201600139.pdf (1.24 MB)
Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches
journal contribution
posted on 2016-10-10, 13:49 authored by Lei Mao, Lisa JacksonLisa Jackson, Sarah DunnettSarah DunnettIn 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 CellsCitation
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 VerlagVersion
- 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
2016-09-14Publication date
2016Notes
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
1615-6854Publisher version
Language
- en