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Design and Optimization of Power Shift Tractor Starting Control Strategy Based on PSO-ELM Algorithm

Author

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  • Yu Qian

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Lin Wang

    (State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 470139, China)

  • Zhixiong Lu

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

Abstract

Power shift tractors have been widely used in agricultural tractors in recent years because of their advantages of uninterrupted power during shifting, high transmission efficiency and high stability. As one of the indispensable driving states of the power shift tractor, the starting process requires a small impact and a starting speed that meets the driver’s requirements. In this paper, aiming at such contradictory requirements, the starting control strategy of a power shift tractor is formulated with the goal of starting quality and the driver’s intention. Firstly, the identification characteristics of the driver under three starting intentions are obtained by a real vehicle test. An extreme learning machine with fast identification speed and short training time is used to establish the basic driver’s intention identification model. For the instability of the identification results of the Extreme Learning Machine (ELM), the particle swarm optimization algorithm (PSO) is used to optimize the ELM. The optimized extreme learning machine model has an accuracy of 96.891% for driver’s intention identification. The wet clutch is an important part of the power shift gearbox. In this paper, the starting control strategy knowledge base of the starting clutch is established by a combination of bench tests and simulation tests. Through the fuzzy algorithm, the driver’s intention is combined with the starting control strategy. Different drivers’ intentions will affect the comprehensive evaluation model of the clutch (the single evaluation index of the clutch is: the maximum sliding power, the sliding power, the speed stability time, the impact degree), thus affecting the final choice of the starting clutch control strategy considering the driver’s intention. On this basis, this paper studies and establishes the MPC starting controller for the power shift gearbox. Compared with the linear control strategy, the PSO-ELM-fuzzy weight starting strategy proposed in this paper can reduce the maximum sliding friction power by 45%, the sliding friction power by 69.45%, and the speed stabilization time by 0.11 s. The effectiveness of the starting control strategy considering the driver’s intention proposed in this paper to improve the starting quality of the power shift tractor is verified.

Suggested Citation

  • Yu Qian & Lin Wang & Zhixiong Lu, 2024. "Design and Optimization of Power Shift Tractor Starting Control Strategy Based on PSO-ELM Algorithm," Agriculture, MDPI, vol. 14(5), pages 1-21, May.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:5:p:747-:d:1392182
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    References listed on IDEAS

    as
    1. Zhou, Xingyu & Qin, Datong & Hu, Jianjun, 2017. "Multi-objective optimization design and performance evaluation for plug-in hybrid electric vehicle powertrains," Applied Energy, Elsevier, vol. 208(C), pages 1608-1625.
    2. Cheng, Zhun, 2023. "High nonlinearity of BEV's stepped automatic transmission design objectives and its optimal solution by a novel ISA-RSA," Energy, Elsevier, vol. 282(C).
    3. Zhang, Junjiang & Feng, Ganghui & Yan, Xianghai & He, Yundong & Liu, Mengnan & Xu, Liyou, 2024. "Cooperative control method considering efficiency and tracking performance for unmanned hybrid tractor based on rotary tillage prediction," Energy, Elsevier, vol. 288(C).
    Full references (including those not matched with items on IDEAS)

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