Vehicle sideslip angle estimation using Kalman filters: modelling and validation

PIERALICE, Cristiano, LENZO, Basilio, BUCCHI, Francesco and GABICCINI, Marco (2018). Vehicle sideslip angle estimation using Kalman filters: modelling and validation. In: CARBONE, Giuseppe and GASPARETTO, Alessandro, (eds.) Advances in Italian Mechanism Science: Proceedings of the Second International Conference of IFToMM ITALY. Mechanisms and Machine Science, 68 (68). Netherlands, Springer, 114-122. [Book Section]

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Abstract
The knowledge of the vehicle sideslip angle provides useful information about the state of the vehicle and it is often considered to increase the performance of the car as well as to develop safety systems, especially in the vehicle equipped with Torque Vectoring control systems. This paper describes two methods, based on the use of Kalman filters, to estimate the vehicle sideslip angle and the tire forces of a vehicle starting from the longitudinal and yaw velocity data. In particular, these data refer to on-track testing of a Range Rover Evoque performing ramp steer maneuvers at constant speed. The results of the sideslip estimation method are compared with the actual vehicle sideslip measured by a Datron sensor and are also used to estimate the tire lateral forces.
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