Optimal usage of vehicle battery by multi-scale modelling

Research Project, 2018 – 2019

Today the usage of the energy storage on-board an electric vehicle is largely determined by estimates and predictions handled by the battery management system (BMS). To be safe with respect to detrimental conditions for the battery cells the margins set severely restricts the usage for the vehicle. The true internal battery cell conditions are, however, not known and cannot be measured online. This project targets how to both model the most crucial aspects of the internal cell conditions at the molecular and meso-scale levels, and how this affects the macroscopically online measurable data (voltage, current and temperature) – thus a multi-scale modelling approach beyond the conventional. The model created will be validated in detail, including a time-dependent ageing mode, by designed cell-cycling of model cells and microscopic materials analysis using several techniques; e-SEM, FIB-SEM and APT. The final objective is to use the better understanding of the correlation of internal conditions, observables and usage history to improve the model parametrization and develop new adaptive control strategies in an updated BMS.