Back to Search
Start Over
Correlation of acoustic emission signatures with electrochemical and mechanical behavior in Li-ion batteries: A comprehensive method for in-operando acoustic emission analysis
- Source :
- Next Energy, Vol 6, Iss , Pp 100189- (2025)
- Publication Year :
- 2025
- Publisher :
- Elsevier, 2025.
-
Abstract
- As the demand for high-performance and long-lasting batteries continues to escalate, understanding the degradation mechanisms of Li-ion batteries (LIBs) has become a pressing concern. In this study, we employed the acoustic emission (AE) technique to detect and quantify the internal changes occurring within LIBs during the degradation processes. Our goal was to propose a comprehensive method to categorize the AE data and correlate them with different battery events, which has not yet been properly established in the state of the art. Two commercial pouch cells at different levels of degradation were monitored using the AE technique during their cycling, and the changes in their electrochemical and mechanical behavior were analyzed. A thorough investigation of the AE hits enabled us to identify 4 distinct AE types in terms of frequency, which could reflect multiple battery degradation events, including intercalation-induced stress, gas generation, and particle/electrode cracking. Our proposed approach was compared with the conventional methods presented in past studies, demonstrating its compatibility in explaining different battery phenomena and the coupled behavior of those phenomena. Overall, this work offers a new approach to in-operando AE analysis of LIBs, which helps further development of the AE technique as a real-time and nondestructive diagnostic tool for LIBs.
Details
- Language :
- English
- ISSN :
- 2949821X
- Volume :
- 6
- Issue :
- 100189-
- Database :
- Directory of Open Access Journals
- Journal :
- Next Energy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5f6c6017d315426a8ac3072e2c90ca97
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.nxener.2024.100189