IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i17p4364-d1468717.html
   My bibliography  Save this article

Integration and Optimization of Multisource Electric Vehicles: A Critical Review of Hybrid Energy Systems, Topologies, and Control Algorithms

Author

Listed:
  • Nikolaos Fesakis

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Georgios Falekas

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Ilias Palaiologou

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Georgia Eirini Lazaridou

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Athanasios Karlis

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

Abstract

Electric vehicles (EVs) are pivotal in addressing the escalating environmental crisis. While EV drivetrains excel compared to those of vehicles with internal combustion engines (ICEs), their energy storage systems are hampered by limited range, lifespan, and lengthy charging times. Hybrid energy storage systems (HESSs) present a viable current solution to these issues. This review thoroughly explores the state of the art in the emerging field of multisource EVs that utilize HESSs, incorporating any combination of batteries (BTs), supercapacitors (SCs), flywheels (FWs), fuel cells (FCs), and/or transmotors. In addition, the paper systematically categorizes and evaluates different hybrid configurations, detailing potential topologies and their respective advantages and limitations. Moreover, the paper examines diverse control algorithms used to manage these complex systems, focusing on their effectiveness and operational efficiency. By identifying current research gaps and technological challenges, this study aims to delineate future research directions that could enhance the deployment and optimization of multisource EVs, thereby addressing critical challenges such as energy density, system reliability, and cost-effectiveness.

Suggested Citation

  • Nikolaos Fesakis & Georgios Falekas & Ilias Palaiologou & Georgia Eirini Lazaridou & Athanasios Karlis, 2024. "Integration and Optimization of Multisource Electric Vehicles: A Critical Review of Hybrid Energy Systems, Topologies, and Control Algorithms," Energies, MDPI, vol. 17(17), pages 1-42, August.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4364-:d:1468717
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/17/4364/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/17/4364/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sulaiman, N. & Hannan, M.A. & Mohamed, A. & Majlan, E.H. & Wan Daud, W.R., 2015. "A review on energy management system for fuel cell hybrid electric vehicle: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 802-814.
    2. 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).
    3. Xia, Quan & Ren, Yi & Wang, Zili & Yang, Dezhen & Yan, Peiyu & Wu, Zeyu & Sun, Bo & Feng, Qiang & Qian, Cheng, 2023. "Safety risk assessment method for thermal abuse of lithium-ion battery pack based on multiphysics simulation and improved bisection method," Energy, Elsevier, vol. 264(C).
    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. Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
    2. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
    3. Juhui Gim & Minsu Kim & Changsun Ahn, 2022. "Energy Management Control Strategy for Saving Trip Costs of Fuel Cell/Battery Electric Vehicles," Energies, MDPI, vol. 15(6), pages 1-15, March.
    4. Sanghyun Yun & Jinwon Yun & Jaeyoung Han, 2023. "Development of a 470-Horsepower Fuel Cell–Battery Hybrid Xcient Dynamic Model Using Simscape TM," Energies, MDPI, vol. 16(24), pages 1-22, December.
    5. Kurnia, Jundika C. & Sasmito, Agus P. & Shamim, Tariq, 2017. "Performance evaluation of a PEM fuel cell stack with variable inlet flows under simulated driving cycle conditions," Applied Energy, Elsevier, vol. 206(C), pages 751-764.
    6. 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).
    7. Yavuz Eray Altun & Osman Akın Kutlar, 2024. "Energy Management Systems’ Modeling and Optimization in Hybrid Electric Vehicles," Energies, MDPI, vol. 17(7), pages 1-39, April.
    8. Zhang, Zhiqing & Dong, Rui & Tan, Dongli & Duan, Lin & Jiang, Feng & Yao, Xiaoxue & Yang, Dixin & Hu, Jingyi & Zhang, Jian & Zhong, Weihuang & Zhao, Ziheng, 2023. "Effect of structural parameters on diesel particulate filter trapping performance of heavy-duty diesel engines based on grey correlation analysis," Energy, Elsevier, vol. 271(C).
    9. Briggs, Ian & Murtagh, Martin & Kee, Robert & McCulloug, Geoffrey & Douglas, Roy, 2017. "Sustainable non-automotive vehicles: The simulation challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 840-851.
    10. Ma, Ying & Yang, Heng & Zuo, Hongyan & Zuo, Qingsong & He, Xiaoxiang & Chen, Wei & Wei, Rongrong, 2023. "EG@Bi-MOF derived porous carbon/lauric acid composite phase change materials for thermal management of batteries," Energy, Elsevier, vol. 272(C).
    11. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    12. Kwan, T.H. & Shen, Y. & Pei, G., 2021. "Recycling fuel cell waste heat to the thermoelectric cooler for enhanced combined heat, power and water production," Energy, Elsevier, vol. 223(C).
    13. Zeng, Tao & Zhang, Caizhi & Zhang, Yanyi & Deng, Chenghao & Hao, Dong & Zhu, Zhongwen & Ran, Hongxu & Cao, Dongpu, 2021. "Optimization-oriented adaptive equivalent consumption minimization strategy based on short-term demand power prediction for fuel cell hybrid vehicle," Energy, Elsevier, vol. 227(C).
    14. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    15. Benmouna, Amel & Becherif, Mohamed & Depernet, Daniel & Ebrahim, Mohamed A., 2018. "Novel Energy Management Technique for Hybrid Electric Vehicle via Interconnection and Damping Assignment Passivity Based Control," Renewable Energy, Elsevier, vol. 119(C), pages 116-128.
    16. Ma, Ying & Yang, Heng & Zuo, Hongyan & Ma, Yi & Zuo, Qingsong & Chen, Ying & He, Xiaoxiang & Wei, Rongrong, 2023. "Three-dimensional EG@MOF matrix composite phase change materials for high efficiency battery cooling," Energy, Elsevier, vol. 278(C).
    17. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    18. Jamila Snoussi & Seifeddine Ben Elghali & Mohamed Benbouzid & Mohamed Faouzi Mimouni, 2018. "Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-20, August.
    19. Zhou, Hongxu & Yu, Zhongwei & Wu, Xiaohua & Fan, Zhanfeng & Yin, Xiaofeng & Zhou, Lingxue, 2023. "Dynamic programming improved online fuzzy power distribution in a demonstration fuel cell hybrid bus," Energy, Elsevier, vol. 284(C).
    20. Shaukat, N. & Khan, B. & Ali, S.M. & Mehmood, C.A. & Khan, J. & Farid, U. & Majid, M. & Anwar, S.M. & Jawad, M. & Ullah, Z., 2018. "A survey on electric vehicle transportation within smart grid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1329-1349.

    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:17:y:2024:i:17:p:4364-:d:1468717. 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.