Work Package 4: Safer Batteries

The driving range extension & the battery lifetime increase expected in the EVERLASTING project have to be balanced with an improvement of the safety management of Li-ion batteries. WP4 main objective is then to provide the BMS with sufficient advanced notifications of precursors of thermal runaways. Consequently, the BMS will have the ability to manage proactive and corrective actions in order to prevent safety hazards.

The first intermediate result of this WP is to experimentally analyse the thermal runaway in representative conditions of occurrence (internal defects, over-use (external short circuit, extended cycling…) and abuse (mechanical shocks, elevated temperature…). During those tests, the physical signatures of the runaway will be analysed in order to develop a proactive predictive intelligence algorithm and a reliable precursor detection multi-sensing strategy.

Simultaneously, other tasks will be carried out in order to improve the in-depth understanding of the internal short circuits and thermal runaway mechanisms, the degradation phenomena, their kinetics and their consequences in a battery module (Post-mortem analysis performed on damaged cells; Electrical & thermal modelling from initiation up to hazard breakout).

Finally, all the data and results obtained during WP4 will be used to feed a statistical self-learning algorithm to finally get a reliable internal short circuit prediction tool.

Partners involved: CEA (lead), TUM, TUV, Algolion, RWTH