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
  
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| Tesi_Pieralice.pdf | 2.52 Mb | 
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