2021 | OriginalPaper | Buchkapitel
Fault Classification of Polymer Electrolyte Membrane Fuel Cell System Based on Empirical Mode Decomposition
Autoren: Yousif Yahia Ahmed Abuker, Zhongyoug Liu, Lisa Jackson, Lei Mao
Verlag: Springer Singapore
Abstract
This paper investigates the empirical mode decomposition (EMD)-based feature selection technique in identifying polymer electrolyte membrane fuel cell water management issue. In the study, EMD is applied to fuel cell voltage signals at various states, including fuel cell flooding and membrane drying out, from which intrinsic mode functions (IMFs) are obtained. Sensitivity index is used to determine the IMFs more sensitive to fuel cell fault, which are then used for the fault diagnosis. The effectiveness of the selected IMFs in discriminating flooding and drying out scenarios is validated using experimental data from a PEM fuel cell system. The results show that different faults can be distinguished effectively. From the findings, a generalized feature extraction and selection technique can be provided for fault diagnosis in practical PEM fuel cell applications.
