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Reliable exponential distribution optimizer-based methodology for modeling proton exchange membrane fuel cells at different conditions

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  • Hassan Ali, Hossam
  • Fathy, Ahmed

Abstract

Establishing a precise model for proton exchange membrane fuel cell (PEMFC) is vital to simulate, manage, control, and estimate the optimal parameters accurately. However, the process has some challenges due to the nonlinear nature of fuel cells (FCs) and the missing parameters in datasheet. Also, the reported approaches have some restrictions in their behaviors. This paper proposes a new methodology incorporated exponential distribution optimizer (EDO) to construct PEMFC's equivalent circuit through estimating their parameters with the aid of experimental data. The algorithm is characterized by exploration/exploitation balance that avoids falling in local solutions. Sum square error (SSE) between the measured and estimated terminal voltages is selected as the target to be mitigated. The analysis is performed on four different FCs which are Ballard Mark V 5 kW, BCS-500 W, SR-12 500 W, and NedStack PS6. The proposed EDO is compared to reported approaches of mayfly optimization algorithm (MOA), chaotic mayfly optimization algorithm (CMOA), modified Harris hawks optimizer (MHHO), fractional order modified HHO (FMHHO), hybrid vortex search algorithm and differential evolution (VSDE), and other programmed approaches of sine cosine algorithm (SCA), seagull optimization algorithm (SOA), tunicate swarm algorithm (TSA), and gold rush optimizer (GRO). The best scores are 0.852056, 1.16978E-02, 1.056628, and 2.079166 obtained through the proposed EDO for Ballard Mark V 5 kW, BCS-500 W, SR-12 500 W, and NedStack PS6 cells, respectively. The absolute error ratios of CMOA, MOA, FMHHO, MHHO, VSDE, SOA, SCA, GRO, and TSA attributed to the error obtained by the proposed EDO in case of BSC-500W are 0.17%, 3.49%, 0.62%, 15.50%, 3.78%, 29.12%, 86.30%, 0.90%, and 10.33%, respectively. Despite the nine approaches considered in comparative analysis having some issues with convergence speed, they converged the best solution. Moreover, the dynamic model of PEMFC is established in Simulink and its performance is assessed through applying step load disturbance. The fetched results demonstrated the superiority of the proposed EDO in establishing reliable models of various PEMFCs.

Suggested Citation

  • Hassan Ali, Hossam & Fathy, Ahmed, 2024. "Reliable exponential distribution optimizer-based methodology for modeling proton exchange membrane fuel cells at different conditions," Energy, Elsevier, vol. 292(C).
    • Handle: RePEc:eee:energy:v:292:y:2024:i:c:s0360544224003724
    DOI: 10.1016/j.energy.2024.130600
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    References listed on IDEAS

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    1. Yang, Bo & Li, Danyang & Zeng, Chunyuan & Chen, Yijun & Guo, Zhengxun & Wang, Jingbo & Shu, Hongchun & Yu, Tao & Zhu, Jiawei, 2021. "Parameter extraction of PEMFC via Bayesian regularization neural network based meta-heuristic algorithms," Energy, Elsevier, vol. 228(C).
    2. Manish Kumar Singla & Jyoti Gupta & Beant Singh & Parag Nijhawan & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "Parameter Estimation of Fuel Cells Using a Hybrid Optimization Algorithm," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    3. Samuel Raafat Fahim & Hany M. Hasanien & Rania A. Turky & Abdulaziz Alkuhayli & Abdullrahman A. Al-Shamma’a & Abdullah M. Noman & Marcos Tostado-Véliz & Francisco Jurado, 2021. "Parameter Identification of Proton Exchange Membrane Fuel Cell Based on Hunger Games Search Algorithm," Energies, MDPI, vol. 14(16), pages 1-21, August.
    4. Ali, M. & El-Hameed, M.A. & Farahat, M.A., 2017. "Effective parameters’ identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer," Renewable Energy, Elsevier, vol. 111(C), pages 455-462.
    5. 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).
    6. Hachana, Oussama & El-Fergany, Attia A., 2022. "Efficient PEM fuel cells parameters identification using hybrid artificial bee colony differential evolution optimizer," Energy, Elsevier, vol. 250(C).
    7. Sun, Zhe & Cao, Dan & Ling, Yawen & Xiang, Feng & Sun, Zhixin & Wu, Fan, 2021. "Proton exchange membrane fuel cell model parameter identification based on dynamic differential evolution with collective guidance factor algorithm," Energy, Elsevier, vol. 216(C).
    8. 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).
    9. Fathy, Ahmed & Elaziz, Mohamed Abd & Alharbi, Abdullah G., 2020. "A novel approach based on hybrid vortex search algorithm and differential evolution for identifying the optimal parameters of PEM fuel cell," Renewable Energy, Elsevier, vol. 146(C), pages 1833-1845.
    10. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    11. 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).
    12. 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.
    13. Javaid, Usman & Mehmood, Adeel & Iqbal, Jamshed & Uppal, Ali Arshad, 2023. "Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies," Energy, Elsevier, vol. 269(C).
    14. 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.
    15. Fathy, Ahmed & Babu, Thanikanti Sudhakar & Abdelkareem, Mohammad Ali & Rezk, Hegazy & Yousri, Dalia, 2022. "Recent approach based heterogeneous comprehensive learning Archimedes optimization algorithm for identifying the optimal parameters of different fuel cells," Energy, Elsevier, vol. 248(C).
    16. 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).
    17. 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).
    18. Rabeh Abbassi & Salem Saidi & Abdelkader Abbassi & Houssem Jerbi & Mourad Kchaou & Bilal Naji Alhasnawi, 2023. "Accurate Key Parameters Estimation of PEMFCs’ Models Based on Dandelion Optimization Algorithm," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
    19. Fathy, Ahmed & Rezk, Hegazy, 2018. "Multi-verse optimizer for identifying the optimal parameters of PEMFC model," Energy, Elsevier, vol. 143(C), pages 634-644.
    20. 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).
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