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|Title: ||The use of bond graph modelling in polymer electrolyte membrane fuel cell fault diagnosis|
|Authors: ||Vasilyev, Andrey|
Jackson, Lisa M.
|Issue Date: ||2018|
|Publisher: ||© Taylor and Francis|
|Citation: ||VASILYEV, A. ... et al., 2018. The use of bond graph modelling in polymer electrolyte membrane fuel cell fault diagnosis. IN: Haugen, S. ... et al. (eds). Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference (ESREL 2018), Trondheim, Norway, 17-21 June 2018, pp. 1545 - 1551.|
|Abstract: ||© 2018 Taylor & Francis Group, London. As a possible alternative energy source, hydrogen fuel cells, especially Polymer Electrolyte Membrane (PEM) fuel cells, have received much more attention in the last few decades, which have already been equipped in many applications. A series of studies have been devoted to PEM fuel cell fault diagnosis to ensure its reliability during its lifetime, but due to the complexity of PEM fuel cell systems and incomplete PEM fuel cell test protocols, it is difficult to test various PEM fuel cell failure modes, thus the performance of fault diagnostic techniques cannot be fully investigated. On this basis, it is necessary to develop a reliable PEM fuel cell model with capability of simulating various PEM fuel cell faults. In this study, a hybrid model is developed to represent the behavior of PEM fuel cells in both continuous and discrete-time domains. With a continuous-time domain sub-model, various aspects of PEM fuel cell behavior can be simulated, including fluid, thermal, and electro-chemical dynamics. Moreover, the PEM fuel cell failure modes are implemented with stochastic Petri nets in the discrete-time domain. Based on the developed hybrid model, various PEM fuel cell failure modes can be simulated and their effects on the system performance can be observed. With the simulated data under different conditions, the performance of fault diagnostic techniques can be better evaluated by studying their performance in different failure mode scenarios.|
|Description: ||This is an Open Access paper. It is published by Taylor & Francis under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/|
|Sponsor: ||The work is supported by grant EP/K02101X/1 for
Loughborough University from the UK Engineering
and Physical Sciences Research Council (EPSRC).|
|Publisher Link: ||https://doi.org/10.1201/9781351174664|
|Appears in Collections:||Conference Papers and Presentations (Aeronautical and Automotive Engineering)|
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