Abstract
The application of Lithium Metal Batteries (LMBs) as secondary cells is still limited due to dendrite degradation mechanisms arising with cycling and responsible for safety risk and early cell failure. Studies to prevent and suppress dendritic growth using state-of-the-art materials are in continuous development. Specific detection techniques can be applied to verify the internal condition of new LMB chemistries through cycling tests. In this work, six non-invasive and BMS-triggerable detection techniques are investigated to anticipate LMB failures and to lay the basis for innovative self-healing mechanisms. The novel methodology is based on: (i) defining detection parameters to track the evolution of cell aging, (ii) defining a detection algorithm and applying it to cycling data, and (iii) validating the algorithm in its capability to detect failure. The proposed methodology is applied to Li||NMC pouch cells. The main outcomes of the work include the characterization results of the tested LMBs under different cycling conditions, the detection techniques performance evaluation, and a sensitivity analysis to identify the most performing parameter and its activation threshold.