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Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles

Startup–shutdown cycling is one of the main factors that contribute to fuel cell deterioration related to high cathode potential. In this study, a coupled model with the carbon corrosion model and agglomerate model of the cathode catalyst layer is built to predict performance degradation during star...

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Autores principales: Li, Yunqi, Chen, Xiran, Liu, Yuwei, Xiong, Danping, Li, Jing, Yin, Sha, Chen, Liang, Li, Congxin, Xu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048716/
https://www.ncbi.nlm.nih.gov/pubmed/35494581
http://dx.doi.org/10.1039/c9ra09572a
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author Li, Yunqi
Chen, Xiran
Liu, Yuwei
Xiong, Danping
Li, Jing
Yin, Sha
Chen, Liang
Li, Congxin
Xu, Jun
author_facet Li, Yunqi
Chen, Xiran
Liu, Yuwei
Xiong, Danping
Li, Jing
Yin, Sha
Chen, Liang
Li, Congxin
Xu, Jun
author_sort Li, Yunqi
collection PubMed
description Startup–shutdown cycling is one of the main factors that contribute to fuel cell deterioration related to high cathode potential. In this study, a coupled model with the carbon corrosion model and agglomerate model of the cathode catalyst layer is built to predict performance degradation during startup–shutdown cycles. The carbon corrosion model calculates the carbon loading loss through the rate equations and material balance expressions of seven reactions, while the agglomerate model describes the catalyst layer performance according to the computed structural parameters. A set of operational and structural parametric studies are used to investigate their effects on initial performance and voltage degradation rate. The maximum voltage of the cyclic load is found to have a greater influence over the voltage degradation rate compared with relative humidity, pressure, and minimum voltage of the cyclic load. Among the structural parameters, the carbon loading and platinum loading have the greatest and least impact on voltage degradation rate, respectively, while ionomer fraction has a complex and nonmonotonic effect. An optimal design strategy is provided with a case demonstration. Results may provide a fundamental and important tool for degradation prediction in startup–shutdown conditions and guidance for catalyst layer design and operation.
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spelling pubmed-90487162022-04-28 Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles Li, Yunqi Chen, Xiran Liu, Yuwei Xiong, Danping Li, Jing Yin, Sha Chen, Liang Li, Congxin Xu, Jun RSC Adv Chemistry Startup–shutdown cycling is one of the main factors that contribute to fuel cell deterioration related to high cathode potential. In this study, a coupled model with the carbon corrosion model and agglomerate model of the cathode catalyst layer is built to predict performance degradation during startup–shutdown cycles. The carbon corrosion model calculates the carbon loading loss through the rate equations and material balance expressions of seven reactions, while the agglomerate model describes the catalyst layer performance according to the computed structural parameters. A set of operational and structural parametric studies are used to investigate their effects on initial performance and voltage degradation rate. The maximum voltage of the cyclic load is found to have a greater influence over the voltage degradation rate compared with relative humidity, pressure, and minimum voltage of the cyclic load. Among the structural parameters, the carbon loading and platinum loading have the greatest and least impact on voltage degradation rate, respectively, while ionomer fraction has a complex and nonmonotonic effect. An optimal design strategy is provided with a case demonstration. Results may provide a fundamental and important tool for degradation prediction in startup–shutdown conditions and guidance for catalyst layer design and operation. The Royal Society of Chemistry 2020-01-13 /pmc/articles/PMC9048716/ /pubmed/35494581 http://dx.doi.org/10.1039/c9ra09572a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Li, Yunqi
Chen, Xiran
Liu, Yuwei
Xiong, Danping
Li, Jing
Yin, Sha
Chen, Liang
Li, Congxin
Xu, Jun
Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title_full Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title_fullStr Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title_full_unstemmed Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title_short Analytical modeling framework for performance degradation of PEM fuel cells during startup–shutdown cycles
title_sort analytical modeling framework for performance degradation of pem fuel cells during startup–shutdown cycles
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048716/
https://www.ncbi.nlm.nih.gov/pubmed/35494581
http://dx.doi.org/10.1039/c9ra09572a
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