Currently, the applied model is typically empirical, meaning that it focusses on predicting output (voltage) based on input (current). While this model can effectively be used for some tasks, it is not suitable for monitoring or enforcing physical limits inside the cell. For this reason, Physics-Based Models (PBMs), which can simulate internal potentials and concentrations inside the cell including ageing reactions, have received significant attention in research and industry. Concrete applications of these models can be to govern fast charging by monitoring the anode potential or to provide power limits which prevent ageing. However, to unlock this potential, the PBM needs to be simulated on the BMS controller. Given that it’s computational footprint is significantly larger than empirical models, this is not trivial. The goal of this internship is to explore the trade-off between model fidelity and computational load. You will model the PBM in Simulink and compile C-code which will run on an embedded BMS platform. The goal is to run the PBM with a footprint that is small enough to leave room for other algorithms while ensuring that its accuracy is sufficient for BMS tasks. The footprint can be influenced by exploring different well known simplified PBMs such as the single particle model.