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Article

Inline Monitoring of Battery Electrode Lamination Processes Based on Acoustic Measurements

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Institute of Machine Tools and Production Technology, Technische Universität Braunschweig, 38106 Braunschweig, Germany
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Battery LabFactory Braunschweig, Technische Universität Braunschweig, 38106 Braunschweig, Germany
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Fraunhofer Institute for Surface Engineering and Thin Films IST, 38108 Braunschweig, Germany
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Fraunhofer Project Center for Energy Storage and Systems ZESS, 38108 Braunschweig, Germany
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Fraunhofer Institute for Ceramic Technologies and Systems IKTS, 01109 Dresden, Germany
*
Authors to whom correspondence should be addressed.
Authors contributed equally.
Academic Editor: Manickam Minakshi
Batteries 2021, 7(1), 19; https://doi.org/10.3390/batteries7010019
Received: 3 February 2021 / Revised: 24 February 2021 / Accepted: 2 March 2021 / Published: 8 March 2021
Due to the energy transition and the growth of electromobility, the demand for lithium-ion batteries has increased in recent years. Great demands are being placed on the quality of battery cells and their electrochemical properties. Therefore, the understanding of interactions between products and processes and the implementation of quality management measures are essential factors that requires inline capable process monitoring. In battery cell lamination processes, a typical problem source of quality issues can be seen in missing or misaligned components (anodes, cathodes and separators). An automatic detection of missing or misaligned components, however, has not been established thus far. In this study, acoustic measurements to detect components in battery cell lamination were applied. 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. While laminating battery electrodes and separators, acoustic emissions were recorded. Signal analysis and machine learning techniques were used to acoustically distinguish the individual components that have been processed. This way, the detection of components with a balanced accuracy of up to 83% was possible, proving the feasibility of the concept as an inline capable monitoring system. View Full-Text
Keywords: lithium-ion batteries; process monitoring; acoustic measurements; lamination; machine learning; artificial neural networks; convolutional neural networks lithium-ion batteries; process monitoring; acoustic measurements; lamination; machine learning; artificial neural networks; convolutional neural networks
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MDPI and ACS Style

Leithoff, R.; Dilger, N.; Duckhorn, F.; Blume, S.; Lembcke, D.; Tschöpe, C.; Herrmann, C.; Dröder, K. Inline Monitoring of Battery Electrode Lamination Processes Based on Acoustic Measurements. Batteries 2021, 7, 19. https://doi.org/10.3390/batteries7010019

AMA Style

Leithoff R, Dilger N, Duckhorn F, Blume S, Lembcke D, Tschöpe C, Herrmann C, Dröder K. Inline Monitoring of Battery Electrode Lamination Processes Based on Acoustic Measurements. Batteries. 2021; 7(1):19. https://doi.org/10.3390/batteries7010019

Chicago/Turabian Style

Leithoff, Ruben, Nikolas Dilger, Frank Duckhorn, Stefan Blume, Dario Lembcke, Constanze Tschöpe, Christoph Herrmann, and Klaus Dröder. 2021. "Inline Monitoring of Battery Electrode Lamination Processes Based on Acoustic Measurements" Batteries 7, no. 1: 19. https://doi.org/10.3390/batteries7010019

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