Title :
Diagnosis of a commercial PEM fuel cell stack via incomplete spectra and fuzzy clustering
Author :
Zheng, Zhengguang ; Petrone, R. ; Pera, M.C. ; Hissel, D. ; Becherif, M. ; Pianese, C.
Author_Institution :
Energy Dept., FEMTO-ST, Besancon, France
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.
Keywords :
durability; electrochemical impedance spectroscopy; fault diagnosis; feature extraction; fuzzy set theory; proton exchange membrane fuel cells; reliability; EIS; EIS measurements; air stoichiometry; analysis methodology; commercial PEM fuel cell stack diagnosis; commercial fuel cell system; diagnostic methodology; drying; durability; electrochemical impedance spectroscopy; fault analysis; fault detection; fault identification; feature extraction; feature selection; fuzzy clustering; incomplete spectra; oxygen starvation; proton exchange membrane fuel cells; reliability; water flooding; Cathodes; Fault diagnosis; Feature extraction; Floods; Humidity; Impedance; Resistance; EIS; PEM fuel cell stack; fault diagnosis; flooding; fuzzy clustering; oxygen starvation;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6699371
