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The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle

Author

Listed:
  • Jiaming Zhou

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
    Yangtze Delta Region Academy, Beijing Institute of Technology, Jiaxing 314019, China)

  • Chunxiao Feng

    (School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Qingqing Su

    (School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Shangfeng Jiang

    (Yutong Bus Co., Ltd., Zhengzhou 450016, China)

  • Zhixian Fan

    (Zhongtong Bus Holding Co., Ltd., Liaocheng 252000, China)

  • Jiageng Ruan

    (Department of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China)

  • Shikai Sun

    (China Transport Telecommunications & Information Center, Beijing 100011, China)

  • Leli Hu

    (School of Automobile and Transportation Engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.

Suggested Citation

  • Jiaming Zhou & Chunxiao Feng & Qingqing Su & Shangfeng Jiang & Zhixian Fan & Jiageng Ruan & Shikai Sun & Leli Hu, 2022. "The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6320-:d:821316
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    References listed on IDEAS

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    Cited by:

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    8. Nikita V. Martyushev & Boris V. Malozyomov & Ilham H. Khalikov & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Vadim Sergeevich Tynchenko & Yadviga Aleksandrovna Tynchenko & Mengxu , 2023. "Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption," Energies, MDPI, vol. 16(2), pages 1-39, January.
    9. Wang, Yichun & Zhang, Yuanzhi & Zhang, Caizhi & Zhou, Jiaming & Hu, Donghai & Yi, Fengyan & Fan, Zhixian & Zeng, Tao, 2023. "Genetic algorithm-based fuzzy optimization of energy management strategy for fuel cell vehicles considering driving cycles recognition," Energy, Elsevier, vol. 263(PF).
    10. Zhiming Zhang & Alexander Rex & Jiaming Zhou & Xinfeng Zhang & Gangqiang Huang & Jinming Zhang & Tong Zhang, 2023. "Dynamic Simulation Model and Experimental Validation of One Passive Fuel Cell–Battery Hybrid Powertrain for an Electric Light Scooter," Sustainability, MDPI, vol. 15(17), pages 1-19, September.

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