Paper Info
Title
Parameter Estimation Of Pemfc Model Based On Harris Hawks' Optimization And Atom Search Optimization Algorithms
Abstract
Proton exchange membrane fuel cell (PEMFC) is considered as propitious solution for an environmentally friendly energy source. A precise model of PEMFC for accurate identification of its polarization curve and in-depth understanding of all its operating characteristics attracted the interest of many researchers. In this paper, novel meta-heuristic optimization methods have been successfully applied to evaluate the unknown parameters of PEMFC models, particularly Harris Hawks' optimization (HHO) and atom search optimization (ASO) techniques. The proposed optimization algorithms have been tested on three different commercial PEMFC stacks, namely BCS 500-W PEM, 500W SR-12PEM and 250W stack, under various operating conditions. The sum of square errors (SSE) between the results obtained by the application of the estimated parameters and the experimentally measured results of the fuel cell stacks was considered as the objective function of the optimization problem. In order to validate the effectiveness of the proposed methods, the results are compared with that obtained in studies. Moreover, theI/Vcurves obtained by the application of HHO and ASO showed a clear matching with data sheet curves for all the studied cases. Finally, PEMFC model based on HHO technique surpasses all compared algorithms in terms of the solution accuracy and the convergence speed.
Year
DOI
Venue
2021
10.1007/s00521-020-05333-4
NEURAL COMPUTING & APPLICATIONS
Keywords
DocType
Volume
Fuel cell modeling, Parameter estimation, Meta-heuristic algorithms
Journal
33
Issue
ISSN
Citations 
11
0941-0643
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Mahmoud A. Mossa111.37
Omar Makram Kamel210.70
Hamdy M. Sultan342.51
Ahmed A. Zaki Diab433.14