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Collaborative design of multi-type parameters for design and operational stage matching in fuel cells

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  • Yang, Qinwen
  • Xiao, Gang
  • Li, Lexi
  • Che, Mengjie
  • Hu, Xu-Qu
  • Meng, Min

Abstract

A collaborative design method for multi-types of graphite end plates geometric parameters, membrane electrolyte assembly physical parameters, and operating parameters, was novelly developed to break bounds of parameter types for design stage and operational stage matching in fuel cells. A multi-step design method, assisted by a surrogate-assisted hierarchical particle swarm optimization algorithm, was used for the optimal design of multi-type parameters. During this multi-step design process, the initial experiments are implemented following the design of experiments, and further experiments are adaptively carried out under the guidance of the layered optimization method. Experimental evidence of cell performance response to the coupled effects of multi-parameters was firstly provided and discussed in details. The collaborative design of multi-type parameters realized using the proposed multi-step design method was proven to improve the energy conversion efficiency by 10.9%. Different performance requirements, from single to multiple objectives in various types of fuel cells, were also shown to be fulfilled using this collaborative design method.

Suggested Citation

  • Yang, Qinwen & Xiao, Gang & Li, Lexi & Che, Mengjie & Hu, Xu-Qu & Meng, Min, 2021. "Collaborative design of multi-type parameters for design and operational stage matching in fuel cells," Renewable Energy, Elsevier, vol. 175(C), pages 1101-1110.
    • Handle: RePEc:eee:renene:v:175:y:2021:i:c:p:1101-1110
    DOI: 10.1016/j.renene.2021.04.142
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    References listed on IDEAS

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    Cited by:

    1. Yang, Qinwen & Gao, Bin & Cheng, Qiang & Xiao, Gang & Meng, Min, 2022. "Adaptive control strategy for power output stability in long-time operation of fuel cells," Energy, Elsevier, vol. 238(PA).
    2. Qinwen Yang & Gang Xiao & Tao Liu & Bin Gao & Shujun Chen, 2022. "Efficient Prediction of Fuel Cell Performance Using Global Modeling Method," Energies, MDPI, vol. 15(22), pages 1-14, November.

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