Journal article
A robust ultrasonic characterization methodology for lithium-ion batteries on frequency-domain damping analysis
Journal of power sources, v 547, 232003
01 Nov 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recently, non-invasive ultrasonic-based detection has emerged as a powerful tool to estimate the state-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries with a promising accuracy and efficiency. However, the currently available non-invasive methodology is highly sensitive to experimental setups and conditions, leading to unpredictable and unstable results. To this end, from a more fundamental stress wave propagation perspective, we discover that the quantified change of ultrasonic damping can be an intrinsic physical quantity to correlate with the state-of-charge (SOC) of batteries. We employ time-harmonic waves with different frequencies to obtain the steady-state dynamic response of lithium-ion batteries at various SOCs and a quasi-periodic energy gap can be observed. A mesoscale physics-based model of lithium-ion batteries is established to explain the observed energy gap carrying the multiple reflections of ultrasonic waves within the multi-layered structure of the cell. Finally, the change of ultrasonic damping with SOC is quantified for fast and accurate SOC prediction based on the frequency-domain damping analysis. Results underpin a robust and accurate frequency-domain ultrasonic characterization methodology for batteries and highlight the promise of the fundamental understanding of wave propagation for advanced characterization of batteries.
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•Continuous waves are input as incident signals to conduct in-situ ultrasonic tests.•The wave dissipation mechanism through the pouch cell is revealed.•A meso-scale analytical model of the pouch cell is established.•An acoustic-based methodology for battery SOC estimation is proposed.
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Details
- Title
- A robust ultrasonic characterization methodology for lithium-ion batteries on frequency-domain damping analysis
- Creators
- Kangpei Meng - Ningbo University of TechnologyXiaoping Chen - Ningbo University of TechnologyWen Zhang - University of North Carolina at CharlotteWesley Chang - Columbia UniversityJun Xu - University of North Carolina at Charlotte
- Publication Details
- Journal of power sources, v 547, 232003
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mechanical Engineering and Mechanics
- Web of Science ID
- WOS:000859532900001
- Scopus ID
- 2-s2.0-85137009944
- Other Identifier
- 991021889834504721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Chemistry, Physical
- Electrochemistry
- Energy & Fuels
- Materials Science, Multidisciplinary