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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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
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    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. Zhimin Guo & Zhiyuan Ye & Pengcheng Ni & Can Cao & Xiaozhao Wei & Jian Zhao & Xing He, 2023. "Intelligent Digital Twin Modelling for Hybrid PV-SOFC Power Generation System," Energies, MDPI, vol. 16(6), pages 1-21, March.
    7. Tie-Qing Zhang & Seunghun Jung & Young-Bae Kim, 2022. "Hydrogen Production System through Dimethyl Ether Autothermal Reforming, Based on Model Predictive Control," Energies, MDPI, vol. 15(23), pages 1-16, November.
    8. 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.
    9. 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).
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