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Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer

Energies • 2019
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Publication Information
Authors Ahmed M. Agwa , Attia A. El-Fergany , Gamal M. Sarhan
Keywords fuel cells; parameter identifications; simulation and modeling; atom search optimizer
Journal Energies
Publisher Not Available
Volume 2019, 12, 1884
Issue Not Available
Pages Not Available
publication.type International
Paper Link Not Available
Supplementary Materials Not Available
Abstract
Abstract: In simulation studies, the precision of fuel cell models has a vital role in the quality of results. Unfortunately, due to the shortage of manufacturer data given in the datasheets, several unknown parameters should be defined to establish the fuel cell model for further precise analysis. This research addresses a novel application of the atom search optimization (ASO) algorithm to generate these unknown parameters of the fuel cell model and in particular of the polymer exchange membrane (PEM) type. The objective of this study is to establish an accurate model of the PEM fuel cells, which will provide accurate results of modeling and simulation in a steady-state condition.Simulations and further demonstrations were performed under MATLAB/SIMULINK. The viability of the proposed models was appraised by comparing its simulation results with the experimental results of number of commercial PEM fuel cells. In the same context, the obtained numerical results by the proposed ASO-based method were compared to other challenging optimization methods-based
results. Finally, parametric tests were made which indicated the robustness of the ASO results as well. It can be stated here that ASO performs well and has a good capability to extract the unknown parameters with lesser errors.