Accurate Key Parameters Estimation of PEMFCs’ Models Based on Dandelion Optimization Algorithm

Rabeh Abbassi (), Salem Saidi, Abdelkader Abbassi, Houssem Jerbi, Mourad Kchaou and Bilal Naji Alhasnawi
Additional contact information
Rabeh Abbassi: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il City 81451, Saudi Arabia
Salem Saidi: LaTICE Laboratory, Higher National Engineering School of Tunis (ENSIT), University of Tunis, 5 Avenue Taha Hussein, P.O. Box 56, Tunis 1008, Tunisia
Abdelkader Abbassi: Institute of Applied Sciences and Technology of Kasserine (ISSATKas), University of Kairouan, P.O. Box 471, Kasserine 1200, Tunisia
Houssem Jerbi: Department of Industrial Engineering, College of Engineering, University of Ha’il, Ha’il City 81451, Saudi Arabia
Mourad Kchaou: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il City 81451, Saudi Arabia
Bilal Naji Alhasnawi: Department of Computer Technical Engineering, College of Information Technology, Imam Ja’afar Al-Sadiq University, Al-Muthanna 66002, Iraq

Mathematics, 2023, vol. 11, issue 6, 1-21

Abstract: With the increasing demand for electrical energy and the challenges related to its production, along with the need to be environmentally friendly to achieve sustainability for future generations, proton exchange membrane fuel cells (PEMFCs) are emerging as a clean energy source that can effectively replace conventional energy sources, in various fields of application and especially in the field of transportation exploiting electric vehicles (EVs). To improve the development and control of the PEMFCs, the precise determination of its mathematical model remains an essential task. Indeed, the accuracy of such a model depends on the ability to overcome the constraints associated with the nonlinearity and the numerous involved unknown parameters. The present paper proposes a new Dandelion Optimizer (DO) to accurately identify, for the first time, the parameters of the PEMFC model. The DO addresses the weaknesses of the majority of metaheuristic algorithms related to the self-adaptation of parameters, the stagnation of convergence to local minima, and the ability to refer to the whole population. The high ability of the proposed method is investigated using both steady-state and dynamic situations. The DO-based parameters estimation approach has been assessed through a specific comparative study with the most recently published techniques including GWO, GBO, HHO, IAEO, VSDE, and ABCDESC is performed using two typical PEMFC modules, namely 250 W PEMFC and NedStack PS6. The results obtained proved that the proposed approach obtained promising achievements and better performances comparatively with well-recognized and competitive methods.

Keywords: proton exchange membrane fuel cell; key parameters estimation; Hail region desert tourism; sum of square error; electric circuit model; dandelion optimization algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/6/1298/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/6/1298/ (text/html)

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:gam:jmathe:v:11:y:2023:i:6:p:1298-:d:1091039

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().