IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i2p587-d1316036.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/2/587/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/2/587/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    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. 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).
    4. 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).
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmed Mohmed Dafalla & Lin Wei & Bereket Tsegai Habte & Jian Guo & Fangming Jiang, 2022. "Membrane Electrode Assembly Degradation Modeling of Proton Exchange Membrane Fuel Cells: A Review," Energies, MDPI, vol. 15(23), pages 1-26, December.
    2. Tomasz Osipowicz & Wawrzyniec Gołębiewski & Wojciech Lewicki & Adam Koniuszy & Karol Franciszek Abramek & Konrad Prajwowski & Oleh Klyus & Dominik Gałdyński, 2024. "Analysis of Energy Efficiency Parameters of a Hybrid Vehicle Powered by Fuel with a Liquid Catalyst," Energies, MDPI, vol. 17(20), pages 1-20, October.
    3. Yao, Jing & Wu, Zhen & Wang, Huan & Yang, Fusheng & Xuan, Jin & Xing, Lei & Ren, Jianwei & Zhang, Zaoxiao, 2022. "Design and multi-objective optimization of low-temperature proton exchange membrane fuel cells with efficient water recovery and high electrochemical performance," Applied Energy, Elsevier, vol. 324(C).
    4. Zhiming Zhang & Jun Zhang & Tong Zhang, 2022. "Endplate Design and Topology Optimization of Fuel Cell Stack Clamped with Bolts," Sustainability, MDPI, vol. 14(8), pages 1-13, April.
    5. Massimo Sicilia & Davide Cervone & Pierpaolo Polverino & Cesare Pianese, 2024. "Advancements on Lumped Modelling of Membrane Water Content for Real-Time Prognostics and Control of PEMFC," Energies, MDPI, vol. 17(19), pages 1-20, September.
    6. Ramesh Kumar Chidambaram & Dipankar Chatterjee & Barnali Barman & Partha Pratim Das & Dawid Taler & Jan Taler & Tomasz Sobota, 2023. "Effect of Regenerative Braking on Battery Life," Energies, MDPI, vol. 16(14), pages 1-24, July.
    7. 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).
    8. Shangzhe Yu & Dominik Schäfer & Shidong Zhang & Roland Peters & Felix Kunz & Rüdiger-A. Eichel, 2023. "A Three-Dimensional Time-Dependent Model of the Degradation Caused by Chromium Poisoning in a Solid Oxide Fuel Cell Stack," Energies, MDPI, vol. 16(23), pages 1-23, November.
    9. Jiang, Wei & Zhang, Kai & Huang, Xing & Cai, Zhen & Zheng, Jinjin & Kai, Yue & Zheng, Bailin & Song, Ke, 2024. "Influence of clamping pressure on contact pressure uniformity and electrical output performance of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 353(PA).
    10. Yanqin Chen & Yuchao Ke & Yingsong Xia & Chongdu Cho, 2021. "Investigation on Mechanical Properties of a Carbon Paper Gas Diffusion Layer through a 3-D Nonlinear and Orthotropic Constitutive Model," Energies, MDPI, vol. 14(19), pages 1-14, October.
    11. Ye, Lingfeng & Qiu, Diankai & Peng, Linfa & Lai, Xinmin, 2024. "Conduction mechanism analysis and modeling of different gas diffusion layers for PEMFC to improve their bulk conductivities via microstructure design," Applied Energy, Elsevier, vol. 362(C).
    12. 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).
    13. Zhiming Zhang & Hui Ren & Song Hu & Xinfeng Zhang & Tong Zhang & Jiaming Zhou & Shangfeng Jiang & Tao Yu & Bo Deng, 2022. "Arrangement of Belleville Springs on Endplates Combined with Optimal Cross-Sectional Shape in PEMFC Stack Using Equivalent Beam Modeling and FEA," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    14. Wu, Jingda & Huang, Chao & He, Hongwen & Huang, Hailong, 2024. "Confidence-aware reinforcement learning for energy management of electrified vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    15. Dapai Shi & Junjie Guo & Kangjie Liu & Qingling Cai & Zhenghong Wang & Xudong Qu, 2023. "Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results," Sustainability, MDPI, vol. 15(13), pages 1-13, July.
    16. Zhiming Zhang & Jun Zhang & Liang Shi & Tong Zhang, 2022. "A Study of Contact Pressure with Thermo-Mechanical Coupled Action for a Full-Dimensional PEMFC Stack," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    17. Liu, Jiaran & Tan, Jinzhu & Yang, Weizhan & Li, Yang & Wang, Chao, 2021. "Better electrochemical performance of PEMFC under a novel pneumatic clamping mechanism," Energy, Elsevier, vol. 229(C).
    18. Abdul Ghani Olabi & Tabbi Wilberforce & Abdulrahman Alanazi & Parag Vichare & Enas Taha Sayed & Hussein M. Maghrabie & Khaled Elsaid & Mohammad Ali Abdelkareem, 2022. "Novel Trends in Proton Exchange Membrane Fuel Cells," Energies, MDPI, vol. 15(14), pages 1-35, July.
    19. Xing, Shuang & Zhao, Chen & Liu, Wei & Zou, Jiexin & Chen, Ming & Wang, Haijiang, 2021. "Effects of bolt torque and gasket geometric parameters on open-cathode polymer electrolyte fuel cells," Applied Energy, Elsevier, vol. 303(C).
    20. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2024. "Real-time automatic control of multi-energy system for smart district community: A coupling ensemble prediction model and safe deep reinforcement learning," Energy, Elsevier, vol. 304(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:587-:d:1316036. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.