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.
Diagnosis of a Commercial PEM Fuel Cell Stack via Incomplete Spectra and Fuzzy Clustering
PETRONE, RAFFAELE;PIANESE, Cesare
2013-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
