Modeling Degradation in Li-ion Batteries: Analyzing Single-cell Degradation and Applying It to Customized Pack-level

The rapid expansion of lithium-ion (Li-ion) battery applications in areas such as electric vehicles (EVs), renewable energy storage, and portable electronics has drawn attention to the need for improving their performance, safety, and longevity. As Li-ion batteries become essential across technologies, understanding degradation mechanisms is critical for optimizing design and ensuring reliable operation. This work provides a detailed overview of modeling degradation in Li-ion batteries, focusing on single-cell behavior and its implications for pack-level performance. The PyBaMM (Python Battery Mathematical Modeling) package, an open-source battery simulation tool written in Python, is used for single-cell simulations. Liionpack, another Python-based library, is employed for pack-level simulations. Additionally, a customized version of Liionpack is introduced to assign specific degradation patterns to individual cells within the pack, overcoming limitations of degradation assumptions. The study investigates how factors like temperature, C-rates, and cycling affect degradation, providing insights into capacity fade, resistance growth, and safety risks. Results highlight the impact of non-uniform aging on pack performance, offering practical guidance for battery management and system design. Advisor: Moe Alahmad