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Diagnosis of a commercial PEM fuel cell stack via incomplete spectra and fuzzy clustering

Abstract : To realize the commercialization of proton exchange membrane (PEM) fuel cells, durability and reliability remain big challenges. This paper aims to develop a fault detection, identification and analysis methodology based on a commercial fuel cell system. Effect of air stoichiometry is studied using electrochemical impedance spectroscopy (EIS). Relevant faults are: oxygen starvation, water flooding and drying. Based on the EIS measurements, a non-model based methodology is proposed consisting of four parts: feature extraction based on the spectra, feature selection, fuzzy clustering and fault analysis. Validity of the proposed diagnostic methodology is verified experimentally.
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https://hal.univ-lorraine.fr/hal-02496076
Contributor : Zhixue Zheng <>
Submitted on : Friday, March 20, 2020 - 3:51:56 PM
Last modification on : Friday, March 20, 2020 - 3:51:56 PM

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Z. Zheng, R. Petrone, M.C. Pera, D. Hissel, M. Becherif, et al.. Diagnosis of a commercial PEM fuel cell stack via incomplete spectra and fuzzy clustering. IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, Nov 2013, Vienna, Italy. pp.1595-1600, ⟨10.1109/IECON.2013.6699371⟩. ⟨hal-02496076⟩

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