Journal of Chongqing University of Technology(Natural Science) ›› 2023, Vol. 37 ›› Issue (6): 66-74.
• Vehicle engineering • Previous Articles Next Articles
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Abstract: In order to improve the recovery rate of HEV braking energy and ensure the braking effect,this paper proposes the particle swarm optimization algorithm to optimize the fuzzy control strategy of HEV regenerative braking.Firstly,considering both braking effect and braking energy recovery,a multi-segment braking force distribution curve between the front and the rear wheels is designed to distribute more braking force to the front wheels as much as possible.Then,by using the fuzzy controller,mechanical braking force and regenerative braking force distributions of the front wheels are achieved.Finally,in order to further improve the braking energy recovery and ensure the braking effect of the vehicle,the braking effect and the braking energy recovery are taken as the optimization objective function,and the fuzzy rules are optimized by using the particle swarm optimization algorithm.The results show that,under LYDC driving conditions,the designed multi-segment front and rear wheel braking force distribution curves and the fuzzy rules optimized by the particle swarm optimization algorithm can effectively improve the regenerative braking energy recovery and meet the requirements of the braking effect.
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http://clgzk.qks.cqut.edu.cn/EN/Y2023/V37/I6/66
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