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Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer

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  • Rezk, Hegazy
  • Ferahtia, Seydali
  • Djeroui, Ali
  • Chouder, Aissa
  • Houari, Azeddine
  • Machmoum, Mohamed
  • Abdelkareem, Mohammad Ali

Abstract

The exact parameter estimation of the fuel cell model is considered a critical stage in delivering a consistent emulation for the fuel cell system characteristics. The aim of this is to suggeste a robust methodology based on the Gradient-based Optimizer (GBO) to identify the best parameters of PEM fuel cell (PEMFC). Three distinct types of PEM fuel cells: 250 W FC stack, BCS 500 W, and SR-12 500 W, were used to demonstrate the superiority of the GBO. To confirm the superiority of GBO, the results were compared with those obtained using different optimizers such as salp swarm algorithm (SSA), heap-based optimizer (HBO), differential evolution (DE), whale optimization algorithm (WOA), moth-flame optimization algorithm (MFO), sine cosine algorithm (SCA), and Harris's hawk optimizer (HHO). During the optimization process, the unknown parameters of PEM fuel cells are used as decision variables, whereas the objective function needs to be minimum is represented by the sum square error between the measured data and estimated data. In addition, the obtained results by GBO are compared with other methods achieved in the literature. The superiority of GBO in determining the optimal parameters of different PEM fuel cells is proved.

Suggested Citation

  • Rezk, Hegazy & Ferahtia, Seydali & Djeroui, Ali & Chouder, Aissa & Houari, Azeddine & Machmoum, Mohamed & Abdelkareem, Mohammad Ali, 2022. "Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer," Energy, Elsevier, vol. 239(PC).
  • Handle: RePEc:eee:energy:v:239:y:2022:i:pc:s0360544221023446
    DOI: 10.1016/j.energy.2021.122096
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    5. Wilberforce, Tabbi & Rezk, Hegazy & Olabi, A.G. & Epelle, Emmanuel I. & Abdelkareem, Mohammad Ali, 2023. "Comparative analysis on parametric estimation of a PEM fuel cell using metaheuristics algorithms," Energy, Elsevier, vol. 262(PB).
    6. Rezk, Hegazy & Olabi, A.G. & Ferahtia, Seydali & Sayed, Enas Taha, 2022. "Accurate parameter estimation methodology applied to model proton exchange membrane fuel cell," Energy, Elsevier, vol. 255(C).
    7. Saka, Kenan & Orhan, Mehmet Fatih, 2022. "Analysis of stack operating conditions for a polymer electrolyte membrane fuel cell," Energy, Elsevier, vol. 258(C).
    8. Ghareeb Moustafa & Mostafa Elshahed & Ahmed R. Ginidi & Abdullah M. Shaheen & Hany S. E. Mansour, 2023. "A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems," Mathematics, MDPI, vol. 11(5), pages 1-30, February.
    9. Abdel-Basset, Mohamed & Mohamed, Reda & Abouhawwash, Mohamed, 2023. "On the facile and accurate determination of the highly accurate recent methods to optimize the parameters of different fuel cells: Simulations and analysis," Energy, Elsevier, vol. 272(C).
    10. Ćalasan, Martin & Abdel Aleem, Shady H.E. & Hasanien, Hany M. & Alaas, Zuhair M. & Ali, Ziad M., 2023. "An innovative approach for mathematical modeling and parameter estimation of PEM fuel cells based on iterative Lambert W function," Energy, Elsevier, vol. 264(C).
    11. Alaa A. Zaky & Rania M. Ghoniem & F. Selim, 2023. "Precise Modeling of Proton Exchange Membrane Fuel Cell Using the Modified Bald Eagle Optimization Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-16, July.
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    14. Hegazy Rezk & A. G. Olabi & Tabbi Wilberforce & Enas Taha Sayed, 2023. "A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    15. Chang, Huawei & Cai, Fengyang & Yu, Xianxian & Duan, Chen & Chan, Siew Hwa & Tu, Zhengkai, 2023. "Experimental study on the thermal management of an open-cathode air-cooled proton exchange membrane fuel cell stack with ultra-thin metal bipolar plates," Energy, Elsevier, vol. 263(PA).
    16. Fathy, Ahmed & Rezk, Hegazy & Alharbi, Abdullah G. & Yousri, Dalia, 2023. "Proton exchange membrane fuel cell model parameters identification using Chaotically based-bonobo optimizer," Energy, Elsevier, vol. 268(C).
    17. Huang, Weifeng & Niu, Tong & Zhang, Caizhi & Fu, Zuhang & Zhang, Yuqi & Zhou, Weijiang & Pan, Zehua & Zhang, Kaiqing, 2023. "Experimental study of the performance degradation of proton exchange membrane fuel cell based on a multi-module stack under selected load profiles by clustering algorithm," Energy, Elsevier, vol. 270(C).
    18. Yang, Bo & Liang, Boxiao & Qian, Yucun & Zheng, Ruyi & Su, Shi & Guo, Zhengxun & Jiang, Lin, 2024. "Parameter identification of PEMFC via feedforward neural network-pelican optimization algorithm," Applied Energy, Elsevier, vol. 361(C).
    19. Yuan, Yongliang & Yang, Qingkang & Ren, Jianji & Mu, Xiaokai & Wang, Zhenxi & Shen, Qianlong & Zhao, Wu, 2024. "Attack-defense strategy assisted osprey optimization algorithm for PEMFC parameters identification," Renewable Energy, Elsevier, vol. 225(C).

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