ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL CELL

D. S. Falcão, J. C. M. Pires, C. Pinho, A. M. F. R. Pinto, F. G. Martins

2009

Abstract

This study proposes the simulation of PEM fuel cell polarization curves using artificial neural networks (ANN). Fuel cell performance can be affected by numerous parameters, namely, reactants pressure, humidification temperature, stoichiometric flow ratios and fuel cell temperature. In this work, the influence of relative humidity (RH) of the gases, as well as gases and fuel cell temperatures was studied. A feedforward ANN with three layers was applied to predict the influence of those parameters, simulating the voltage of a fuel cell of 25 cm2 area. Different ANN models were tested, varying the number of neurons in the hidden layer (1 to 6). The model performance was evaluated using the Pearson correlation coefficient (R) and the index of agreement of the second order (d2). The results showed that feedforward ANN can be used with success in order to obtain the optimal operating conditions to improve PEM fuel cell performance.

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Paper Citation


in Harvard Style

Falcão D., Pires J., Pinho C., Pinto A. and Martins F. (2009). ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL CELL . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 435-439. DOI: 10.5220/0002317604350439


in Bibtex Style

@conference{icnc09,
author={D. S. Falcão and J. C. M. Pires and C. Pinho and A. M. F. R. Pinto and F. G. Martins},
title={ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL CELL},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)},
year={2009},
pages={435-439},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002317604350439},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)
TI - ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL CELL
SN - 978-989-674-014-6
AU - Falcão D.
AU - Pires J.
AU - Pinho C.
AU - Pinto A.
AU - Martins F.
PY - 2009
SP - 435
EP - 439
DO - 10.5220/0002317604350439