| KEYWORD |
Meccanica del Veicolo
Theses abroad
automated workflow for parameter identification and model validation on full vehicle data
Thesis in external company 
Thesis abroad
keywords DIGITAL TWIN, EXPERIMENTAL ANALYSIS, PARAMETER IDENTIFICATION
Reference persons ENRICO GALVAGNO, ALESSANDRO VIGLIANI
External reference persons VELLA ANGELO
GELUK THEO (SIEMENS)
Research Groups Meccanica del Veicolo
Thesis type EXPERIMENTAL IN COMPANY, MODELING AND SIMULATION
Description The main scope of the thesis is to develop an automated workflow for digital twin identification and validation by applying parameter id algorithms based on test data from pre-defined test conditions. Test data acquisition only in full vehicle condition, hence not from vehicle disassembly and/or component test data.
THESIS CONTENT
Literature study of actual methodologies for vehicle parameter identification
Develop a Testlab Process Design workflow for deploy parameter identification methodologies
Support test-data acquisition: test maneuver definition, sensors choice and placement
Compare test and simulated results
Use of Matlab/Python and advanced Siemens simulation software and analysis of simulation/test data
BACKGROUND:
In recent years, the advent of digitalization has led to increasing interest of Automotive OEMs towards processes & methods enabling early stage simulation, hence prediction of vehicle (dynamic) responses.
By relying more and more on these simulations, OEMs can reduce the need for costly and time-consuming physical testing. This can lead to significant cost savings throughout the vehicle development process while accelerating time-to-market for new models.
In this context, the need to have a correct and efficient vehicle parameterization has led engineers to look for smart methods that would further help to develop and enhance the digital twin identification process as well as accuracy.
Required skills modelling and simulation; vehicle dynamics; Matlab/Python
Notes Thesis at Siemens facilities in Leuven (Belgium) starting from END of 2024 EARLY 2025
Deadline 29/12/2024
PROPONI LA TUA CANDIDATURA