second, according to the definition of the end of event time from NHTSA 49 CFR Part 563. [10] Third, the end of event time determined from the collision acceleration data in the EDR report.

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Figure 1: The total Delta-V is the area under the acceleration versus time curve. The area under the effective acceleration curve represents the bullet vehicle effective Delta-V without the effects of hard braking.

2. Find the deceleration due to hard braking. The deceleration was calculated from the pre-crash data, specifically the pre-crash vehicle speed history and the pre-crash brake history provided in the vehicle’s EDR report. [11,12] The Hyundai’s speed was reported in kilometers per hour (km/h) whereas the Chevrolet’s speed was reported in both km/h and miles per hour (mph). The speed in km/h was used to calculate the deceleration for this analysis. The deceleration and estimated speed loss for each 0.5 second time interval were calculated and analyzed in conjunction with when the EDR-reported braking as “ON” or “OFF.” Deceleration values less than 0.2 g’s were excluded when calculating the vehicle’s deceleration due to braking. The deceleration when the driver was exhibiting hard braking was calculated as the final deceleration.

Once the impact duration and deceleration have been determined from the EDR report, the following three methods were used to calculate the effective Delta-V of the bullet vehicle: Method 1: Subtracting Delta-V component due to hard braking (VL) from EDR Delta-V:

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a. The analyzed Delta-V was determined from the EDR report according to the Part 563 definition. b. The Delta-V component due to hard braking (VL) was calculated with the formula above (Equation 2) using the deceleration calculated and impact duration from the EDR data. This calculated Delta-V was then be applied to the analyzed EDR Delta-V to account for the effects of hard braking, resulting in the effective Delta-V. c. ∆VEff. Analyzed ∆V Method 2: Using EDR longitudinal acceleration data: a. Using the deceleration calculated from the pre-crash data, a correction was applied to each time interval of the EDR-reported longitudinal acceleration. The adjusted acceleration pulse was then integrated to calculate effective Delta-V for the bullet vehicle. See Figure 1 for a representation of the effect of hard braking on the acceleration pulse. b. ∆VEff. Accel. Data Method 3: Correcting the EDR-reported Delta-V trace to account for deceleration due to braking:

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a. An acceleration pulse was calculated from the longitudinal Delta-V data provided in the EDR report. The deceleration calculated from the pre-crash data was then applied to each time interval the calculated acceleration pulse. The adjusted acceleration pulse was then integrated to calculate the effective Delta-V. b. ∆VEff. ∆V Trace Emori et al. provided a momentum equation that considers the external forces on the vehicles, such as rolling resistance or braking force. [13] However, using the methods outlined above, the bullet vehicle’s effective Delta-V has been calculated to remove the Delta-V component due to hard braking (VL). Therefore, the law of conservation of momentum was then applied to calculate a more accurate Delta-V of the target vehicle, using the equations below.

Conservation of Momentum [14] Equation 3: mTvT+mBvB=mTvT'+mBvB'

Figure 2: The Delta-V due to the collision, or effective DeltaV, vs. the Delta-V component due to hard braking.

Coefficient of Restitution [11] Equation 4: vT'-vB'=e(vB-vT) Methods A series of four low-speed collinear impacts were conducted to assess the effects of bullet vehicle hard braking on EDR Delta-Vs. In each of the four tests (Tests 1A, 3A, 6A, 7A), events were triggered after a period of steady state driving and then maximally applied braking from the bullet vehicle. The collision occurred after hard braking from an initial speed of 35 mph. All tests were conducted on a paved asphalt surface in January of 2021 in Glendale, Arizona.

Vehicles and Impact Configuration In Tests 1A and 3A, the bullet vehicle was a 2015 Hyundai Elantra SE sedan (5NPDH4AE4F-XXXXXXX). The tested weight, with all instrumentation and human driver, was 2,900 pounds. The target vehicle was a 2015 Chevrolet Sonic LT (1G1JC6SB7FXXXXXXX). The tested weight, with all instrumentation, was 2,960 pounds.

Table 2: Impact Configurations In Tests 6A and 7A, the bullet vehicle was the 2015 Chevrolet Sonic LT. The tested weight, with all instrumentation and human driver, was 2,890 pounds. The target vehicle was the 2015 Hyundai Elantra. The tested weight, with all instrumentation, was 2,950 pounds.

Table 2 demonstrates the impact configuration for each test.

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Vehicle Instrumentation

Crash Test Results

In each test, a human-driven bullet vehicle was instrumented with a Video VBOX and VBOX III, with the antennas on the roof. A tri-axial accelerometer was mounted on the top surface of the vehicle EDR module.

The deceleration calculated from the EDR pre-crash data was compared to the measured reference values from the vehicle-mounted accelerometer. VBOX deceleration data was found to be consistent with the vehiclemounted accelerometer data.

The target vehicle was instrumented with a tri-axial accelerometer mounted on the vehicle EDR module. There were no humans present in any of the target vehicles. The target vehicle was stationary, with the engine running and transmission in neutral.

Data Collection And Processing The Chevrolet CDR was imaged using Crash Data Retrieval Tool 21.0 and reported using Crash Data Retrieval Tool 21.5.1. The Hyundai EDR was imaged using EDR Tool version E-η-H-01-00-0038 and reported using EDR Report Version EDR001-R01. Hyundai Delta-V values were reported in kilometers per hour. Chevrolet Delta-V values reported in kilometers per hour were converted to miles per hour.

Vehicle accelerometer data were collected at 10 kHz using Diversified Technical System’s SLICE signal input modules. All filtering, polarity, and axis orientation are in accordance with SAE J211 recommended practices, unless otherwise specified. Standard up-down rounding was used when reporting calculated Delta-V data values.

The impact duration calculation methods from each EDR report (the time of maximum Delta-V, the impact duration according to Part 563, and the impact duration from the acceleration trace) were compared with the measured impact duration from the vehicle mounted accelerometer data.

The bullet vehicle effective Delta-V was calculated from the vehicle-mounted accelerometer data and compared with the EDR-reported Delta-V from each vehicle. In each test, the EDR-reported Delta-V for the bullet vehicle was higher in magnitude than the reference effective Delta-V from vehicle mounted accelerometer data, from 1.4-1.8 mph (16% to 51%).

Analysis

Test 1A 3A 6A 7A

Deceleration Deceleration Bullet (Based on Vehicle (Based on EDR Percent Vehicle Mounted Accel.

Pre-Crash Difference Data) Data) Hyundai -0.76 -0.82 9% Hyundai -0.77 -0.71 -8% Chevrolet -0.82 -0.85 4% Chevrolet -0.78 -0.57 -27%

Table 3: Comparison of Deceleration Measured versus Calculated Test

1A 3A 6A 7A

Veh. Mounted Accel. Impact Duration (ms) 99 98 139 122

Time of max Delta-V (ms) 170 292.5 108 114

Percent Difference 72% 198% -22% -7%

Part 563 duration (ms) 90 90 100 110

The measured Delta-V component due to hard braking (VL) of the bullet vehicle for each test is reported below in Table 7. The VL was calculated by applying the deceleration over the impact duration measured by vehicle mounted accelerometers (Equation 2).

Using Method 1, subtracting Delta-V component due to hard braking (VL) from the analyzed EDR Delta-V, the measured effective Delta-V compared to the calculated Delta-V resulted in difference of -0.2 to 0.5 mph (-6% to 6%). Using Method 2, using Percent Difference -9% -8% -28% -10%

EDR-acceleration trace duration (ms) 120 110 90 120

Percent Difference 21% 12% -35% -2%

Table 4: Comparison of Impact Duration Calculation Methods

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Test 1A 3A 6A 7A

Measured Vehicle Effective Delta-V (mph) Hyundai -7.3 Hyundai -8.7 Chevrolet -3.3 Chevrolet -10.7

EDR Delta-V (mph)

Percent Difference

-8.7 -10.6 -5.0 -12.4

19% 21% 51% 16%

Table 5: Comparison of Measured Bullet Vehicle Effective Vehicle Delta-V vs. EDR Delta-V Test 1A 3A 6A 7A

Vehicle Chevrolet Chevrolet Hyundai Hyundai

Measured Delta-V (mph) 7.2 8.6 3.3 11.0

Table 6: Measured Target Vehicle Delta-V

Test

Bullet Vehicle

Deceleration (Based on Vehicle Mounted Accel. Data)

1A 3A 6A 7A

Hyundai Hyundai Chevrolet Chevrolet

-0.76 -0.77 -0.82 -0.78

Impact Delta-V Duration Component (Based on Due to Hard Vehicle Braking (V1) Mounted (mph) Accel.) (ms) 99 98 139 122

-1.6 -1.7 -2.5 -2.1

Table 7: Bullet Vehicle Measured Delta-V Component due to Hard Braking (Based on Equation 2) (VL) Test

1A 3A 6A 7A

Bullet Vehicle

Measured Percent Effective Effective Error Delta-V Delta-V (Method 1) (mph) ∆VEff. Analyzed ∆V (mph) Hyundai -7.3 -7.1 -3% Hyundai -8.7 -9.2 6% Chevrolet -3.3 -3.1 -6% Chevrolet -10.7 -11.1 4%

EDR longitudinal acceleration data, the measured effective Delta-V compared to the calculated Delta-V resulted in a difference of -1.4 to 0.3 mph (-19% to 3%). Using Method 3, correcting the Delta-V trace to account for deceleration due to braking, the measured effective Delta-V compared to the calculated Delta-V resulted in a difference of -0.6 to 0.2 mph (-13% to 2%).

For each impact, the Delta-V for the target vehicle was calculated by applying Equation 3 and 4 using the bullet vehicle effective Delta-Vs calculated from Methods 1, 2 and 3. These target vehicle Delta-Vs calculated using the effective Delta-V of the bullet vehicle from all three methods were then compared to the Delta-V of the target vehicle measured by onboard accelerometers (Table 9).

Using Method 1, subtracting Delta-V component due to hard braking (VL) from EDR Delta-V, the measured effective Delta-V compared to the calculated Delta-V resulted in a difference of -0.3 to 0.4 mph (-3% to 5%). Using Method 2, using EDR longitudinal acceleration data, the measured effective Delta-V compared to the calculated Delta-V resulted in a difference of percent error of -1.5 to -0.2 mph (-21% to -2%).

Using Method 3, correcting the Delta-V trace to account for deceleration due to braking, the measured effective Delta-V compared to the calculated Delta-V resulted in a difference of -1.1 to 0.1 mph (-15% to 1%).

Effective Delta-V (Method 2) ∆VEff. Accel. Data (mph) -5.9 -7.8 -3.2 -11.0

Percent Error

-19% -10% -4% 3%

Effective Delta-V (Method 3) ∆VEff. ∆V Tracea (mph) -6.9 -8.9 -2.9 -10.1

Percent Error

-5% 2% -13% -6%

Table 8: Comparison of Bullet Vehicle Measured Effective Delta-V vs. Calculated Effective Delta-V

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Test

Target Vehicle

Measured Effective Delta-V (mph)

1A 3A 6A 7A

Hyundai Hyundai Chevrolet Chevrolet

-7.3 -8.7 -3.3 -10.7

Calculated Delta-V (Conservation of Momentum Based on Method 1) (mph) -7.1 -9.2 -3.1 -11.1

Percent Error

-3% 6% -6% 4%

Calculated Delta-V (Conservation of Momentum Based on Method 2) (mph) -5.9 -7.8 -3.2 -11.0

Percent Error

-19% -10% -4% 3%

Calculated Delta-V (Conservation of Momentum Based on Method 3) (mph) -6.9 -8.9 -2.9 -10.1

Percent Error

-5% 2% -13% -6%

Table 9: Comparison of Target Vehicle Measured Delta-V vs. Calculated Delta-V Discussion The effects of braking and tire friction apply to all collisions, however in low-speed collisions, the Delta-V component due to hard braking (VL) can account for a greater percentage of the total Delta-V. For example, the measured VL in tests 6A and 7A were 2.5 mph and 2.1 mph, respectively (Table 7). However, the EDR Delta-V in test 6A was -5.0 mph and -12.4 mph in test 7A (Table 5). Because test 7A has a higher total Delta-V, VL accounts for less of the total Delta-V. This resulted in a lower percent error for the calculated effective Delta-V for test 7A (Table 8).

When attempting to calculate VL from EDR data, it was found that Method 1 had the smallest range for the difference between the target vehicle measured Delta-V compared to the calculated Delta-V. For Method 1 (∆V Eff. ), VL was calculated using the impact durations deReported ∆V termined by the Part 563 definition (Table 4). In some cases, the EDR-reported time of maximum Delta-V may be used as the impact duration. However, there are recognized limitations in insufficient recording times and insufficient memory to record the entire crash pulse that could lead to incorrect reporting. [15,16,17,18] For most of these tests, the EDR-reported time of maximum Delta-V did not reflect the measured impact duration and was therefore excluded. Table 4 shows a comparison of measured impact duration to calculated impact duration for each impact. In addition, in cases where the EDR-reported time of maximum Delta-V was longer than the impact duration, the EDR-reported maximum Delta-V was higher in magnitude than the analyzed EDR Delta-V. In each case, the analyzed EDR Delta-V was determined according to the Part 563 definition. Of note, the Chevrolet impact duration appeared to cut off at or near the Part 563 defined impact duration. It was found that the Hyundai Delta-V continued to increase after the crash pulse had concluded.

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This can account for an over-reported Delta-V due to the addition of post-impact deceleration.

The Hyundai and Chevrolet both reported pre-crash data in 0.5 second intervals. However, the Hyundai reported the longitudinal crash pulse in 10 ms intervals, while the Chevrolet reported in 2 ms intervals. EDR sampling rates can vary across makes and manufacturers, as well as which data elements are reported. This study analyzed two vehicles, and the methods discussed can be applied to others, but not all methods will be applicable based on the data elements provided in the EDR report.

In test 7A, the deceleration due to hard braking calculated from the EDR pre-crash data was -0.57, while the deceleration from the vehicle mounted accelerometers was -0.78. Following the method outlined in Section III, there was only one 0.5 second interval in the pre-crash data that exhibited hard braking criteria. The measured data shows the driver began braking between the -1 and -0.5 time interval, however, that was not captured in the EDR report.

Therefore, the last two 0.5 second intervals were included in the calculation of the deceleration, although one interval reported a deceleration of 0.11 g’s, which is under the threshold of 0.2 g’s discussed in the Theoretical Calculations section. Because the full interval of hard braking was not captured in the pre-crash data, the calculated deceleration due to hard braking was under-reported. In test 3A, the deceleration at time zero was reported to be 0.11 g’s, under the threshold of 0.2 g’s, and was therefore excluded.

A sufficient amount of braking and speed data needs to be available in the EDR pre-crash data to calculate the appropriate deceleration. When there is not adequate data available, appropriate braking values for that vehicle and surface should be used.

When the law of conservation of momentum was applied to calculate the target vehicle Delta-V using the bullet ve-

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hicle’s effective Delta-V, the difference in the measured Delta-V ranged from -1.5 to 0.4 mph. For comparison, the law of conservation of momentum was applied using the bullet vehicle’s EDR Delta-V, without correction for hard braking, and compared to the measured target vehicle Delta-V (Table 10). Without applying any of the methods discussed previously to correct for the effects of hard braking, the Delta-V of the target vehicle was over-estimated, from 1.1 to 1.8 mph, up to 48%.

A recent publication by Vandiver and Anderson reported that tire friction with a drag factor of 0.75 and an impact duration of 1/10th of a second resulted in a Delta-V reduction 1 ⅔ mph. The results of the tests reported in the current study were consistent with the Delta-V reduction reported by Vandiver and Anderson.

In tests with deceleration of 0.76-0.82 and an impact duration of 98-139 ms, the resulting reduction in Delta-V ranged from 1.62.5 mph (Table 7).

Previous research has shown that hard braking by the target vehicle can reduce the Delta V experienced by the target vehicle.

Because all of our target vehicles were in neutral during testing the effects of hard braking by the target vehicle were not considered in this study. However, it should be noted that target vehicle hard braking can further reduce the Delta V experienced by the target vehicle even when accounting for the hard braking of the bullet vehicle and should be considered.

Conclusion The results of this study show that utilizing bullet vehicle EDRreported Delta V to calculate the target vehicle Delta-V can overestimate the actual Delta V experienced by the target vehicle when there is evidence of hard braking by the bullet vehicle during the collision. In all tests, the bullet vehicle EDR-reported Delta-V was higher in magnitude than the effective Delta-V from vehicle mounted accelerometer data, from 1.4 to 1.8 mph (16% to 51%).

For collisions where there is evidence of hard braking in the bullet vehicle and the bullet vehicle has an accessible EDR, the three

Test

Target Vehicle

Measured Delta-V (mph)

1A 3A 6A 7A

Chevrolet Chevrolet Hyundai Hyundai

7.2 8.6 3.3 11.0

Calculated Delta-V (Conservation of Percent Momentum Based Error on EDR Total Delta-V) (mph) 8.5 10.4 4.9 12.1

18% 21% 48% 10%

Table 10: Bullet Vehicle Measured Delta-V Component due to Hard Braking (Based on Equation 2) (VL) www.collisionpublishing.com

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previously described methods can be used to calculate its effective Delta-V and provide a more accurate representation of the Delta-V experienced by the bullet vehicle as a result of the vehicle-to-vehicle interaction alone. The effective Delta-V for the bullet vehicle can then be used to calculate the target vehicle’s Delta-V using the law of conservation of momentum.

When the law of conservation of momentum was applied to the target vehicle without the correction for the effects of hard braking in the bullet vehicle, the calculated Delta-V of the target vehicle was higher in magnitude than the Delta-V from vehicle mounted accelerometer data, from 1.1 to 1.8 mph (10% to 48%). This method is particularly useful in cases where the target vehicle does not have an EDR to be imaged, or is inaccessible altogether, and can provide a more accurate calculation for the DeltaV experienced by the target vehicle.

Glossary ∆VTotal: Total Delta-V of the bullet vehicle ∆VEffective: Delta-V due to the collision or the effective Delta-V ∆VL: Delta-V component due to hard braking or speed loss µ: drag factor g: acceleration of gravity t: impact duration e: coefficient of restitution ∆VEff. Analyzed ∆V: Effective Delta-V calculated by subtracting the Delta-V component due to hard braking from the EDR Delta-V ∆VEff. Accel. Data: Effective Delta-V calculated by applying the deceleration to each time interval of the EDR-reported longitudinal acceleration pulse ∆VEff. Delta-V Trace: Effective Delta-V calculated by first calculating the longitudinal acceleration from the EDR-reported Delta-V crash pulse, then applying the deceleration to each time interval of the calculated acceleration pulse References

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1. Vandiver, Wesley, and Robert Anderson. Analysis of Crash Data from a 2012 Hyundai Genesis Coupe Event Data Recorder. No. 2021-01-0905. SAE Technical Paper, 2021.

2. Lawrence, Jonathan M., et al. "The accuracy and sensitivity of event data recorders in low-speed collisions."

SAE Transactions (2002): 941-951.

3.

Bortles, W., et al. "A Compendium of Passenger Vehicle Event Data Recorder Literature and Analysis of Validation Studies.” SAE Technical Paper 2016-011497 (2016).

4. Reust, Timothy J., and James M. Morgan. "The accuracy of speed recorded by an [EDR] SDM and the effects of brake, yaw and other factors." Collision: the international compendium for crash research 1.1 (2006): 9-15.

5. Ruth, Richard, and Jeremy Daily. "Accuracy of Event Data Recorder in 2010 Ford Flex During Steady State and Braking Conditions." SAE International Journal of Passenger Cars-Mechanical Systems 4.2011-010812 (2011): 677-699.

6. Ruth, Richard, Wade Bartlett, and Jeremy Daily. "Accuracy of event data in the 2010 and 2011 Toyota Camry during steady state and braking conditions."

SAE International journal of passenger cars-electronic and electrical systems 5.1 (2012): 358-372.

7. Ruth, Rick, and Bill Wright. "Using EDR Pre-Crash Data to Calculate a Range for Speed at Impact." Accident Reconstruction Journal 27.3 (2017).

8. Vandiver, Wesley and Robert Anderson. “Event Data Recorder Delta V: The Effect of Tire Friction.” Collison Magazine, The International Compendium for Crash Research 16.1 (2022).

9. Tingwall, Eric. “2019 Chevrolet Corvette ZR1 vs.

2018 Porsche 911 GT2 RS.” Car and Driver, 29 Nov. 2021, https://www.caranddriver.com/reviews/comparison-test/a22516381/2019-chevrolet-corvette-zr1vs-2018-porsche-911-gt2-rs-comparison-test/.

11. Kusano, Kristofer D., and Hampton Gabler. "Method for estimating time to collision at braking in realworld, lead vehicle stopped rear-end crashes for use in pre-crash system design." SAE International Journal of Passenger Cars-Mechanical Systems 4.2011-010576 (2011): 435-443.

12. Ruth, Rick, and Bill Wright. "Using EDR Pre-Crash Data to Calculate a Range for Speed at Impact." Accident Reconstruction Journal 27.3 (2017).

13. Emori, Richard I., and Junji Horiguchi. Whiplash in low speed vehicle collisions. No. 900542. SAE Technical Paper, 1990.

14. Cipriani, A. L., et al. "Low speed collinear impact severity: a comparison between full scale testing and analytical prediction tools with restitution analysis."

SAE Transactions (2002): 625-639.

15. Hampton, Carolyn E., and Hampton C. Gabler.

"Evaluation of the accuracy of NASS/CDS Delta-V estimates from the enhanced WinSmash algorithm."

Annals of Advances in Automotive Medicine/Annual Scientific Conference. Vol. 54. Association for the Advancement of Automotive Medicine, 2010.

16. Tsoi, Ada, et al. "Validation of event data recorders in high severity full-frontal crash tests." SAE International Journal of Transportation Safety 1.1 (2013): 76-99.

17. Niehoff, Peter, et al. "Evaluation of event data recorders in full systems crash tests." Proceedings of the 19th International Conference on the Enhanced Safety of Vehicles. 2005.

18. Wusk, Grace, and Hampton Gabler. "Evaluation of vehicle-based crash severity metrics using Event Data Recorders." 25th International Technical Conference on the Enhanced Safety of Vehicles (ESV) National Highway Traffic Safety Administration. 2017.

19. Anderson, Robert D., et al. "Effect of braking on human occupant and vehicle kinematics in low speed rear-end collisions." SAE transactions (1998): 629640.

10. NHTSA. Code of Federal Regulation (CRF) 49: Part 563 – Event Data Recorders. [Online] Available: https://www.ecfr.gov/current/title-49/subtitle-B/ chapter-V/part-563

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Crash Data and Images Available After Automotive Repair with Airbag Control Module Replacement Robert Anderson Biomechanics Analysis

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A

bstract In the following case example, it is demonstrated that a VCH/PCS equipped Toyota/Lexus automobile still had accessible PCS FFD data and images even after the ACM has been discarded as part of the postcrash repair.

Introduction Since their introduction in the 1990s, Event Data Recorders (EDRs) have become a common source of important data for those investigating or analyzing crash events. For the Toyota family of automobiles, additional electronic evidence became available through the introduction of the Vehicle Control History (VCH). A coverage chart for the Lexus and Toyota models sold in the United States is shown in Figure 1 as described in the EDR Tech Series presentation by Dave Hallman.

Starting in vehicle Model Year 2013, Toyota quietly added a data recording feature to the Toyota Rav4 which collected a large amount of data based on a wide variety of possible trigger events defined by Toyota. Similar to EDR data, when a trigger event occurs, data preceding, and post trigger data is captured and stored.

This data cannot be manually erased but will eventually be overwritten by newer events as the write locations fill up. The recording time, frequency, number of data points captured, and number of events stored prior to overwrite depends on the type of event and is defined in the Toyota Information System (TIS) available by subscription through the Toyota Technical Information website. The data is stored in the airbag control module (ACM) and can be imaged through the DLC using the Toyota Tech Stream software, also available through www.

TechStreamSupport.com for an annual fee.

Since the introduction in the 2013 Rav4, this recording capability has been added to virtually all Toyota and Lexus models as well as one Scion model (see Figure 1) and a more detailed discussion in crash·ol·o·gy in Collision (Vol 14, Issue 2).

As this data has become more widely available across all Toyota models, there are increasing opportunities to put this data to use as a reconstruction tool. Also in Collision Vol 14, www.collisionpublishing.com

Volume 16 Issue 2.indd 93

Issue 2, one may find “Toyota Vehicle Control History Case Studies “ The article provided an overview of seven case studies where the VCH data was utilized with and without EDR data to assist in determining the facts of, and reconstructing, a crash. The purpose of that article was to demonstrate some of the potential uses for this data as another tool for the reconstructionist’s toolbox.

The VCH data becomes important in situations where EDR data may not be available, including non-contact situations, as well as low speed and low delta-V impacts, such as pedestrian and bicyclist collisions, which often do not qualify for an EDR recording. However, when the automobile has been repaired after a crash for which deployments were commanded, the replacement of the Airbag Control Module (ACM), where the EDR and VCH data is stored, results in loss of access to this key information. Unlike the EDR and VCH data, which is stored in the ACM, the Pre-collision Safety (PCS) images associated with the VCH are stored in the front recognition camera module.

The residual data following the replacement of an ACM during repairs was discovered during a recent vehicle inspection of a late model Lexus that was hit in the passenger side after turning left into the path of an oncoming vehicle.

Unbeknownst to the crash reconstructionists prior to the inspection, the vehicle had been repaired and returned to service. As expected, the CDR report showed no events, and the VCH showed a small number of events, but none that pre-dated the repairs and presumed replacement of the ACM. However, the PCS read data function retrieved the images related to the crash. Evidently, resetting the forward recognition camera is not part of the repair protocol. As shown in Figure 2 in frames 0 through 20, the images show the Lexus following another left turning vehicle, before the oncoming vehicle becomes visible around the oncoming vehicles waiting to turn left. The post-collision images shown the clockwise rotation of the Lexus from the impact. The trigger for the camera data corresponds to image 10 as “time zero” for this system.

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Figure 1: Toyota/Lexus vehicles with Vehicle Control History – Hallman Engineering Retrieving the VCH/FFD data and then a review of the Data Report revealed that the Freeze Frame Data (FFD) included several important collision parameters at approximately 10 Hz. Included in the set of retrieved data were these elements from T0 -4.8 to +3.744 seconds for each of the following: • • • • • • • •

92

Running Distance (odometer) Collision Detection Signal Vehicle Speed Accelerator Opening % Brake Master Cylinder pressure Steering Angle and Speed Longitudinal Acceleration Yaw Rate

Collision Magazine - Volume 16 Issue 2

Examples of other elements and the output display are attached at the end of the document under the heading "VCH/FFD Data Report." The magnitude, timing and polarity of these FFD parameters favorably corresponded with the PCS images and the crash scenario.

The above case example was for a second-generation Toyota/Lexus Safety Sense (TSS/LSS 2.0). To investigate whether or not the first generation of TSS stored comparable data, a Toyota Tacoma equipped with TSS-P was interrogated for PCS data, while the ACM was disconnected, to prevent VCH data from the ACM being included.

However, while the Toyota Techstream software indicated that a PCS data read was occurring, data was not obtained, even after waiting four times the estimated duration of the download time. Reconnecting the ACM resulted in a

www.collisionpublishing.com

-5.4 sec

-4.8 sec

-4.2 sec

-3.6 sec

-3.0 sec

-2.4 sec

-1.8 sec

-1.2 sec

-0.6 sec

T0, Collision Detected

0.6 sec

1.2 sec

1.8 sec

2.4 sec

3.0 sec

3.6 sec

4.2 sec

4.8 sec

5.4 sec

6.0 sec

Figure 2: The Lexus’ PCS images in 0.6 second increments from the subject crash Conclusion There is a reasonable expectation that a VCH/PCS equipped Toyota/Lexus automobile may still have accessible PCS FFD data and images even after the ACM has been discarded as part of a proper post-crash/deployment repair. The accessible data is comparable to that obtained through the EDR and VCH, but without some parameters, such as lateral and longitudinal delta-V or restraint use.

This author wishes to express thanks to Joseph Manning and Christoph Fromme for consenting to the use of their vehicles in this study.

References 1. Hallman, D., Anderson, B., Cox, W, “Toyota Vehicle Control History Case Studies,” Collision Magazine Volume 14, Issue 2

A more complete explanation of Toyota Techstream Vehicle Control History data, go to the Crash Data Group’s YouTube channel and look for the EDR Tech series, in particular, find “Edition 4: Toyota Techstream Vehicle Control History Data” by Dave Hallman. https://www. youtube.com/watch?v=HXdX1Zqi1ng Topics include Compatible interface devices, DLC/ OBD data retrieval with Techstream software, Steps to access data using Techstream software, Direct-to-module download with Techstream, What causes Vehicle Control History data to be recorded, What “types” of data are recorded/available, How to correlate Techstream data to a crash event, How is Techstream data used in conjunction with traditional EDR data, and Examples of actual cases where Techstream data was utilized among other topics in the EDR Tech presentation.

www.collisionpublishing.com

Volume 16 Issue 2.indd 95

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VCH/FFD Data Report This report created by PCS Data Viewer.

PCS Data Viewer data output 1.

2.

3.

4.

5.

General information File information User selected FFD data and graph Image FFD Hexadecimal Data

1.General Information 1.1.Data Limitations - Due to limitations of the data recorded, such as the resolution, data range, sampling interval, time period of the recording, and the items recorded, the information provided by this data may not be sufficient to capture the entire event.

Data storage properties may also affect the way data is output.

- The recorded data is recorded in discrete intervals.

Due to different refresh rates within the vehicle's electronics, the data recorded may not be synchronous to each other.

- Newer events with Vehicle Control History “VCH”/ Freeze Frame Data “FFD” s may overwrite data from past events.

- If power supply to the airbag ECU and/or other systems are lost during an event, all or part of the data may not be recorded.

- This Global TechStream, TaSCAN, or Intelligent Tester II devices (or any other Toyota genuine diagnostic tool) can be used to obtain detailed information on the diagnostic trouble codes from the airbag system, as well as diagnostic information from other systems.

1.2.About VCH/FFD Data - The vehicle control history is a function that records control data (record data) when triggered by specific vehicle behavior.

Checking the vehicle control history may provide quantitativediagnostic information that can be used as a reference, along with the vehicle’s repair manual, to proceed with malfunction diagnosis.

- Maximum recording number, Sampling period for recording and Data sampling rate depend on the triggers and recording data.

- VCH data is recorded in the memory of the airbag ECU, and some of the data recorded by the airbag ECU is transmitted from various vehicle control modules by the vehicle’s Control Area Network (CAN).

- In some cases, the airbag ECU part number printed on the ECU label may not match the airbag ECU part number that the PCS data viewer reports. The part number retrieved by the PCS data viewer should be considered as the official ECU part number.

The following table identifies data that may be recorded (data recorded varies by vehicle and type of event:

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www.collisionpublishing.com

3.23 Vehicle Speed [km/h] Time Stamp

-4.800 -4.704 -4.608 -4.512 -4.416 -4.320 -4.224 -4.128 -4.032 -3.936 -3.840 -3.744 -3.648 -3.552 -3.456 -3.360 -3.264 -3.168 -3.072 -2.976 -2.880 -2.784 -2.688 -2.592 -2.496 -2.400 -2.304 -2.208 -2.112 -2.016 -1.920 -1.824 -1.728 -1.632 -1.536 -1.440 -1.344 -1.248 -1.152 -1.056 -0.960 -0.864 -0.768 -0.672 -0.576 -0.480 -0.384 -0.288 -0.192 -0.096 0.000 0.000 0.096 0.192 0.288

Parameter Value

4.5 4.6 4.8 4.8 4.8 5 5.1 5.3 5.3 5.5 5.8 6.2 6.6 7.1 7.6 8 8.4 8.8 9.2 9.7 10.3 10.8 11.3 11.7 12 12.5 13 13.5 13.9 14.3 14.6 15.2 15.6 16.1 16.5 16.9 17.1 17.2 17.5 17.6 18 18 18.4 18.8 19.6 19.9 20 22.2 23.7 24.2 26.3 26.3 22.7 21.7 18.8

Time Stamp

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0.384 0.480 0.576 0.672 0.768 0.864 0.960 1.056 1.152 1.248 1.344 1.440 1.536 1.632 1.728 1.824 1.920 2.016 2.112 2.208 2.304 2.400 2.496 2.592 2.688 2.784 2.880 2.976 3.072 3.168 3.264 3.360 3.456 3.552 3.648 3.744

Parameter Value

17.8 18.6 14.6 12.8 11.6 10.8 10.2 8.9 9 9.4 8.8 8.8 7.8 7.7 7.8 8 8.1 7.7 7.6 7.6 7.5 7.3 7.3 7.3 7.2 7.1 7 7 6.8 6.8 6.8 6.8 6.8 6.8 7 6.6

Collision Magazine - Volume 16 Issue 2 95

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