Zhou, Shangwei;
Jervis, Rhodri;
(2023)
A Review of Polymer Electrolyte Fuel Cells Fault Diagnosis: Progress and Perspectives.
Chemistry–Methods
, Article e202300030. 10.1002/cmtd.202300030.
(In press).
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Abstract
Polymer electrolyte fuel cells (PEFCs) are regarded as a substitution for the combustion engine with high energy conversion efficiency and zero CO2 emissions. Stable system operation requires control within a relatively narrow range of operating conditions to achieve the optimal output, leading to faults that can easily cause accelerated degradation when operating conditions deviate from the control targets. Performance recovery of the system can be realized through early fault diagnosis; therefore, accurate and effective diagnostic characterisation is vital for long-term serving. A review of off-line and on-line techniques applied to the fault diagnosis of fuel cells is presented in this work. Off-line approaches include electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), galvanostatic charge (GSC), visualisation-based and image-based techniques; the on-line methods can be divided into model-based, data-driven, signal-based and hybrid methods. Since each methodology has advantages and drawbacks, its effectiveness is analysed, and limitations are highlighted.
Type: | Article |
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Title: | A Review of Polymer Electrolyte Fuel Cells Fault Diagnosis: Progress and Perspectives |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/cmtd.202300030 |
Publisher version: | https://doi.org/10.1002/cmtd.202300030 |
Language: | English |
Additional information: | Copyright © 2023 The Authors. Chemistry - Methods published by Chemistry Europe and Wiley-VCH GmbH This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by-nc-nd/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Cyclic Voltammetry; Data-driven; Fault Diagnosis; Fuel Cells; Off-line and On-line |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
URI: | https://discovery.ucl.ac.uk/id/eprint/10176757 |
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