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A Petri net approach for performance modelling of polymer electrolyte membrane fuel cell systems

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journal contribution
posted on 20.07.2017, 13:15 authored by Claudia Fecarotti, John Andrews, Rui Chen
Fuel cells are promising technologies for zero-emission energy conversion and power generation. However, durability and reliability are among the main barriers to their commercialisation. Clearly the system performance depends on the reliability of the overall system including both the stack and the balance of plant. This paper seeks to introduce a modelling approach based on the Petri net method for the performance analysis of fuel cell systems. The proposed Petri net model intends to simulate the operation of the fuel cell stack and its supporting system to predict the system performance based on the system structure, along with the components deterioration process. The model considers the causal relationship between the operation of the balance of plant and the fuel cell stack performance. Purging is performed periodically in order to restore some of the voltage loss due to water accumulation or impurities within the cell. Failures of single components of the supporting systems are considered, which will have an immediate effect on the output voltage as well as long term effects on the stack performance.

Funding

EPSRC (grant number EP/K02101X/1)

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

International Journal of Hydrogen Energy

Volume

41

Issue

28

Pages

12242 - 12260

Citation

FECAROTTI, C., ANDREWS, J. and CHEN, R., 2016. A Petri net approach for performance modelling of polymer electrolyte membrane fuel cell systems. International Journal of Hydrogen Energy, 41 (28), pp. 12242-12260.

Publisher

Elsevier (© The Authors)

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

15/05/2016

Publication date

2016

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

0360-3199

Language

en