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Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches

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journal contribution
posted on 10.10.2016 by Lei Mao, Lisa Jackson, Sarah Dunnett
In this paper, data-driven approaches are applied to identify faults of a practical PEM fuel cell system. Signal processing approaches are selected and employed to multiple sensor measurements, including methodologies reducing the dimension of the original dataset, and techniques extracting features. Both supervised and unsupervised techniques are applied in this study to investigate the robustness of the diagnostic procedure. Moreover, due to the fact that a series of features can be extracted from these sensors, the singular value decomposition (SVD) technique is applied to select features providing better diagnostic performance. Results demonstrate that with features selected from SVD, fuel cell system faults can be detected more effectively, and various fuel cell faults can also be discriminated with good quality. From the findings, conclusions are made and further work suggested.

Funding

This work is supported by grant EP/K02101X/1 from the UK Engineering and Physical Sciences Research Council (EPSRC).

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Fuel Cells

Citation

MAO, L., JACKSON, L.M. and DUNNETT, S.J., 2016. Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches. Fuel Cells, 17 (2), pp. 247–258.

Publisher

© The authors. Published by Wiley-VCH Verlag

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by-nc/4.0/

Acceptance date

14/09/2016

Publication date

2016

Notes

This is the peer reviewed version of the following article: MAO, L., JACKSON, L.M. and DUNNETT, S.J., 2016. Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches. Fuel Cells, 17 (2), pp. 247–258, which has been published in final form at http://dx.doi.org/10.1002/fuce.201600139. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

ISSN

1615-6854

Language

en

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