Tesi etd-04082018-104545 |
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Tipo di tesi
Tesi di laurea magistrale
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 (Inglese)
Riassunto (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.
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| Tesi_Pieralice.pdf | 2.52 Mb |
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