IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v267y2020ics0306261920305985.html
   My bibliography  Save this article

Min-max game based energy management strategy for fuel cell/supercapacitor hybrid electric vehicles

Author

Listed:
  • Sun, Zhendong
  • Wang, Yujie
  • Chen, Zonghai
  • Li, Xiyun

Abstract

The fuel cell hybrid electric vehicles have received widespread attention in recent years due to their zero-emission and long mileage. However, the durability of the fuel cell declines rapidly under frequent start and stop and power fluctuation. The fuel efficiency of the power system is affected by the power allocation strategy. For low hydrogen consumption and fuel cell durability, an energy management strategy based on the game theory is proposed in this paper, which considers the controller and the future driving condition as both sides of the game to enhance the operational stability in complex driving conditions. The interval forecast for driving conditions is realized by introducing the Markov chain method. To obtain the optimal power allocation strategy in the speed forecast window, it is reasonable to integrate the co-evolutionary algorithm with the game model to leverage its superior ability in solving the constrained min-max problem. In order to verify the robustness and the economic performance of this method, the comparison with other methods is conducted in the typical urban, highway and mixed driving conditions. What is more, the fuel cell degradation and operational stability of four energy management strategies are evaluated by the fuel cell degradation model. The results show that the proposed method can reduce hydrogen consumption by more than 6.82% and avoid fuel cell degradation caused by frequent start and stop and power fluctuation compared with other real-time strategies.

Suggested Citation

  • Sun, Zhendong & Wang, Yujie & Chen, Zonghai & Li, Xiyun, 2020. "Min-max game based energy management strategy for fuel cell/supercapacitor hybrid electric vehicles," Applied Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:appene:v:267:y:2020:i:c:s0306261920305985
    DOI: 10.1016/j.apenergy.2020.115086
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920305985
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.115086?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
    2. Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
    3. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    4. Jenelius, Erik & Koutsopoulos, Haris N., 2013. "Travel time estimation for urban road networks using low frequency probe vehicle data," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 64-81.
    5. Ettihir, K. & Boulon, L. & Agbossou, K., 2016. "Optimization-based energy management strategy for a fuel cell/battery hybrid power system," Applied Energy, Elsevier, vol. 163(C), pages 142-153.
    6. Daud, W.R.W. & Rosli, R.E. & Majlan, E.H. & Hamid, S.A.A. & Mohamed, R. & Husaini, T., 2017. "PEM fuel cell system control: A review," Renewable Energy, Elsevier, vol. 113(C), pages 620-638.
    7. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine," Applied Energy, Elsevier, vol. 254(C).
    8. Zhang, Shuo & Xiong, Rui & Sun, Fengchun, 2017. "Model predictive control for power management in a plug-in hybrid electric vehicle with a hybrid energy storage system," Applied Energy, Elsevier, vol. 185(P2), pages 1654-1662.
    9. Tribioli, Laura & Cozzolino, Raffaello & Chiappini, Daniele & Iora, Paolo, 2016. "Energy management of a plug-in fuel cell/battery hybrid vehicle with on-board fuel processing," Applied Energy, Elsevier, vol. 184(C), pages 140-154.
    10. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    11. Zhang, Hongtao & Li, Xianguo & Liu, Xinzhi & Yan, Jinyue, 2019. "Enhancing fuel cell durability for fuel cell plug-in hybrid electric vehicles through strategic power management," Applied Energy, Elsevier, vol. 241(C), pages 483-490.
    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. Desantes, J.M. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2022. "A modeling framework for predicting the effect of the operating conditions and component sizing on fuel cell degradation and performance for automotive applications," Applied Energy, Elsevier, vol. 317(C).
    2. 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).
    3. 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.
    4. Macias, A. & Kandidayeni, M. & Boulon, L. & Trovão, J.P., 2021. "Fuel cell-supercapacitor topologies benchmark for a three-wheel electric vehicle powertrain," Energy, Elsevier, vol. 224(C).
    5. Mohsen Kandidayeni & Alvaro Macias & Loïc Boulon & João Pedro F. Trovão, 2020. "Online Modeling of a Fuel Cell System for an Energy Management Strategy Design," Energies, MDPI, vol. 13(14), pages 1-17, July.
    6. Duan, Hao & Zhang, Caizhi & Wang, Gucheng & Chen, Yu'an & Liu, Zhixiang & Xie, Xianshu & Shuai, Qi, 2022. "Experimental study of the dynamic and transient characteristics of sub-health fuel cell multi-stack systems without DC/DC," Energy, Elsevier, vol. 238(PC).
    7. Mubashir Rasool & Muhammad Adil Khan & Runmin Zou, 2023. "A Comprehensive Analysis of Online and Offline Energy Management Approaches for Optimal Performance of Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 16(8), pages 1-33, April.
    8. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
    9. Zou, Weitao & Li, Jianwei & Yang, Qingqing & Wan, Xinming & He, Yuntang & Lan, Hao, 2023. "A real-time energy management approach with fuel cell and battery competition-synergy control for the fuel cell vehicle," Applied Energy, Elsevier, vol. 334(C).
    10. Molina, S. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2021. "Optimization and sizing of a fuel cell range extender vehicle for passenger car applications in driving cycle conditions," Applied Energy, Elsevier, vol. 285(C).
    11. Li, Qi & Wang, Tianhong & Li, Shihan & Chen, Weirong & Liu, Hong & Breaz, Elena & Gao, Fei, 2021. "Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation," Applied Energy, Elsevier, vol. 285(C).
    12. Aissa Benhammou & Hamza Tedjini & Mohammed Amine Hartani & Rania M. Ghoniem & Ali Alahmer, 2023. "Accurate and Efficient Energy Management System of Fuel Cell/Battery/Supercapacitor/AC and DC Generators Hybrid Electric Vehicles," Sustainability, MDPI, vol. 15(13), pages 1-27, June.
    13. Qicheng Xue & Xin Zhang & Teng Teng & Jibao Zhang & Zhiyuan Feng & Qinyang Lv, 2020. "A Comprehensive Review on Classification, Energy Management Strategy, and Control Algorithm for Hybrid Electric Vehicles," Energies, MDPI, vol. 13(20), pages 1-30, October.
    14. Li, Yapeng & Wang, Feng & Tang, Xiaolin & Hu, Xiaosong & Lin, Xianke, 2022. "Convex optimization-based predictive and bi-level energy management for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 257(C).
    15. Kandidayeni, M. & Macias, A. & Boulon, L. & Kelouwani, S., 2020. "Investigating the impact of ageing and thermal management of a fuel cell system on energy management strategies," Applied Energy, Elsevier, vol. 274(C).

    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. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine," Applied Energy, Elsevier, vol. 254(C).
    3. Kandidayeni, M. & Macias, A. & Boulon, L. & Kelouwani, S., 2020. "Investigating the impact of ageing and thermal management of a fuel cell system on energy management strategies," Applied Energy, Elsevier, vol. 274(C).
    4. Nicu Bizon & Phatiphat Thounthong, 2021. "A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle," Mathematics, MDPI, vol. 9(6), pages 1-29, March.
    5. Xueqin Lü, & Wu, Yinbo & Lian, Jie & Zhang, Yangyang, 2021. "Energy management and optimization of PEMFC/battery mobile robot based on hybrid rule strategy and AMPSO," Renewable Energy, Elsevier, vol. 171(C), pages 881-901.
    6. Bizon, Nicu, 2019. "Fuel saving strategy using real-time switching of the fueling regulators in the proton exchange membrane fuel cell system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    8. Yao He & Changchang Miao & Ji Wu & Xinxin Zheng & Xintian Liu & Xingtao Liu & Feng Han, 2021. "Research on the Power Distribution Method for Hybrid Power System in the Fuel Cell Vehicle," Energies, MDPI, vol. 14(3), pages 1-15, January.
    9. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    10. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    11. Ioan-Sorin Sorlei & Nicu Bizon & Phatiphat Thounthong & Mihai Varlam & Elena Carcadea & Mihai Culcer & Mariana Iliescu & Mircea Raceanu, 2021. "Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies," Energies, MDPI, vol. 14(1), pages 1-29, January.
    12. Nie, Zhigen & Jia, Yuan & Wang, Wanqiong & Chen, Zheng & Outbib, Rachid, 2022. "Co-optimization of speed planning and energy management for intelligent fuel cell hybrid vehicle considering complex traffic conditions," Energy, Elsevier, vol. 247(C).
    13. Bizon, Nicu & Thounthong, Phatiphat, 2018. "Real-time strategies to optimize the fueling of the fuel cell hybrid power source: A review of issues, challenges and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1089-1102.
    14. Nicu Bizon & Valentin Alexandru Stan & Angel Ciprian Cormos, 2019. "Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus," Energies, MDPI, vol. 12(10), pages 1-15, May.
    15. Nicu Bizon & Mircea Raceanu & Emmanouel Koudoumas & Adriana Marinoiu & Emmanuel Karapidakis & Elena Carcadea, 2020. "Renewable/Fuel Cell Hybrid Power System Operation Using Two Search Controllers of the Optimal Power Needed on the DC Bus," Energies, MDPI, vol. 13(22), pages 1-26, November.
    16. Nicu Bizon & Alin Gheorghita Mazare & Laurentiu Mihai Ionescu & Phatiphat Thounthong & Erol Kurt & Mihai Oproescu & Gheorghe Serban & Ioan Lita, 2019. "Better Fuel Economy by Optimizing Airflow of the Fuel Cell Hybrid Power Systems Using Fuel Flow-Based Load-Following Control," Energies, MDPI, vol. 12(14), pages 1-17, July.
    17. Quan, Shengwei & Wang, Ya-Xiong & Xiao, Xuelian & He, Hongwen & Sun, Fengchun, 2021. "Feedback linearization-based MIMO model predictive control with defined pseudo-reference for hydrogen regulation of automotive fuel cells," Applied Energy, Elsevier, vol. 293(C).
    18. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Development of energy management system based on a rule-based power distribution strategy for hybrid power sources," Energy, Elsevier, vol. 175(C), pages 1055-1066.
    19. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    20. Bizon, Nicu, 2017. "Energy optimization of fuel cell system by using global extremum seeking algorithm," Applied Energy, Elsevier, vol. 206(C), pages 458-474.

    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:eee:appene:v:267:y:2020:i:c:s0306261920305985. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.