engleski

Vehicle Sideslip Angle EKF Estimator based on Nonlinear Vehicle Dynamics Model and Stochastic Tire Forces Modeling

This paper presents the extended Kalman filter-based sideslip angle estimator design using 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 and it is robust against the variations of 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 validated by running the estimator algorithm off-line on the experimental data sets recorded on the test vehicle.

sideslip angle; estimation; Kalman filter; stochastic tire force modeling

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