SBIR-STTR Award

Lithium-ion batteries have become a vital technology enabling renewable energy, electric transport and other low carbon technologies. However, there are significant concerns about their safety as there have been a small number of accidents in which batteries have caused fires and explosions, due in many cases by a thermal runaway phenomenon. Current techniques to identify potentially dangerous batteries are crude and provide very little time for reaction. This project seeks to develop means to detect degenerated conditions within batteries before they become dangerous using ultrasound methodology already developed to characterize the states of healthy batteries. Deviations from normal signals and the appearance of novel signal features associated with abnormal states will be identified and categorized as signatures of battery degradation phenomena.These will form the basis of an ultrasonic early warning system. Batteries and degradation mechanisms considered the greatest safety risk will be identified and selected for testing. A set of batteries prepared by hard cycling techniques with various types and degrees of degradation will be scanned with Titan’s ionView ultrasonic methodology. Features that appear in the ultrasonic signals caused by the degradation phenomena will be isolated and characterized as signatures of these mechanisms. This project will lead to the development of commercial systems to monitor batteries in energy storage applications to provide early warning of the development of degraded conditions within a battery that could lead to dangerous events. These could take the form of permanently installed hardware in battery stacks, either as standalone system or as part of a BMS, or a handheld device for use in routine maintenance. This will greatly reduce the probability of fires or explosions and encourage acceptance of lithium ion batteries for backup storage where energy generation is intermittent, e.g., wind turbines and solar arrays. The overall public benefits will be the expansion of renewable energy generation and the reduction of greenhouse gasses responsible for global warming.

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