Parameter Estimation Techniques for Determining Safe Vehicle Speeds in UGVs

Abstract

This thesis develops simplified equations to predict a velocity in which vehicle rollover or tire saturation occurs. These equations are functions of different vehicle parameters that are important to vehicle handling characteristics. Therefore, various algorithms are developed to estimate parameters such as vehicle tire stiffness, peak tire force, and center of gravity position on-line. A number of vehicle control systems have been developed in order to reduce rollover and help maintain vehicle stability. However, many of these control systems do not take into account changing vehicle parameters. Therefore using the on-line estimates of these parameters, the control systems could be more effective in decreasing the number of vehicle accidents. The thesis first explains the fundamentals of lateral vehicle dynamics. Basic vehicle dynamic models are derived and validated to show the effectiveness and shortcomings of the different models. Many assumptions are used to simplify the models. The assumptions leads to simplified equations that predict a velocity in which vehicle rollover or tire saturation occur. An equation to predict the vehicle stopping distance is also derived. Experiments are run to control the vehicle speed to the predictive velocity. This velocity is updated with the identified parameters from the estimation algorithms. By providing the updated velocity to the steering controller, a vehicle is able to transverse a maneuver at a safe speed.