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Comparison of proton exchange membrane fuel cell static models

Author

Listed:
  • Saadi, A.
  • Becherif, M.
  • Aboubou, A.
  • Ayad, M.Y.

Abstract

Using experimental study results, this paper aims at evaluating the different analytical models that are used for modeling Proton Exchange Membrane Fuel Cell Stack (PEMFC). Three static models such as those of Amphlett, Larminie–Dicks and Chamberlin–Kim are demonstrated. These models are studied and validated experimentally with identification of their parameters separately. Hence, experimental results are compared for fuel cell test bench for two rated powers (400 W and 700 W). Furthermore, simulation results explicitly verify the accuracy and efficiency of these static models.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:56:y:2013:i:c:p:64-71
    DOI: 10.1016/j.renene.2012.10.012
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    Citations

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    Cited by:

    1. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    2. Mehroze Iqbal & Amel Benmouna & Frederic Claude & Mohamed Becherif, 2023. "Efficient and Reliable Power-Conditioning Stage for Fuel Cell-Based High-Power Applications," Energies, MDPI, vol. 16(13), pages 1-15, June.
    3. 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).
    4. Bai, Fan & Quan, Hong-Bing & Yin, Ren-Jie & Zhang, Zhuo & Jin, Shu-Qi & He, Pu & Mu, Yu-Tong & Gong, Xiao-Ming & Tao, Wen-Quan, 2022. "Three-dimensional multi-field digital twin technology for proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 324(C).
    5. Wang, Shengnan & Li, Yunhua & Li, Yun-Ze & Peng, Xing & Mao, Yufeng, 2018. "Exergy based parametric analysis of a cooling and power co-generation system for the life support system of extravehicular spacesuits," Renewable Energy, Elsevier, vol. 115(C), pages 1209-1219.
    6. 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.
    7. Guilbert, Damien & Gaillard, Arnaud & N'Diaye, Abdoul & Djerdir, Abdesslem, 2016. "Power switch failures tolerance and remedial strategies of a 4-leg floating interleaved DC/DC boost converter for photovoltaic/fuel cell applications," Renewable Energy, Elsevier, vol. 90(C), pages 14-27.
    8. Victor Mercier & Adriano Ceschia & Toufik Azib & Cherif Larouci, 2023. "Pre-Sizing Approach of a Fuel Cell-Battery Hybrid Power System with Interleaved Converters," Energies, MDPI, vol. 16(10), pages 1-21, May.
    9. 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.
    10. Chakraborty, Uttara, 2016. "Fuel crossover and internal current in proton exchange membrane fuel cell modeling," Applied Energy, Elsevier, vol. 163(C), pages 60-62.

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