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Review and Outlook of Fuel Cell Power Systems for Commercial Vehicles, Buses, and Heavy Trucks

Author

Listed:
  • Xingxing Wang

    (School of Mechanical Engineering, Nantong University, Nantong 226019, China)

  • Jiaying Ji

    (School of Mechanical Engineering, Nantong University, Nantong 226019, China)

  • Junyi Li

    (School of Mechanical Engineering, Nantong University, Nantong 226019, China)

  • Zhou Zhao

    (Technology Center-Foresight Technology Research Institute, Higer Bus Co., Ltd., Suzhou 215062, China)

  • Hongjun Ni

    (School of Mechanical Engineering, Nantong University, Nantong 226019, China)

  • Yu Zhu

    (School of Mechanical Engineering, Nantong University, Nantong 226019, China)

Abstract

The power system, which is also one of the most crucial parts of fuel cell cars, marks the biggest distinction between them and conventional automobiles. Fuel cell hybrid power systems are reviewed in this paper along with their current state of research. Three different kinds of fuel cell hybrid power systems—fuel cell–battery, fuel cell–supercapacitor, and fuel cell–battery–supercapacitor—are thoroughly compared and analyzed, and they are systematically explained in the three areas of passenger cars, buses, and heavy duty trucks. Existing fuel cell hybrid systems and energy strategies are systematically reviewed and summarized, including predictive control strategies based on game theory, power allocation strategies, fuzzy control strategies, and adaptive super twisted sliding mode control (ASTSMC) energy management techniques. This study offers recommendations and direction for the future direction of fuel cell hybrid power system research and development.

Suggested Citation

  • Xingxing Wang & Jiaying Ji & Junyi Li & Zhou Zhao & Hongjun Ni & Yu Zhu, 2025. "Review and Outlook of Fuel Cell Power Systems for Commercial Vehicles, Buses, and Heavy Trucks," Sustainability, MDPI, vol. 17(13), pages 1-30, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6170-:d:1695224
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    References listed on IDEAS

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    1. Li, Tianyu & Huang, Lingtao & Liu, Huiying, 2019. "Energy management and economic analysis for a fuel cell supercapacitor excavator," Energy, Elsevier, vol. 172(C), pages 840-851.
    2. Jia, Chunchun & Zhou, Jiaming & He, Hongwen & Li, Jianwei & Wei, Zhongbao & Li, Kunang & Shi, Man, 2023. "A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal- and health-constrained awareness," Energy, Elsevier, vol. 271(C).
    3. Mian, Shahid Hassan & Nazir, Muhammad Saqib & Ahmad, Iftikhar & Khan, Safdar Abbas, 2023. "Optimized nonlinear controller for fuel cell, supercapacitor, battery, hybrid photoelectrochemical and photovoltaic cells based hybrid electric vehicles," Energy, Elsevier, vol. 283(C).
    4. Ettihir, K. & Boulon, L. & Agbossou, K., 2016. "Optimization-based energy management strategy for a fuel cell/battery hybrid power system," Applied Energy, Elsevier, vol. 163(C), pages 142-153.
    5. Wang, Yujie & Sun, Zhendong & Li, Xiyun & Yang, Xiaoyu & Chen, Zonghai, 2019. "A comparative study of power allocation strategies used in fuel cell and ultracapacitor hybrid systems," Energy, Elsevier, vol. 189(C).
    6. Li, Tianyu & Liu, Huiying & Ding, Daolin, 2018. "Predictive energy management of fuel cell supercapacitor hybrid construction equipment," Energy, Elsevier, vol. 149(C), pages 718-729.
    7. Jia, Chunchun & Li, Kunang & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao, 2023. "Health-aware energy management strategy for fuel cell hybrid bus considering air-conditioning control based on TD3 algorithm," Energy, Elsevier, vol. 283(C).
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