Accurate parameters extraction of PEMFC model based on metaheuristics algorithms. (November 2021)

• Record Type: Journal Article
• Authors: Diab, Ahmed A. Zaki; Ali, Hamdi; Abdul-Ghaffar, H.I.; Abdelsalam, Hany A.; Sattar, Montaser Abd El
• Is Part Of: Energy reports. Volume 7(2021)
• Page Start: 6854
• Page End: 6867
• Publication Date: 2021-11
• Subjects: Fuel cell model -- Parameter extraction -- Metaheuristics algorithms; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2021.09.145
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: The electro-chemical proton exchange membrane fuel cell (PEMFC) is an inventing electrical generator from chemical reaction process as a green energy source. An accurate PEMFC model with its precise parameters should be used to carefully fitting of polarization curve to best study and design of its characteristics and performance. This paper introduces an accurate PEMFC model based on recent metaheuristics algorithms to evaluate precisely the unknown parameters of PEMFC . Algorithms of; Whale Optimization Algorithm (WOA), Weighted Differential Evolution Algorithm (WDE), Differential evolution algorithm with strategy adaptation (SADE), Moth- Flame Optimization Algorithm (MFO), adaptive differential evolution with optional external archive (JADE), Improved mine blast algorithm (IMBA), Gray Wolf Optimizer (GWO), Dragonfly algorithm (DA), Differential EVOLUTION ALGORITHM (DE), Cumulative Population Distribution Information in Differential Evolution (CPIJDE), Differential evolution based on covariance matrix learning (COBIDE), Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Bernstain-search differential evolution algorithm (BSD), Backtracking Search Optimization Algorithm (BSA), Bezier Search Differential Evolution Algorithm (BESD ), DIFFERENTIAL SEARCH ALGORITHM (DSA) and Bijective DSA (B-DSA), Biogeography-based optimization (BBO); have been applied to estimate model of PEMFC. The verification of the suggested optimizing algorithms is applied on three practical PEMFC stacks of BCS 500-W PEM, 500 W SR-12PEM and 250 W stacks, for different operating conditions. The accuracies of the PEMFC extracted parameters are measured in sum of square errors (SSE) between the results obtained by the optimizing parameters and the test results of the fuel cell stacks in the objective function. Also, the applied methods have been validated as compared results with different research works that were listed in literatures. Moreover, the polarization curves of the applied methods are clear and coinciding with manufacturing polarization curves for all the case study results. So, the suggested PEMFC optimizing model has superiority on the comparative models with respect to the system accuracy and convergence process. Highlights: Focusing on the optimizing proton exchange membrane fuel cells (PEMFCs) model parameters. A wide review of various PEMFC models based on variety different algorithms. Different optimization techniques have been discussed from view of their merits, de-merits, suitability. Parameters of PEMFC model have been estimated using recent metaheuristics algorithms. The optimization algorithms have been elaborated to solve the considered optimization problem. A comprehensive comparison among the results of the applied optimization algorithms have been presented.