Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1784695991847354368 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9048716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT liyunqi analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT chenxiran analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT liuyuwei analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT xiongdanping analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT lijing analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT yinsha analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT chenliang analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT licongxin analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles AT xujun analyticalmodelingframeworkforperformancedegradationofpemfuelcellsduringstartupshutdowncycles |