- Conference Article
- 10.1109/ecce58356.2025.11259944
Development of a Digital Twin Model for Electric Vehicles: Real-Time Battery Management and Performance Optimization
- Oct 19, 2025
- Mohammed Elsayed + 3 more +3
A Digital Twin (DT) for Electric Vehicles (EVs) is a virtual replica or digital model of a physical EV that captures its characteristics, performance, and real-time behavior. This study presents the development of a comprehensive DT model for EVs, designed to enable real-time monitoring, performance optimization, and predictive maintenance. The suggested framework features physical modeling and data-driven analytics to replicate the dynamic behavior of the EV powertrain, with particular emphasis on the battery, motor, and thermal subsystems. Using real driving cycle data (FTP-75), the DT continuously assesses key performance indicators (KPIs) such as battery state of charge (SoC), state of health (SoH), temperature, and motor torque to indicate real-world operating conditions. A degradation-aware battery model and simplified thermal dynamics are integrated to estimate remaining useful life (RUL) and enhance reliability. DT's predictive capability enables early fault detection and adaptive control strategies, minimizing downtime and advancing energy efficiency. Simulation results demonstrate the model's ability to accurately track SoC and thermal responses with minimal estimation error, validating its capability for integration in intelligent EV management systems. This innovative approach aims to improve the overall efficiency and reliability of EVs, thereby supporting a more sustainable transportation ecosystem.
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