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An Electrochemical Performance Model Considering of Non-Uniform Gas Distribution Based on Porous Media Method in PEMFC Stack

Author

Listed:
  • Zhiming Zhang

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Chenfu Quan

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Sai Wu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Tong Zhang

    (School of Automotive Studies, Tongji University, Shanghai 201804, China
    Yangtze Delta Region Institute of Tsinghua University Zhejiang, Jiaxing 314006, China)

  • Jinming Zhang

    (School of Intelligent Manufacturing, Weifang University of Science and Technology, Weifang 262700, China)

Abstract

Proton exchange membrane fuel cell (PEMFC) is significant and favorable to the long-range and short refueling time in the vehicle industry. However, the non-uniform distribution of gas flow supply, particularly in the fuel cell stack is neglected in the electrochemical model for PEMFC performance optimization. The purpose of this study is to break through this limitation to establish an optimized electrochemical fuel cell performance model, with porous media methods considering the non-uniform gas flow distribution in fuel cell stack with different compression of the gas distribution layer (GDL). The numerical models are validated by experimentation of a practical fuel cell stack. For the established fuel cell model, there is a 5% difference between the maximum and minimum speeds of various flow channels in the anode flow field under 10% GDL compression. Furthermore, the single-channel electrochemical performance model is optimized by considering the non-uniform gas flow distribution of the fuel cell stack. The results of the optimized electrochemical fuel cell performance model demonstrate that the correlation coefficient between the experiment results and the simulation results is nearly 99.50%, which is higher than that of the original model under 20% GDL compression. This established model is effective in enhancing the prediction accuracy of the PEMFC performance.

Suggested Citation

  • Zhiming Zhang & Chenfu Quan & Sai Wu & Tong Zhang & Jinming Zhang, 2024. "An Electrochemical Performance Model Considering of Non-Uniform Gas Distribution Based on Porous Media Method in PEMFC Stack," Sustainability, MDPI, vol. 16(2), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:587-:d:1316036
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    References listed on IDEAS

    as
    1. Yan, Xiaohui & Lin, Chen & Zheng, Zhifeng & Chen, Junren & Wei, Guanghua & Zhang, Junliang, 2020. "Effect of clamping pressure on liquid-cooled PEMFC stack performance considering inhomogeneous gas diffusion layer compression," Applied Energy, Elsevier, vol. 258(C).
    2. Jia, Chunchun & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao & Li, Kunang, 2023. "A novel health-aware deep reinforcement learning energy management for fuel cell bus incorporating offline high-quality experience," Energy, Elsevier, vol. 282(C).
    3. Jia, Chunchun & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao & Li, Kunang, 2024. "Learning-based model predictive energy management for fuel cell hybrid electric bus with health-aware control," Applied Energy, Elsevier, vol. 355(C).
    4. 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).
    5. Antonio Nicolò Mancino & Carla Menale & Francesco Vellucci & Manlio Pasquali & Roberto Bubbico, 2023. "PEM Fuel Cell Applications in Road Transport," Energies, MDPI, vol. 16(17), pages 1-27, August.
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