Algorithm for the Prediction of Traction Performance of Terrain Vehicles

Abstract

This paper presents the development of an algorithm to estimate the tractive force of an off-road vehicle with uncertainties in the tire stiffness and in the soil moisture content. The algorithm compares the average ground pressure with the critical ground pressure to decide if the tire can be approximated as a rigid wheel, or if it should be modeled as a flexible wheel, and involves using previously developed vehicle and stochastic soil models, and computing along the way the vehicle sinkage, resistance force, tractive force and drawbar pull. The soil modeling focuses on the efficient treatment of poorly known parameters, such as the soil moisture content, and on the impact of these uncertainties on relationships critical in defining the mobility of an off-road vehicle, such as the pressure-sinkage and the shear stress-shear displacement relations. The uncertainties in the tire stiffness and in the soil properties are propagated through the model, and the uncertainty in the output of the vehicle model is analyzed. Such simulations can provide the basis for the study of ride performance, handling, and mobility of the vehicle in off-road conditions. The vehicle model used has seven degrees of freedom. Each of the four suspension systems comprises of a nonlinear spring and a linear viscous damper. The analysis of the dynamic response of the vehicle is performed for two scenarios: a light cargo, and a heavy cargo.