IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i10p6320-d821316.html
   My bibliography  Save this article

The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle

Author

Listed:
  • Jiaming Zhou

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
    Yangtze Delta Region Academy, Beijing Institute of Technology, Jiaxing 314019, China)

  • Chunxiao Feng

    (School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Qingqing Su

    (School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Shangfeng Jiang

    (Yutong Bus Co., Ltd., Zhengzhou 450016, China)

  • Zhixian Fan

    (Zhongtong Bus Holding Co., Ltd., Liaocheng 252000, China)

  • Jiageng Ruan

    (Department of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China)

  • Shikai Sun

    (China Transport Telecommunications & Information Center, Beijing 100011, China)

  • Leli Hu

    (School of Automobile and Transportation Engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.

Suggested Citation

  • Jiaming Zhou & Chunxiao Feng & Qingqing Su & Shangfeng Jiang & Zhixian Fan & Jiageng Ruan & Shikai Sun & Leli Hu, 2022. "The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6320-:d:821316
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/10/6320/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/10/6320/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pei, Pucheng & Chen, Huicui, 2014. "Main factors affecting the lifetime of Proton Exchange Membrane fuel cells in vehicle applications: A review," Applied Energy, Elsevier, vol. 125(C), pages 60-75.
    2. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Han, Xuebing & Ouyang, Minggao, 2015. "Optimization for a hybrid energy storage system in electric vehicles using dynamic programing approach," Applied Energy, Elsevier, vol. 139(C), pages 151-162.
    3. Fengyan Yi & Dagang Lu & Xingmao Wang & Chaofeng Pan & Yuanxue Tao & Jiaming Zhou & Changli Zhao, 2022. "Energy Management Strategy for Hybrid Energy Storage Electric Vehicles Based on Pontryagin’s Minimum Principle Considering Battery Degradation," Sustainability, MDPI, vol. 14(3), pages 1-17, January.
    4. Omar, Noshin & Monem, Mohamed Abdel & Firouz, Yousef & Salminen, Justin & Smekens, Jelle & Hegazy, Omar & Gaulous, Hamid & Mulder, Grietus & Van den Bossche, Peter & Coosemans, Thierry & Van Mierlo, J, 2014. "Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model," Applied Energy, Elsevier, vol. 113(C), pages 1575-1585.
    5. Song, Ziyou & Li, Jianqiu & Han, Xuebing & Xu, Liangfei & Lu, Languang & Ouyang, Minggao & Hofmann, Heath, 2014. "Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 135(C), pages 212-224.
    6. Aritra Ghosh, 2020. "Possibilities and Challenges for the Inclusion of the Electric Vehicle (EV) to Reduce the Carbon Footprint in the Transport Sector: A Review," Energies, MDPI, vol. 13(10), pages 1-22, May.
    7. Olivier Bethoux, 2020. "Hydrogen Fuel Cell Road Vehicles: State of the Art and Perspectives," Energies, MDPI, vol. 13(21), pages 1-28, November.
    8. Ally, Jamie & Pryor, Trevor, 2016. "Life cycle costing of diesel, natural gas, hybrid and hydrogen fuel cell bus systems: An Australian case study," Energy Policy, Elsevier, vol. 94(C), pages 285-294.
    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. Peng Yin & Jinzhou Chen & Hongwen He, 2023. "Control of Oxygen Excess Ratio for a PEMFC Air Supply System by Intelligent PID Methods," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    2. Nikita V. Martyushev & Boris V. Malozyomov & Svetlana N. Sorokova & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Modeling of the State of the Battery of Cargo Electric Vehicles," Mathematics, MDPI, vol. 11(3), pages 1-19, January.
    3. Zhiming Zhang & Sai Wu & Huimin Miao & Tong Zhang, 2022. "Numerical Investigation of Flow Channel Design and Tapered Slope Effects on PEM Fuel Cell Performance," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    4. Imed Khabbouchi & Dhaou Said & Aziz Oukaira & Idir Mellal & Lyes Khoukhi, 2023. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)," Energies, MDPI, vol. 16(5), pages 1-15, February.
    5. Nikita V. Martyushev & Boris V. Malozyomov & Ilham H. Khalikov & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Vadim Sergeevich Tynchenko & Yadviga Aleksandrovna Tynchenko & Mengxu , 2023. "Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption," Energies, MDPI, vol. 16(2), pages 1-39, January.
    6. Kun He & Dongchen Qin & Jiangyi Chen & Tingting Wang & Hongxia Wu & Peizhuo Wang, 2023. "Adaptive Equivalent Consumption Minimization Strategy for Fuel Cell Buses Based on Driving Style Recognition," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    7. Wang, Yichun & Zhang, Yuanzhi & Zhang, Caizhi & Zhou, Jiaming & Hu, Donghai & Yi, Fengyan & Fan, Zhixian & Zeng, Tao, 2023. "Genetic algorithm-based fuzzy optimization of energy management strategy for fuel cell vehicles considering driving cycles recognition," Energy, Elsevier, vol. 263(PF).
    8. Zhiming Zhang & Alexander Rex & Jiaming Zhou & Xinfeng Zhang & Gangqiang Huang & Jinming Zhang & Tong Zhang, 2023. "Dynamic Simulation Model and Experimental Validation of One Passive Fuel Cell–Battery Hybrid Powertrain for an Electric Light Scooter," Sustainability, MDPI, vol. 15(17), pages 1-19, September.
    9. Xin, Yuntong & Hu, Jianjun & Wang, Zhouxin, 2024. "An energy management strategy with considering ultracapacitor ideal state of charge for fuel cell/battery/ultracapacitor vehicle," Energy, Elsevier, vol. 304(C).
    10. Mojgan Fayyazi & Paramjotsingh Sardar & Sumit Infent Thomas & Roonak Daghigh & Ali Jamali & Thomas Esch & Hans Kemper & Reza Langari & Hamid Khayyam, 2023. "Artificial Intelligence/Machine Learning in Energy Management Systems, Control, and Optimization of Hydrogen Fuel Cell Vehicles," Sustainability, MDPI, vol. 15(6), pages 1-38, March.
    11. Xiaoping Li & Junming Zhou & Wei Guan & Feng Jiang & Guangming Xie & Chunfeng Wang & Weiguang Zheng & Zhijie Fang, 2023. "Optimization of Brake Feedback Efficiency for Small Pure Electric Vehicles Based on Multiple Constraints," Energies, MDPI, vol. 16(18), pages 1-20, September.

    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. Jiang, Hongliang & Xu, Liangfei & Li, Jianqiu & Hu, Zunyan & Ouyang, Minggao, 2019. "Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms," Energy, Elsevier, vol. 177(C), pages 386-396.
    2. da Silva, Samuel Filgueira & Eckert, Jony Javorski & Corrêa, Fernanda Cristina & Silva, Fabrício Leonardo & Silva, Ludmila C.A. & Dedini, Franco Giuseppe, 2022. "Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle," Applied Energy, Elsevier, vol. 324(C).
    3. Wieczorek, Maciej & Lewandowski, Mirosław, 2017. "A mathematical representation of an energy management strategy for hybrid energy storage system in electric vehicle and real time optimization using a genetic algorithm," Applied Energy, Elsevier, vol. 192(C), pages 222-233.
    4. Oh, Ki-Yong & Epureanu, Bogdan I., 2016. "Characterization and modeling of the thermal mechanics of lithium-ion battery cells," Applied Energy, Elsevier, vol. 178(C), pages 633-646.
    5. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Zhang, Xiaowu & Ouyang, Minggao, 2015. "The optimization of a hybrid energy storage system at subzero temperatures: Energy management strategy design and battery heating requirement analysis," Applied Energy, Elsevier, vol. 159(C), pages 576-588.
    6. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
    7. Jiajun Liu & Tianxu Jin & Li Liu & Yajue Chen & Kun Yuan, 2017. "Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    8. Zhou, Quan & Zhang, Wei & Cash, Scott & Olatunbosun, Oluremi & Xu, Hongming & Lu, Guoxiang, 2017. "Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization," Applied Energy, Elsevier, vol. 189(C), pages 588-601.
    9. Hou, Jun & Song, Ziyou & Park, Hyeongjun & Hofmann, Heath & Sun, Jing, 2018. "Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 230(C), pages 62-77.
    10. Huang, Jiangfan & An, Qing & Zhou, Mingyu & Tang, Ruoli & Dong, Zhengcheng & Lai, Jingang & Li, Xin & Yang, Xiangguo, 2024. "A self-adaptive joint optimization framework for marine hybrid energy storage system design considering load fluctuation characteristics," Applied Energy, Elsevier, vol. 361(C).
    11. Hu, Lin & Tian, Qingtao & Zou, Changfu & Huang, Jing & Ye, Yao & Wu, Xianhui, 2022. "A study on energy distribution strategy of electric vehicle hybrid energy storage system considering driving style based on real urban driving data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    12. Roshandel, Ramin & Parhizkar, Tarannom, 2016. "Degradation based optimization framework for long term applications of energy systems, case study: Solid oxide fuel cell stacks," Energy, Elsevier, vol. 107(C), pages 172-181.
    13. Xiaogang Wu & Tianze Wang, 2017. "Optimization of Battery Capacity Decay for Semi-Active Hybrid Energy Storage System Equipped on Electric City Bus," Energies, MDPI, vol. 10(6), pages 1-20, June.
    14. Halder, Pobitra & Babaie, Meisam & Salek, Farhad & Shah, Kalpit & Stevanovic, Svetlana & Bodisco, Timothy A. & Zare, Ali, 2024. "Performance, emissions and economic analyses of hydrogen fuel cell vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    15. Song, Ziyou & Feng, Shuo & Zhang, Lei & Hu, Zunyan & Hu, Xiaosong & Yao, Rui, 2019. "Economy analysis of second-life battery in wind power systems considering battery degradation in dynamic processes: Real case scenarios," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Wu, Yue & Huang, Zhiwu & Li, Dongjun & Li, Heng & Peng, Jun & Stroe, Daniel & Song, Ziyou, 2024. "Optimal battery thermal management for electric vehicles with battery degradation minimization," Applied Energy, Elsevier, vol. 353(PA).
    17. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    18. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    19. Jiajun Liu & Huachao Dong & Tianxu Jin & Li Liu & Babak Manouchehrinia & Zuomin Dong, 2018. "Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation," Energies, MDPI, vol. 11(10), pages 1-25, October.
    20. Ruan, Jiageng & Song, Qiang & Yang, Weiwei, 2019. "The application of hybrid energy storage system with electrified continuously variable transmission in battery electric vehicle," Energy, Elsevier, vol. 183(C), pages 315-330.

    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:jsusta:v:14:y:2022:i:10:p:6320-:d:821316. 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.