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Active Control and Validation of the Electric Vehicle Powertrain System Using the Vehicle Cluster Environment

Author

Listed:
  • Ming Ye

    (Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China)

  • Yitao Long

    (Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China)

  • Yi Sui

    (College of Mechanical and Power Eengineering, Chongqing University of Science and Technology, Chongqing 401331, China)

  • Yonggang Liu

    (State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China)

  • Qiao Li

    (Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China)

Abstract

With the development of intelligent vehicle technologies, vehicles can obtain more and more information from various sensors. Many researchers have focused on the vertical and horizontal relationships between vehicles in a vehicle cluster environment and control of the vehicle power system. When the vehicle is driving in the cluster environment, the powertrain system should quickly respond to the driver’s dynamic demand, so as to achieve the purpose of quickly passing through the cluster environment. The vehicle powertrain system should be regarded as a separate individual to research its active control strategy in a vehicle cluster environment to improve the control effect. In this study, the driving characteristics of vehicles in a cluster environment have been analyzed, and a vehicle power-demanded prediction algorithm based on a vehicle-following model has been proposed in a cluster environment. Based on the vehicle power demand forecast and driver operation, an active control strategy of the vehicle powertrain system has been designed considering the passive control strategy of the powertrain system. The results show that the vehicle powertrain system can ensure a sufficient backup power with the active control proposed in the paper, and the motor efficiency is improved by 0.61% compared with that of the passive control strategy. Moreover, the overall efficiency of the powertrain system is increased by 0.6% and the effectiveness of the active control is validated using the vehicle cluster environment.

Suggested Citation

  • Ming Ye & Yitao Long & Yi Sui & Yonggang Liu & Qiao Li, 2019. "Active Control and Validation of the Electric Vehicle Powertrain System Using the Vehicle Cluster Environment," Energies, MDPI, vol. 12(19), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3642-:d:270194
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    References listed on IDEAS

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    2. Jin, Sheng & Wang, Dianhai & Tao, Pengfei & Li, Pingfan, 2010. "Non-lane-based full velocity difference car following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4654-4662.
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    4. Laura Tribioli, 2017. "Energy-Based Design of Powertrain for a Re-Engineered Post-Transmission Hybrid Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-22, July.
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