APPLICATIONS OF TECHNOLOGY:
- Battery testing
- Fast, scalable
The battery industry generally lacks a fast and scalable solution for determining the physical condition of batteries in various stages of their manufacture and use, e.g., during research and development, testing, production, bench assembly, and post fabrication and sealing. The current techniques for diagnosing the physical condition of a battery, e.g., employed at-scale, are limited to electrical and thermal techniques, which are recognized as being inaccurate, destructive, and/or unsuitable for battery diagnostics while the battery is in-use. There is a recognized need for scalable and non-destructive diagnostic techniques for accurately monitoring and assessing a battery’s internal state in a way that can inform further analyses of the battery’s physical condition, including the ability to determine state of charge (SOC), state of health (SOH), quality of construction, defect or failure state, and other physical properties of the battery.
A team of researchers from Lawrence Berkeley National Laboratory and Feasible, Inc. have developed systems and methods of determining physical conditions of a battery, such as state of charge (SOC), state of health (SOH), quality of construction, defect, or failure state include driving two or more acoustic signals of two or more amplitudes, each acoustic signal having two or more frequencies, into the battery and detecting vibrations generated in the battery based on the two or more acoustic signals. Nonlinear response characteristics of the battery for the two or more acoustic signals are determined from the detected vibrations. The physical conditions of the battery are determined based at least in part on the nonlinear response characteristics, using nonlinear acoustic resonance spectroscopy (NARS) or nonlinear resonant ultrasound spectroscopy (NRUS).
For details regarding this invention, see Published U. S. Patent Application 15/836,531 (Publication No. US 2018/0164383).
DEVELOPMENT STAGE: Proven principle.
STATUS: Published U. S. Patent Application 15/836,531 (Publication No. US 2018/0164383). Available for licensing or collaborative research.
REFERENCE NUMBER: 2017-025