Enhancing Li-Ion Battery Safety by Early Detection of Nascent Internal Shorts

Catastrophic failure concerns of Li-ion batteries create anxiety in electric vehicle and energy storage markets. Currently, no fast method to forecast catastrophic failure has existed for lithium ion or other battery types. This work presents a solution by very early detection of nascent internal shorts that are precursors of catastrophic failure. The new metric, the self-discharge current, which is determined under potentiostatic conditions at a slight discharge overvoltage, is proposed as a fast metric for detection of shorts and assessment of battery safety that can be completed in minutes. The assessment time for self-discharge analysis can be further shortened by at least two times using a sigmoidal model that displays only 5.6% variation from experimental values. The method is non-invasive and applicable to any battery chemistry or design. It can be easily adapted to any battery management system for monitoring battery state of health at any time and at any battery state of charge. The technology based on this method can be used in electric drive vehicles, stationary energy storage, military, aeronautic, as final control in battery production, for first responders in electric vehicle accidents, and many other applications.