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Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries

The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves...

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Detalles Bibliográficos
Autores principales: Zhang, Kai, Yin, Jianxiang, He, Yunze
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864529/
https://www.ncbi.nlm.nih.gov/pubmed/33494311
http://dx.doi.org/10.3390/s21030712
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author Zhang, Kai
Yin, Jianxiang
He, Yunze
author_facet Zhang, Kai
Yin, Jianxiang
He, Yunze
author_sort Zhang, Kai
collection PubMed
description The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.
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spelling pubmed-78645292021-02-06 Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries Zhang, Kai Yin, Jianxiang He, Yunze Sensors (Basel) Article The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries. MDPI 2021-01-21 /pmc/articles/PMC7864529/ /pubmed/33494311 http://dx.doi.org/10.3390/s21030712 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Kai
Yin, Jianxiang
He, Yunze
Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title_full Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title_fullStr Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title_full_unstemmed Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title_short Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries
title_sort acoustic emission detection and analysis method for health status of lithium ion batteries
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864529/
https://www.ncbi.nlm.nih.gov/pubmed/33494311
http://dx.doi.org/10.3390/s21030712
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