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.

Vehicle sideslip angle estimation using Kalman filters: Modelling and validation

Lenzo B.;
2019

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.
2019
Mechanisms and Machine Science
978-3-030-03319-4
978-3-030-03320-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3402901
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