Speakers Information - Controls, Measurement & Calibration Congress
Concept Development for Complex EMS Application Using Matlab Simulink – A Case Study Mr.Seetareddy Beeravalli Senior Technical Specialist Powertrain Engine Systems, Continental Automotive Components (India) Pvt. Ltd
ABSTRACT In automotive industry, increasing complexity of system driven by stringent emission standards is leading to development of more complex functions. One of the proven technologies for performance improvement, emission reduction is the variable valve timing (VVT). In this paper, development of an algorithm to control VVT integrated with mid-lock pin is discussed in the context of efficiency brought by employing model based development method. This development was driven by certain drawback associated with existing VVT system, the new system is designed to achieve lower emission at transient conditions like cold start wherein emission is higher than at normal operating conditions. The model based development proved very useful in terms of development and validation, and to reduce the time to market.
Author: Seetareddy Beeravalli
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INTRODUCTION Automotive OEMs are focusing on improving the systems associated with combustion and emission control in order to meet the emission norms apart from achieving fuel efficiency to have a bigger market share. The time to market for new systems is shrinking due to competition, which demands that new systems are designed, developed and validated in less time, and in a robust way. In the existing VVT system, greater intake phasing is needed to further improve part-load fuel economy and to reduce emission, but in-turn this will lead to startability problem. This gap in VVT operation is bridged by introducing a new hardware with additional lock pin in the mid-position of VVT range that has to be controlled based on engine operating conditions using digital actuator. This system needed an algorithm to work with new hardware as well as support the old configuration for vehicles that are running with conventional VVT system. In general, algorithm development for new concepts takes multiple loops to refine the solution and rectify defects. This needs a development method to cover all facets of operating environment with extensive requirement engineering. To reduce the risk of errors and time for development, model based approach is used for this concept development. Using MBD, the number of loops required to arrive at a refined solution is reduced. The MBD gives a platform to validate the behavior before integrating with the HW system. The hardware requirement and control strategy was analyzed and the design is conceptualized. Algorithm is designed in SDA (System Design Automation) [3], which is based on Matlab-SimulinkŠ (SDA is the MBD platform used at Continental Engine System - figure 1). The new VVT solution consists of several modules interacting with other functions as well as the new hardware. The VVT concept algorithm is simulated to observe whether expected behavior is attained with the test vectors. Any deviation in the simulated behavior points to deviation in the solution identified for requirement. With solution frozen, the model is tested with scaled model (from floating point to fixed point) and verified using existing test vectors. SW code is generated out of the model using Embedded Coder Š, and verified using defined test vectors to check whether software works as intended via SIL (Software In the Loop) mode (where generated code will be part of Matlab environment as S-function). To verify that the code works as expected in the target environment, generated code is compiled with target compiler and will be simulated via PIL (Processor In the Loop) mode and executed on a target simulator. The function behavior should be same in all the modes of simulation. MBD helps by guidance at each stage of development to verify function behavior and rectify problems before progressing to next stage of development.
Figure 1 - Integrated MBD environment at Continental [3]
Author: Seetareddy Beeravalli
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MAIN SECTION VARIABLE VALVE TIMING: The variable valve timing is also referred as variable cam phasing (VCP). The mechanism behind this system is to phase the angle of opening/closing of inlet/exhaust valves with respect to crankshaft position. In other words, it is possible to change the closing point of the inlet valves and/or the closing point of the exhaust valves. The VVT influences the gas exchange process. The torque characteristics dependent on the engine speed and load can be modified. The closing point of the inlet valves can be optimized for inertial and wave effects of the air flow in the intake manifold, i.e., for increasing the air flow into the combustion chamber. Especially the phasing of the exhaust camshaft can be used for the internal exhaust gas recirculation. It has effects on the emission production, torque and fuel efficiency. Further, VVT can have effects on the wall film behavior in multi-port injection engines. The phasing is achieved by controlling engine oil flow into cam phasing chambers using solenoid valves. The set-point for the valve timing is decided by the engine operating condition and the feedback circuit is established by cam and crank sensors. SYSTEM SCHEMATIC:
Figure 2 - Variable Cam phasing actuator hydraulic ring Chamber A
Chamber B
Figure 3 - Cam phasing device Author: Seetareddy Beeravalli
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Adjustment angle
Oil line to A Drive from crankshaft
B
A
Cam
Camshaft Oil line to B
Rotor Stator
Outflow to oil pan O
Oil line to chamber A
Pressurized oil P
Oil line to chamber B
Outflow to oil pan O
Figure 4 - VCP actuator principle
Spring Control piston
Stick
Solenoid
Holding, 50% PWM O
B
O
B
P
A
O
Adjustment, 100% PWM P
A
O
Adjustment, 0% PWM
Figure 5 - Oil Control Valve Principle
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CONCEPT OF MID-LOCK: With the current VVT system, default position is at one end of cam phasing range. The cam can move in only one direction. There are some specific areas where there is further scope in improving fuel efficiency and cold start emission. This is achieved by introducing mid-lock in the VVT where in the default position is moved to an intermediate position. To start the VVT actuator from intermediate position a new lock is introduced which is controlled by digital actuator to lock or unlock with additional pin on ECU. Along with this new requirement, the concept should also support existing VVT system. The current solution is upgraded to meet the new requirement wherein the actuator to move in both directions. This needed a complete function update of VVT from the base function models. The algorithm was updated for new VVT actuator along with the test vectors.
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Figure 6 – Adjustment range relative to default position for intlet side
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PITFALL IDENTIFIED IN THE DESIGN BY MVS: One of the requirements of the algorithm was to Cam phase Set point ( Desired value ) limitation. During the design, the strategy implemented did not work for the negative cam phasing. This was detected by simulating the model using test vectors. The deviation from expected value is observed as shown below. The design is corrected and rechecked for the function behavior (picture below).
STIMULI setpoint/Signal Builder : Group 1 CAM SP_PREL
10 0 -10
20
CAM_SP_LIM
10 0 -10 -20 0
1
2
3
4
5 6 Time (sec)
7
8
9
10
Figure 7 – Input stimuli for model (signal A and B)
MODEL
Figure 8 – Design of logic before and after detecting design deviation Author: Seetareddy Beeravalli
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RESULT
Figure 9 - Verification with MVS
AUTO CODE GENERATION: The model is converted to fixed point in which scaling is done for the signals and their operations. Scaling is the technique used to represent floating point signals in double precision with implementation variables using single precision float or integer resolution. To cross check whether scaling is correct, the fixed point model is simulated using the same test vectors. The deviation of the result from FLP (Floating Point) simulation result is observed (refer figure 11). The verified FXP models were used for code generation using Embedded Coder Š in Matlab environment. The code was tested against the same test vectors used for validating the SDA model by using SIL/ PIL (refer figure 10) and confirmed with minimal effort that the software is working as expected and also confirmed that it will work on target platform (refer figure 11). The generated auto-code has been integrated in the Engine management Software (EMS) and tested on vehicle.
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Figure 10 - MBD flow chart with SDA Adhering to above steps of MBD results in a defect free code.
Figure 11 - Result from FLP, FXP, SIL, and PIL are identical
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ALGORITHM OPTIMIZATION BASED ON SIL COVERAGE REPORT: Based on SIL coverage report where dead codes are found due to design or scaling, are removed from the model. This is helpful even to test robustness of solution and even to save memory.
<CAM_PHA>
C_CAM_LOCK_TOL_VCP V.6.5
V.6.4
<CAM_PHA>
Dead Code
AND
C_CAM_LOCK_BOL_VCP V.6.9
V.6.5
V.6.4
C_CAM_LOCK_AMP_VCP
NOT
V.6.4
SET
V.6.6
<CAM_PHA>
OR
+ + C_CAM_LOCK_HYS_VCP
V.7.5
V.6.4
V.6.6
V.6.5
RST
Q
LV_CAM_LOCK
LV_CAM_LOCK
Q_in RST_DOMINANT
<LV_CAM_LOCK>
V.6.11
Figure 12: Detection of dead code during MBD
Coverage report of decisions
Coverage in %
100
80 60
Time sync tasks Async tasks
40 20 0
Events
Figure13: Coverage report for decisions
EFFORT COMPARISON: To develop and validate the above solution for the new concept by manual coding was estimated to take 3 months. With MBD approach, the effort consumed for this algorithm development was 2 months, with added benefit of verified code against same test vectors.
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Effort comparison 250
Effort in hr
200 150
Manual Coding
100
MBD
50 0
Figure 14 â&#x20AC;&#x201C; Comparison of effort between manual coding and MBD
CONCLUSION The model based development approach is very useful to find pitfalls in solution at an early stage of development, and reduce probability of any software defect by detecting early using SIL/PIL. With above development, concept solution is validated and the time to develop is faster because lot of effort can be saved in development and testing of feedback control algorithms.
ACKNOWLEDGMENTS I thank Continental for assigning the responsibility work on complex functions.
REFERENCES 1. Modern Control Engineering book written by Katsuhiko Ogata 2. Model based development environment at SiemensVDO Automotive AG, Division Powertrain, IAC2004 (Kunze, M.; Reuther, A.) 3. Verification by Simulation within the model based development process at Continental Automotive Group, Business Unit Engine Systems; Simulation and Test 2010 (Burger, T.; Kunze, M.; Schmidt, S.; Neiva Camargo, I.; MĂźller, R.)
CONTACT Mr. Seetareddy Beeravalli Powertrain Engine Systems, Continental Automotive Components (India) Pvt. Ltd, Author: Seetareddy Beeravalli
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Technical Center, Ozone Manay Tech Park, 4th Floor, 56/18 and 55/9, Garvebhavi palya, Hosur main Road, Bangalore - 560068 Karnataka, India Email: Seetareddy.Beeravalli@continental-corporation.com
ADDITIONAL SOURCES DEFINITIONS, ACRONYMS, ABBREVIATIONS ACG: Auto Code Generation EMS: Engine Management System FLP: Floating point model FXP: Fixed point model. MIL: Model In Loop SIL: Software In Loop PIL: Processor In Loop VVT: Variable Valve Timing MBD: Model Based Development SDA: System Design Automation
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