This paper presents the development of dynamic models for proton exchange membrane fuel cells (PEMFC). The PEMFC control system has an important effect on operation of cell. Traditional controllers could not lead to acceptable responses because of time-change, long-hysteresis, uncertainty, strong-coupling and nonlinear characteristics of PEMFCs, This paper presents a dynamic model for PEMFC system, so an intelligent or adaptive controller is needed. In this paper, a neural network predictive controller have been designed to control the voltage of at the presence of fluctuations of temperature. The results of implementation of this designed NN Predictive controller on a dynamic electrochemical model of a small size 5 KW, PEM fuel cell have been simulated by matlab/SIMULINK.
A Predictive Control Based on Neural Network for Dynamic Model of Proton Exchange Membrane Fuel Cell
Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received September 6, 2012; final manuscript received January 29, 2013; published online May 7, 2013. Assoc. Editor: Whitney Colella.
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Rezaei, M., and Mohseni, M. (May 7, 2013). "A Predictive Control Based on Neural Network for Dynamic Model of Proton Exchange Membrane Fuel Cell." ASME. J. Fuel Cell Sci. Technol. June 2013; 10(3): 035001. https://doi.org/10.1115/1.4023838
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