Fault detection and isolation for Polymer Electrolyte Membrane Fuel Cell systems by analyzing cell voltage generated space

Zhongliang Li, Rachid Outbib, Stefan Giurgea, Daniel Hissel and Yongdong Li

Applied Energy, 2015, vol. 148, issue C, 260-272

Abstract: This paper proposes a data-driven diagnostic approach for Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems. Fault detection and isolation (FDI) is realized by analyzing individual cell voltages. A feature extraction method Fisher Discriminant Analysis (FDA) and a multi-class classification method Directed Acyclic Graph Support Vector Machine (DAGSVM) are utilized successively to extract the useful features from raw data and classify the extracted features into various classes related to health states. Experimental data of two different stacks are used to validate the proposed approach. The results show that five concerned faults can be detected and isolated with a high accuracy. Moreover, the light computational cost of the approach enhances the possibility of its online implementation.

Keywords: Fault diagnosis; Proton exchange membrane fuel cell system; Individual cell voltages; Multi-fault isolation; Feature extraction; Classification (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915003682
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:148:y:2015:i:c:p:260-272

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2015.03.076

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().