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Study on low-frequency torsional vibration suppression of integrated electric drive system considering nonlinear factors

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  • Hu, Jianjun
  • Guo, Qi
  • Sun, Zhicheng
  • Yang, Dianzhao

Abstract

The integrated electric drive system (IEDS) is widely used in battery electric vehicles due to its advantages of high power density, small size, and low cost. However, on account of the electromechanical coupling between its subsystems, the problem of high torsional vibration is brought about. Therefore, based on the establishment of the electromechanical coupling model of IEDS and the analysis of the influence of time-varying mesh stiffness and backlash on the system characteristics, this paper proposes a double-layer optimization control strategy of IEDS torsional vibration basis of the torque command optimization and the principle of minimum error of instantaneous current tracking. By adjusting the motor torque command in real-time and reducing the error between the actual current and the target current, the oscillation amplitude of IEDS under Tip in/out condition is reduced by 63.7%, and the time required to achieve stability is shortened by 79.04% and 76.90% respectively. The simulation results show that the proposed control strategy greatly reduces the torsional vibration of IEDS and improves the comfort of the vehicle.

Suggested Citation

  • Hu, Jianjun & Guo, Qi & Sun, Zhicheng & Yang, Dianzhao, 2023. "Study on low-frequency torsional vibration suppression of integrated electric drive system considering nonlinear factors," Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s0360544223026452
    DOI: 10.1016/j.energy.2023.129251
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    References listed on IDEAS

    as
    1. Zhang, LiPeng & Liu, Wei & Qi, Bingnan, 2019. "Innovation design and optimization management of a new drive system for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 186(C).
    2. Tang, Xiaolin & Zhang, Dejiu & Liu, Teng & Khajepour, Amir & Yu, Haisheng & Wang, Hong, 2019. "Research on the energy control of a dual-motor hybrid vehicle during engine start-stop process," Energy, Elsevier, vol. 166(C), pages 1181-1193.
    3. Yang, Yang & He, Qiang & Fu, Chunyun & Liao, Shuiping & Tan, Peng, 2020. "Efficiency improvement of permanent magnet synchronous motor for electric vehicles," Energy, Elsevier, vol. 213(C).
    4. Hu, Jianjun & Deng, Chenghao & Yang, Dianzhao & Yang, Ying & Jia, Meixia, 2022. "Optimal energy consumption and torque fluctuation control of integrated electric drive system based on mechanical-electromagnetic-thermal coupling characteristics," Energy, Elsevier, vol. 247(C).
    5. Mesloub, H. & Boumaaraf, R. & Benchouia, M.T. & Goléa, A. & Goléa, N. & Srairi, K., 2020. "Comparative study of conventional DTC and DTC_SVM based control of PMSM motor — Simulation and experimental results," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 167(C), pages 296-307.
    6. Liu, Qin & Zhang, Wencan & Zhang, Zhongbo & Qin, Qichao, 2022. "A drive system global control strategy for electric vehicle based on optimized acceleration curve," Energy, Elsevier, vol. 248(C).
    7. Yang, Jian & Liu, Bo & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin, 2023. "Multi-parameter controlled mechatronics-electro-hydraulic power coupling electric vehicle based on active energy regulation," Energy, Elsevier, vol. 263(PC).
    8. Bouguenna, Ibrahim Farouk & Azaiz, Ahmed & Tahour, Ahmed & Larbaoui, Ahmed, 2019. "Robust neuro-fuzzy sliding mode control with extended state observer for an electric drive system," Energy, Elsevier, vol. 169(C), pages 1054-1063.
    Full references (including those not matched with items on IDEAS)

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