| REGENERATIVE BRAKING CONTROL STRATEGIES WITH
FIXED RATIO AND VARIABLE RATIO BRAKING FORCES
OPTIMIZATION DISTRIBUTION FOR ELECTRIC VEHICLES
DURING DOWNHILL PROCESS |
| Li Xiangjie 1, Zhang Xiangwen 1, Wang Yangxiong 2 |
1Guilin University of Electronic Technology
2Huizhou Desay SV Automotive Co., Ltd. |
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| ABSTRACT |
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The regenerative braking system can recover the braking energy to extend the mileage of electric vehicles, however, recovering more energy and ensuring the braking stability are conflicted each other. In addition, during the downhill process, the road slope angle has a great influence on braking stability and braking energy recovery efficiency. In this study, considered the road slope angle estimation, the fixed ratio and variable ratio braking forces optimization distribution methods are designed based on the vehicle stability demand, and the regenerative braking control strategies are proposed to recovery more energy with the designed braking forces distribution methods. In this way, the conflict between braking stability and energy recovery can be solved. In order to verify the strategies, the system model, road condition and driving intentions are established on dSPACE’s ASM and Simulink co-simulation platform, and the regenerative braking control strategies are realized and simulated on different slope roads and UDDS urban road cycle conditions. The results show that the estimated error of the road slope angle can be within 0.4°. The two strategies can ensure the vehicle braking stability. The recovered energy increases obviously with the increase of slope angle. The optimization distribution methods have a better energy recovery effect than the unoptimized methods, the optimal variable ratio method increases the recovered energy by up to 3.67 %, and the optimal fixed ratio method increases the recovered energy by up to 3.38 %. |
| Key Words:
Electric vehicles, Regenerative braking, Extended kalman filter, Slope angle estimation, Braking force distribution, Downhill process |
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Corresponding Author.
Zhang Xiangwen , Email. 
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