Abstract

In the last few years, many closed-loop control systems have been introduced in the automotive field to increase the level of safety and driving automation. For the integration of such systems, it is critical to estimate motion states and parameters of the vehicle that are not exactly known or that change over time. This paper presents a model-based ob- server to assess online key motion and mass properties. It uses common onboard sensors, i.e. a gyroscope and an accelerometer, and it aims to work during normal vehicle man- oeuvres, such as turning motion and passing. First, basic lateral dynamics of the vehicle is discussed. Then, a parameter estimation framework is presented based on an Extended Kalman filter. Results are included to demonstrate the effectiveness of the estimation approach and its potential benefit towards the implementation of adaptive driving as- sistance systems or to automatically adjust the parameters of onboard controllers.

Autore Pugliese

• Reina Giulio

Tutti gli autori

• Reina G. , Paiano M. , Blanco-Claraco J.

Titolo volume/Rivista

MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Anno di pubblicazione

2017

ISSN

0888-3270

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

5

Ultimo Aggiornamento Citazioni

22/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile