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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-04082018-104545


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
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.
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