Development of an Integrated Estimation Method for Vehicle States, Parameters and Tire Forces

Abstract

Stability and desirable performance of vehicle control systems are directly dependent on the quality and accuracy of sensory and estimated data provided to the controllers. Tire forces and vehicle states such as lateral and longitudinal velocities are required information for most vehicle control systems. However, there are challenges associated with efficient estimation of tire forces and vehicle states. Furthermore, changes in vehicle inertial parameters, road grade, and bank angle all have major influences on both tire forces and vehicle states. Efficient identification of these parameters requires sufficient information about a set of vehicle states and tire forces. This duality relationship mandates the development of efficient methods for simultaneous estimation of tire forces, vehicle states, and vehicle and road parameters. This research proposes the design of an integrated estimation structure that can simultaneously estimate tire forces, vehicle velocity, vehicle inertial parameters, and road angles. The proposed structure is robust against variations in tire parameters because of tire brand, wear, and road friction coefficient. The methods developed in this thesis are all validated experimentally on multiple vehicle platform.