SUMMARY

To estimate friction coefficients during highly dynamic driving maneuvers with a vehicle, an nonlinear estimator (Extended Kalman Filter) is developed. A 14 Degree of Freedom simulation model serves as a reference vehicle. The observer model is based on a nonlinear single track model wich uses a modified version of the Magic Formula (MF) Tire Model. The parameters for the MF Tire model are identified beforehand with dynamic driving maneuvers. Gradient based optimization is used to identify the tire parameters. The same dynamic maneuvers and optimization method are performed to tune the covariance matrices of the Extended Kalman Filter. The results are verified by performing maneuvers on surfaces with various friction