Features of the Data Collection and Transmission Technology in an Intelligent Thermal Conditioning System for Engines and Vehicles Operating on Thermal Energy Storage Technology Based on a Digital Twin

This article examines an integrated approach to data acquisition and transmission within an intelligent thermal conditioning system for engines and vehicles that operates using thermal energy storage and the digital twin concept. The system is characterized by its use of multiple primary energy sources to power internal subsystems and maintain optimal engine and vehicle temperature conditions. Building on a formalized conceptual model of the intelligent thermal conditioning system, the study identifies key technological features required for implementing complex operational processes, as well as the stages necessary for applying the proposed approach during the design and modernization phases throughout the system’s life cycle. A core block diagram of the system’s digital twin is presented, developed using mathematical models that describe support and monitoring processes under real operating conditions. Additionally, an architectural framework for organizing data collection and transmission is proposed, highlighting the integration of digital twin technologies into the thermal conditioning workflow. The article also introduces methods for adaptive data formation, transfer, and processing, supported by a specialized onboard software-diagnostic complex that enables structured information management. The practical implementation of the proposed solutions has the potential to enhance the energy efficiency of thermal conditioning processes and improve the reliability of vehicles employing thermal energy storage technologies.

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Publication Details

Journal
Machines
Published
2026-01-22
DOI
https://doi.org/10.3390/machines14010130
Primary Topic
Electric Power Systems and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Features of the Data Collection and Transmission Technology in an Intelligent Thermal Conditioning System for Engines and Vehicles Operating on Thermal Energy Storage Technology Based on a Digital Twin

Justas Žaglinskis, Igor V. Gritsuk
Machines
Electric Power Systems and Control
article

Features of the Data Collection and Transmission Technology in an Intelligent Thermal Conditioning System for Engines and Vehicles Operating on Thermal Energy Storage Technology Based on a Digital Twin

Justas Žaglinskis, Igor V. Gritsuk
article en

Abstract

This article examines an integrated approach to data acquisition and transmission within an intelligent thermal conditioning system for engines and vehicles that operates using thermal energy storage and the digital twin concept. The system is characterized by its use of multiple primary energy sources to power internal subsystems and maintain optimal engine and vehicle temperature conditions. Building on a formalized conceptual model of the intelligent thermal conditioning system, the study identifies key technological features required for implementing complex operational processes, as well as the stages necessary for applying the proposed approach during the design and modernization phases throughout the system’s life cycle. A core block diagram of the system’s digital twin is presented, developed using mathematical models that describe support and monitoring processes under real operating conditions. Additionally, an architectural framework for organizing data collection and transmission is proposed, highlighting the integration of digital twin technologies into the thermal conditioning workflow. The article also introduces methods for adaptive data formation, transfer, and processing, supported by a specialized onboard software-diagnostic complex that enables structured information management. The practical implementation of the proposed solutions has the potential to enhance the energy efficiency of thermal conditioning processes and improve the reliability of vehicles employing thermal energy storage technologies.

MachinesVol. 14(1)
Vilnius Gediminas Technical University (LT)
Affordable and clean energy
Openalex Percentile: Top 79%
Electric Power Systems and Control
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