Improved Prediction Model for Maximum Static Friction Force of Agricultural Tractor with Front-End Loader on Paved Road.

Abstract

Highlights: The friction force is one of the important influence factors on tire slip, overturning, and rollover characteristics of tractors. The maximum static friction forces of three different tractors were measured on paved roads under various loading conditions. The prediction models of the previous study were improved through regression analysis for the measured data. The model that uses the front and rear axle's reaction forces as variables showed the highest prediction accuracy.

Abstract: The overturning and rollover safety of a tractor located on a slope is decreased by tire slip, which is affected by static friction force. Existing regression models for predicting the static friction force of tractors demonstrate inadequate accuracy, necessitating further refinement. Therefore, this study was conducted to improve the accuracy of the maximum static friction force prediction model developed in a previous study for tractors with a front-end loader. As a result of measuring the maximum static friction, it tended to increase as the rear ballast weight increased and to decrease as the payload increased. The accuracy of the regression models in this study was significantly improved compared to that in previous studies. The regression model that used the reaction forces of the front and rear axles as variables exhibited the highest accuracy, followed by the model using the rear axle reaction only. The reaction force of the rear axle had a greater effect on the maximum static friction than that of the front axle. The developed regression model will predict the maximum static friction force of a tractor with a front-end loader on paved roads with high accuracy using the reaction forces of the front and rear axles. Future studies will focus on extending these predictions to various soil types and under dynamic conditions.