English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Lithium-ion batteries, which have high energy density, are the most suitable batteries for use in high-tech electromechanical applications requiring high performance. Because one of the important components that determines the efficiency of lithium-ion batteries is the electrode, the manufacturing process for this junction plays an important role in the entire production process. In particular, the process related to the resistance spot welding of the electrode is very important, directly affecting the safety of users, and greatly affecting the performance of the batteries. However, because the electrode tab is spot-welded onto the inner surface of the case, it is impossible to verify with visual testing (using the naked eye) whether the junction is well bonded. Therefore, it is very important to perform quality evaluation of the resistance welding of electrodes after completing the manufacturing process, using non-destructive testing methods. In this paper, a non-destructive ultrasonic testing technique was applied to examine the quality of lithium-ion batteries in which the negative electrode tabs were welded to the inner surface of the cell cans. The status of resistance spot welding between the electrode and the can was verified using deep-learning techniques with the experimentally acquired ultrasonic signal database.

Discrimination of Poor Electrode Junctions within Lithium-Ion Batteries by Ultrasonic Measurement and Deep Learning