Issue link: https://resources.randsim.com/i/1510288
Health management & predictive maintenance: battery ageing Customer Goal Solution Benefits • Accurately predict battery performance degradation attributed to aging • Critical enablement for IoT-based battery health management and predicative maintenance • Create a digital twin of the EV battery running on the cloud that predicts the life degradation due to battery aging, based on real-life field operating history • High-fidelity: 3D CHT analysis to create training data for Reduced Order Model (Fluent+HPC) • Real-time Models: electrical ECM & thermal ROM (Twin Builder) • Dynamic aging model: Empirical correlation-based aging model implemented with ECM and Thermal ROM, continuously augmented by field data for updated usable remaining life • Connectivity: compatibility with mainstream IoT platforms Capacity Degradation vs Ageing Parameters Architecture of Battery Hybrid Twin with Consideration of Ageing Battery Life Prediction Model Schematic