Loughborough University
Jackson_1-s2.0-S0360319917336352-main.pdf (1.29 MB)

Component-based modelling of PEM fuel cells with bond graphs

Download (1.29 MB)
journal contribution
posted on 2017-10-13, 15:23 authored 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.


The authors gratefully acknowledge the support of EPSRC (grant number EP/K02101X/1) which has enabled the research reported in this paper.



  • Aeronautical, Automotive, Chemical and Materials Engineering


  • Aeronautical and Automotive Engineering

Published in

International Journal of Hydrogen Energy


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.




  • 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


Publication date



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/




  • en