201600139.pdf (1.24 MB)
Download fileFault 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