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Parameter extraction of PEMFC via Bayesian regularization neural network based meta-heuristic algorithms

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  • Yang, Bo
  • Li, Danyang
  • Zeng, Chunyuan
  • Chen, Yijun
  • Guo, Zhengxun
  • Wang, Jingbo
  • Shu, Hongchun
  • Yu, Tao
  • Zhu, Jiawei

Abstract

It is essential to establish an accurate model for precise and reliable evaluation of the characteristics of proton exchange membrane fuel cell (PEMFC). However, the inherent multi-variable, multi-peak, and nonlinear features of PEMFC seriously increase the difficulty and complexity of its parameter extraction. Besides, noised data, which is inevitable in various operation conditions, usually hinders meta-heuristic algorithms (MhAs) to obtain high-quality PEMFC parameters. For the sake of solving these obstacles, a Bayesian regularized neural network (BRNN) based parameter extraction strategy of PEMFC is proposed. Furthermore, performance of the proposed approach is thoroughly evaluated and analyzed through a comprehensive comparison with several advanced MhAs under various operation conditions. Lastly, simulation results verified that BRNN based MhAs (BRNN-MhAs) can effectively extract the parameters of PEMFC with higher accuracy, faster speed, and enhanced stability. In particular, the accuracy of parameter extraction of PEMFC is growing by 34.18%.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:228:y:2021:i:c:s0360544221008410
    DOI: 10.1016/j.energy.2021.120592
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    1. 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.
    2. 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.
    3. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Han, Xuebing & Ouyang, Minggao, 2014. "Energy management strategies comparison for electric vehicles with hybrid energy storage system," Applied Energy, Elsevier, vol. 134(C), pages 321-331.
    4. Sharaf, Omar Z. & Orhan, Mehmet F., 2014. "An overview of fuel cell technology: Fundamentals and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 810-853.
    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. Saadi, A. & Becherif, M. & Aboubou, A. & Ayad, M.Y., 2013. "Comparison of proton exchange membrane fuel cell static models," Renewable Energy, Elsevier, vol. 56(C), pages 64-71.
    7. Guerrero Moreno, Nayibe & Cisneros Molina, Myriam & Gervasio, Dominic & Pérez Robles, Juan Francisco, 2015. "Approaches to polymer electrolyte membrane fuel cells (PEMFCs) and their cost," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 897-906.
    8. Oliva, Diego & Cuevas, Erik & Pajares, Gonzalo, 2014. "Parameter identification of solar cells using artificial bee colony optimization," Energy, Elsevier, vol. 72(C), pages 93-102.
    9. Ijaodola, O.S. & El- Hassan, Zaki & Ogungbemi, E. & Khatib, F.N. & Wilberforce, Tabbi & Thompson, James & Olabi, A.G., 2019. "Energy efficiency improvements by investigating the water flooding management on proton exchange membrane fuel cell (PEMFC)," Energy, Elsevier, vol. 179(C), pages 246-267.
    10. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    11. Zeng, Tao & Zhang, Caizhi & Hao, Dong & Cao, Dongpu & Chen, Jiawei & Chen, Jinrui & Li, Jin, 2020. "Data-driven approach for short-term power demand prediction of fuel cell hybrid vehicles," Energy, Elsevier, vol. 208(C).
    Full references (including those not matched with items on IDEAS)

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    2. Hegazy Rezk & Tabbi Wilberforce & A. G. Olabi & Rania M. Ghoniem & Mohammad Ali Abdelkareem & Enas Taha Sayed, 2023. "Fuzzy Modelling and Optimization to Decide Optimal Parameters of the PEMFC," Energies, MDPI, vol. 16(12), pages 1-16, June.
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    7. Chen, Chaogang & Gao, Yuan, 2024. "Using multi-threshold non-local means joint distribution method to analysis the spatial distribution patterns of binder and fibers in gas diffusion layers of fuel cells," Applied Energy, Elsevier, vol. 358(C).
    8. 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).
    9. Hegazy Rezk & Tabbi Wilberforce & A. G. Olabi & Rania M. Ghoniem & Enas Taha Sayed & Mohammad Ali Abdelkareem, 2023. "Optimal Parameter Identification of a PEM Fuel Cell Using Recent Optimization Algorithms," Energies, MDPI, vol. 16(14), pages 1-20, July.
    10. Peng He & Xin Zhou & Mingqun Liu & Kewei Xu & Xian Meng & Bo Yang, 2023. "Generalized Regression Neural Network Based Meta-Heuristic Algorithms for Parameter Identification of Proton Exchange Membrane Fuel Cell," Energies, MDPI, vol. 16(14), pages 1-30, July.
    11. 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).
    12. 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).
    13. Abel Rubio & Wilton Agila & Leandro González & Jonathan Aviles-Cedeno, 2023. "Distributed Intelligence in Autonomous PEM Fuel Cell Control," Energies, MDPI, vol. 16(12), pages 1-25, June.
    14. Fan, Lixin & Tu, Zhengkai & Chan, Siew Hwa, 2022. "Technological and Engineering design of a megawatt proton exchange membrane fuel cell system," Energy, Elsevier, vol. 257(C).
    15. 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).
    16. 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).

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