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Research on Optimized Torque-Distribution Control Method for Front/Rear Axle Electric Wheel Loader

Author

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  • Zhiyu Yang
  • Jixin Wang
  • Guangzong Gao
  • Xiangyun Shi

Abstract

Optimized torque-distribution control method (OTCM) is a critical technology for front/rear axle electric wheel loader (FREWL) to improve the operation performance and energy efficiency. In the paper, a longitudinal dynamics model of FREWL is created. Based on the model, the objective functions are that the weighted sum of variance and mean of tire workload is minimal and the total motor efficiency is maximal. Four nonlinear constraint optimization algorithms, quasi-newton Lagrangian multiplier method, sequential quadratic programming, adaptive genetic algorithms, and particle swarm optimization with random weighting and natural selection, which have fast convergent rate and quick calculating speed, are used as solving solutions for objective function. The simulation results show that compared to no-control FREWL, controlled FREWL utilizes the adhesion ability better and slips less. It is obvious that controlled FREWL gains better operation performance and higher energy efficiency. The energy efficiency of FREWL in equipment transferring condition is increased by 13–29%. In addition, this paper discussed the applicability of OTCM and analyzed the reason for different simulation results of four algorithms.

Suggested Citation

  • Zhiyu Yang & Jixin Wang & Guangzong Gao & Xiangyun Shi, 2017. "Research on Optimized Torque-Distribution Control Method for Front/Rear Axle Electric Wheel Loader," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-12, September.
    • Handle: RePEc:hin:jnlmpe:7076583
    DOI: 10.1155/2017/7076583
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    Cited by:

    1. Xiaotao Fei & Yunwu Han & Shaw Voon Wong & Muhammad Amin Azman & Wenlong Shen, 2024. "Design and Testing of Innovative Type of Dual-Motor Drive Electric Wheel Loader," Energies, MDPI, vol. 17(7), pages 1-28, March.
    2. Deping Wang & Changyang Guan & Junnian Wang & Haisheng Wang & Zhenhao Zhang & Dachang Guo & Fang Yang, 2023. "Review of Energy-Saving Technologies for Electric Vehicles, from the Perspective of Driving Energy Management," Sustainability, MDPI, vol. 15(9), pages 1-17, May.

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