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Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration

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  • Adriano Ceschia

    (ESTACA’LAB, S2ET Department, École Supérieure des Techniques Aéronautiques et de Construction Automobile (ESTACA)—Paris Sacley, 12 Avenue Paul Delouvrier, 78180 Montigny-le-Bretonneux, France
    GeePs, Group of Electrical Engineering—Paris, UMR CNRS 8507, CentraleSupélec, Univ. Paris-Sud, Univ. Paris-Saclay, Sorbonne Université, 3 rue Joliot-Curie, 91192 Gif-sur-Yvette, France)

  • Toufik Azib

    (ESTACA’LAB, S2ET Department, École Supérieure des Techniques Aéronautiques et de Construction Automobile (ESTACA)—Paris Sacley, 12 Avenue Paul Delouvrier, 78180 Montigny-le-Bretonneux, France)

  • Olivier Bethoux

    (GeePs, Group of Electrical Engineering—Paris, UMR CNRS 8507, CentraleSupélec, Univ. Paris-Sud, Univ. Paris-Saclay, Sorbonne Université, 3 rue Joliot-Curie, 91192 Gif-sur-Yvette, France)

  • Francisco Alves

    (GeePs, Group of Electrical Engineering—Paris, UMR CNRS 8507, CentraleSupélec, Univ. Paris-Sud, Univ. Paris-Saclay, Sorbonne Université, 3 rue Joliot-Curie, 91192 Gif-sur-Yvette, France)

Abstract

This paper addresses the issue of optimal sizing reliability applied to a fuel cell/battery hybrid system. This specific problem raises the global problem of strong coupling between hardware and control parameters. To tackle this matter, the proposed methodology uses nested optimization loops. Furthermore, to increase the optimal design relevance, a reliability assessment of the optimal sizing set is introduced. This new paradigm enables showing the early impact of the reliability criteria on design choices regarding energetic performance index. It leads to a smart design methodology permitting to avoid complexity and save computing time. It considerably helps design engineers set up the best hybridization rate and enables practicing tradeoffs, including reliability aspects in the early design stages.

Suggested Citation

  • Adriano Ceschia & Toufik Azib & Olivier Bethoux & Francisco Alves, 2020. "Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration," Energies, MDPI, vol. 13(13), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3510-:d:381597
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    References listed on IDEAS

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    1. Rui Yang & Yupeng Yuan & Rushun Ying & Boyang Shen & Teng Long, 2020. "A Novel Energy Management Strategy for a Ship’s Hybrid Solar Energy Generation System Using a Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 13(6), pages 1-14, March.
    2. Junhui Liu & Lei Feng & Zhiwu Li, 2017. "The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption," Energies, MDPI, vol. 10(5), pages 1-31, May.
    3. Zou Yuan & Liu Teng & Sun Fengchun & Huei Peng, 2013. "Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle," Energies, MDPI, vol. 6(4), pages 1-14, April.
    4. Alessandro Serpi & Mario Porru, 2019. "Modelling and Design of Real-Time Energy Management Systems for Fuel Cell/Battery Electric Vehicles," Energies, MDPI, vol. 12(22), pages 1-21, November.
    5. Yi Yang & Zhihao Shang & Yao Chen & Yanhua Chen, 2020. "Multi-Objective Particle Swarm Optimization Algorithm for Multi-Step Electric Load Forecasting," Energies, MDPI, vol. 13(3), pages 1-19, January.
    6. Tao, Laifa & Ma, Jian & Cheng, Yujie & Noktehdan, Azadeh & Chong, Jin & Lu, Chen, 2017. "A review of stochastic battery models and health management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 716-732.
    7. Martinez-Laserna, E. & Gandiaga, I. & Sarasketa-Zabala, E. & Badeda, J. & Stroe, D.-I. & Swierczynski, M. & Goikoetxea, A., 2018. "Battery second life: Hype, hope or reality? A critical review of the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 701-718.
    8. Song, Ziyou & Zhang, Xiaobin & Li, Jianqiu & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system," Energy, Elsevier, vol. 144(C), pages 393-403.
    9. Tran, Dai-Duong & Vafaeipour, Majid & El Baghdadi, Mohamed & Barrero, Ricardo & Van Mierlo, Joeri & Hegazy, Omar, 2020. "Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    10. Zeyu Chen & Rui Xiong & Kunyu Wang & Bin Jiao, 2015. "Optimal Energy Management Strategy of a Plug-in Hybrid Electric Vehicle Based on a Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 8(5), pages 1-18, April.
    11. Gang Yao & Changbo Du & Quanbo Ge & Haoyu Jiang & Yide Wang & Mourad Ait-Ahmed & Luc Moreau, 2019. "Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles," Energies, MDPI, vol. 12(23), pages 1-21, November.
    12. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    13. Xueying Song & Hongyu Lin & Gejirifu De & Hanfang Li & Xiaoxu Fu & Zhongfu Tan, 2020. "An Energy Optimal Dispatching Model of an Integrated Energy System Based on Uncertain Bilevel Programming," Energies, MDPI, vol. 13(2), pages 1-24, January.
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    Cited by:

    1. Naoya Shigeta & Seyed Ehsan Hosseini, 2020. "Sustainable Development of the Automobile Industry in the United States, Europe, and Japan with Special Focus on the Vehicles’ Power Sources," Energies, MDPI, vol. 14(1), pages 1-32, December.
    2. Olivier Bethoux, 2020. "Hydrogen Fuel Cell Road Vehicles: State of the Art and Perspectives," Energies, MDPI, vol. 13(21), pages 1-28, November.
    3. Adriano Ceschia & Toufik Azib & Olivier Bethoux & Francisco Alves, 2022. "Multi-Criteria Optimal Design for FUEL Cell Hybrid Power Sources," Energies, MDPI, vol. 15(9), pages 1-18, May.
    4. Yang Gao & Changhong Liu & Yuan Liang & Sadegh Kouhestani Hamed & Fuwei Wang & Bo Bi, 2022. "Minimizing Energy Consumption and Powertrain Cost of Fuel Cell Hybrid Vehicles with Consideration of Different Driving Cycles and SOC Ranges," Energies, MDPI, vol. 15(17), pages 1-12, August.

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