Tesi etd-04082018-104545 |
Link copiato negli appunti
Tipo di tesi
Tesi di laurea magistrale
Autore
PIERALICE, CRISTIANO
Indirizzo email
c.pieralice@gmail.com
URN
etd-04082018-104545
Titolo
Vehicle sideslip angle estimation using Kalman Filters: analysis, modelling and simulation
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
INGEGNERIA DEI VEICOLI
Relatori
relatore Ing. Bucchi, Francesco
relatore Prof. Gabiccini, Marco
relatore Prof. Frendo, Francesco
relatore Ing. Lenzo, Basilio
relatore Prof. Gabiccini, Marco
relatore Prof. Frendo, Francesco
relatore Ing. Lenzo, Basilio
Parole chiave
- Dynamics
- Kalman Filter
- Sideslip estimation
- state estimation
- tyre force
Data inizio appello
26/04/2018
Consultabilità
Completa
Riassunto
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.
File
Nome file | Dimensione |
---|---|
Tesi_Pieralice.pdf | 2.52 Mb |
Contatta l’autore |