A method for estimating the sideslip angle of a Formula SAE vehicle with torque vectoring is presented. Torque vectoring introduces large tire longitudinal forces which lead to a reduction of the tire lateral forces. A novel tire model is utilized to represent this reduction of the lateral forces. The estimation is realized using an extended Kalman filter which takes in standard sensor measurements. The developed algorithm is tested by simulating slalom and figure eight maneuvers on a validated VI-CarRealTime vehicle model. Results indicate that the algorithm is able to estimate the sideslip angle of the vehicle reliably on a high friction surface track.

Sideslip Angle Estimation of a Formula SAE Racing Vehicle / Ghosh, Jyotishman; Tonoli, Andrea; Amati, Nicola; Weitao, Chen. - In: SAE INTERNATIONAL JOURNAL OF PASSENGER CARS - MECHANICAL SYSTEMS. - ISSN 1946-3995. - (2016).

Sideslip Angle Estimation of a Formula SAE Racing Vehicle

GHOSH, JYOTISHMAN;TONOLI, Andrea;AMATI, NICOLA;
2016

Abstract

A method for estimating the sideslip angle of a Formula SAE vehicle with torque vectoring is presented. Torque vectoring introduces large tire longitudinal forces which lead to a reduction of the tire lateral forces. A novel tire model is utilized to represent this reduction of the lateral forces. The estimation is realized using an extended Kalman filter which takes in standard sensor measurements. The developed algorithm is tested by simulating slalom and figure eight maneuvers on a validated VI-CarRealTime vehicle model. Results indicate that the algorithm is able to estimate the sideslip angle of the vehicle reliably on a high friction surface track.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2643530
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