Unscented Kalman Filter for Vehicle State Estimation
نویسندگان
چکیده
Vehicle Dynamics Control (VDC) systems require the information about system variables, which cannot be directly measured, e.g., the wheel slip or the vehicle side-slip angle. This paper presents a new concept for the vehicle state estimation under assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilize an Unscented Kalman Filter (UKF) for estimation purposes, since it is based on a numerically efficient nonlinear stochastic estimation technique. A planar two-track model is combined with the empiric Magic Formula in order to describe the vehicle and tire behavior. Moreover, an advanced vertical tire load calculation method is developed that additionally considers the vertical tire stiffness and increases the estimation accuracy. Experimental tests show the good accuracy and robustness of the designed vehicle state estimation concept.
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