Vehicle state estimation with friction adaptation for four-wheel independent drive electric vehicle

Abstract

To improve the vehicle state estimation accuracy and robustness of four-wheel independent drive electric vehicle, a novel method for estimating vehicle state based on the measured wheel torque information is proposed, which is robust with respect to different road surface conditions. The dynamic characteristics of four-wheel independent drive electric vehicle is analysis, and then a three degree of freedom nonlinear dynamic model of vehicle and a tire longitudinal dynamics equation are established. The relationship between the longitudinal and lateral tire friction forces is derived based on Dugoff's tire model. The unknown input reconstruction technique of sliding mode observer is used to achieve longitudinal tire friction force estimation. Using the relationship between the longitudinal and lateral tire friction forces and the estimated longitudinal tire friction force, a nonlinear observer for vehicle states estimation is provided, which does not need to know the tire-road friction coefficient. Finally, the proposed method is evaluated experimentally under a variety of maneuvers and road conditions.