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Research on personalized control strategy of EHB system for consistent braking feeling considering driving behaviors

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  • Zhang, Ruijun
  • Zhao, Wanzhong
  • Wang, Chunyan
  • Tai, Kang

Abstract

Since the existing control strategy for electro-hydraulic composite braking (EHB) system is essentially "vehicle-centered", it is liable to cause incompatibility with current driving behavior, torque fluctuation and inconsistent braking feeling occur, which affects braking safety. In view of the above issue, a personalized MPC control strategy in accordance with the design methodology of characteristic E is presented. To do this, the data collection platform for characterizing driving behavior is constructed under typical vehicle-following conditions. Then, a generalized radial basis function (GRBF) neural network is adopted to accurately identify braking intensity of different driving behaviors. Next, an optimization model for the maximum energy recovery of EHB system is established in terms of required braking torque and motor speed, the distribution coefficient of braking torque is optimized by applying the adaptive particle swarm optimization (APSO) algorithm. Finally, the proposed personalized MPC control strategy is verified under different driving behaviors, the results display that: (1) the personalized MPC controller possess superiority of acquiring stable braking feeling, the torque tracking error is decreased by 96.8 %; (2) energy recovery for EHB system with optimized torque distribution is increased by 34.47 % under FTP-75 cycle conditions, and the response amplitude of braking feeling is increased by 5.6 %.

Suggested Citation

  • Zhang, Ruijun & Zhao, Wanzhong & Wang, Chunyan & Tai, Kang, 2024. "Research on personalized control strategy of EHB system for consistent braking feeling considering driving behaviors," Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224003402
    DOI: 10.1016/j.energy.2024.130568
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    References listed on IDEAS

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    1. Zhengrong Chen & Ruochen Wang & Renkai Ding & Bin Liu & Wei Liu & Dong Sun & Zhongyang Guo, 2025. "Research Progress and Future Prospects of Brake-by-Wire Technology for New Energy Vehicles," Energies, MDPI, vol. 18(11), pages 1-30, May.
    2. Wu, Jiajun & Liu, Hui & Ren, Xiaolei & Nie, Shida & Qin, Yechen & Han, Lijin, 2025. "A multi-objective optimization approach for regenerative braking control in electric vehicles using MPE-SAC algorithm," Energy, Elsevier, vol. 318(C).
    3. Li, Xuebo & Zhao, Xuan & Xu, Shiwei & Wei, Lulu & He, Jingjing & Shi, Peilong & Li, Meiying, 2025. "A novel braking energy management strategy for battery electric trucks with hydraulic retarder on long downhill," Energy, Elsevier, vol. 322(C).

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