IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i20p7048-d1257759.html
   My bibliography  Save this article

Dual-Motor Dual-Source High Performance EV: A Comprehensive Review

Author

Listed:
  • Chi T. P. Nguyen

    (e-TESC Laboratory, Département de Génie Électrique et de Génie Informatique, Faculté de Génie, University of Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
    Faculty of Electrical Engineering, Thainguyen University of Technology, Thainguyen 250000, Vietnam)

  • Bảo-Huy Nguyễn

    (CTI Laboratory, Hanoi University of Science and Technology, Hanoi 100000, Vietnam)

  • Minh C. Ta

    (e-TESC Laboratory, Département de Génie Électrique et de Génie Informatique, Faculté de Génie, University of Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
    CTI Laboratory, Hanoi University of Science and Technology, Hanoi 100000, Vietnam)

  • João Pedro F. Trovão

    (e-TESC Laboratory, Département de Génie Électrique et de Génie Informatique, Faculté de Génie, University of Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
    IPC-ISEC and INESC Coimbra, 3030-199 Coimbra, Portugal)

Abstract

Electric vehicles (EVs) have been regarded as one of the promising alternatives to zero-emission transportation. New EV registrations have increased as a result of government policies and consumers’ awareness of climate change. Moreover, EV technology is being improved through ongoing research and development efforts. Among these, a powertrain with a combination of two electric motors has been proposed for high driving and efficiency performance. The study presents a comprehensive state-of-the-art review of architectures and energy distribution for a dual-motor equipped with dual-source EV system. In detail, various dual-motor configurations, and energy management strategies (EMSs) used in the literature are investigated and categorized. A comparison of the benefits and drawbacks of existing topologies and the EMSs of hybrid energy storage systems (HESSs) is also discussed. Following that, research gaps have been considered. This study can be used as a reference for researchers who are interested in the design and optimal control of the dual-motor dual-source EVs.

Suggested Citation

  • Chi T. P. Nguyen & Bảo-Huy Nguyễn & Minh C. Ta & João Pedro F. Trovão, 2023. "Dual-Motor Dual-Source High Performance EV: A Comprehensive Review," Energies, MDPI, vol. 16(20), pages 1-28, October.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7048-:d:1257759
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/20/7048/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/20/7048/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Song, Ziyou & Li, Jianqiu & Hou, Jun & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study," Energy, Elsevier, vol. 154(C), pages 433-441.
    2. Shi, Junzhe & Xu, Bin & Shen, Yimin & Wu, Jingbo, 2022. "Energy management strategy for battery/supercapacitor hybrid electric city bus based on driving pattern recognition," Energy, Elsevier, vol. 243(C).
    3. Yu, Xiao & Lin, Cheng & Zhao, Mingjie & Yi, Jiang & Su, Yue & Liu, Huimin, 2022. "Optimal energy management strategy of a novel hybrid dual-motor transmission system for electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    4. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    5. Hoai-Linh T. Nguyen & Bảo-Huy Nguyễn & Thanh Vo-Duy & João Pedro F. Trovão, 2021. "A Comparative Study of Adaptive Filtering Strategies for Hybrid Energy Storage Systems in Electric Vehicles," Energies, MDPI, vol. 14(12), pages 1-23, June.
    6. Castaings, Ali & Lhomme, Walter & Trigui, Rochdi & Bouscayrol, Alain, 2016. "Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints," Applied Energy, Elsevier, vol. 163(C), pages 190-200.
    7. Hong, Xianqian & Wu, Jinglai & Zhang, Nong & Wang, Bing, 2022. "Energy efficiency optimization of Simpson planetary gearset based dual-motor powertrains for electric vehicles," Energy, Elsevier, vol. 259(C).
    8. Zhang, Shuo & Xiong, Rui & Zhang, Chengning, 2015. "Pontryagin’s Minimum Principle-based power management of a dual-motor-driven electric bus," Applied Energy, Elsevier, vol. 159(C), pages 370-380.
    9. Zhang, Shuo & Xiong, Rui & Cao, Jiayi, 2016. "Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system," Applied Energy, Elsevier, vol. 179(C), pages 316-328.
    10. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    11. Asensio, E. Maximiliano & Magallán, Guillermo A. & Pérez, Laura & De Angelo, Cristian H., 2022. "Short-term power demand prediction for energy management of an electric vehicle based on batteries and ultracapacitors," Energy, Elsevier, vol. 247(C).
    12. Kwon, Kihan & Seo, Minsik & Min, Seungjae, 2020. "Efficient multi-objective optimization of gear ratios and motor torque distribution for electric vehicles with two-motor and two-speed powertrain system," Applied Energy, Elsevier, vol. 259(C).
    13. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Ruan, Haijun & Jiang, Zhihao, 2021. "Adaptive energy management of a battery-supercapacitor energy storage system for electric vehicles based on flexible perception and neural network fitting," Applied Energy, Elsevier, vol. 292(C).
    14. 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).
    15. 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).
    16. Hu, Jie & Liu, Di & Du, Changqing & Yan, Fuwu & Lv, Chen, 2020. "Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition," Energy, Elsevier, vol. 198(C).
    17. Hou, Jun & Song, Ziyou, 2020. "A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity," Applied Energy, Elsevier, vol. 257(C).
    18. 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.
    19. Wilberforce, Tabbi & Anser, Afaaq & Swamy, Jangam Aishwarya & Opoku, Richard, 2023. "An investigation into hybrid energy storage system control and power distribution for hybrid electric vehicles," Energy, Elsevier, vol. 279(C).
    20. He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
    21. Wang, Zhenzhen & Zhou, Jun & Rizzoni, Giorgio, 2022. "A review of architectures and control strategies of dual-motor coupling powertrain systems for battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    22. Wu, Yue & Huang, Zhiwu & Liao, Hongtao & Chen, Bin & Zhang, Xiaoyong & Zhou, Yanhui & Liu, Yongjie & Li, Heng & Peng, Jun, 2020. "Adaptive power allocation using artificial potential field with compensator for hybrid energy storage systems in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
    23. Zhang, Shuo & Xiong, Rui & Zhang, Chengning & Sun, Fengchun, 2016. "An optimal structure selection and parameter design approach for a dual-motor-driven system used in an electric bus," Energy, Elsevier, vol. 96(C), pages 437-448.
    24. Gang Xiao & Qihong Chen & Peng Xiao & Liyan Zhang & Quansen Rong, 2022. "Multiobjective Optimization for a Li-Ion Battery and Supercapacitor Hybrid Energy Storage Electric Vehicle," Energies, MDPI, vol. 15(8), pages 1-13, April.
    25. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Han, Xuebing & Ouyang, Minggao, 2014. "Energy management strategies comparison for electric vehicles with hybrid energy storage system," Applied Energy, Elsevier, vol. 134(C), pages 321-331.
    26. Lin, Xinyou & Li, Yalong & Zhang, Guangji, 2022. "Bi-objective optimization strategy of energy consumption and shift shock based driving cycle-aware bias coefficients for a novel dual-motor electric vehicle," Energy, Elsevier, vol. 249(C).
    27. Qingxing Zheng & Shaopeng Tian & Qian Zhang, 2020. "Optimal Torque Split Strategy of Dual-Motor Electric Vehicle Using Adaptive Nonlinear Particle Swarm Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-21, May.
    28. Ruan, Jiageng & Walker, Paul & Zhang, Nong, 2016. "A comparative study energy consumption and costs of battery electric vehicle transmissions," Applied Energy, Elsevier, vol. 165(C), pages 119-134.
    29. Jianjun Hu & Lingling Zheng & Meixia Jia & Yi Zhang & Tao Pang, 2018. "Optimization and Model Validation of Operation Control Strategies for a Novel Dual-Motor Coupling-Propulsion Pure Electric Vehicle," Energies, MDPI, vol. 11(4), pages 1-14, March.
    30. Zhang, Kaixuan & Ruan, Jiageng & Li, Tongyang & Cui, Hanghang & Wu, Changcheng, 2023. "The effects investigation of data-driven fitting cycle and deep deterministic policy gradient algorithm on energy management strategy of dual-motor electric bus," Energy, Elsevier, vol. 269(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. Louback, Eduardo & Biswas, Atriya & Machado, Fabricio & Emadi, Ali, 2024. "A review of the design process of energy management systems for dual-motor battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    2. Yu, Xiao & Lin, Cheng & Tian, Yu & Zhao, Mingjie & Liu, Huimin & Xie, Peng & Zhang, JunZhi, 2023. "Real-time and hierarchical energy management-control framework for electric vehicles with dual-motor powertrain system," Energy, Elsevier, vol. 272(C).
    3. 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).
    4. Tian, Yang & Zhang, Yahui & Li, Hongmin & Gao, Jinwu & Swen, Austin & Wen, Guilin, 2023. "Optimal sizing and energy management of a novel dual-motor powertrain for electric vehicles," Energy, Elsevier, vol. 275(C).
    5. Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    6. Wu, Yue & Huang, Zhiwu & Liao, Hongtao & Chen, Bin & Zhang, Xiaoyong & Zhou, Yanhui & Liu, Yongjie & Li, Heng & Peng, Jun, 2020. "Adaptive power allocation using artificial potential field with compensator for hybrid energy storage systems in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
    7. Yang, Weiwei & Ruan, Jiageng & Yang, Jue & Zhang, Nong, 2020. "Investigation of integrated uninterrupted dual input transmission and hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    8. 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).
    9. Yu, Xiao & Lin, Cheng & Xie, Peng & Liang, Sheng, 2022. "A novel real-time energy management strategy based on Monte Carlo Tree Search for coupled powertrain platform via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 256(C).
    10. Wang, Hong & Huang, Yanjun & Khajepour, Amir & Song, Qiang, 2016. "Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle," Applied Energy, Elsevier, vol. 182(C), pages 105-114.
    11. Zhuang, Weichao & Ye, Jianwei & Song, Ziyou & Yin, Guodong & Li, Guangmin, 2020. "Comparison of semi-active hybrid battery system configurations for electric taxis application," Applied Energy, Elsevier, vol. 259(C).
    12. Wu, Yue & Huang, Zhiwu & Hofmann, Heath & Liu, Yongjie & Huang, Jiahao & Hu, Xiaosong & Peng, Jun & Song, Ziyou, 2022. "Hierarchical predictive control for electric vehicles with hybrid energy storage system under vehicle-following scenarios," Energy, Elsevier, vol. 251(C).
    13. Ashleigh Townsend & Rupert Gouws, 2023. "A Comparative Review of Capacity Measurement in Energy Storage Devices," Energies, MDPI, vol. 16(10), pages 1-26, May.
    14. Trovão, João P. & Silva, Mário A. & Antunes, Carlos Henggeler & Dubois, Maxime R., 2017. "Stability enhancement of the motor drive DC input voltage of an electric vehicle using on-board hybrid energy storage systems," Applied Energy, Elsevier, vol. 205(C), pages 244-259.
    15. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    16. 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.
    17. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Ruan, Haijun & Jiang, Zhihao, 2021. "Adaptive energy management of a battery-supercapacitor energy storage system for electric vehicles based on flexible perception and neural network fitting," Applied Energy, Elsevier, vol. 292(C).
    18. 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.
    19. 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).
    20. Li, Guidan & Yang, Zhe & Li, Bin & Bi, Huakun, 2019. "Power allocation smoothing strategy for hybrid energy storage system based on Markov decision process," Applied Energy, Elsevier, vol. 241(C), pages 152-163.

    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:16:y:2023:i:20:p:7048-:d:1257759. 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.