Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 56, Issue 12, Pages 4903-4914Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2009.2026768
Keywords
Artificial neural network (ANN); fuel-cell model; proton exchange membrane (PEM); real time
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Funding
- National University of Singapore [R-263-000-248-112]
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A simple and accurate fuel-cell model is required for fuel-cell-based power-electronic applications. An artificial neural network (ANN) model is developed in this paper to model some nonlinear structures within the hybrid model of a proton-exchange-membrane fuel-cell stack. It improves accuracy and allows the model to adapt itself to operating conditions. Moreover, the temperature effect on the fuel-cell stack is represented as the current effect by using ANN to help estimate the relationship between current and temperature. The real-time implementation of the proposed ANN model is realized via a dSPACE system. Experimental results are provided to verify the validity of the proposed model.
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