Process monitoring of ultrasonic metal welding of battery tabs using external sensor data

• Main Authors: I. Balz, E. Abi Raad, E. Rosenthal, R. Lohoff, A. Schiebahn, U. Reisgen, M. Vorländer
• Format: Article
• Language: English
• Published: Elsevier 2020-03-01
• Series: Journal of Advanced Joining Processes
• Subjects: Ultrasonic metal welding; Battery manufacturing; Process monitoring; Sensor; Quality control
• Online Access: http://www.sciencedirect.com/science/article/pii/S2666330920300030

Ultrasonic metal welding (USMW) is a common used manufacturing technology for cell, module or pack assembly of Lithium-ion battery systems of pouch type. Since every single joint can affect the efficiency and safety of the entire battery system, quality fluctuations of the joint are one of the greatest challenges. Despite its industrial spread in battery manufacturing, USMW has a large number of influencing variables that may affect the bond quality but cannot be detected 100% failsafe with existing monitoring methods.Therefore the aim of this paper is to investigate the oscillation behavior of the tools and the joining members during USMW under different manufacturing conditions by monitoring external sensor data of structure-borne sound.In this paper typical manufacturing conditions in battery tab welding such as rolling direction and amplitude are set in order to study their effects on joint quality and the corresponding sensor signals. Therefore two laser vibrometers record the tool vibrations of the anvil and horn during the process. Occasionally, high-speed image capturing is also used to investigate the mechanism of process influences by studying the in-situ oscillation behavior of horn, anvil and the workpieces during USMW process. The sensor data analysis is correlated to thermal measurements and to the results of T-peel tensile testing and microstructural characterization of the bond interface to understand the effects of process influences during the welding process and its resulting joint quality.Based on the results, new insights for enhancing the process monitoring of USMW in Lithium-ion battery manufacturing are provided from identified sensor signals, that are correlating with the joint quality respectively different manufacturing conditions.