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Component-based modelling of PEM fuel cells with bond graphs

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journal contribution
posted on 13.10.2017, 15:23 by Andrey Vasilyev, John Andrews, Lisa JacksonLisa Jackson, Sarah DunnettSarah Dunnett, Benjamin Davies
A 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 Energy

Citation

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

Elsevier

Version

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

20/09/2017

Publication date

2017

Notes

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

0360-3199

Language

en

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