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2021
Conference Paper
Titel
Inline monitoring of battery electrode lamination processes based on acoustic measurements
Abstract
Great demands are being placed on the quality of battery cells and their electrochemical properties. Through the use of innovative measurement methods over the entire life cycle of batteries, relevant product and process data can be collected and leveraged to identify correlations between e.g. the product properties defined during production and the resulting performance characteristics in the use phase. The understanding of interactions between products and processes and the implementation of quality management measures in the production phase are essential factors that require inline capable process monitoring. Although the use of acoustic measurement methods for process monitoring has already proven its usefulness in various fields of application, it has not yet been applied to battery cell production. In our work, a process monitoring system based on acoustic measurements was applied to processes in the battery cell process chain. One example is the application in battery cell lamination for an automatic detection of components by interpretation of acoustic emissions. Signal analysis and machine learning techniques were used to distinguish between processed components. As a result, a detection accuracy of up to 83 % could be achieved, proofing the general feasibility of the approach as an inline capable monitoring system. Therefore, it can contribute to minimize sources of error in the complex production chain of batteries.