Lorenzo, Mosconi (2022) Development of methodologies for tyre characterization and performance evaluation from on-board sensors data. [Tesi di dottorato]

[img]
Preview
Text
Mosconi_Lorenzo_34.pdf

Download (7MB) | Preview
[error in script] [error in script]
Item Type: Tesi di dottorato
Resource language: English
Title: Development of methodologies for tyre characterization and performance evaluation from on-board sensors data
Creators:
CreatorsEmail
Lorenzo, Mosconilorenzo.mosconi@unina.it
Date: 14 March 2022
Number of Pages: 172
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Industriale
Dottorato: Ingegneria industriale
Ciclo di dottorato: 34
Coordinatore del Corso di dottorato:
nomeemail
Grassi, Michelemichele.grassi@unina.it
Tutor:
nomeemail
Farroni, FlavioUNSPECIFIED
Date: 14 March 2022
Number of Pages: 172
Keywords: Tyre performance evaluation, Vehicle model, parameter identification
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/13 - Meccanica applicata alle macchine
Date Deposited: 30 Mar 2022 12:01
Last Modified: 28 Feb 2024 11:01
URI: http://www.fedoa.unina.it/id/eprint/14410

Collection description

In recent years, aiming to reduce costs and time to market, the automotive world has experienced a drastic increase in the demand to reproduce vehicle dynamics through simulation models. Autonomous vehicles are increasingly widespread and more advanced, often electric, they are strictly dependent on control algorithms that need to know the dynamic state of the vehicle and the tyre, which vary continuously both for road conditions, for wear, for the change in temperature and pressure. This manuscript illustrates procedures that allow the estimation of tyre modeling parameters from the data collected by the vehicle in its real operating conditions, obtaining the results from post-processing procedures, and employed on the vehicle design process, or in real-time, for vehicle control. The first methodology presented can estimate the instantaneous grip in real-time using the vehicle standard sensors with the addition of a chassis velocity sensor. The second methodology can perform the tyre transient parameters characterization with the same measurements. The last is an algorithm based on an Extended Kalman filter able to estimate the vehicle velocity, inclination angle, tyre grip and cornering stiffness.

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item