IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i13p3510-d381597.html
   My bibliography  Save this article

Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/13/3510/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/13/3510/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    3. Du, Guodong & Zou, Yuan & Zhang, Xudong & Liu, Teng & Wu, Jinlong & He, Dingbo, 2020. "Deep reinforcement learning based energy management for a hybrid electric vehicle," Energy, Elsevier, vol. 201(C).
    4. Qi, Chunyang & Zhu, Yiwen & Song, Chuanxue & Yan, Guangfu & Xiao, Feng & Da wang, & Zhang, Xu & Cao, Jingwei & Song, Shixin, 2022. "Hierarchical reinforcement learning based energy management strategy for hybrid electric vehicle," Energy, Elsevier, vol. 238(PA).
    5. Li, Shuangqi & He, Hongwen & Zhao, Pengfei, 2021. "Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective," Energy, Elsevier, vol. 230(C).
    6. Ying Yang & Weige Zhang & Shaoyuan Wei & Zhenpo Wang, 2020. "Optimal Sizing of On-Board Energy Storage Systems and Stationary Charging Infrastructures for a Catenary-Free Tram," Energies, MDPI, vol. 13(23), pages 1-21, November.
    7. Wu, Wei & Lin, Boqiang & Xie, Chunping & Elliott, Robert J.R. & Radcliffe, Jonathan, 2020. "Does energy storage provide a profitable second life for electric vehicle batteries?," Energy Economics, Elsevier, vol. 92(C).
    8. Zou, Runnan & Fan, Likang & Dong, Yanrui & Zheng, Siyu & Hu, Chenxing, 2021. "DQL energy management: An online-updated algorithm and its application in fix-line hybrid electric vehicle," Energy, Elsevier, vol. 225(C).
    9. Kegang Zhao & Jinghao Bei & Yanwei Liu & Zhihao Liang, 2019. "Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method," Energies, MDPI, vol. 12(17), pages 1-23, August.
    10. Phatiphat Thounthong & Matheepot Phattanasak & Damien Guilbert & Noureddine Takorabet & Serge Pierfederici & Babak Nahid-Mobarakeh & Nicu Bizon & Poom Kumam, 2020. "Differential Flatness Based-Control Strategy of a Two-Port Bidirectional Supercapacitor Converter for Hydrogen Mobility Applications," Energies, MDPI, vol. 13(11), pages 1-24, June.
    11. Liu, Teng & Tan, Wenhao & Tang, Xiaolin & Zhang, Jinwei & Xing, Yang & Cao, Dongpu, 2021. "Driving conditions-driven energy management strategies for hybrid electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    12. Asadullah Khalid & Alexander Stevenson & Arif I. Sarwat, 2021. "Performance Analysis of Commercial Passive Balancing Battery Management System Operation Using a Hardware-in-the-Loop Testbed," Energies, MDPI, vol. 14(23), pages 1-14, December.
    13. Reddi Khasim, Shaik & Dhanamjayulu, C., 2021. "Selection parameters and synthesis of multi-input converters for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    14. Wang, Jing & Kang, Lixia & Liu, Yongzhong, 2020. "Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    15. Shi, Dehua & Liu, Sheng & Cai, Yingfeng & Wang, Shaohua & Li, Haoran & Chen, Long, 2021. "Pontryagin’s minimum principle based fuzzy adaptive energy management for hybrid electric vehicle using real-time traffic information," Applied Energy, Elsevier, vol. 286(C).
    16. Zhou, Yu & Meng, Qiang & Ong, Ghim Ping, 2022. "Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 49-75.
    17. Yongbing Xiang & Xiaomin Yang, 2021. "An ECMS for Multi-Objective Energy Management Strategy of Parallel Diesel Electric Hybrid Ship Based on Ant Colony Optimization Algorithm," Energies, MDPI, vol. 14(4), pages 1-21, February.
    18. Luigi Fortuna & Arturo Buscarino, 2022. "Sustainable Energy Systems," Energies, MDPI, vol. 15(23), pages 1-7, December.
    19. Pierpaolo Polverino & Ivan Arsie & Cesare Pianese, 2021. "Optimal Energy Management for Hybrid Electric Vehicles Based on Dynamic Programming and Receding Horizon," Energies, MDPI, vol. 14(12), pages 1-11, June.
    20. Barelli, L. & Bidini, G. & Bonucci, F. & Castellini, L. & Fratini, A. & Gallorini, F. & Zuccari, A., 2019. "Flywheel hybridization to improve battery life in energy storage systems coupled to RES plants," Energy, Elsevier, vol. 173(C), pages 937-950.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3510-:d:381597. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.