Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on the Torque Distribution for Improving the Turning Performance of a Vehicle with Torque Vectoring System

토크 벡터링 시스템이 적용된 차량의 선회 성능 향상을 위한 토크 분배에 관한 연구

  • Received : 2023.04.02
  • Accepted : 2023.08.17
  • Published : 2023.08.30
Download PDF
⟨ Previous Next ⟩

Abstract

In next-generation electric vehicles, research is being conducted on an in-wheel motor system that directly controls torque by each wheel to improve total cost and driving performance. Accordingly, in this paper, a study was conducted on an algorithm that distributes the torque applied to each wheel in a torque vectoring system applied to an in-wheel motor for driving an electric vehicle. In order to implement a vehicle model that applies actual vehicle characteristic parameters according to vehicle driving and steering, a simulation was conducted in the MATLAB Simulink environment, and it was confirmed that torque distribution was performed according to the proposed algorithm.

차세대 전기자동차에서는 전비 향상 및 주행 성능 개선을 위하여 각 휠에 의해 직접적으로 토크를 제어하는 인 휠 모터 시스템에 대한 연구가 진행되고 있다. 이에 따라 본 논문에서는 전기자동차 구동용 인 휠 모터에 적용되는 토크 벡터링 시스템에서 각 휠에 가해지는 토크를 분배하는 알고리즘에 대한 연구를 수행하였다. 차량의 주행 및 조향에 따른 실제 차량 특성 파라미터를 적용한 차량 모델을 구현하기 위해 MATLAB Simulink 환경에서 시뮬레이션을 진행하였으며 제안된 알고리즘에 따라 토크 분배가 이뤄지는 것을 확인하였다.

Keywords

Acknowledgement

This research was supported by Changwon National University in 2023~2024.

References

  1. Behrouz Najjari, Mehdi Mirzaei, Amin Tahouni, (2022), Decentralized integration of constrained active steering and torque vectoring systems to energy-efficient stability control of electric vehicles, Journal of the Franklin Institute, 8713-8741
  2. DonKyu Beak. (2020). Energy Efficient Electric Vehicle Driving Optimization Method Satisfying Driving Time Constraint. Korea Industrial Information Systems Research, 25(2), 39-47.
  3. Jamie, Hamilton. and Bryn, Walton. (2020). Electric Vehicle Market Forecast ategy for 2030, Deloitte insight, 31-52.
  4. Jinhyun Park, Jeonghun Choi, Hyeonwoo Song, Sung-Ho Hwang. (2013). Study of Driving Stability Performance of 2-Wheeled Independently Driven Vehicle Using Electric Corner Module. Transactions of the Korean Society of Mechanical Engineers, 37(7), 937-943. https://doi.org/10.3795/KSME-A.2013.37.7.937
  5. Jonathan C. Wheals (2005), Torque Vectoring Driveline: SUV-based Demonstrator and Practical Actuation Technologies, SAE Technical Paper 2005-01-0553
  6. Kanghyun, Nam. (2015). Application of Novel Lateral Tire Force Sensors to Vehicle Parameter Estimation of Electric Vehicles, Sensors (Basel), 15(11), 28385-28401. https://doi.org/10.3390/s151128385
  7. Peikun Sun, Drugge, Lars and Jerrelind, Jenny. (2020). Energy-Efficient Direct Yaw Moment Control for In-Wheel Motor Electric Vehicles Utilising Motor Efficiency Maps, Energies 2020, 13(3), 593-319.
  8. Seo, Jongsang, Yi, Kyongsu, Kang, Juyong. (2013). Development of Driving Control Algorithm for Vehicle Maneuverability Performance and Lateral Stability of 4WD Electric Vehicle, Journal of Auto-vehicle Safety Association, 5(1), 62-68.
  9. Smith, Edward., Velenis, Efstathios., Cao, Dongpu. and Tavernini, Davide. (2015). Evaluation of Optimal Yaw Rate Reference for Electric Vehicle Torque Vectoring, Proceedings of the 13th International Symposium on Advanced Vehicle C