吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1176-1183.doi: 10.13229/j.cnki.jdxbgxb20170751

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Static rollover stability of semi-mounted agricultural machinery based on ADAMS

CHEN Dong-hui1,2, LYU Jian-hua1,2, LONG Gang1,2, ZHANG Yu-chen1,2, CHANG Zhi-yong1,2   

  1. 1.College of Biological and Agricultural Engineering, Jilin University, Changchun 130022,China;
    2.Key Laboratory of Bionic Engineering, Ministry of Education, Changchun 130022,China
  • Received:2017-07-15 Online:2018-07-01 Published:2018-07-01
  • Supported by:
     

Abstract: To overcome the current deficiency in studying the Rollover Stability (RS) of Semi-mounted Agricultural Machine Unit (SMAMU, including a tractor and semi-mounted machine), a new method to characterize the RS of SMAMU is proposed. The Lateral Load Transfer Ratio (LLTR) is chosen as the evaluation indicator of RS, the rollover mathematical model is established and quasi static simulation is carried out. Through ADAMS dynamic modeling, the simulation results are in good agreement with the mathematical model, which verifies the correctness of the theoretical model. The effects of the parameters of SMAMU on the RS are discussed and the sensitivity of the influencing factors is analyzed. The LLTR is correlated to the height of center of gravity, the wheel-base of the tractor, the weight of the SMAMU, the wheel-center-distance, the distance from the center of gravity to the tow point and the height of tow point. The results show that the height of the center of gravity and the wheel-base of both the tractor and the semi-mounted machine are the important factors affecting the RS. Besides reducing the height of center of gravity or increasing the wheel-base, reducing the height of the tow point or increasing the distance from the center of gravity to the tow point can also improve RS. This work may provide reference for the optimal design of SMAMU.

Key words: agricultural engineering, agricultural semi-mounted unit, statically lateral roll stability, lateral load transfer ratio (LTR), mathematical model, sensitivity analysis

CLC Number: 

  • S220.1
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