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Download fileComponent-based modelling of PEM fuel cells with bond graphs
journal contribution
posted on 2017-10-13, 15:23 authored by Andrey Vasilyev, John Andrews, Lisa JacksonLisa Jackson, Sarah DunnettSarah Dunnett, Benjamin DaviesA polymer electrolyte membrane (PEM) fuel cell is a power generation device that transforms chemical energy contained within hydrogen and oxygen gases into useful electricity. The performance of a PEMFC unit is governed by three interdependent physical phenomena: heat, mass, and charge transfer. When modelling such a multi-physical system it is advantageous to use an approach capable of representing all the processes in a unified fashion. This paper presents a component-based model of PEMFCs developed using the bond graph (BG) technique in Modelica language. The basics of the BG method are outlined and a number of relevant publications are reviewed. Model assumptions and necessary equations for each fuel cell component are outlined. The overall model is constructed from a set of bond-graphic blocks within thermal, pneumatic and electrical domains.
The model output was compared with the experimental data gathered from a two-cell stack and demonstrated a good accuracy in predicting system behaviour. In the future the designed model will be used for fuel cell reliability studies.
Funding
The authors gratefully acknowledge the support of EPSRC (grant number EP/K02101X/1) which has enabled the research reported in this paper.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
International Journal of Hydrogen EnergyCitation
VASILYEV, A. ... et al, 2017. Component-based modelling of PEM fuel cells with bond graphs. International Journal of Hydrogen Energy, 42(49), pp. 29406-29421.Publisher
ElsevierVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 4.0 Unported Licence (CC BY 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2017-09-20Publication date
2017Notes
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/ISSN
0360-3199Publisher version
Language
- en