Effect of sensor set size on polymer electrolyte membrane fuel cell fault diagnosis
journal contributionposted on 21.03.2019 by Lei Mao, Lisa Jackson
Any type of content formally published in an academic journal, usually following a peer-review process.
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This paper presents a comparative study on the performance of different sizes of sensor sets on polymer electrolyte membrane (PEM) fuel cell fault diagnosis. The effectiveness of three sizes of sensor sets, including fuel cell voltage only, all the available sensors, and selected optimal sensors in detecting and isolating fuel cell faults (e.g., cell flooding and membrane dehydration) are investigated using the test data from a PEM fuel cell system. Wavelet packet transform and kernel principal component analysis are employed to reduce the dimensions of the dataset and extract features for state classification. Results demonstrate that the selected optimal sensors can provide the best diagnostic performance, where different fuel cell faults can be detected and isolated with good quality.
This research was funded by UK Engineering and Physical Sciences Research Council (EPSRC) with number of EP/K02101X/1, and Hundreds of Talents Program of Chinese Academy of Sciences—Young Talents
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering