Issue 4, 2020, Issue in Progress

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

Abstract

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.

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

Supplementary files

Article information

Article type
Paper
Submitted
17 Nov 2019
Accepted
31 Dec 2019
First published
13 Jan 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 2216-2226

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

Y. Li, X. Chen, Y. Liu, D. Xiong, J. Li, S. Yin, L. Chen, C. Li and J. Xu, RSC Adv., 2020, 10, 2216 DOI: 10.1039/C9RA09572A

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