Research Direction
The high-fidelity modeling framework is intended to support improved battery thermal-management design, reduced-order models, predictive tools, future electro-thermal integration, and AI-enabled battery digital twins.
Battery Thermal Management Research Expands through High-Fidelity FVDBM
ITES Lab is advancing high-fidelity computational modeling for battery thermal management using the Finite-Volume Discrete Boltzmann Method (FVDBM). Current work examines thermal gradients, hotspot evolution, transient transport, and PCM-based thermal buffering to support safer and more effective battery thermal-management strategies.