Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique

Ibrahim Alsaidan, Mohamed A. M. Shaheen, Hany M. Hasanien, Muhannad Alaraj and Abrar S. Alnafisah
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Ibrahim Alsaidan: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Qassim, Saudi Arabia
Mohamed A. M. Shaheen: Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt
Hany M. Hasanien: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Muhannad Alaraj: Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Qassim, Saudi Arabia
Abrar S. Alnafisah: Department of Chemistry, College of Science, Qassim University, Buraydah 52571, Qassim, Saudi Arabia

Sustainability, 2021, vol. 13, issue 14, 1-24

Abstract: For the precise simulation performance, the accuracy of fuel cell modeling is important. Therefore, this paper presents a developed optimization method called Chaos Game Optimization Algorithm (CGO). The developed method provides the ability to accurately model the proton exchange membrane fuel cell (PEMFC). The accuracy of the model is tested by comparing the simulation results with the practical measurements of several standard PEMFCs such as Ballard Mark V, AVISTA SR-12.5 kW, and 6 kW of the Nedstack PS6 stacks. The complexity of the studied problem stems from the nonlinearity of the PEMFC polarization curve that leads to a nonlinear optimization problem, which must be solved to determine the seven PEMFC design variables. The objective function is formulated mathematically as the total error squared between the laboratory measured terminal voltage of PEMFC and the estimated terminal voltage yields from the simulation results using the developed model. The CGO is used to find the best way to fulfill the preset requirements of the objective function. The results of the simulation are tested under different temperature and pressure conditions. Moreover, the results of the proposed CGO simulations are compared with alternative optimization methods showing higher accuracy.

Keywords: laboratory results; optimization techniques; PEMFC modelling; polarization curves; parameters extraction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (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)

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