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Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle

Author

Listed:
  • Yang, Jian
  • Zhang, Tiezhu
  • Hong, Jichao
  • Zhang, Hongxin
  • Zhao, Qinghai
  • Meng, Zewen

Abstract

To reduce large peak torque and improve the vehicle's dynamic performance during frequent stops and starts, a novel mechatronics-electro-hydraulic power coupling system (MEH-PCS) is proposed. It combines a conventional electric motor and a piston pump/motor into a single unit that converts electrical, mechanical, and hydraulic energy. After a theoretical analysis of the system power flow, the paper establishes a rule-based dynamic optimal energy management strategy to control energy distribution and the dynamic switching of working modes in real-time. Moreover, a prototype vehicle model (MEH-PCEV) based on the MEH-PCS is developed by analyzing the working modes of the system. Thereafter, the feasibility and superiority of MEH-PCEV are verified by comparing it with AMESim certified pure electric vehicles. The verification results indicate that the MEH-PCEV's battery consumption rate is reduced by 14.418% and 21.174%, respectively, in the new European driving cycle and the American city cycle. Furthermore, the time for the vehicle to reach the start-up speed threshold is enhanced, and the electric peak torque is substantially reduced. Ultimately, the paper proposes a fuzzy controller with vehicle speed and pressure of the accumulator as variables to optimize the logic threshold control strategy. The electric torque is substantially reduced while the overall efficiency of the motor operating point is enhanced. The consumption rate of electric energy has been improved somewhat. Under the drive strategy's control, the MEH-PCS is well suited for frequent stops and starts conditions. As a development, this research is expected to provide a reference for improving electric torque.

Suggested Citation

  • Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:energy:v:233:y:2021:i:c:s0360544221014699
    DOI: 10.1016/j.energy.2021.121221
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    References listed on IDEAS

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    Cited by:

    1. Yu, Xiao & Lin, Cheng & Xie, Peng & Liang, Sheng, 2022. "A novel real-time energy management strategy based on Monte Carlo Tree Search for coupled powertrain platform via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 256(C).
    2. Hong, Jichao & Zhang, Tiezhu & Zhang, Zhen & Zhang, Hongxin, 2023. "Investigation of energy management strategy for a novel electric-hydraulic hybrid vehicle: Self-adaptive electric-hydraulic ratio," Energy, Elsevier, vol. 278(C).
    3. Li, Lin & Zhang, Tiezhu & Sun, Binbin & Wu, Kaiwei & Sun, Zehao & Zhang, Zhen & Lin, Lianhua & Xu, Haigang, 2023. "Research on electro-hydraulic ratios for a novel mechanical-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 270(C).
    4. Zhao, Chengxuan & Yang, Xiao & Yu, Jie & Yang, Minghan & Wang, Jianye & Chen, Shuai, 2023. "Interval type-2 fuzzy logic control for a space nuclear reactor core power system," Energy, Elsevier, vol. 280(C).
    5. Grzegorz Filo, 2023. "A Review of Fuzzy Logic Method Development in Hydraulic and Pneumatic Systems," Energies, MDPI, vol. 16(22), pages 1-19, November.
    6. Xinming Xu & Yang Gu & Guangjun Liu, 2022. "Study on a Wheel Electric Drive System with SRD for Loader," Energies, MDPI, vol. 15(10), pages 1-16, May.
    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. Lin Li & Tiezhu Zhang & Kaiwei Wu & Liqun Lu & Lianhua Lin & Haigang Xu, 2022. "Design and Research on Electro-Hydraulic Drive and Energy Recovery System of the Electric Excavator Boom," Energies, MDPI, vol. 15(13), pages 1-17, June.
    9. Grzegorz Filo, 2023. "Artificial Intelligence Methods in Hydraulic System Design," Energies, MDPI, vol. 16(8), pages 1-19, April.

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