08270568.pdf (580.68 kB)
0/0

Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis

Download (580.68 kB)
journal contribution
posted on 23.01.2018 by Lei Mao, Lisa Jackson, Benjamin Davies
The 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 Electronics

Citation

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 Engineers

Version

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

30/12/2017

Publication date

2018

Notes

This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/

ISSN

0278-0046

Language

en

Licence

Exports

Logo branding

Licence

Exports