Ψηφιακό Δίδυμο Αυτοκινήτου
Automotive Digital Twin
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Keywords
Vehicle digital twin ; Digital twin ; Ψηφιακό δίδυμο οχήματος ; Ψηφιακό δίδυμοAbstract
This postgraduate thesis focuses on the development and evaluation of a Digital Twin
(DT) for the engine of a SUBARU Forester XT (2005) vehicle. The aim of the study is to
investigate the potential of digital twin technology in monitoring, predicting, and optimizing the
performance of an internal combustion system, while also supporting maintenance processes.
The theoretical part presents the conceptual framework of Digital Twins, their typology,
maturity levels, and their applications in the automotive industry. Special emphasis is placed
on distinguishing DTs from conventional simulations and exploring the technological dimensions
of DTs, particularly those involving artificial intelligence and machine learning.
The experimental component involves the collection of real-time data through the OBD
II diagnostic interface, using Subaru Select Monitor 4 (SSM4) equipment during 57 minutes of
mixed driving conditions. Data from over 70 sensors were recorded and subsequently analyzed
using the ORANGE software platform and the DBSCAN algorithm, aiming to detect patterns,
correlations, and anomalies in engine behavior.
The findings highlight the viability of implementing Digital Twins as tools for predictive
maintenance and industrial optimization. The study underscores the relevance of DT technology
to contemporary smart mobility initiatives and contributes to the broader understanding of the
technical, functional, and methodological aspects involved in developing a practical DT system.
Postgraduate Studies Programme
Ψηφιακός Πολιτισμός, Έξυπνες Πόλεις, IoT και Προηγμένες Ψηφιακές ΤεχνολογίεςDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
108Language
GreekCollections
Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού - Παρόμοια Διανομή 3.0 Ελλάδα
Αναφορά Δημιουργού - Παρόμοια Διανομή 3.0 Ελλάδα