Adaptive and efficient optimization model for optimal parameters of proton exchange membrane fuel cells: A comprehensive analysis

Mohamed Abdel-Basset, Reda Mohamed, Attia El-Fergany, Ripon K. Chakrabortty and Michael J. Ryan

Energy, 2021, vol. 233, issue C

Abstract: Optimum modeling of the proton exchange membrane fuel cell (PEMFC) has attracted considerable research over the last decades to simulate, control, evaluate, manage, and optimize the performance of PEMFC stacks. The main problem in optimal modeling is that the model parameters are not provided by manufacturers, and the empirical dataset points are not sufficient to accurately model the cell. Therefore, a new approach based on the improved chimp optimization algorithm (IChOA) is proposed to define the uncertain parameters of the PEMFC. A ranking-based updating strategy and a balanced exploration and exploitation strategy (BEES) are employed here within the IChOA. In the first strategy, the unbeneficial solutions in the population are replaced with other solutions covering other regions, which are unreachable by the original one. The second strategy aims at utilizing iteration as much as possible so that, at the beginning, the method maximizes the exploration operator in the first half of the optimization process to ensure the balance between the exploration and exploitation framework; and then, in the second half, the exploitation capability is maximized attempting to find a better solution than the best-so-far. The proposed IChOA is validated by three well-known commercial PEMFCs, namely 250 W stack, Ballard Mark V, and AVISTA SR-12 500 W modular. The best results of the IChOA are compared with 15 nature-inspired metaheuristics algorithms and another one known as gradient-based optimizer under various statistical analyses and under varied operating conditions. The superiority of the IChOA is demonstrated in terms of convergence stability, and final accuracy.

Keywords: Fuel cells; Steady-state characterization; PEMFC; Optimization methods; Modeling (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422101344X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:233:y:2021:i:c:s036054422101344x

DOI: 10.1016/j.energy.2021.121096

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().