Development and validation of sloped ground pressure prediction model for a tracked tractor in hilly and mountainous environments

Abstract

Tracked tractors are better suited for agricultural production in hilly environments because of their excellent stability and flotation. The ground pressure in these environments is highly irregular owing to the ground slope, which has led to a lack of theoretical foundation and data support for the development of hillside tracked tractors (HTTs). Therefore, accurate prediction of the ground pressure at the track-soil interface on inclined terrain is important. In this study, sloped ground pressure prediction model composed of sloped terrain soil pressure-sinkage model was developed to analyse the distribution characteristics of the ground pressure of tracked tractors in agricultural operations on hillside slopes. Considering the influence of the slope angle, soil conditions, operating conditions, and important parameters of the tracked tractors (including mass, centre of gravity, and track gauge), the ground pressure prediction model used harmonic oscillator functions and peak-valley control primitive functions. To validate the proposed model, ground pressure tests of the experimental tracked tractor were conducted at different slope angles and operating conditions in an experimental platform integrating a "soil-machine-crop" system. The results showed that the maximum error between the predicted results and the test data under various slopes and operating conditions was approximately 6.3%, with an average error of approximately 4.7%; the consistency between the test results and the simulated results indicate that the model established in this study is accurate and credible. Based on the ground pressure model, the developed tractive performance prediction model for HTTs had high prediction accuracy for the slip rate and traction force in the climbing traction test. The developed theoretical model and results provide practical guidance for the structural design of advanced HTTs and manoeuvrability optimization.