Dange, Soham Suneel2025-01-232025-01-232025-01-22vt_gsexam:42439https://hdl.handle.net/10919/124317Lithium-ion batteries are critical components in electric vehicles, portable electronics, and grid energy storage systems, necessitating advanced modeling techniques to enhance their safety, performance, and lifespan. This thesis presents the development and validation of a coupled electrical and lumped thermal model for cylindrical lithium-ion batteries along with a finite difference thermal model for spatial temperature prediction of cylindrical cell These models address key challenges in simulating real-world battery behavior. The electrical model utilizes a 2 R-C pair equivalent circuit framework integrated with a busbar model to account for current imbalances in parallel-connected cells. This model is a common equivalent circuit model used to represent a Li-ion cell using a voltage source, series resistor, and two resistor-capacitor pair connected in parallel. A lumped thermal model coupled with the electrical framework dynamically adjusts parameters based on temperature variations, achieving a voltage prediction error of less than 200 mV. Additionally, the thermal model employs a finite difference method (FDM) to solve the 3D transient heat conduction equation, providing spatial temperature distribution within cells and capturing critical gradients between core and surface temperatures. The vectorization of the thermal solver reduced simulation time by half, and its validation against Ansys™ simulations and module-level data demonstrated temperature prediction accuracy within a 2–3°C margin. The developed tool is scalable for any number of cylindrical cells arranged in a rectangular grid, addressing key gaps identified in the literature, including the need to simulate spatial and temporal non-uniformities in state-of-charge (SOC), state-of-health (SOH), and temperature, which significantly affect battery performance and lifespan. It provides a scalable, efficient tool for predicting thermal and electrical behavior across cell and module levels. This work contributes to the development of a tool that will, enable informed design decisions for next-generation energy storage systems. Future research could focus on extending the model to incorporate aging effects, enhanced thermal management configurations, and real-time simulations for battery management systems.ETDenIn CopyrightBattery Electric VehiclesCell ModelingEquivalent Circuit ModelingBusbar ModelingCell Thermal ModelingThesis