Andrea Tordi
Sideslip angle identification for tires performance development.
Rel. Enrico Galvagno, Alessandro Vigliani. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2020
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Abstract
During these six months the goal was to compute some parameters of dynamic vehicle such as sideslip angle and cornering stiffnesses, applying a linear Kalman filter, using as acquisition system either the CAN network or an IMU (Inertial measurement unit) platform. Indeed, this method works obtaining data in either case from the CAN system and from the IMU. In the first part of the thesis, some general theory topics, of dynamic vehicle especially about sideslip angle estimation. A general explanation of vehicle models particularly for the bicycle model, the model picked for the sideslip angle estimation. The Kalman filter will be explained, first generally then a comparison trough different types of Kalman filters; the linear Kalman filter, the EKF (Extended Kalman filter) and the UKF (Unscented Kalman filter).
All the sensors used and the approach picked will be explained in detail
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