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Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique

Author

Listed:
  • 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)

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.

Suggested Citation

  • Ibrahim Alsaidan & Mohamed A. M. Shaheen & Hany M. Hasanien & Muhannad Alaraj & Abrar S. Alnafisah, 2021. "Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7911-:d:594859
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Andrew J. Riad & Hany M. Hasanien & Rania A. Turky & Ahmed H. Yakout, 2023. "Identifying the PEM Fuel Cell Parameters Using Artificial Rabbits Optimization Algorithm," Sustainability, MDPI, vol. 15(5), pages 1-17, March.
    2. Ahmed Fathy & Abdulmohsen Alanazi, 2023. "An Efficient White Shark Optimizer for Enhancing the Performance of Proton Exchange Membrane Fuel Cells," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    3. Mohamed Abdel-Basset & Reda Mohamed & Victor Chang, 2021. "An Efficient Parameter Estimation Algorithm for Proton Exchange Membrane Fuel Cells," Energies, MDPI, vol. 14(21), pages 1-23, November.
    4. Ćalasan, Martin & Micev, Mihailo & Hasanien, Hany M. & Abdel Aleem, Shady H.E., 2024. "PEM fuel cells: Two novel approaches for mathematical modeling and parameter estimation," Energy, Elsevier, vol. 290(C).
    5. Abdelghani Dahou & Samia Allaoua Chelloug & Mai Alduailij & Mohamed Abd Elaziz, 2023. "Improved Feature Selection Based on Chaos Game Optimization for Social Internet of Things with a Novel Deep Learning Model," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    6. Nagwa F. Ibrahim & Sid Ahmed El Mehdi Ardjoun & Mohammed Alharbi & Abdulaziz Alkuhayli & Mohamed Abuagreb & Usama Khaled & Mohamed Metwally Mahmoud, 2023. "Multiport Converter Utility Interface with a High-Frequency Link for Interfacing Clean Energy Sources (PV\Wind\Fuel Cell) and Battery to the Power System: Application of the HHA Algorithm," Sustainability, MDPI, vol. 15(18), pages 1-25, September.
    7. Mohamed Ahmed Ali & Mohey Eldin Mandour & Mohammed Elsayed Lotfy, 2023. "Adaptive Estimation of Quasi-Empirical Proton Exchange Membrane Fuel Cell Models Based on Coot Bird Optimizer and Data Accumulation," Sustainability, MDPI, vol. 15(11), pages 1-20, June.
    8. Hasanien, Hany M. & Shaheen, Mohamed A.M. & Turky, Rania A. & Qais, Mohammed H. & Alghuwainem, Saad & Kamel, Salah & Tostado-Véliz, Marcos & Jurado, Francisco, 2022. "Precise modeling of PEM fuel cell using a novel Enhanced Transient Search Optimization algorithm," Energy, Elsevier, vol. 247(C).

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