Research Projects

Title: Advanced Multiphysics Modeling and Optimization of Thermal Management Strategies in Prismatic Lithium-Ion Batteries Rationale: Lithium-ion batteries are essential for powering electric vehicles and stationary energy systems due to their high energy density and reliability. However, thermal instability poses a serious challenge, leading to uneven degradation, reduced lifespan, and safety risks like thermal runaway. Conventional air cooling often fails to maintain uniform temperature across battery cells, especially in high-power applications. This project addresses the need for advanced thermal regulation by developing a validated computational framework that evaluates and optimizes immersion cooling strategies for prismatic lithium-ion batteries. Scientific Objectives: Develop a coupled electrochemical-thermal model for battery simulation. Evaluate the performance of immersion cooling versus air cooling. Optimize flow patterns, coolant rates, and battery geometry to reduce temperature gradients. Validate simulations with experimental data from lab-scale battery tests. Provide actionable recommendations for battery thermal management system design. Hypothesis and Model: The working hypothesis is that immersion cooling, when optimized, offers significantly improved temperature uniformity and safety over traditional air cooling. A multiphysics simulation approach will be used, integrating a pseudo-2D electrochemical model with a 3D heat conduction model. COMSOL Multiphysics will simulate internal heat generation and battery behavior, while OpenFOAM will model external coolant flow. These simulations will dynamically exchange boundary conditions to replicate real-time interactions between the battery and coolant environment. Experimental Work: A dedicated test rig will be built using prismatic lithium-ion cells immersed in mineral oil. Temperature sensors will monitor critical points such as cell centers and coolant inlets/outlets. Comparative experiments will be conducted with air cooling under equivalent conditions. The resulting data will be used to verify simulation accuracy and refine model parameters. Expected Significance: If successful, this project will provide a predictive and validated tool for designing advanced thermal management systems. Benefits include improved thermal safety, extended battery life, and higher efficiency. The findings will support innovation in electric mobility, renewable energy storage, and thermal system engineering. Moreover, the results will enhance the fundamental understanding of coupled thermal-electrochemical behavior in lithium-ion batteries and contribute to the development of next-generation battery management strategies.