Digital Twin-Based Intelligent System for Thermal Conditioning of Engines and Vehicles with Phase Change Thermal Energy Storage

The development of modern transport energy systems is driven by increasing demands for energy efficiency, environmental sustainability, and operational reliability of vehicles. One of the most critical challenges in internal combustion engine operation is the cold-start condition, which results in increased fuel consumption, intensified component wear, and elevated emissions. Under these conditions, the development of intelligent thermal conditioning systems capable of accelerating engine warm-up and maintaining optimal thermal regimes becomes essential. This study proposes an intelligent engine and vehicle thermal conditioning system based on the integration of digital twin technology and phase-change thermal (PCM) energy storage. A digital twin architecture of the engine thermal conditioning system is developed to enable the integration of monitoring, simulation and predictive control of engine thermal processes. A mathematical model of the thermal conditioning system describing the dynamic temperature behavior of the engine, coolant, engine oil and PCM-based thermal energy storage units is formulated. A model predictive control strategy is implemented within the digital twin environment to support decision-making and optimization of engine thermal conditioning processes. Simulation and experimental results demonstrate that the proposed system can reduce engine warm-up time by 17.8–68.4%, decrease fuel consumption during the cold start phase by approximately 19.5–56.25%, and reduce harmful emissions. These findings confirm the potential of integrating digital twin technologies, predictive control and phase change thermal energy storage for improving the energy efficiency and environmental performance of modern transport power systems.