IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v337y2025ics0360544225042586.html

Optimization of multi-motor and multi-speed powertrain system for electric vehicles based on efficiency characteristics between motor and inverter

Author

Listed:
  • Lee, Jung-Hwan
  • Lim, Sang-Kil
  • Kwon, Kihan

Abstract

Multi-motor, multi-speed powertrain systems for electric vehicles (EVs) provide superior EV efficiency and performance. The electric efficiency, determined by motor and inverter losses, directly relates to EV efficiency. This study proposes a process for efficiency characteristic analysis between the motor and inverter to analyze the integrated efficiency of the motor and inverter. The results of the motor parameter effects on the motor and inverter efficiencies showed the need to consider both efficiency characteristics to improve EV efficiency. To optimize the EV powertrain system, a multi-objective optimization problem was formulated using design variables of the motor and transmission, such as the stack length, coil turns, motor torque distribution, and gear ratios, to improve both energy efficiency and dynamic performance. To address the computational burden during optimization, an artificial neural network (ANN)-based optimization method was introduced. Optimization was conducted for two cases, considering (i) motor efficiency only and (ii) integrated efficiency, to confirm the importance of including both motor and inverter efficiencies in the optimization of EV powertrain systems. Comparison of EV efficiency and performance results for both cases demonstrated the superiority of the optimal solutions based on the integrated efficiency case. Additionally, a comparison of the calculation times between the EV simulation and ANN prediction models demonstrated the practicality of the ANN-based multi-objective optimization for EV powertrain systems.

Suggested Citation

  • Lee, Jung-Hwan & Lim, Sang-Kil & Kwon, Kihan, 2025. "Optimization of multi-motor and multi-speed powertrain system for electric vehicles based on efficiency characteristics between motor and inverter," Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225042586
    DOI: 10.1016/j.energy.2025.138616
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225042586
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.138616?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

    for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    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. 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).
    4. Jiajia Liang & Xiangyang Xu & Peng Dong & Tao Feng & Wei Guo & Shuhan Wang, 2022. "Energy Management Strategy of a Novel Electric Dual-Motor Transmission for Heavy Commercial Vehicles Based on APSO Algorithm," Sustainability, MDPI, vol. 14(3), pages 1-12, January.
    5. Sun, Zhicheng & Hu, Jianjun & Yao, Zutang & Xue, Shouzhi, 2024. "Optimization of electromagnetic vibration for integrated electric drive systems based on electric vehicle driving cycle considering energy consumption," Energy, Elsevier, vol. 313(C).
    6. 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).
    7. Kwon, Kihan & Jo, Junhyeong & Min, Seungjae, 2021. "Multi-objective gear ratio and shifting pattern optimization of multi-speed transmissions for electric vehicles considering variable transmission efficiency," Energy, Elsevier, vol. 236(C).
    8. Došljak, Velibor & Ćorović, Velimir & Mihailovic, Andrej, 2025. "A two-layer optimization model for electric vehicle charging station distribution using a custom genetic algorithm: Application to Montenegro," Energy, Elsevier, vol. 330(C).
    9. Gao, Ye & Feng, Lei & Liu, Ding & Li, Zhiwu, 2025. "Multi-objective co-optimization of powertrain sizing, energy management, and eco-driving for the architectural design of electric vehicles," Applied Energy, Elsevier, vol. 398(C).
    10. Chen, Yong & Liu, Chunhua, 2025. "Energy efficient optimization for multi-motor system with novel inverter topology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
    11. He, Hongwen & Han, Mo & Liu, Wei & Cao, Jianfei & Shi, Man & Zhou, Nana, 2022. "MPC-based longitudinal control strategy considering energy consumption for a dual-motor electric vehicle," Energy, Elsevier, vol. 253(C).
    12. Zhao, Mingjie & Shi, Junhui & Lin, Cheng, 2019. "Optimization of integrated energy management for a dual-motor coaxial coupling propulsion electric city bus," Applied Energy, Elsevier, vol. 243(C), pages 21-34.
    13. Kwon, Kihan & Lee, Jung-Hwan & Lim, Sang-Kil, 2023. "Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis," Applied Energy, Elsevier, vol. 342(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. Tian, Yang & Zhao, Yin & Wang, Zhong & Zhang, Yahui & Miao, Yusen & Zhang, Lipeng & Wen, Guilin & Zhang, Nong, 2024. "Non-dominated sorting artificial rabbit multi-objective sizing optimization for a conceptual powertrain of a 6 × 4 battery electric tractor truck," Energy, Elsevier, vol. 304(C).
    3. 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.
    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. Wang, Shaohua & Zhang, Kaimei & Shi, Dehua & Li, Meng & Yin, Chunfang, 2024. "Research on economical shifting strategy for multi-gear and multi-mode parallel plug-in HEV based on DIRECT algorithm," Energy, Elsevier, vol. 286(C).
    6. 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).
    7. Guo, Jun & Wu, Jinglai & Zhang, Yunqing & Peng, Yayun, 2025. "Driving mode shift strategy for an electric heavy truck to minimize the energy consumption and shift frequency," Energy, Elsevier, vol. 319(C).
    8. Jin, Rui & Li, Lei & Liang, Xiaoling & Zou, Xiang & Yang, Zeyuan & Ge, Shuzhi Sam & Huang, Haihong, 2024. "Energy-efficient design of the powertrain for mechanical-electro-hydraulic equipment via configuring multidimensional controllable variables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    9. 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).
    10. Kwon, Kihan & Lee, Jung-Hwan & Lim, Sang-Kil, 2023. "Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis," Applied Energy, Elsevier, vol. 342(C).
    11. Md Ragib Ahssan & Mehran Ektesabi & Saman Gorji, 2023. "Evaluation of a Three-Parameter Gearshift Strategy for a Two-Speed Transmission System in Electric Vehicles," Energies, MDPI, vol. 16(5), pages 1-28, March.
    12. He, Hongwen & Han, Mo & Liu, Wei & Cao, Jianfei & Shi, Man & Zhou, Nana, 2022. "MPC-based longitudinal control strategy considering energy consumption for a dual-motor electric vehicle," Energy, Elsevier, vol. 253(C).
    13. Zhou, Xingyu & Guo, Yuekai & Huang, Youliang & Zhao, Nianhan, 2025. "Driving cycle reproduction supported deep learning co-optimization of freight EV powertrains in stochastic operation environments," Energy, Elsevier, vol. 340(C).
    14. 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).
    15. Gao, Bingzhao & Meng, Dele & Shi, Wentong & Cai, Wenqi & Dong, Shiying & Zhang, Yuanjian & Chen, Hong, 2022. "Topology optimization and the evolution trends of two-speed transmission of EVs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    16. 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).
    17. Tian, Yang & Miao, Yusen & Ji, Xiaoyu & Dong, Peng & Zhang, Yahui, 2025. "Crucial parameters design and control for a novel dual-motor powertrain in electric vehicles," Applied Energy, Elsevier, vol. 402(PA).
    18. Zhou, Xingyu & Sun, Chao & Sun, Fengchun & Zhang, Chuntao, 2023. "Commuting-pattern-oriented stochastic optimization of electric powertrains for revealing contributions of topology modifications to the powertrain energy efficiency," Applied Energy, Elsevier, vol. 344(C).
    19. Gobbi, Massimiliano & Sattar, Aqeab & Palazzetti, Roberto & Mastinu, Gianpiero, 2024. "Traction motors for electric vehicles: Maximization of mechanical efficiency – A review," Applied Energy, Elsevier, vol. 357(C).
    20. Peng Wu & Penghui Qiang & Tao Pan & Huaiquan Zang, 2022. "Multi-Objective Optimization of Gear Ratios of a Seamless Three-Speed Automated Manual Transmission for Electric Vehicles Considering Shift Performance," Energies, MDPI, vol. 15(11), pages 1-27, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:337:y:2025:i:c:s0360544225042586. 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.journals.elsevier.com/energy .

    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.