Activity-analysis based modeling of the circular production of traction batteries of electric vehicles to determine an optimal capacity build-up strategy

Student research project / Master thesis

Supervisor: Raphael Ginster

Through the combustion of fossil fuels and the resulting emission of carbon dioxide (CO2), the transport sector contributes significantly to the depletion of resources and global climate change. As a result, government regulations are aimed at reducing CO2 emissions from the transportation sector, which also poses new challenges for the automotive industry. To meet these requirements, the transition from vehicles with internal combustion engines (ICEV) to alternative powertrain technologies such as battery electric vehicles (BEV) or fuel cell electric vehicles (FCEV) is being discussed. These alternative powertrain technologies require a traction battery to provide energy, which is currently designed as a lithium-ion battery. The production of these traction batteries requires limited and valuable resources (e.g., cobalt, nickel, lithium), which is why politicians are initiating measures to promote battery recycling in order to enable the circular production of traction batteries in the long term. Circular production is characterized by the recycling of materials from old batteries and new raw materials to produce new batteries and meet the primary demand for new electric vehicles (EV).

The aim of this work is the activity-analysis based modeling of the circular production of traction batteries of electric vehicles to determine an optimal capacity build-up strategy in a production-recycling network. In particular, different technologies, parameters of machines and systems (including investment and cost structure) as well as possible cost degression effects must be considered.

Experience with activity-analysis based modeling as well as experience with operations research methods (optimization models, Gurobi, Python, etc.) is recommended for successful completion of the topic.

If you are interested, please contact Raphael Ginster.