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Research on TVD Control of Cornering Energy Consumption for Distributed Drive Electric Vehicles Based on PMP

Author

Listed:
  • Wen Sun

    (College of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213001, China
    School of Mechanical and Aerospace Engineering, Queen’s University Belfast, Belfast BT7 1NN, UK)

  • Yang Chen

    (College of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213001, China)

  • Junnian Wang

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Xiangyu Wang

    (College of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213001, China)

  • Lili Liu

    (College of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213001, China)

Abstract

This paper aims to study the torque optimization control of distributed drive electric vehicles in the cornering process and reduce the cornering energy consumption. The main energy consumption of the vehicle in the cornering process is analyzed clearly based on the 7-DOF vehicle dynamics model. The torque vectoring distribution (TVD) of a distributed drive electric vehicle in the process of turning was studied on the basis of the Pontryagin Minimum Principle (PMP). The Beetle Antenna Search–Particle Swarm Optimization (BAS-PSO) algorithm was used to optimize the torque distribution coefficient offline, and the algorithm was improved to improve the operation speed. Based on the vehicle dynamics characteristics, the table of torque distribution coefficient of minimum turning energy consumption and the optimal energy-saving degree of TVD control in different bending conditions were worked out.

Suggested Citation

  • Wen Sun & Yang Chen & Junnian Wang & Xiangyu Wang & Lili Liu, 2022. "Research on TVD Control of Cornering Energy Consumption for Distributed Drive Electric Vehicles Based on PMP," Energies, MDPI, vol. 15(7), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2641-:d:786791
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    References listed on IDEAS

    as
    1. Xiaogang Wu & Dianyu Zheng & Tianze Wang & Jiuyu Du, 2019. "Torque Optimal Allocation Strategy of All-Wheel Drive Electric Vehicle Based on Difference of Efficiency Characteristics between Axis Motors," Energies, MDPI, vol. 12(6), pages 1-16, March.
    2. Qinghua Meng & Tingting Zhao & Chunjiang Qian & Zong-yao Sun & Panpan Ge, 2018. "Integrated stability control of AFS and DYC for electric vehicle based on non-smooth control," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(7), pages 1518-1528, May.
    3. Sara Salamone & Basilio Lenzo & Giovanni Lutzemberger & Francesco Bucchi & Luca Sani, 2021. "On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model," Sustainability, MDPI, vol. 13(8), pages 1-20, April.
    4. Wen Sun & Juncai Rong & Junnian Wang & Wentong Zhang & Zidong Zhou, 2021. "Research on Optimal Torque Control of Turning Energy Consumption for EVs with Motorized Wheels," Energies, MDPI, vol. 14(21), pages 1-15, October.
    5. Mohammed Kharrich & Salah Kamel & Mohamed H. Hassan & Salah K. ElSayed & Ibrahim B. M. Taha, 2021. "An Improved Heap-Based Optimizer for Optimal Design of a Hybrid Microgrid Considering Reliability and Availability Constraints," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
    6. Xudong Zhang & Dietmar Göhlich, 2017. "Integrated Traction Control Strategy for Distributed Drive Electric Vehicles with Improvement of Economy and Longitudinal Driving Stability," Energies, MDPI, vol. 10(1), pages 1-18, January.
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