Measuring effective stiffness of Li-ion batteries via acoustic signal processing. Issue 32 (4th August 2020)

• Record Type: Journal Article
• Authors: Chang, Wesley; Mohr, Robert; Kim, Andrew; Raj, Abhi; Davies, Greg; Denner, Kate; Park, Jeung Hun; Steingart, Daniel
• Is Part Of: Journal of materials chemistry. Volume 8:Issue 32(2020)
• Page Start: 16624
• Page End: 16635
• Publication Date: 2020-08-04
• Subjects: Materials -- Research -- Periodicals; Chemistry, Analytic -- Periodicals; Environmental sciences -- Research -- Periodicals; 543.0284
• DOI: 10.1039/d0ta05552b
• Languages: English
• ISSNs: 2050-7488

Abstract

Abstract : Accurate signal processing of acoustic waves is utilized to measure the intrinsic material stiffness of a layered cell stack and explore relationships between battery displacement, sound speed and stiffness during high rate cycling. Abstract : In this work we build upon acoustic–electrochemical correlations to investigate the relationships between sound wave structure and chemo-mechanical properties of a pouch cell battery. Cell thickness imaging and wave detection during pouch cell cycling are conducted in parallel. Improved acoustic hardware and signal processing are used to validate the direct measurement of material stiffness, which is an intrinsic physical property. Measurement of cell thickness to micron resolution and wave transmit time to nanosecond resolution in a temperature and pressure controlled acoustic rig allows for estimation of the effective stiffness. We further explore the effects of material type and cell layering on the acoustic signal, demonstrating that the operando acoustic method can accurately measure the changes in physical state properties of a battery with high dynamic temporal and spatial range.