Optimal thermal design of LED automotive headlamp with the response surface method

Optimal thermal design of LED automotive headlamp with the response surface method Zhibin Tang1,4, Jiajie Fan1,2,3*, Wei Chen2, Yutong Li1,2, Moumouni Guero Mohamed1, Ru Li4 College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China; 2 Changzhou Institute of Technology Research for Solid State Lighting, Changzhou 213161, China 3 EEMCS Faculty, Delft University of Technology, Delft 2628, the Netherlands 4 Changzhou Xingyu Automotive Lighting System Co, Ltd. China. *Corresponding: E-mail: jay.fan@connect.polyu.hk, jiajie.fan@hhu.edu.cn. Tel: +86-519-85191933.

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Abstract Light Emitting Diode (LED) is gradually being applied in automotive lighting systems as the new generation of light source. Recently, increasing demands are adapt on automotive headlamps, including not only being functionally perfect, cost-effective and durable, but also with fashion, energy saving and environmental protection. LED light source has the advantages of long lifetime, high efficiency and energy saving, compact size etc., therefore, it has been widely used in headlamps, turn signals, brake lights, position lights, etc., and will soon become the mainstream of the automotive light source market. Although it has higher energy conversion efficiency, LED headlamp is still suffering difficulties on the thermal management. In this paper, we optimize the designs of heatsink for a commercialized LED automotive headlamp module by using the response surface method. Firstly, the temperature distribution of the test sample is simulated by the finite element (FE) method. Then, we use the response surface method to optimize the design parameters of heatsink on its thermal dissipation capacity. The results indicate that: (1) Through optimizing the structure of the heat sink with the thickness, spacing and height of fins as 3mm, 9mm and 60mm respectively, the LED junction temperature drops by 2.9%; (2) By changing the materials of heat sink and PCB substrate as 6063 aluminum alloy and AlN respectively, the LED junction temperature lowers down by 11.9%.

Keywords: LED; Automotive headlamp; Thermal management; Finite element; Response surface method 1. Introduction As a new type of light source, Light-emitting Diode (LED) has the following advantages: (1) small size, easy to design and meet the requirements of automotive lightweight; (2) good photoelectric performance and quick response to effectively increase the active safety of the car [1]; (3) it has excellent characteristics of energy saving, environmental resistance and vibration[2-3]. At present, LED light sources are mainly used in automotive brake lights, turn signals, reversing lights, tail lights, and instrument lights [4]. However, the application of LED in automobiles still has technical limitations, for instance, the thermal effect caused by poor heat dissipation is one of the main bottlenecks [5]. When it works in a high temperature environment for a long time, the life of LED will be greatly shortened [6], and the optical performance will be greatly affected [7], which has a great negative impact on the safe driving of the car. Therefore, it is important to solve the thermal management problem for LED automotive lighting.

In terms of thermal management for LEDs, Luo et al. [8] proposed a new heat dissipation method with the steam chamber coupling finned heat sink. Ma et al. [9] developed a

heat dissipation method for the front surface of cooling used in high power LED lamp. Ye et al. [10] proposed a new way to realize the thermal management by using phase change technology. Yang et al. [11] studied the heat transfer characteristics of different layer crack shapes and positions on the LED package interface by constructing different interface spallation models. Shaeri et al. [12] enhanced the heat dissipation performance of the heat sink through the fin opening. S. W. Jang et al. [13] used the micro jet to dissipate the vehicle lights’ heat, and discussed the effect of heat sink shape on heat dissipation. S. J. Park et al. [14] studied the effects of fin shapes on the heat dissipation of the lamp, and obtained the best heat dissipation effect with the radioactive radial fins.

Generally, the main objective of thermal management for LED automotive headlamp is to maintain the LED junction temperature lowest for the stability, reliability and longevity of LED. In this study, the FEA simulation with CFD software and the response surface method based on the Design-Expert program were used to optimize the thermal design of heatsink for a commercialized LED automotive headlamp module.

2. Modeling and simulation 2.1 3D modeling The high power LED automotive headlamp used in this study is LUW HWQP, which delivers high brilliant white light for automotive forward lighting .This type of LED can work in the temperature range from -40 to 150°C, the maximum permissible junction temperature is 130°C, the light-emission area is less than 1mm ² , and the typical correlated color temperature (CCT) is 5600K. Its colorimetric properties conform to the ECE regulation. Figure 1 presents the 3D model of this headlamp.

Figure1. 3D modeling of the LED automotive headlamp used in this study.

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2.2 Simulation result of original model The temperature of each component in the initial model is determined by the FEA simulation. First, the air module is built according to the size of the heat sink module. Table 1 and 2 show the simulation parameter and the boundary condition settings, respectively. Finally, the mesh numbers of air domain, heat sink, PCB substrate, and LED are 8, 3, 2, 1 respectively and we used 150 steps iterative to solve. Figure 2 shows the simulation result under the boundary condition set in Table 2.

Table 1. Simulation parameter setting Heat sink material PCB substrate material LED model

Die-cast Al Aluminum plate LUW HWQP

Table 2. Boundary condition setting Pressure on the upper and lower sides Six-sided temperature LED thermal power

0Pa 25℃ 3w*70%

Considering the aspects of weight and material cost, the copper with high thermal conductivity is used as the material of lamppost, and the aluminum alloy with high thermal conductivity is usually used as the heat sink base. As copper has highest thermal conductivity up to 398W/m·K at room temperature, it can reduce the LED’s junction temperature to 72.020℃. Because the density of copper is three times higher than that of aluminum, the weight of copper-based heat sink with the same structure is three times higher than that of aluminum-based heat sink. At the same time, the price of copper is higher than aluminum, so aluminum is generally applied as a raw material for LED heat sink. However, the hardness of pure aluminum is too low to prepare forceresistant products, it is also not suitable to be as a heat sink material. Compared to pure aluminum, aluminum alloys possess better physical properties and a simpler preparation process with a lightweight. Figure 4 shows the FEA simulation result of using the 6063 Al alloy material in heat sink.

Figure 2. The simulated temperature distribution of original LED headlamp model.

Figure 3. The simulated characteristic temperatures of four conditions with different heat sink materials.

2.3 Effect of heat sink material on the heat dissipation Heat sinks are designed using materials with high thermal conductivity, such as aluminum alloys and copper. In the auxiliary heat sink design for LED headlamps, the heat dissipation effect can be achieved through increasing the air convection between the interior lamp and the base of heat sink. Thus, the thermal characteristics of heat sink have a direct influence on the heat transfer of headlamp. To understand the influence rule of heat sink on the LED junction temperature distribution, we used the steady-state FEA method to simulate the temperature distributions of heat sinks with different materials. Table 3 shows the parameter settings for different heat sink materials. Figure 3 lists the simulated characteristic temperatures.

Table 3. Parameter settings for different heat sink materials Materials

Cu

Thermal conductivity (W/m·K)

398

Die-cast Al 110

6061 Al alloy

6063 Al alloy

154

200

Figure 4. The simulated temperature distribution of model with 6063 Al alloy heatsink.

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2.4 Effect of substrate material on the heat dissipation During the heat dissipation process of headlamp, the substrate not only mechanically supports LEDs, but also acts as the heat transfer from the LEDs to the external radiator, which is a very important heat dissipation channel. Therefore, the substrate material should not only provide structural strength, but also achieve the high thermal conductivity requirement. Traditional FR-4 PCB can meet the demand of cooling at low power applications, however, with the increase of LED power, it has difficulty to meet the demand. Thus, the aluminum-based metal circuit board (MCPCB) and ceramic substrate (Al3O2, AlN) appear. To make clear the impact of different substrate materials on the heat dissipation, we compared four substrate materials, including FR-4, MCPCB, Al3O2 and AlN by simulation calculation on thermal dissipation characteristic of LED headlamps. Table 4 shows the thermal conductivity of each substrate material used in simulation.

Table 4. The thermal conductivity of each substrate materialused in simulation Materials

FR-4

MCPCB

Al3O2

AlN

Thermal conductivity (W/m·K)

16.9

50

29

170

Figure 5 .The simulated characteristic temperatures of four conditions with different substrates.

The simulation results shown in Figure 5 indicate that the AlN substrate with highest thermal conductivity can lower the LED junction temperature around 5.573 ℃ , which builds essential basis for selecting AlN as the better substrate material in high power LED headlamp. Figure 6 shows the temperature distribution simulation result with the AlN substrate.

3. Optimization with Response Surface Method Response surface method (RSM) is a useful method for optimization modeling processed by the mathematical analysis and statistical techniques. It combines the experimental design with regression analysis to implement systematically the experiments within the defined area. After collecting the required response values, it conducts the regression analyses to collate the relations between response values and parameters for optimal solution found within the planned experiments. Thus, we applied the RSM design optimization in this paper to estimate the parameters and confirm the influences with respect to target value.

3.1 Design of Experiments There are many variables that can be optimized, such as fin spacing, fin thickness, fin height, dimension of heat sink, airflow velocity, etc. In this paper, the fin thickness, spacing and height of heat sink were considered. When process factors (independent variables) satisfy an important assumption that they are measurable, continuous, and controllable by experiments, we carried out the RSM procedure as follows: (1) Perform a series of experiments for adequate and reliable measurement of the response of interest.

(2) Develop a mathematical model of the second-order response surface with the best fit.

(3) Determine the optimal set of experimental parameters producing the optimum response value.

(4) Represent the direct and interactive effects of the process parameters (factors) were through two and threedimensional plots.

In order to determine if a relationship existed between the factors and the responses investigated, the collected data was statistically analyzed by using the regression analyses [15].

We employed a regression design to model the response as a function of a few continuous factors.

3.2 Box-Behnken test results and analysis On the basis of changing the heat sink material and the PCB substrate material, three significant factors affecting the thickness, spacing and height of the heat sink fins were considered as factors. The Box-behnken test factors and levels are shown in Table 5. Where A, B, and C represent the thickness, spacing, and height of the heat sink fins, respectively. The test results are shown in Table6.

Table 5. Factors and levels of Box-Behnken of radiator structure design.

Factors A Fin thickness/mm B Fin spacing/mm C Fin height/mm

Figure 6 .The simulated temperature distribution of model with AlN substrate.

-1 1 5 20

0 2 7 40

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1 3 9 60

Table 6. Results and analysis of Box-Behnken experiments of radiator structure design.

Serial number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

A 3 2 2 1 1 2 2 2 2 1 2 1 3 2 2 3 3

B 5 7 7 7 9 7 9 7 9 5 7 7 7 5 5 7 9

C 40 40 40 20 40 40 60 40 20 40 40 60 60 20 60 20 40

Y/Temperature 76.126 71.271 71.161 79.609 70.407 71.245 65.242 71.154 81.094 73.525 71.283 69.806 65.623 84.273 70.049 81.185 71.503

Using the Design Expert software to fit the results in Table 6, the regression equation is obtained: Y = 71.22 + 0.14A - 1.97B - 6.93C - 0.38AB - 1.44AC - 0.41BC + 0.28A 2 + 1.39B 2 + 2.55C 2 Performing the variance analysis on the above regression equation. The results are shown in Table 7. It can be seen that the established model with P<0.0001 is significant, which indicates that the model has high reliability. After variance analysis, the primary and secondary relationships of three factors on the temperature of the radiator can be obtained: C>A>B, that means the heat sink fin height > the fin thickness > the fin pitch. The one-time coefficient C has a most significant effect on the results. The cross-terms AB and BC have no significant effect on the results. The quadratic coefficients A2 and C2 have extremely significant effects on the results.

Table 7. Variance analysis of response surface test results.

Source Model A B C AB AC BC A2 B2 C2 Residual Lack of Fit Pure Error

Squares 463.10 0.15 30.93 384.21 0.56 8.29 0.66 0.33 8.12 27.45 7.76 7.75 0.015

Df 9 1 1 1 1 1 1 1 1 1 7 3 4

Cor Total

470.86

16

Square 51.46 0.15 30.93 384.21 0.56 8.29 0.66 0.33 8.12 27.45 1.11 2.58 3.784E003

Value 46.41 0.13 27.89 346.54 0.51 7.48 0.60 0.30 7.32 24.76

Prob <0.0001 0.7257 0.0011 <0.0001 0.4985 0.0291 0.4648 0.6028 0.0304 0.0016

688.86

<0.0001

Figure 7 shows the diagnostics result in Design Expert, in which the closer of data to the line means the higher reliability. According to this result, we can confirm that this model has high significance.

Figure 7. Reliability diagnosis chart 3.3 Response surface results and analysis The influence of the fin thickness, spacing and height on the LED junction temperature are obtained and shown in Figure 8-10.

Figure 8. The effect of heat sink fin thickness and spacing of on the heat dissipation.

Figure 9. The effect of heat sink fin thickness and height of on the heat dissipation.

Figure 10. The effect of heat sink fin spacing and height of on the heat dissipation.

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The above results indicate that: (1) When the height of the fins is fixed, with the thickness and spacing of the fins increasing, the junction temperature of the LED’s firstly decreases and then increases. The fin thickness between 2mm and 3mm and the fin spacing between 7mm and 9mm are more suitable; (2) When the distance of the heat sink is fixed, with the height of the fins increasing, the junction temperature of the heat sink LED is getting higher and higher, indicating that the higher heights of the heat sink fin, the better effects of the heat dissipation; (3) When the thickness of the fins is fixed, with the pitch and height of the fins increasing, the junction temperature of the LED’s firstly decreases and then increases, indicating that the spacing and height of the heat sink fins have strong interaction, which has a great influence on the junction temperature of the LED. According to the optimization conditions of the Box-Behnken software prediction model, the results show that when the thickness of heat sink fin is 3 mm, the spacing is 8.98 mm, and the height is 60 mm, the LED junction temperature can be controlled at the lowest.

3.4 Simulation and verification According to the above analysis, we used the optimized heat sink fin design. In the optimization model 1, the heat sink material is selected as die-cast aluminum and the PCB substrate material is aluminum substrate. After setting the boundary conditions and solving the mesh, the simulation result of optimized is shown in Figure 11. Moreover, setting the heatsink material as 6063 aluminum alloy and the PCB substrate material as AlN in the optimization model 2, the simulation result of optimized is shown in Figure 12.

Figure 11. The simulated temperature distribution of the optimized model 1.

Figure 12. The simulated temperature distribution of the optimized model 2.

Table 8 shows the simulated maximum temperatures of the heat sink, substrate, and LED. The results indicate that compared with the initial model, the LED junction temperature caused by the optimization of the fin structure drops by 2.9%. Due to the optimization of the heat sink material, PCB substrate material and fin structure, the LED junction temperature drops by 11.9%. It indicates that the response surface method is an effective tool to optimize the design of heatsink for LED automotive headlamp.

Table 8. Model temperature distribution after simulation.

The heat sink Temperature/℃

PCB substrate Temperature / ℃

LED Junction Temperature /℃ 73.867 71.684

Initial model 64.378 68.197 Optimization 61.995 63.219 model 1 Optimization 56.619 56.487 65.085 model 2 Note: The initial model represents the original LED headlamp model with the heat sink material as cast aluminum, the PCB substrate material as aluminum substrate. The optimized model 1 is the model only with the structure optimization. The optimization model 2 represents the model by replacing the heat sink material as 6063 aluminum alloy and the PCB substrate material as AlN.

4. Conclusions In this paper, we optimize the heat dissipation design of a commercialized LED automotive headlamp module by using the response surface method and the FEA simulation.

The structure of heatsink is optimized with the thickness, spacing and height of fins as 3mm, 9mm and 60mm respectively. Meanwhile, the 6063 aluminum alloy and AlN are selected as new heat sink and PCB materials. The results indicate that: compared to the initial model, the LED junction temperature contributed by the structure optimization drops by 2.9%; the LED junction temperature due to the material optimization drops by 11.9%. This improvement can provide a new design for this type LED automotive headlamp module with more effective thermal management.

Acknowledgements The work described in this paper was partially supported by the National Natural Science Foundation of China (51805147), the Six Talent Peaks Project in Jiangsu Province (GDZB-017) ,the Fundamental Research Funds for the Central Universities (2017B15014) and the Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No.2018K200C).

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