Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle

被引:23
作者
Geng, Cong [1 ]
Ning, Dawen [1 ]
Guo, Linfu [1 ]
Xue, Qicheng [1 ]
Mei, Shujian [1 ]
机构
[1] Beijing Jiaotong Univ, Beijing Key Lab Powertrain Technol New Energy Veh, Beijing 100044, Peoples R China
关键词
hybrid electric vehicle; energy recovery; braking strength; control strategy;
D O I
10.3390/en14082202
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper proposes a double layered multi parameters braking energy recovery control strategy for Hybrid Electric Vehicle, which can combine the mechanical brake system with the motor brake system in the braking process to achieve higher energy utilization efficiency and at the same time ensure that the vehicle has sufficient braking performance and safety performance. The first layer of the control strategy proposed in this paper aims to improve the braking force distribution coefficient of the front axle. On the basis of following the principle of braking force distribution, the braking force of the front axle and the rear axle is reasonably distributed according to the braking strength. The second layer is to obtain the proportional coefficient of regenerative braking, considering the influence of vehicle speed, braking strength, and power battery state of charge (SOC) on the front axle mechanical braking force and motor braking force distribution, and a three-input single-output fuzzy controller is designed to realize the coordinated control of mechanical braking force and motor braking force of the front axle. Finally, the AMESim and Matlab/Simulink co-simulation model was built; the braking energy recovery control strategy proposed in this paper was simulated and analyzed based on standard cycle conditions (the NEDC and WLTC), and the simulation results were compared with regenerative braking control strategies A and B. The research results show that the braking energy recovery rate of the proposed control strategy is respectively 2.42%, 18.08% and 2.56%, 16.91% higher than that of the control strategies A and B, which significantly improves the energy recovery efficiency of the vehicle.
引用
收藏
页数:19
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