IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1721-d758297.html
   My bibliography  Save this article

Research on Multi-Objective Compound Energy Management Strategy Based on Fuzzy Control for FCHEV

Author

Listed:
  • Cuixia Lin

    (Guangxi Key Laboratory of Auto Parts and Vehicle Technology, School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China)

  • Wenguang Luo

    (Guangxi Key Laboratory of Auto Parts and Vehicle Technology, School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China)

  • Hongli Lan

    (Guangxi Key Laboratory of Auto Parts and Vehicle Technology, School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China)

  • Cong Hu

    (Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, School of Electronic Engineering and Automation, Guilin University of Electronic Science and Technology, Guilin 541004, China)

Abstract

A compound energy management strategy is proposed to improve the fuel cell’s durability and the economy of fuel cell hybrid electric vehicles (FCHEV). A control strategy that combines fuzzy control and switching control is proposed, taking into account factors that affect the fuel cell’s durability and the supercapacitor park’s safety. To smooth the output power of fuel cells under frequent variable load conditions, a moving average filtering algorithm has been added. Finally, co-simulation using Advisor and Matlab/Simulink under the World Light Vehicle Test Cycle (WLTC) compares the proposed strategy with fuzzy control and power following strategies. The experimental results show that the proposed strategy ensures the safety of the supercapacitor park and improves the durability of the fuel cell while improving the economy of the whole vehicle.

Suggested Citation

  • Cuixia Lin & Wenguang Luo & Hongli Lan & Cong Hu, 2022. "Research on Multi-Objective Compound Energy Management Strategy Based on Fuzzy Control for FCHEV," Energies, MDPI, vol. 15(5), pages 1-14, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1721-:d:758297
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1721/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/5/1721/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xu, Liangfei & Mueller, Clemens David & Li, Jianqiu & Ouyang, Minggao & Hu, Zunyan, 2015. "Multi-objective component sizing based on optimal energy management strategy of fuel cell electric vehicles," Applied Energy, Elsevier, vol. 157(C), pages 664-674.
    Full references (including those not matched with items on IDEAS)

    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. Pregelj, Boštjan & Micor, Michał & Dolanc, Gregor & Petrovčič, Janko & Jovan, Vladimir, 2016. "Impact of fuel cell and battery size to overall system performance – A diesel fuel-cell APU case study," Applied Energy, Elsevier, vol. 182(C), pages 365-375.
    2. 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.
    3. 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.
    4. 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.
    5. Xu, Liangfei & Fang, Chuan & Hu, Junming & Cheng, Siliang & Li, Jianqiu & Ouyang, Minggao & Lehnert, Werner, 2017. "Parameter extraction of polymer electrolyte membrane fuel cell based on quasi-dynamic model and periphery signals," Energy, Elsevier, vol. 122(C), pages 675-690.
    6. Lin, Zichang & Wang, Feng & Zhang, Haoxiang & Xu, Bing, 2024. "Extending battery lifetime of electric-hydraulic hybrid wheel loader through system parameter optimization," Energy, Elsevier, vol. 313(C).
    7. Iqbal, Mehroze & Laurent, Julien & Benmouna, Amel & Becherif, Mohamed & Ramadan, Haitham S. & Claude, Frederic, 2022. "Ageing-aware load following control for composite-cost optimal energy management of fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 254(PA).
    8. Zhu, Jianyun & Chen, Li & Wang, Xuefeng & Yu, Long, 2020. "Bi-level optimal sizing and energy management of hybrid electric propulsion systems," Applied Energy, Elsevier, vol. 260(C).
    9. Feroldi, Diego & Carignano, Mauro, 2016. "Sizing for fuel cell/supercapacitor hybrid vehicles based on stochastic driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 645-658.
    10. Jianyun, Zhu & Li, Chen & Lijuan, Xia & Bin, Wang, 2019. "Bi-objective optimal design of plug-in hybrid electric propulsion system for ships," Energy, Elsevier, vol. 177(C), pages 247-261.
    11. 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.
    12. Lin, Zhenhong & Ou, Shiqi & Elgowainy, Amgad & Reddi, Krishna & Veenstra, Mike & Verduzco, Laura, 2018. "A method for determining the optimal delivered hydrogen pressure for fuel cell electric vehicles," Applied Energy, Elsevier, vol. 216(C), pages 183-194.
    13. 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.
    14. Liu, Bo & Sun, Chao & Wang, Bo & Liang, Weiqiang & Ren, Qiang & Li, Junqiu & Sun, Fengchun, 2022. "Bi-level convex optimization of eco-driving for connected Fuel Cell Hybrid Electric Vehicles through signalized intersections," Energy, Elsevier, vol. 252(C).
    15. Kyoungho Ahn & Hesham A. Rakha, 2024. "Simple Energy Model for Hydrogen Fuel Cell Vehicles: Model Development and Testing," Energies, MDPI, vol. 17(24), pages 1-21, December.
    16. Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(C).
    17. He, Yinglong & Wang, Chongming & Zhou, Quan & Li, Ji & Makridis, Michail & Williams, Huw & Lu, Guoxiang & Xu, Hongming, 2020. "Multiobjective component sizing of a hybrid ethanol-electric vehicle propulsion system," Applied Energy, Elsevier, vol. 266(C).
    18. Lei, Fei & Du, Bin & Liu, Xin & Xie, Xiaoping & Chai, Tian, 2016. "Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle," Energy, Elsevier, vol. 113(C), pages 980-990.
    19. Ghimar Merhy & Ahmed Nait-Sidi-Moh & Nazih Moubayed, 2021. "A multi-objective optimization of electric vehicles energy flows: the charging process," Annals of Operations Research, Springer, vol. 296(1), pages 315-333, January.
    20. Peng, Hujun & Chen, Zhu & Li, Jianxiang & Deng, Kai & Dirkes, Steffen & Gottschalk, Jonas & Ünlübayir, Cem & Thul, Andreas & Löwenstein, Lars & Pischinger, Stefan & Hameyer, Kay, 2021. "Offline optimal energy management strategies considering high dynamics in batteries and constraints on fuel cell system power rate: From analytical derivation to validation on test bench," Applied Energy, Elsevier, vol. 282(PA).

    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:15:y:2022:i:5:p:1721-:d:758297. 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.