Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm

Abstract

Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which first combines auxiliary particle filter and the iterated extended kalman filter (APF-IEKF), and then processes the results of the first step using iteration algorithm. APF-IEKF is used to estimate the slip angle of the front tires with strong nonlinearity and non-Gaussian noise, in which APF filters non-Gaussian noise and reach a preliminary estimation of sideslip angle, then IEKF is used to optimize the result, making the estimation of the sideslip angle more accurate. The iteration algorithm is used to estimate the tire-road friction coefficient based on self-aligning torque, which is more sensitive to tire slip angle and provides faster estimation. In this way, this method can estimate tire road friction coefficient more accurately and in real time. Both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm.