Thesis etd-04082018-104545 | |
Thesis type
Tesi di laurea magistrale
Thesis title
Vehicle sideslip angle estimation using Kalman Filters: analysis, modelling and simulation
Department
INGEGNERIA CIVILE E INDUSTRIALE
Course of study
INGEGNERIA DEI VEICOLI
Keywords
- Dynamics
- Kalman Filter
- Sideslip estimation
- state estimation
- tyre force
Graduation session start date
26/04/2018
Abstract (Italiano)
The present work is developed in the Material and Engineering Research Institute of the Sheffield Hallam University with the aim to develop a method to estimate the sideslip angle and the tire forces of a car using Kalman Filter. The estimation method based on this filters is useful because it allows to reach the goal using common and cheap sensors equipped on normal vehicles. After a first review of the methods listed in literature, the Kalman Filter is studied in both its formulations: the Kalman filter (KF) and the Extended Kalman Filter (EKF) for non-linear systems. The differences between these methods are shown analysing telemetry of a Range Rover Evoque, from the Project iCompose, equipped with a Datron sensor that provides reliable data about the Sideslip angle, useful for the validation of the model. In the end is proposed a procedure for the Pacejka Coefficient adaptation to the model of the car.
