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Efficient PEM fuel cells parameters identification using hybrid artificial bee colony differential evolution optimizer

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  • Hachana, Oussama
  • El-Fergany, Attia A.

Abstract

On the bases of meta-heuristic optimizers and experimental datasets, the parameter extraction of the proton exchange membrane fuel cells (PEMFCs) model to reach accurate current/voltage (I/V) curves remain an active research area during these last years. In this paper, an improved hybridized optimizer is developed to accurately estimate the PEMFC model parameters namely artificial bee colony differential evolution optimizer (ABCDE). In the developed ABCDE, the double execution of the mutation strategy allows enhancing the exploitation phase and avoiding to get stuck into the local minima. To assess the proposed ABCDE based parameter's identification, a comparative study with the recently published techniques including shuffled complex evolution, artificial ecosystem-based optimizer, and enhanced Lévy flight bat algorithm is performed using five typical PEMFCs modules. In this context, the reached sum of squared errors (SSE) and the standard deviations (STD) are very competitive among the challenging methodologies. ABCDE reaches the best SSE values within interesting overall STD and CPU run time less than 3e−15 and 0.225 s, respectively, for the five cases under study. It can be confirmed that the cropped SSE values and the STD among other challenging methodologies are very competitive with the best convergence speed. The ABCDE reaches 0.011697781, 2.07916558, 0.85360752, 9.6536060e−02, and 1.42098181379214e−04 for BCS 500W, NedStack PS6, Ballard Mark V, Horizon H-12, and Modular SR-12; respectively. In addition to that, the comparison results indicate that the proposed ABCDE is successfully utilized to characterize the PEMFC's model reliably and rapidly.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222007332
    DOI: 10.1016/j.energy.2022.123830
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    References listed on IDEAS

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    1. Fathy, Ahmed & Rezk, Hegazy & Mohamed Ramadan, Haitham Saad, 2020. "Recent moth-flame optimizer for enhanced solid oxide fuel cell output power via optimal parameters extraction process," Energy, Elsevier, vol. 207(C).
    2. 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.
    3. El-Hay, Enas A. & El-Hameed, Mohamed A. & El-Fergany, Attia A., 2018. "Performance enhancement of autonomous system comprising proton exchange membrane fuel cells and switched reluctance motor," Energy, Elsevier, vol. 163(C), pages 699-711.
    4. Miao, Tianwei & Tongsh, Chasen & Wang, Jianan & Cheng, Peng & Liang, Jinqiao & Wang, Zixuan & Chen, Wenmiao & Zhang, Chao & Xi, Fuqiang & Du, Qing & Wang, Bowen & Bai, Fuqiang & Jiao, Kui, 2022. "Current density and temperature distribution measurement and homogeneity analysis for a large-area proton exchange membrane fuel cell," Energy, Elsevier, vol. 239(PA).
    5. Chakraborty, Uday K. & Abbott, Travis E. & Das, Sajal K., 2012. "PEM fuel cell modeling using differential evolution," Energy, Elsevier, vol. 40(1), pages 387-399.
    6. 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).
    7. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    8. Gouda, Eid A. & Kotb, Mohamed F. & El-Fergany, Attia A., 2021. "Jellyfish search algorithm for extracting unknown parameters of PEM fuel cell models: Steady-state performance and analysis," Energy, Elsevier, vol. 221(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. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    12. Kandidayeni, M. & Macias, A. & Khalatbarisoltani, A. & Boulon, L. & Kelouwani, S., 2019. "Benchmark of proton exchange membrane fuel cell parameters extraction with metaheuristic optimization algorithms," Energy, Elsevier, vol. 183(C), pages 912-925.
    13. El-Fergany, Attia A., 2018. "Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer," Renewable Energy, Elsevier, vol. 119(C), pages 641-648.
    14. Abdel-Basset, Mohamed & Mohamed, Reda & El-Fergany, Attia & Chakrabortty, Ripon K. & Ryan, Michael J., 2021. "Adaptive and efficient optimization model for optimal parameters of proton exchange membrane fuel cells: A comprehensive analysis," Energy, Elsevier, vol. 233(C).
    15. Ahmed M. Agwa & Attia A. El-Fergany & Gamal M. Sarhan, 2019. "Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer," Energies, MDPI, vol. 12(10), pages 1-14, May.
    16. 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).
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    6. 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).

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