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Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis
journal contribution
posted on 2018-01-23, 14:25 authored by Lei Mao, Lisa JacksonLisa Jackson, Benjamin DaviesThe monitoring of engineering systems is
becoming more common place because of the increasing demands on reliability and safety. Being able to diagnose a fault has been facilitated by technology developments.
This has resulted in the application of methods yielding an earlier detection and thus prompter mitigation of corrective measures. The level of maturity of monitoring systems varies across domain areas, with more nascent systems in
newly emerging technologies, such as fuel cells. With the increasing complexity of systems comes the inclusion of more sensors, and for expedient on-line diagnosis utilizing the information from the most appropriate sensors is key to enabling excellent diagnostic
resolution. In this paper, a novel sensor selection algorithm is proposed and its performance in Polymer Electrolyte Membrane (PEM) fuel cell on-line diagnosis is investigated. In the selection procedure, both sensor
sensitivities to various failure modes and corresponding fuel cell degradation rates are considered. The optimal sensors determined from the proposed algorithm are compared with previous sensor selection techniques,
where results show that the proposed algorithm can provide more efficient sensor selection results using less computational time, which makes this method better applied in practical PEM fuel cell systems for on-line
diagnostic tasks.
Funding
This work was supported by the Department of Aeronautical and Automotive Engineering, Loughborough University under Grant EP/K02101X/1 from UK Engineering and Physical Sciences Research Council (EPSRC).
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Industrial ElectronicsCitation
MAO, L., JACKSON, L.M. and DAVIES, B., 2018. Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis. IEEE Transactions on Industrial Electronics, 65 (9), pp.7301-7310.Publisher
Institute of Electrical and Electronics EngineersVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/Acceptance date
2017-12-30Publication date
2018Notes
This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ISSN
0278-0046Publisher version
Language
- en