The optimization of EV powertrain s efficiency control strategy under dynamic operation condition

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1 ELECTRI C MACHINES AND CONTROL Vol. 16 No. 3 Mar % U A X The optimization of EV powertrain s efficiency control strategy under dynamic operation condition HUANG Wan-you 1 CHENG Yong 1 JI Shao-bo 1 LI Chuang 2 ZHANG Xiao-wen 2 ZHANG Hai-bo 3 1. College of Energy & Power Engineering Shandong University Jinan China 2. Jinan Electric Vehicle Operation Co. Ltd Jinan China 3. Shandong Baoya New Energy Vehicle Co. Ltd Jinan China Abstract A control strategy of Electric Vehicle EV powertrain under dynamic operation conditions was optimized in order to lower power consumption and prolong EV's endurance mileage. Based on measured data from an AC asynchronous motor and a LiFePO4 /C Li-ion battery pack a powertrain's working efficiency describing model was developed. An optimal control method to improve EV powertrain's efficiency was deduced following the model. To verify the method a powertrain's simulating model was established and its validation was conformed in contrast to the results of experiments. An EV s start acceleration process control strategy was optimized according to the simulating results and the strategy was implemented in the test bench. The testing results show a 3. 3% efficiency improvement of the new strategy over the original one which suggests that this powertrain efficiency model can be used to optimize the control strategy at dynamic operation conditions. Key words electric vehicles optimal control strategy dynamic operation condition efficiency model powertrain simulating model AA11A GGX10506 yzc

54 16 0 75% state of charge SOC 1-2 2 2.

2 % state of charge SOC Matlab /SIMULINK V /100 Ah CAN 20 kw 8 η m 1 GB /T Fig. 1 Real curves of power-train's working parameters SOC ± 5 Fig. 2 Schematic of test bench CAN SOC 2. 2

3 55 SOC 9 20 ~ 40 5 6 34 ± 3 Fig. 3 3 Efficiency curve of driving motor 3 η m = - 5. 958 10-12 n 4 + 3. 813 10-8 n 3-7. 723 10-5 n 2 + 4. 341 10-2 n - 1. 099 10-4 P 4 + 1. 423 10-2 P 3-6.

5 1 4 4 5 Real battery pack s temperature vs time 4 Fig. 4 p SOC 2-9. 226 10-2 p SOC - 3. 913 10-5 Comparison of measured driving motor system s efficiency and simulation s 2. 3 Fig.

3 3 55 SOC 9 20 ~ ± 3 Fig. 3 3 Efficiency curve of driving motor 3 η m = n n n n P P P P np np np n 2 P n 2 P n 3 P η m % n r /min P kw Fig Real battery pack s temperature vs time 4 Fig. 4 p SOC p SOC Comparison of measured driving motor system s efficiency and simulation s 2. 3 Fig. 6 6 Discharge efficiency of battery pack Simulink 6 SOC 6 η b = p SOC P P P p SOC 2 P p SOC P p SOC P

56 16 η b % p SOC 10-4 P 4 + 1. 488 10-2 P 3-5. 728 10-1 % P kw P 2 + 3. 202 P + 7. 546 10-6 np 2 + 7. 322 7 10-2 np - 2. 995 10-4 n 2 P + 4. 022 10-7 n 3 P + 55. 268-9. 832 10-6 p SOC 3 + 1. 03% 1.

4 56 16 η b % p SOC 10-4 P P % P kw P P np np n 2 P n 3 P p SOC % p SOC p SOC P P P /100 5 Table 1 1 Simplifying of motor system s efficiency model 7 n 2 p Fig. 7 Comparison of measured battery pack s discharge efficiency and simulation s n 2 p 2 n 3 p r /min η = η m η b /100 3 η % 1 2 S S S = n i = 1 x f i - x i 2 4 x f i x i i = 1 2 n n 484 n 180 S b S K np np np np 3 + n 2 p K = S b S S b S Fig. 8 Efficiency MAP of powertrain at r / min SOC 1 5 np 3 n 2 P % SOC 2. 5 η = n n n n r /min

3 57 10 T f T w T limit1 4 T j T limit2 T limit1 = T f + T w T limit2 = T limit1 + ct j T dem T limit1 a > 0 T dem T limit2 a > 0 T dem T limit1 a < 0 T dem T limit2 a < 0 6 T dem a c 5 SOC 11 5 P p

5 T f T w T limit1 4 T j T limit2 T limit1 = T f + T w T limit2 = T limit1 + ct j T dem T limit1 a > 0 T dem T limit2 a > 0 T dem T limit1 a < 0 T dem T limit2 a < 0 6 T dem a c 5 SOC 11 5 P p k + 1 = p k - η' p k k = 0 η p k P k p k ε p dem = p k + 1 T dem Fig. 10 EV powertrain's simulation model 1 SOC 2 11 Fig. 9 9 Optimal control diagram at dynamic operation conditions 9 Fig. 11 Real curves of motor speed and torque S - 11 SOC % Matlab /Simulink 11

58 16 2 Infineon XC164CM Table 2 Data table of powertrain s efficiency / r /min /N m /A SOC /% /% /% /% 333 143. 7 22. 0 98. 24 71. 7 74. 6 4. 0 710 172. 8 52. 9 97. 6 77. 4 79. 1 2. 2 845 129. 9 44.

6 Infineon XC164CM Table 2 Data table of powertrain s efficiency / r /min /N m /A SOC /% /% /% /% Fig. 12 Relationship between powertrain s efficiency and motor torque Fig. 13 Comparison of EV s start acceleration process = 1. 4 i 0 = 4. 4 m = kg r = m 32 kw 100 Ah SOC 80% r /min i g between new strategy and the original's % % SOC

7 SOC Matlab /Simulink sing dynamic programming J Simulation % 7 3 conditions J distribution and factors of influence in electric vehicles J. Transact - ions of Beijing Institute of Technology J ZHANG Caiping ZHANG Chengning SONG Qiang. Efficiency testing research on electromotor drive system working districts of e- lectric vehicle J. Micromotors Servo Technique J ZHANG Bin LIN Chengtao CHEN Quanshi. Performance of 2. LiFePO4 /C Li - ion battery for electric vehicle J. Chinese Journal of Power Sources J D. JIANG Jiuchun WEN Feng WEN Jiapeng et al. Li - ion battery modeling and on-line model parameters identification for PEV 11. M. J. Journal of Electric Power Science and Technology MORTEZA Montazeri-Gh AMIR Poursamad BABAK Ghalichi. Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles J. Journal of The Franklin Institute SCHOUTEN Niels J SALMAN Mutasim A KHEIR Naim A. Energy management strategies for parallel hybrid vehicles using fuzzy logic J. Control Engineering Practice PĚREZ Laura V BOSSIO Guillermo R MOITRE Diego et al. Optimization of power management in an hybrid electric vehicle u-. Mathematics and Computers in D J Hu Jianjun GUO Chen QIN Datong et al. Control of electrical power driving systems based on optimal efficiency under driving. Journal of Chongqing University J WANG Zhenpo SUN Fengchun. Analysis of energy consumption 9. LiFePO4 /C

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