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Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

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  • Huiyuan Xiong
  • Xionglai Zhu
  • Ronghui Zhang

Abstract

Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.

Suggested Citation

  • Huiyuan Xiong & Xionglai Zhu & Ronghui Zhang, 2018. "Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation," Complexity, Hindawi, vol. 2018, pages 1-14, August.
    • Handle: RePEc:hin:complx:4071743
    DOI: 10.1155/2018/4071743
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    1. B Yu & Z-Z Yang & J-X Xie, 2011. "A parallel improved ant colony optimization for multi-depot vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 183-188, January.
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    1. 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).
    2. 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).
    3. Huiyuan Xiong & Huan Liu & Jian Ma & Yuelong Pan & Ronghui Zhang, 2021. "An NN-Based Double Parallel Longitudinal and Lateral Driving Strategy for Self-Driving Transport Vehicles in Structured Road Scenarios," Sustainability, MDPI, vol. 13(8), pages 1-16, April.
    4. Hong, Jichao & Wang, Zhenpo & Zhang, Tiezhu & Yin, Huaixian & Zhang, Hongxin & Huo, Wei & Zhang, Yi & Li, Yuanyuan, 2019. "Research on integration simulation and balance control of a novel load isolated pure electric driving system," Energy, Elsevier, vol. 189(C).
    5. Guang Chen & Tonghai Jiang & Meng Wang & Xinyu Tang & Wenfei Ji, 2020. "Design and model checking of timed automata oriented architecture for Internet of thing," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
    6. Yang Yang & Qiang He & Yongzheng Chen & Chunyun Fu, 2020. "Efficiency Optimization and Control Strategy of Regenerative Braking System with Dual Motor," Energies, MDPI, vol. 13(3), pages 1-21, February.
    7. Ying Lyu & Xuenan Sun & Hong Chu & Bingzhao Gao, 2020. "Improvement of Battery Life and Energy Economy for Electric Vehicles with Two-Speed Transmission," Energies, MDPI, vol. 13(13), pages 1-20, July.
    8. Jie Hu & Wentong Cao & Feng Jiang & Lingling Hu & Qian Chen & Weiguang Zheng & Junming Zhou, 2023. "Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    9. Yang, Lu & Xie, Pengli & Bi, Chongke & Zhang, Ronghui & Cai, Bowen & Shao, Xiaowei & Wang, Rongben, 2020. "Household power consumption pattern modeling through a single power sensor," Renewable Energy, Elsevier, vol. 155(C), pages 121-133.

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