Bachelor and Master Theses

Industrial electric vehicle batteries is a large financial investment for many companies within the Swedish industry. Tracking and predicting the degradation rate of these batteries can enable the optimization of battery use throughout its lifetime and enable fleet level planning, thus providing significant value. There is currently a need for acquiring vehicle battery data for research purposes. It is only in recent years that data-based research methods have started taking off, and as modern industrial batteries typically have a long lifespan the amount of currently available data is often insufficient to produce significant results. In this thesis you will be developing a digital framework using the battery modelling tool PyBaMM to simulate industrial electric vehicle operations focusing on vehicle batteries. The thesis project will be executed within the context of the Circul8 – Smart Battery Circularity research project (https://www.mdu.se/en/malardalen-university/research/research-projects/smart-battery-circularity---circul8) funded by the Knowledge Foundation’s (KK-stiftelsen) in collaboration with Volvo, Epiroc, and IBM.

Proficient English

Some programming experience, Python is desirable.