Digital Twin Simulation for Electric Vehicle Battery Management

This research article presents a digital twin simulation for lithium-ion batteries in electric vehicles, integrating multiphysics models and reduced-order models (ROM) for real-time battery management. The study utilizes machine learning techniques to derive latent variables from simulation data, improving battery performance monitoring and control. Key findings include the relationship between battery voltage response and ambient temperature, validated through experimental data from A123 System