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|Title: ||Development of a fuzzy diagnostic model for polymer electrolyte fuel cells|
|Authors: ||Davies, Ben|
Jackson, Lisa M.
Dunnett, Sarah J.
|Issue Date: ||2015|
|Publisher: ||© CRC Press (Taylor & Francis Group)|
|Citation: ||DAVIES, B., JACKSON, L.M. and DUNNETT, S.J., 2015. Development of a fuzzy diagnostic model for polymer electrolyte fuel cells. IN: Podofillini, L. ... et al. (eds.) Safety and Reliability of Complex Engineered Systems
ESREL 2015. London: Taylor & Francis Group, pp. 2373–2378.|
|Abstract: ||Polymer Electrolyte Fuel Cells (PEFCs) offer a number of advantages over traditional power
generation systems, including high efficiency, high power density, and no local carbon-emissions. However,
even the best demonstrator projects suffer in lifetime durability; only surviving up to half the current US Department
of Energy (2006) targets.
Prognostics and Health Management (PHM) has been identified as a methodology that could be applied to
PEFCs to enhance and extend functional lifetime. PHM techniques would be applied through the control systems
for the fuel cell; monitoring and managing the operational parameters, and measuring state of health.
The approach selected in this investigation is to call upon expert knowledge and understanding of the
PEFC functionality; this produces a rule-based fuzzy-logic model. This paper introduces a diagnosticorientated
fuzzy-inference model of a PEFC. This combines with existing fuel cell control and monitoring
processes, to diagnose a range of commonly documented failure modes.|
|Description: ||Closed access. Presented at ESREL 2015, 7-10 September, Zurich, Switzerland.|
|Sponsor: ||This research project is funded by the Engineering
and Physical Sciences Research Council
(EP/G037116/6) and supported by the Doctoral
Training Centre for Hydrogen, Fuel Cells and their
|Version: ||Accepted for publication|
|Publisher Link: ||http://dx.doi.org/10.1201/b19094-311|
|Appears in Collections:||Closed Access (Aeronautical and Automotive Engineering)|
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