Numerical Study on the Thermal Management Performance of Immersion Cooling for Cylindrical Lithium-Ion Batteries under Multiparameter Conditions

Abstract Fast charging at C-rates ≥4C poses thermal challenges for lithium-ion batteries, as conventional cooling strategies cannot adequately suppress hotspots or temperature nonuniformity at these rates. In this study, a multiparameter CFD framework is developed to evaluate immersion cooling for cylindrical battery modules, considering four coolant categories, flow velocities ranging from 0.00125 to 0.05 m/s, and charging rates from 1C to 4C. The model integrates validated heat generation properties with anisotropic thermal properties to capture the combined effects of coolant type, flow velocity, and charge rate. The results demonstrate that coolants with high thermal conductivity (e.g., Novec series) suppress 4C hotspots but require high pumping power, whereas coolants with high specific heat (e.g., PAO, Shell Thermal Fluid) achieve increased energy efficiency at 1C–2C. Low-viscosity coolants (e.g., mineral oil and esters) reduce circulation losses but underperform under high thermal loads, whereas high-stability coolants (e.g., silicone oil) provide uniform temperature fields but with significant energy costs. In addition to the coolant type, the flow velocity is a key factor, with improvements plateauing at rates greater than 0.02 m/s, and outlet-adjacent regions are identified as critical risks via hotspot mapping. This study provides practical guidelines for immersion-based BTMS design in fast-charging EVs and stationary energy storage systems and lays the foundation for integrating aging mechanisms and intelligent flow control.