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Energy-saving drive control strategy for electric tractors based on terrain parameter identification

Author

Listed:
  • Luo, Zhen-hao
  • Xie, Bin
  • Tong, Yi-kun
  • Zhao, Zi-hao
  • Zheng, Bo-wen
  • Chen, Zhou-yang
  • Wen, Chang-kai

Abstract

Emissions from agricultural production already have a significant impact on the global environment. New energy, zero-emission electric tractors have great potential for application. How to further reduce energy consumption under the premise of ensuring operational stability is an urgent problem to be solved to realize the broad application of electric tractors. For this purpose, this paper proposed an energy-saving drive control strategy for electric tractors based on terrain parameter identification. At first, the longitudinal dynamics model and load transfer model of the electric tractor were established by considering the terrain information of the area to be operated. Mathematical principles for adjusting wheel slip to reduce energy consumption in electric tractors are presented. Then, a wheel longitudinal force estimation algorithm was designed based on the principle of sliding-mode observer and dynamics compensation. To achieve energy-saving drives for electric tractors, a particle filter based on a wheel-soil model was designed to identify terrain parameters in real time and calculate the optimal slip to control the torque of the drive motor. Lastly, the strategy is validated by hardware-in-the-loop (HIL) simulation tests and real-vehicle tests. HIL tests show that this strategy results in a 25.35% increase in operational speed stability and a 6.79% reduction in operational energy consumption compared to the conventional drive control strategy. The real vehicle test shows a 45.09% increase in operating speed stability and a 9.51% reduction in total energy consumption of the proposed method. The proposed drive control strategy reduces operational energy consumption and operational costs on the premise of ensuring the stability of operational speed, which is conducive to the implementation of cleaner production.

Suggested Citation

  • Luo, Zhen-hao & Xie, Bin & Tong, Yi-kun & Zhao, Zi-hao & Zheng, Bo-wen & Chen, Zhou-yang & Wen, Chang-kai, 2024. "Energy-saving drive control strategy for electric tractors based on terrain parameter identification," Applied Energy, Elsevier, vol. 376(PA).
    • Handle: RePEc:eee:appene:v:376:y:2024:i:pa:s0306261924016131
    DOI: 10.1016/j.apenergy.2024.124230
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    References listed on IDEAS

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    1. Zhang, Sheng-li & Wen, Chang-kai & Ren, Wen & Luo, Zhen-hao & Xie, Bin & Zhu, Zhong-xiang & Chen, Zhong-ju, 2023. "A joint control method considering travel speed and slip for reducing energy consumption of rear wheel independent drive electric tractor in ploughing," Energy, Elsevier, vol. 263(PD).
    2. Janulevičius, Algirdas & Damanauskas, Vidas, 2015. "How to select air pressures in the tires of MFWD (mechanical front-wheel drive) tractor to minimize fuel consumption for the case of reasonable wheel slip," Energy, Elsevier, vol. 90(P1), pages 691-700.
    3. Zhenhao Luo & Jihang Wang & Jing Wu & Shengli Zhang & Zhongju Chen & Bin Xie, 2023. "Research on a Hydraulic Cylinder Pressure Control Method for Efficient Traction Operation in Electro-Hydraulic Hitch System of Electric Tractors," Agriculture, MDPI, vol. 13(8), pages 1-18, August.
    4. Taghavifar, Hamid & Mardani, Aref, 2014. "Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices," Energy, Elsevier, vol. 68(C), pages 651-657.
    Full references (including those not matched with items on IDEAS)

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