Early Warning System for Hazardous Conditions in Lithium-Ion Batteries Using Ultrasound

Lithiumion batteries are becoming more prominent in everyday applications; however, catastrophic events caused by these batteries have been a limiting factor for their adoption into energy storage systems. These systems are necessary for the integration of renewable energy sources, improvement of the electric grid energy efficiency, and the reduction of carbon emissions, which is of great interest to the DOE. Without timely warnings to prevent these catastrophic events, the adoption of lithiumion systems will be drastically hindered. The objective of this project is the development of a commercially viable ultrasoundbased system, which will integrate with a battery management system, to provide early warnings of potential battery failures and hazardous events in energy storage installations. In Phase I, the ability of ultrasound to rapidly detect abnormal and potentially dangerous conditions were demonstrated. Several lithiumion batteries were subjected to overcharging conditions and allowed to proceed to failure while being continuously monitored by ultrasound. It was found that ultrasonic signatures that depict the onset of the abnormal conditions appeared almost immediately after overcharging began, and more pronounced signature changes appeared shortly before final stages of failure. Algorithms were developed to generate warnings, which were detected far enough in advance of failure to demonstrate feasibility that ultrasound can provide earlier actionable warnings not available with other current technologies. In Phase II, the ability of ultrasound to generate early warnings of abnormal battery states in gridscale batteries will be confirmed through inducing failure conditions, cycling batteries to monitor aging behavior, and performing postmortem. Appropriate ultrasound signatures of battery failure will be identified, and algorithms will be developed to detect and notify impending failure. A benchtop prototype system for commercial energy storage applications will be demonstrated. Development of this methodology will greatly increase the safety of lithiumion batteries in all applications by providing warnings that batteries may fail far enough in advance that action can be