The automotive industry's role in curbing carbon emissions and addressing climate change is vital. Electric vehicles offer an efficient and eco-friendly transportation solution. Understanding automotive batteries is key to enhancing their performance and reliability. Electro-chemical-mechanical models help capture the intricate dynamics of battery performance, aging, and mechanical impacts. This master's thesis opportunity involves developing and validating precise electro-chemical-mechanical models using the Python tool PyBaMM, an open-source resource enabling tailored modeling of lithium-ion batteries and their aging processes. WHAT WE OFFER YOU: Review state-of-the-art electro-chemical-mechanical modeling approaches for automotive batteries. Investigate the fundamental electrochemical aging processes and their coupling with mechanical deformation and cell thickness growth (swelling). Develop mathematical and computational models for battery behavior under different mechanical conditions. Validate the developed models using experimental data.