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Low energy consumption traction control for centralized and distributed dual-mode coupling drive electric vehicle on split ramps

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  • Lipeng, Zhang
  • Xin, Liu
  • Shuaishuai, Liu
  • Haoran, Guo
  • Kaixin, Shi

Abstract

Distributed drive electric vehicle has good pass ability on split ramps, but it has high power demand for driving motors, resulting in low driving efficiency and limited economy. To address the aforementioned deficiencies, a centralized and distributed dual-mode coupling drive system (DMC) capable of drive force transfer between coaxial wheels is designed to avoid single-side wheel high-intensity driving and reduce vehicle energy consumption. To guarantee the longitudinal dynamics performance, a traction control based on online sliding mode extremum search (SES) was proposed, and the traction control based on the ρ_SES algorithm as a means to suppress the controller damage caused by the steady-state oscillation has also been adopted. The simulation and experiment results show that the dual-mode coupling drive electric vehicle significantly reduces the energy consumption and reduces the power demands of the drive motor than those of the distributed drive electric vehicle. Apparently, the ρ_SES algorithm based traction control suppresses the steady-state oscillations of the SES, which can protect the motor controller. This study lays the theoretical foundation for the use of DMC and achieving superior traction control for electric vehicles.

Suggested Citation

  • Lipeng, Zhang & Xin, Liu & Shuaishuai, Liu & Haoran, Guo & Kaixin, Shi, 2024. "Low energy consumption traction control for centralized and distributed dual-mode coupling drive electric vehicle on split ramps," Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:energy:v:289:y:2024:i:c:s0360544223032723
    DOI: 10.1016/j.energy.2023.129878
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    References listed on IDEAS

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    1. Tang, Qingsong & Yang, Yang & Luo, Chang & Yang, Zhong & Fu, Chunyun, 2022. "A novel electro-hydraulic compound braking system coordinated control strategy for a four-wheel-drive pure electric vehicle driven by dual motors," Energy, Elsevier, vol. 241(C).
    2. Wen, Chang-kai & Zhang, Sheng-li & Xie, Bin & Song, Zheng-he & Li, Tong-hui & Jia, Fang & Han, Jian-gang, 2022. "Design and verification innovative approach of dual-motor power coupling drive systems for electric tractors," Energy, Elsevier, vol. 247(C).
    3. 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).
    4. Zhang, LiPeng & Liu, Wei & Qi, BingNan, 2020. "Energy optimization of multi-mode coupling drive plug-in hybrid electric vehicles based on speed prediction," Energy, Elsevier, vol. 206(C).
    5. Desreveaux, A. & Bouscayrol, A. & Trigui, R. & Hittinger, E. & Castex, E. & Sirbu, G.M., 2023. "Accurate energy consumption for comparison of climate change impact of thermal and electric vehicles," Energy, Elsevier, vol. 268(C).
    6. Deng, Huifan & Zhao, Youqun & Feng, Shilin & Wang, Qiuwei & Zhang, Chenxi & Lin, Fen, 2021. "Torque vectoring algorithm based on mechanical elastic electric wheels with consideration of the stability and economy," Energy, Elsevier, vol. 219(C).
    7. Zhang, Sheng-li & Wen, Chang-kai & Ren, Wen & Luo, Zhen-hao & Xie, Bin & Zhu, Zhong-xiang & Chen, Zhong-ju, 2023. "A joint control method considering travel speed and slip for reducing energy consumption of rear wheel independent drive electric tractor in ploughing," Energy, Elsevier, vol. 263(PD).
    8. Guo, Lingxiong & Liu, Hui & Han, Lijin & Yang, Ningkang & Liu, Rui & Xiang, Changle, 2023. "Predictive energy management strategy of dual-mode hybrid electric vehicles combining dynamic coordination control and simultaneous power distribution," Energy, Elsevier, vol. 263(PA).
    9. Zhang, Junjiang & Yang, Yang & Hu, Minghui & Yang, Zhong & Fu, Chunyun, 2021. "Longitudinal–vertical comprehensive control for four-wheel drive pure electric vehicle considering energy recovery and ride comfort," Energy, Elsevier, vol. 236(C).
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