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Thermodynamic Optimization of a High Temperature Proton Exchange Membrane Fuel Cell for Fuel Cell Vehicle Applications

Author

Listed:
  • Bing Xu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Dongxu Li

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Zheshu Ma

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Meng Zheng

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Yanju Li

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

Abstract

In this paper, a finite time thermodynamic model of high temperature proton exchange membrane fuel cell (HT-PEMFC) is established, in which the irreversible losses of polarization and leakage current during the cell operation are considered. The influences of operating temperature, membrane thickness, phosphoric acid doping level, hydrogen and oxygen intake pressure on the maximum output power density P m a x and the maximum output efficiency η m a x are studied. As the temperature rises, P m a x and η m a x will increase. The decrease of membrane thickness will increase P m a x , but has little influence on the η m a x . The increase of phosphoric acid doping level can increase P m a x , but it has little effect on the η m a x . With the increase of hydrogen and oxygen intake pressure, P m a x and η m a x will be improved. This article also obtains the optimization relationship between power density and thermodynamic efficiency, and the optimization range interval of HT-PEMFC which will provide guidance for applicable use of HT-PEMFCs.

Suggested Citation

  • Bing Xu & Dongxu Li & Zheshu Ma & Meng Zheng & Yanju Li, 2021. "Thermodynamic Optimization of a High Temperature Proton Exchange Membrane Fuel Cell for Fuel Cell Vehicle Applications," Mathematics, MDPI, vol. 9(15), pages 1-14, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:15:p:1792-:d:603502
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    References listed on IDEAS

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    1. Haji, Shaker, 2011. "Analytical modeling of PEM fuel cell i–V curve," Renewable Energy, Elsevier, vol. 36(2), pages 451-458.
    2. Wu, Zhen & Zhu, Pengfei & Yao, Jing & Tan, Peng & Xu, Haoran & Chen, Bin & Yang, Fusheng & Zhang, Zaoxiao & Ni, Meng, 2020. "Thermo-economic modeling and analysis of an NG-fueled SOFC-WGS-TSA-PEMFC hybrid energy conversion system for stationary electricity power generation," Energy, Elsevier, vol. 192(C).
    3. Zhang, Xin & Cai, Ling & Liao, Tianjun & Zhou, Yinghui & Zhao, Yingru & Chen, Jincan, 2018. "Exploiting the waste heat from an alkaline fuel cell via electrochemical cycles," Energy, Elsevier, vol. 142(C), pages 983-990.
    4. Sieniutycz, Stanisław & Poświata, Artur, 2012. "Thermodynamic aspects of power production in thermal, chemical and electrochemical systems," Energy, Elsevier, vol. 45(1), pages 62-70.
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    Cited by:

    1. Li, Yanju & Li, Dongxu & Ma, Zheshu & Zheng, Meng & Lu, Zhanghao & Song, Hanlin & Guo, Xinjia & Shao, Wei, 2022. "Performance analysis and optimization of a novel vehicular power system based on HT-PEMFC integrated methanol steam reforming and ORC," Energy, Elsevier, vol. 257(C).

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