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Model parameter estimation of the PEMFCs using improved Barnacles Mating Optimization algorithm

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  • Yang, Zixuan
  • Liu, Qian
  • Zhang, Leiyu
  • Dai, Jialei
  • Razmjooy, Navid

Abstract

In this paper, a new optimal method is proposed to select unknown parameters of the proton exchange membrane fuel cell (PEMFC) models. The method was based on minimizing the sum of squared error (SSE) value between the experimental output voltage and the estimated output voltage for the PEMFC stack. The minimization is based on employing a new improved design of the Barnacles Mating Optimization (IBMO) algorithm for increasing the system accuracy and robustness. The method is then validated based on two different case studies, including Horizon 500W PEMFC and NedSstack PS6 PEMFCs by comparing its results by the real data and also some well-known methods including Emperor Penguin Optimizer (EPO), Elephant Herding behavior Optimization (EHO) Algorithm, and world cup optimization algorithm (WCO). The results show that the suggested IBMO with 2.11 SSE has the minimum error and the EPO, EHO, and the WCO with 2.13, 2.26, and 2.29 SSE are in the next ranks. Also, for the Horizon 500W, the SSE value of the IBMO, EPO, WCO, and BMO are 0.012, 0.019, 0.029, and 0.031, respectively which shows the suggested method’s superiority. Simulation results indicate that the suggested method has the best agreement with the empirical data.

Suggested Citation

  • Yang, Zixuan & Liu, Qian & Zhang, Leiyu & Dai, Jialei & Razmjooy, Navid, 2020. "Model parameter estimation of the PEMFCs using improved Barnacles Mating Optimization algorithm," Energy, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220318454
    DOI: 10.1016/j.energy.2020.118738
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    1. Cai, Wei & Mohammaditab, Rasoul & Fathi, Gholamreza & Wakil, Karzan & Ebadi, Abdol Ghaffar & Ghadimi, Noradin, 2019. "Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach," Renewable Energy, Elsevier, vol. 143(C), pages 1-8.
    2. Wu, Zhen & Zhu, Pengfei & Yao, Jing & Tan, Peng & Xu, Haoran & Chen, Bin & Yang, Fusheng & Zhang, Zaoxiao & Ni, Meng, 2020. "Thermo-economic modeling and analysis of an NG-fueled SOFC-WGS-TSA-PEMFC hybrid energy conversion system for stationary electricity power generation," Energy, Elsevier, vol. 192(C).
    3. Liu, Yang & Wang, Wei & Ghadimi, Noradin, 2017. "Electricity load forecasting by an improved forecast engine for building level consumers," Energy, Elsevier, vol. 139(C), pages 18-30.
    4. San Martin, J.I. & Zamora, I. & San Martin, J.J. & Aperribay, V. & Torres, E. & Eguia, P., 2010. "Influence of the rated power in the performance of different proton exchange membrane (PEM) fuel cells," Energy, Elsevier, vol. 35(5), pages 1898-1907.
    5. Li, Huan & Li, Kun & Zafetti, Nicholas & Gu, Jianfeng, 2020. "Improvement of energy supply configuration for telecommunication system in remote area s based on improved chaotic world cup optimization algorithm," Energy, Elsevier, vol. 192(C).
    6. Paria Akbary & Mohammad Ghiasi & Mohammad Reza Rezaie Pourkheranjani & Hamidreza Alipour & Noradin Ghadimi, 2019. "Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 1-26, January.
    7. Miao, Di & Chen, Wei & Zhao, Wei & Demsas, Tekle, 2020. "Parameter estimation of PEM fuel cells employing the hybrid grey wolf optimization method," Energy, Elsevier, vol. 193(C).
    8. Xu, Jiamin & Zhang, Caizhi & Fan, Ruijia & Bao, Huanhuan & Wang, Yi & Huang, Shulong & Chin, Cheng Siong & Li, Congxin, 2020. "Modelling and control of vehicle integrated thermal management system of PEM fuel cell vehicle," Energy, Elsevier, vol. 199(C).
    9. 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.
    10. Yang, Dixiong & Li, Gang & Cheng, Gengdong, 2007. "On the efficiency of chaos optimization algorithms for global optimization," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1366-1375.
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