Vehicle sideslip angle estimation via a Riccati equation based nonlinear filter

The vehicle sideslip angle is an important variable that contains information concerning the directional behaviour and stability of vehicles. As a consequence, it represents a very functional feedback for all the actual vehicle dynamics control systems. Since the measurement of the sideslip angle is expensive and unsuitable for common vehicles, its estimation is nowadays an important task. To this aim, several approaches have been adopted and the limits due to the nonlinear nature of the vehicle system are emerged. In order to overcome these limits, this paper focuses on an alternative nonlinear estimation method based on the State-Dependent-Riccati-Equation (SDRE). The technique is able to fully take into account the system nonlinearities and the measurement noise. A single track vehicle model has been employed for the synthesis of the estimator. Simulations have been conducted and comparisons with the largely used Extended Kalman Filter are illustrated. Performance of the estimator have subsequently been verified by means of experimental data acquired with an instrumented vehicle. The results show the effectiveness of the SDRE based technique, able to give an estimated sideslip angle fully in accordance with the measured one.