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.

• 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.