Determination of optimal parameters for dual-layer cathode of polymer electrolyte fuel cell using computational intelligence-aided design

Yi Chen; Weina Huang; Bei  Peng

doi:10.1371/journal.pone.0114223

Determination of optimal parameters for dual-layer cathode of polymer electrolyte fuel cell using computational intelligence-aided design

Yi Chen, Weina Huang, Bei Peng

Mechanical Engineering

Research output: Contribution to journal › Article

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Abstract

Because of the demands for sustainable and renewable energy, fuel cells have become increasingly popular, particularly the polymer electrolyte fuel cell (PEFC). Among the various components, the cathode plays a key role in the operation of a PEFC. In this study, a quantitative dual-layer cathode model was proposed for determining the optimal parameters that minimize the over-potential difference η and improve the efficiency using a newly developed bat swarm algorithm with a variable population embedded in the computational intelligence-aided design. The simulation results were in agreement with previously reported results, suggesting that the proposed technique has potential applications for automating and optimizing the design of PEFCs.

Original language	English
Pages (from-to)	e114223
Journal	PLoS ONE
Volume	9
Issue number	12
DOIs	https://doi.org/10.1371/journal.pone.0114223
Publication status	Published - 9 Dec 2014

Keywords

cathode
renewable energy
sustainable energy
electrolyte fuel cell

Documents and Links

10.1371/journal.pone.0114223

Chen, Y et al (2014) PLoSONE article
Copyright: © 2014 Chen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Final published version, 3.41 MB

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Chen, Y., Huang, W., & Peng, B. (2014). Determination of optimal parameters for dual-layer cathode of polymer electrolyte fuel cell using computational intelligence-aided design. PLoS ONE , 9(12), e114223. https://doi.org/10.1371/journal.pone.0114223

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