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A Novel Torque Matching Strategy for Dual Motor-Based All-Wheel-Driving Electric Vehicles

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  • Hyeon-Woo Kim

    (Department of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea
    Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Angani Amarnathvarma

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Eugene Kim

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Myeong-Hwan Hwang

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Kyoungmin Kim

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Hyunwoo Kim

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

  • Iksu Choi

    (Department of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Hyun-Rok Cha

    (Automotive Material & Component R&D Group, Korea Institute of Industrial Technology, Gwangju 61012, Korea)

Abstract

The market for electric vehicles is growing rapidly. Among them, the demand for a dual motor type 4 WD (Four -Wheel Driving) system is increasing. In this paper, we present the Torque Matching Strategy (TMS) method to select the optimal torque distribution ratio for dual motors. The TMS controller operates to set the optimal efficiency point by linearizing the drive efficiency combination of the two motors. Driving simulation and testing were performed through five drive cycles in the driver model interworking environment implemented in MATLAB and Carsim. The optimal distribution ratio was derived according to the front and rear gear ratios under the load condition, and the driving was verified by comparing it with the TMS control method. The efficiency was numerically verified by comparing the power loss of the driving motor. It reduced up to 34% in Urban Dynamometer Driving Schedule and up to 56.3% in Highway fuel efficiency test. The effectiveness of the TMS control method was demonstrated through the distribution rate trend based on the operation cycle and power loss.

Suggested Citation

  • Hyeon-Woo Kim & Angani Amarnathvarma & Eugene Kim & Myeong-Hwan Hwang & Kyoungmin Kim & Hyunwoo Kim & Iksu Choi & Hyun-Rok Cha, 2022. "A Novel Torque Matching Strategy for Dual Motor-Based All-Wheel-Driving Electric Vehicles," Energies, MDPI, vol. 15(8), pages 1-16, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2717-:d:788784
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    References listed on IDEAS

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    1. Zarazua de Rubens, Gerardo, 2019. "Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market," Energy, Elsevier, vol. 172(C), pages 243-254.
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    Cited by:

    1. Cao, Kaibin & Hu, Minghui & Chen, Shuang & Xiao, Zongxin, 2024. "Dynamic torque coordination control of dual-motor all-wheel drive axles to suppress the longitudinal jerk of the vehicle," Energy, Elsevier, vol. 288(C).

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