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Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method

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  • Xu, Shuhui
  • Wang, Yong
  • Wang, Zhi

Abstract

Building an accurate mathematical model is vital for the simulation, control, evaluation, management, and optimization of proton exchange membrane fuel cells (PEMFCs). Usually this work is processed through building a mathematical model based on empirical or semi-empirical equations firstly and then estimating the unknown model parameters using optimization technologies. In this study, a simple two stage eagle strategy based on JAYA algorithm and Nelder-Mead simplex algorithm is proposed for effectively estimating the unknown model parameters of PEMFCs. In the proposed strategy, JAYA algorithm is employed for the coarse global exploration, and Nelder–Mead simplex search algorithm is employed for the intensive local search. The effectiveness of the proposed strategy is verified through estimation experiments with 7 and 9 unknown parameters. Compared with the basic JAYA algorithm and four other newly reported excellent meta-heuristic algorithms including Grey Wolf Optimizer, Grasshopper Optimization Algorithm, Salp Swarm Optimizer, and Multi-Verse Optimizer, the proposed strategy possesses better performance in terms of accuracy, convergence speed, and stability, thus it is a promising approach for parameter estimation of PEMFC.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:173:y:2019:i:c:p:457-467
    DOI: 10.1016/j.energy.2019.02.106
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    1. Rao, R. Venkata & Saroj, Ankit, 2017. "Constrained economic optimization of shell-and-tube heat exchangers using elitist-Jaya algorithm," Energy, Elsevier, vol. 128(C), pages 785-800.
    2. Salim, Reem & Nabag, Mahmoud & Noura, Hassan & Fardoun, Abbas, 2015. "The parameter identification of the Nexa 1.2 kW PEMFC's model using particle swarm optimization," Renewable Energy, Elsevier, vol. 82(C), pages 26-34.
    3. Xu, Liangfei & Fang, Chuan & Hu, Junming & Cheng, Siliang & Li, Jianqiu & Ouyang, Minggao & Lehnert, Werner, 2017. "Parameter extraction of polymer electrolyte membrane fuel cell based on quasi-dynamic model and periphery signals," Energy, Elsevier, vol. 122(C), pages 675-690.
    4. 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.
    5. Fathy, Ahmed & Rezk, Hegazy, 2018. "Multi-verse optimizer for identifying the optimal parameters of PEMFC model," Energy, Elsevier, vol. 143(C), pages 634-644.
    6. Shao, Meng & Zhu, Xin-Jian & Cao, Hong-Fei & Shen, Hai-Feng, 2014. "An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system," Energy, Elsevier, vol. 67(C), pages 268-275.
    7. 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.
    8. 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.
    9. Gong, Wenyin & Cai, Zhihua, 2013. "Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution," Energy, Elsevier, vol. 59(C), pages 356-364.
    10. Yang, Shipin & Chellali, Ryad & Lu, Xiaohua & Li, Lijuan & Bo, Cuimei, 2016. "Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm," Energy, Elsevier, vol. 109(C), pages 569-577.
    11. Li, Dazi & Yu, Yadi & Jin, Qibing & Gao, Zhiqiang, 2014. "Maximum power efficiency operation and generalized predictive control of PEM (proton exchange membrane) fuel cell," Energy, Elsevier, vol. 68(C), pages 210-217.
    12. 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.
    13. Abdin, Z. & Webb, C.J. & Gray, E.MacA., 2016. "PEM fuel cell model and simulation in Matlab–Simulink based on physical parameters," Energy, Elsevier, vol. 116(P1), pages 1131-1144.
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    Cited by:

    1. Yang, Fan & Li, Yuehua & Chen, Dongfang & Hu, Song & Xu, Xiaoming, 2024. "Parameter identification of PEMFC steady-state model based on p-dimensional extremum seeking via simplex tuning optimization method," Energy, Elsevier, vol. 292(C).
    2. 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).
    3. 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).
    4. 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.
    5. Hsun-Heng Tsai & Chyun-Chau Fuh & Jeng-Rong Ho & Chih-Kuang Lin, 2021. "Design of Optimal Controllers for Unknown Dynamic Systems through the Nelder–Mead Simplex Method," Mathematics, MDPI, vol. 9(16), pages 1-14, August.
    6. 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).
    7. Fan Yang & Xiaoming Xu & Yuehua Li & Dongfang Chen & Song Hu & Ziwen He & Yi Du, 2023. "A Review on Mass Transfer in Multiscale Porous Media in Proton Exchange Membrane Fuel Cells: Mechanism, Modeling, and Parameter Identification," Energies, MDPI, vol. 16(8), pages 1-24, April.
    8. 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).
    9. Pan, Mingzhang & Li, Chao & Liao, Jinyang & Lei, Han & Pan, Chengjie & Meng, Xianpan & Huang, Haozhong, 2020. "Design and modeling of PEM fuel cell based on different flow fields," Energy, Elsevier, vol. 207(C).
    10. Jian Sun & Ling Wang & Dianxuan Gong, 2023. "A Joint Optimization Algorithm Based on the Optimal Shape Parameter–Gaussian Radial Basis Function Surrogate Model and Its Application," Mathematics, MDPI, vol. 11(14), pages 1-20, July.
    11. Abdelhady Ramadan & Salah Kamel & Mohamed H. Hassan & Marcos Tostado-Véliz & Ali M. Eltamaly, 2021. "Parameter Estimation of Static/Dynamic Photovoltaic Models Using a Developed Version of Eagle Strategy Gradient-Based Optimizer," Sustainability, MDPI, vol. 13(23), pages 1-29, November.
    12. 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.
    13. Blanco-Cocom, Luis & Botello-Rionda, Salvador & Ordoñez, L.C. & Valdez, S. Ivvan, 2021. "Robust parameter estimation of a PEMFC via optimization based on probabilistic model building," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 218-237.
    14. Mohamed Louzazni & Sameer Al-Dahidi & Marco Mussetta, 2020. "Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique," Sustainability, MDPI, vol. 12(19), pages 1-23, October.
    15. Seleem, Sameh I. & Hasanien, Hany M. & El-Fergany, Attia A., 2021. "Equilibrium optimizer for parameter extraction of a fuel cell dynamic model," Renewable Energy, Elsevier, vol. 169(C), pages 117-128.
    16. 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).

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