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Investigating the effects of operational factors on PEMFC performance based on CFD simulations using a three-level full-factorial design

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  • Cheng, Shan-Jen
  • Miao, Jr-Ming
  • Wu, Sheng-Ju

Abstract

This study uses the 33 full-factorial design, a factorial arrangement with three factors at three-levels, to investigate the main and interaction effects of design parameters on the performance of a single 25 cm2 PEMFC cell. The factors considered in this study include the flow channel design, the operational temperature, and the relative humidity of the cathode gas mixture. The gas flow channel patterns for both the anode side and the cathode side are the same as a straight parallel channel design and two modified parallel channel designs. The operational temperatures are selected as 333 K, 343 K, and 353 K. The relative humidity of the cathode gas mixture varies from 50% to 100% at 25% intervals, while the relative humidity of the anode gas mixture remains fixed at 100%. All runs are conducted with a three-dimensional, non-isothermal steady-state fuel cell computational fluid dynamic model (FCFD) with specified boundary conditions. The FCFD model can not only output the polarization curve, but also predict complex multi-physics flow, thermal, mass and ion transport phenomena inside the tiny fuel cell multi-layer structures. This full-factorial design of experimental method reveals that it is possible to not only explore the main effects of this complex multi-physics problem, but also investigate the effects of two-factor interactions for generating maximum power density. Results show that the flow channel design has the most significant effect on the polarization curve; the next is the cell temperature, while the relative humidity of the cathode gas mixture plays only a minor role.

Suggested Citation

  • Cheng, Shan-Jen & Miao, Jr-Ming & Wu, Sheng-Ju, 2012. "Investigating the effects of operational factors on PEMFC performance based on CFD simulations using a three-level full-factorial design," Renewable Energy, Elsevier, vol. 39(1), pages 250-260.
    • Handle: RePEc:eee:renene:v:39:y:2012:i:1:p:250-260
    DOI: 10.1016/j.renene.2011.08.009
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    References listed on IDEAS

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    1. Akbari, Mohammad Hadi & Rismanchi, Behzad, 2008. "Numerical investigation of flow field configuration and contact resistance for PEM fuel cell performance," Renewable Energy, Elsevier, vol. 33(8), pages 1775-1783.
    2. Sopian, Kamaruzzaman & Wan Daud, Wan Ramli, 2006. "Challenges and future developments in proton exchange membrane fuel cells," Renewable Energy, Elsevier, vol. 31(5), pages 719-727.
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    Cited by:

    1. Lei, Gang & Zheng, Hualin & Zhang, Jun & Siong Chin, Cheng & Xu, Xinhai & Zhou, Weijiang & Zhang, Caizhi, 2023. "Analyzing characteristic and modeling of high-temperature proton exchange membrane fuel cells with CO poisoning effect," Energy, Elsevier, vol. 282(C).
    2. Najmi, Aezid-Ul-Hassan & Anyanwu, Ikechukwu S. & Xie, Xu & Liu, Zhi & Jiao, Kui, 2021. "Experimental investigation and optimization of proton exchange membrane fuel cell using different flow fields," Energy, Elsevier, vol. 217(C).
    3. Zhang, Jun & Zhang, Caizhi & Li, Jin & Deng, Bo & Fan, Min & Ni, Meng & Mao, Zhanxin & Yuan, Honggeng, 2021. "Multi-perspective analysis of CO poisoning in high-temperature proton exchange membrane fuel cell stack via numerical investigation," Renewable Energy, Elsevier, vol. 180(C), pages 313-328.
    4. Pessot, Alexandra & Turpin, Christophe & Jaafar, Amine & Soyez, Emilie & Rallières, Olivier & Gager, Guillaume & d’Arbigny, Julien, 2019. "Contribution to the modelling of a low temperature PEM fuel cell in aeronautical conditions by design of experiments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 179-198.
    5. Elham Hosseinzadeh & James Marco & Paul Jennings, 2017. "Electrochemical-Thermal Modelling and Optimisation of Lithium-Ion Battery Design Parameters Using Analysis of Variance," Energies, MDPI, vol. 10(9), pages 1-22, August.
    6. Cheng, Shan-Jen & Miao, Jr-Ming & Wu, Sheng-Ju, 2013. "Use of metamodeling optimal approach promotes the performance of proton exchange membrane fuel cell (PEMFC)," Applied Energy, Elsevier, vol. 105(C), pages 161-169.
    7. Jian, Qi-fei & Ma, Guang-qing & Qiu, Xiao-liang, 2014. "Influences of gas relative humidity on the temperature of membrane in PEMFC with interdigitated flow field," Renewable Energy, Elsevier, vol. 62(C), pages 129-136.
    8. Wang, Junye, 2015. "Theory and practice of flow field designs for fuel cell scaling-up: A critical review," Applied Energy, Elsevier, vol. 157(C), pages 640-663.
    9. Zhang, Shuanyang & Liu, Shun & Xu, Hongtao & Liu, Gaojie & Wang, Ke, 2022. "Performance of proton exchange membrane fuel cells with honeycomb-like flow channel design," Energy, Elsevier, vol. 239(PB).
    10. Lu, Guolong & Fan, Wenxuan & Lu, Dafeng & Zhao, Taotao & Wu, Qianqian & Liu, Mingxin & Liu, Zhenning, 2024. "Lung-inspired hybrid flow field to enhance PEMFC performance: A case of dual optimization by response surface and artificial intelligence," Applied Energy, Elsevier, vol. 355(C).

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