Vehicle Sideslip Angle EKF Estimator based on Nonlinear Vehicle Dynamics Model and Stochastic Tire Forces Modeling 2014-01-0144
This paper presents the extended Kalman filter-based sideslip angle estimator design using a nonlinear 5DoF single-track vehicle dynamics model with stochastic modeling of tire forces. Lumped front and rear tire forces have been modeled as first-order random walk state variables. The proposed estimator is primarily designed for vehicle sideslip angle estimation; however it can also be used for estimation of tire forces and cornering stiffness. This estimator design does not rely on linearization of the tire force characteristics, it is robust against the variations of the tire parameters, and does not require the information on coefficient of friction. The estimator performance has been first analyzed by means of computer simulations using the 10DoF two-track vehicle dynamics model and underlying magic formula tire model, and then experimentally validated by using data sets recorded on a test vehicle.
Citation: Hrgetic, M., Deur, J., Ivanovic, V., and Tseng, E., "Vehicle Sideslip Angle EKF Estimator based on Nonlinear Vehicle Dynamics Model and Stochastic Tire Forces Modeling," SAE Int. J. Passeng. Cars - Mech. Syst. 7(1):86-95, 2014, https://doi.org/10.4271/2014-01-0144. Download Citation
Mario Hrgetic, Josko Deur, Vladimir Ivanovic, Eric Tseng
Univ. of Zagreb, Ford Motor Co.
SAE 2014 World Congress & Exhibition
SAE International Journal of Passenger Cars - Mechanical Systems-V123-6EJ, SAE International Journal of Passenger Cars - Mechanical Systems-V123-6