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Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle

Author

Listed:
  • Cong Geng

    (Beijing Key Laboratory of Powertrain Technology for New Energy Vehicles, Beijing Jiaotong University, Beijing 100044, China)

  • Dawen Ning

    (Beijing Key Laboratory of Powertrain Technology for New Energy Vehicles, Beijing Jiaotong University, Beijing 100044, China)

  • Linfu Guo

    (Beijing Key Laboratory of Powertrain Technology for New Energy Vehicles, Beijing Jiaotong University, Beijing 100044, China)

  • Qicheng Xue

    (Beijing Key Laboratory of Powertrain Technology for New Energy Vehicles, Beijing Jiaotong University, Beijing 100044, China)

  • Shujian Mei

    (Beijing Key Laboratory of Powertrain Technology for New Energy Vehicles, Beijing Jiaotong University, Beijing 100044, China)

Abstract

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.

Suggested Citation

  • Cong Geng & Dawen Ning & Linfu Guo & Qicheng Xue & Shujian Mei, 2021. "Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle," Energies, MDPI, vol. 14(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2202-:d:536600
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    References listed on IDEAS

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    1. Di Zhao & Liang Chu & Nan Xu & Chengwei Sun & Yanwu Xu, 2018. "Development of a Cooperative Braking System for Front-Wheel Drive Electric Vehicles," Energies, MDPI, vol. 11(2), pages 1-24, February.
    2. Enang, Wisdom & Bannister, Chris, 2017. "Modelling and control of hybrid electric vehicles (A comprehensive review)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1210-1239.
    3. Qiu, Chengqun & Wang, Guolin & Meng, Mingyu & Shen, Yujie, 2018. "A novel control strategy of regenerative braking system for electric vehicles under safety critical driving situations," Energy, Elsevier, vol. 149(C), pages 329-340.
    4. Hanwu Liu & Yulong Lei & Yao Fu & Xingzhong Li, 2020. "An Optimal Slip Ratio-Based Revised Regenerative Braking Control Strategy of Range-Extended Electric Vehicle," Energies, MDPI, vol. 13(6), pages 1-21, March.
    5. Boyi Xiao & Huazhong Lu & Hailin Wang & Jiageng Ruan & Nong Zhang, 2017. "Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis," Energies, MDPI, vol. 10(11), pages 1-19, November.
    6. Yang Yang & Qiang He & Yongzheng Chen & Chunyun Fu, 2020. "Efficiency Optimization and Control Strategy of Regenerative Braking System with Dual Motor," Energies, MDPI, vol. 13(3), pages 1-21, February.
    7. Wu, Jian & Wang, Xiangyu & Li, Liang & Qin, Cun'an & Du, Yongchang, 2018. "Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control," Energy, Elsevier, vol. 145(C), pages 301-312.
    8. Yafei Xin & Tiezhu Zhang & Hongxin Zhang & Qinghai Zhao & Jian Zheng & Congcong Wang, 2019. "Fuzzy Logic Optimization of Composite Brake Control Strategy for Load-Isolated Electric Bus," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-14, October.
    9. Qinghai Zhao & Hongxin Zhang & Yafei Xin, 2021. "Research on Control Strategy of Hydraulic Regenerative Braking of Electrohydraulic Hybrid Electric Vehicles," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, February.
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    Cited by:

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