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Research on Loading Method of Tractor PTO Based on Dynamic Load Spectrum

Author

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  • Yu Wang

    (Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, College of Engineering, China Agricultural University (East Campus), Beijing 100083, China)

  • Ling Wang

    (Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, College of Engineering, China Agricultural University (East Campus), Beijing 100083, China)

  • Jianhua Zong

    (Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, College of Engineering, China Agricultural University (East Campus), Beijing 100083, China)

  • Dongxiao Lv

    (Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, College of Engineering, China Agricultural University (East Campus), Beijing 100083, China)

  • Shumao Wang

    (Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, College of Engineering, China Agricultural University (East Campus), Beijing 100083, China)

Abstract

The torque load spectrum is an important basis for the strength design and durability test verification of tractor power take-off (PTO), and the performance and reliability of tractor PTO directly affect the quality and efficiency of agricultural operations. In this paper, taking the PTO torque load as the object, a PTO loading method based on the dynamic load spectrum acquired in the actual field work was proposed in this paper. Based on the Peak Over Threshold model, the extrapolation of the PTO load spectrum was realized, and the load spectrum throughout the whole life cycle was obtained. On the basis of this, the mobile tractor PTO loading test bench and Fuzzy-Proportional-Integral-Derivative (Fuzzy-PID) controller were developed to achieve the dynamic loading of the PTO load spectrum, and the dynamic characteristics were analyzed and verified by the simulation and laboratory test. The results showed that with the time domain extrapolation method, the load extreme value was expanded from (63.24, 469.50) to (60.88, 475.18), and the coverage was expanded by 1.98%. By comparing with the fitting results, statistical characteristics and rain flow counting results, the load spectrum extrapolation method was effective. In addition, the response time of simulation and laboratory test were 0.05s and 0.75s, respectively; the maximum error was 1.77% and 4.03%, respectively; and the goodness of fit was 16.78 N·m, which indicated that the PTO loading test bench, can accurately restore the dynamic loading of the tractor and the Fuzzy-PID controller had better accuracy and stability. It would provide a reference for the practical application of PTO load spectrum of the tractors.

Suggested Citation

  • Yu Wang & Ling Wang & Jianhua Zong & Dongxiao Lv & Shumao Wang, 2021. "Research on Loading Method of Tractor PTO Based on Dynamic Load Spectrum," Agriculture, MDPI, vol. 11(10), pages 1-14, October.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:10:p:982-:d:652517
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    References listed on IDEAS

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    1. Markus Lips, 2017. "Length of Operational Life and Its Impact on Life-Cycle Costs of a Tractor in Switzerland," Agriculture, MDPI, vol. 7(8), pages 1-9, August.
    2. Md. Abu Ayub Siddique & Wan-Soo Kim & Yeon-Soo Kim & Taek-Jin Kim & Chang-Hyun Choi & Hyo-Jai Lee & Sun-Ok Chung & Yong-Joo Kim, 2020. "Effects of Temperatures and Viscosity of the Hydraulic Oils on the Proportional Valve for a Rice Transplanter Based on PID Control Algorithm," Agriculture, MDPI, vol. 10(3), pages 1-20, March.
    3. Ted S. Kornecki & Manuel R. Reyes, 2020. "Equipment Development for Small and Urban Conservation Farming Systems," Agriculture, MDPI, vol. 10(12), pages 1-16, December.
    4. Max Grazier G'Sell & Stefan Wager & Alexandra Chouldechova & Robert Tibshirani, 2016. "Sequential selection procedures and false discovery rate control," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 423-444, March.
    5. Md. Abu Ayub Siddique & Seung-Min Baek & Seung-Yun Baek & Wan-Soo Kim & Yeon-Soo Kim & Yong-Joo Kim & Dae-Hyun Lee & Kwan-Ho Lee & Joon-Yeal Hwang, 2021. "Simulation of Fuel Consumption Based on Engine Load Level of a 95 kW Partial Power-Shift Transmission Tractor," Agriculture, MDPI, vol. 11(3), pages 1-17, March.
    6. Volodymyr Bulgakov & Aivars Aboltins & Hristo Beloev & Volodymyr Nadykto & Volodymyr Kyurchev & Valerii Adamchuk & Viktor Kaminskiy, 2021. "Experimental Investigation of Plow-Chopping Unit," Agriculture, MDPI, vol. 11(1), pages 1-14, January.
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    Cited by:

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    2. Dong Dai & Du Chen & Shumao Wang & Song Li & Xu Mao & Bin Zhang & Zhenyu Wang & Zheng Ma, 2023. "Compilation and Extrapolation of Load Spectrum of Tractor Ground Vibration Load Based on CEEMDAN-POT Model," Agriculture, MDPI, vol. 13(1), pages 1-20, January.
    3. Yao Yu & Shuaihua Hao & Songbao Guo & Zhong Tang & Shuren Chen, 2022. "Motor Torque Distribution Strategy for Different Tillage Modes of Agricultural Electric Tractors," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
    4. Meng Yang & Xiaoxu Sun & Xiaoting Deng & Zhixiong Lu & Tao Wang, 2023. "Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-20, May.

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