Unscented Kalman filter for road friction coefficient estimation

Abstract:

To obtain current road information quickly and to improve vehicle active safety performance accurately, a vehicle state estimation method was proposed to real-time track changes in road friction coefficient. A 7-DOF non-linear vehicle dynamic model including Pacejka 89 tire model was established. The normal force of tire was approximately calculated from the vehicle dynamic model, the tire slip and longitudinal force were estimated by a combination of tire mechanical model and UKF algorithm. Then Slip-slope of different road friction coefficient was obtained. A mapping relationship between several typical road friction coefficient and Slip-slope was built. By constructing various ground test environment with different road friction coefficient using the Road Builder in ADAMS/Car, the estimation method proposed was verified to be effective and reliable. Moreover, the simulation results indicated that Slip-slope theory is also applicable in the virtual test under the ADAMS/Car environment.