Estimation of the vehicle sideslip angle of a GT3 race car based on track data

This work presents the development of a method for estimating the vehicle sideslip angle of a GT3 race car based on track data, in order to avoid the use of expensive slip angle sensors. The algorithm relies on the signals of the standard set of sensors installed on the vehicle, including an inertial measurement unit, wheel speed sensors, and a steering angle sensor. Track data is imported into MATLAB and processed using zero-phase filtering techniques. Roll rate sensor data is used to compensate for the gravity component induced in the lateral acceleration by chassis roll and track banking angles. A lever-arm correction is also introduced to compensate for the position of the accelerometer and obtain the lateral acceleration at the center of gravity of the vehicle. A kinematic-based model is then employed to compute the sideslip angle by numerical integration of the fundamental kinematic differential equation. Boundary conditions are enforced to impose null sideslip angle both at the beginning and at the end of each cornering event. The accuracy of the results of this implementation is then anlysed using data from an optical sensor as a reference for validation, showing that the proposed workflow allows for the estimation of the vehicle sideslip angle with sufficient accuracy to perform vehicle dynamics evaluations.