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Durability Oriented Fuel Cell Electric Vehicle Energy Management Strategies Based on Vehicle Drive Cycles

Author

Listed:
  • Xin Fu

    (School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, China)

  • Zengbin Fan

    (School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, China)

  • Shangfeng Jiang

    (School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, China)

  • Ashley Fly

    (Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK)

  • Rui Chen

    (School of Mechanical Engineering, Tianjin University, Tianjin 300072, China)

  • Yong Han

    (School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, China)

  • An Xie

    (School of Materials Science and Engineering, Xiamen University of Technology, Xiamen 361000, China)

Abstract

With the increasing severity of environmental problems and energy scarcity, fuel cell electric vehicles (FCEVs), as a sustainable and efficient means of transportation, are attracting more attention. The ageing of fuel cells (FCs) has become an urgent problem with the development of FCEV. In order to prolong the lifetime of FCs, this paper builds a model of a vehicle driven by two power sources, FC and lithium battery (Lib) using AVL Cruise. A rule-based energy management strategy (EMS) is developed in Simulink to explore the optimal control strategy for the vehicle in terms of the durability of the FC. An FC ageing model is used to quantify the degradation voltage of different duty cycles. The results show that the FC engagement levels, OCV operations, and start/stop operations can affect the lifetime of the FC significantly. By optimising the EMS, the lifetime of the FC is improved by 9.47%.

Suggested Citation

  • Xin Fu & Zengbin Fan & Shangfeng Jiang & Ashley Fly & Rui Chen & Yong Han & An Xie, 2024. "Durability Oriented Fuel Cell Electric Vehicle Energy Management Strategies Based on Vehicle Drive Cycles," Energies, MDPI, vol. 17(22), pages 1-17, November.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:22:p:5721-:d:1521731
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    References listed on IDEAS

    as
    1. Zhuang Tian & Zheng Wei & Jinhui Wang & Yinxiang Wang & Yuwei Lei & Ping Hu & S. M. Muyeen & Daming Zhou, 2023. "Research Progress on Aging Prediction Methods for Fuel Cells: Mechanism, Methods, and Evaluation Criteria," Energies, MDPI, vol. 16(23), pages 1-21, November.
    2. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    3. Tang, Xingwang & Zhang, Yujia & Xu, Sichuan, 2023. "Experimental study of PEM fuel cell temperature characteristic and corresponding automated optimal temperature calibration model," Energy, Elsevier, vol. 283(C).
    4. Qiu, Diankai & Peng, Linfa & Liang, Peng & Yi, Peiyun & Lai, Xinmin, 2018. "Mechanical degradation of proton exchange membrane along the MEA frame in proton exchange membrane fuel cells," Energy, Elsevier, vol. 165(PB), pages 210-222.
    5. Zou, Weitao & Li, Jianwei & Yang, Qingqing & Wan, Xinming & He, Yuntang & Lan, Hao, 2023. "A real-time energy management approach with fuel cell and battery competition-synergy control for the fuel cell vehicle," Applied Energy, Elsevier, vol. 334(C).
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