Dynamics of Battery Tabs Under Ultrasonic Welding

Ultrasonic metal welding (USMW) for battery tabs must be performed with 100% reliability in battery pack manufacturing as the failure of a single weld essentially results in a battery that is inoperative or cannot deliver the required power due to the electrical short caused by the failed weld. In ultrasonic metal welding processes, high-frequency ultrasonic energy is used to generate an oscillating shear force (sonotrode force) at the interface between a sonotrode and few metal sheets to produce solid-state bonds between the sheets clamped under a normal force. These forces, which influence the power needed to produce the weld and the weld quality, strongly depend on the mechanical and structural properties of the weld parts and fixtures in addition to various welding process parameters, such as weld frequencies and amplitudes. In this work, the effect of structural vibration of the battery tab on the required sonotrode force during ultrasonic welding is studied by applying a longitudinal vibration model for the battery tab. It is found that the sonotrode force is greatly influenced by the kinetic properties, quantified by the equivalent mass, equivalent stiffness, and equivalent viscous damping, of the battery tab and cell pouch interface. This study provides a fundamental understanding of battery tab dynamics during ultrasonic welding and its effect on weld quality, and thus provides a guideline for design and welding of battery tabs from tab dynamics point of view.

Microstructure, welding mechanism, and failure of Al/Cu ultrasonic welds

Microstructure, welding mechanism, and failure of Al/Cu ultrasonic welds

Ultrasonic metal welding is widely used for joining multiple layers of dissimilar metals, such as aluminum/copper battery tabs welding onto copper busbars. It is therefore important to have a robust product/process design using ultrasonic metal welding that ensures consistent welds with desired quality. In this work, the effects of longitudinal and flexural vibrations of the battery tab during ultrasonic welding on the development of axial normal stresses that occasionally cause cracks near the weld area are studied by applying a one-dimensional continuous vibration model for the battery tab. Analysis results indicate that fracture could occur near the weld area, due to low cycle fatigue as a result of large dynamic stresses induced by resonant flexural vibration of the battery tab during welding. This study provides a fundamental understanding of battery tab dynamics during ultrasonic welding and its effects on weld quality, and can be used to develop guidelines for product/process design of ultrasonically welded battery tabs.

Ultrasonic metal welding is often used as a rapid and effective technique for joining sheet metals without causing them to melt. Precise management of the welding process parameters is crucial for achieving excellent joint quality. However, modeling the behavior of the weld material and the welding process is still very challenging. This study aimed to create 3D finite element models that accurately simulate the ultrasonic metal welding process. The proposed material model integrates frictional heat and ultrasonic softening, as well as the cyclic plasticity model. A friction law incorporating a variable friction coefficient is examined to investigate surface impacts. This coefficient is influenced by contact pressure, slippage, temperature, and the number of cycles. The findings of this study demonstrate that the oscillation frequency significantly influences both the temperature fluctuation and the extent of the heat-affected zone. Increased frequencies lead to accelerated temperature fluctuations and expanded heat-affected. Furthermore, ultrasonic welding combined with preheating led to a much wider heat-affected zone than ultrasonic welding without heating. The minimum preheating temperature required for ultrasonic welding of aluminum is 150 °C. This model can predict the relative displacement between welded plates. Assessing the oscillations that arise during the ultrasonic welding process is beneficial in selecting suitable welding settings to prevent excessive heating. This aids engineers in choosing appropriate welding parameters to avoid excessive heat generation during ultrasonic welding, hence limiting the reduction in tensile strength of the weld. Consequently, it can decrease the expense of the experimental methodology.

Ultrasonic metal welding has been used to join multiple layers of battery tabs with the bus bar in lithium-ion battery assembly operations. This paper describes joint performance models for ultrasonic metal welds of multiple layers of dissimilar battery tab materials, i.e., aluminum and copper. Finite element (FE) models are developed to predict the mechanical performance of the ultrasonically welded joints. The models predict peak shear load, energy absorption capability, and failure modes, which are necessary for modeling product performance and defining process requirements for the welds. The models can be adjusted to represent different quality of welds created in conditions of underweld (UW), normal-weld (NW), or overweld (OW) using physical attributes observed through microscopic analysis. The models are validated through lap shear tests, which demonstrate excellent agreement for the maximum force in the NW condition and good agreement for the UW and OW conditions. The models provide in-depth understanding of the relationship among welding process parameters, physical weld attributes, and the weld performance. The models also provide significant insight for further development of ultrasonic welding process for battery tabs and help optimize welding process for more than four-layered joints.

Vibrational energy loss analysis in battery tab ultrasonic welding

Online process monitoring in ultrasonic welding of automotive lithium-ion batteries is essential for robust and reliable battery pack assembly. Effective quality monitoring algorithms have been developed to identify out of control parts by applying purely statistical classification methods. However, such methods do not provide the deep physical understanding of the manufacturing process that is necessary to provide diagnostic capability when the process is out of control. The purpose of this study is to determine the physical correlation between ultrasonic welding signal features and the ultrasonic welding process conditions and ultimately joint performance. A deep understanding in these relationships will enable a significant reduction in production launch time and cost, improve process design for ultrasonic welding, and reduce operational downtime through advanced diagnostic methods. In this study, the fundamental physics behind the ultrasonic welding process is investigated using two process signals, weld power and horn displacement. Several online features are identified by examining those signals and their variations under abnormal process conditions. The joint quality is predicted by correlating such online features to weld attributes such as bond density and postweld thickness that directly impact the weld performance. This study provides a guideline for feature selection and advanced diagnostics to achieve a reliable online quality monitoring system in ultrasonic metal welding.

Online process monitoring in ultrasonic welding of automotive lithium-ion batteries is essential for robust and reliable battery pack assembly. Effective quality monitoring algorithms have been developed to identify out of control parts by applying purely statistical classification methods. However, such methods do not provide the deep physical understanding of the manufacturing process that is necessary to provide diagnostic capability when the process is out of control. The purpose of this study is to determine the physical correlation between ultrasonic welding signal features and the ultrasonic welding process conditions and ultimately joint performance. A deep understanding in these relationships will enable a significant reduction in production launch time and cost, improve process design for ultrasonic welding, and reduce operational downtime through advanced diagnostic methods. In this study, the fundamental physics behind the ultrasonic welding process is investigated using two process signals, weld power and horn displacement. Several online features are identified by examining those signals and their variations under abnormal process conditions. The joint quality is predicted by correlating such online features to weld attributes such as bond density and post-weld thickness that directly impact the weld performance. This study provides a guideline for feature selection and advanced diagnostics to achieve a reliable online quality monitoring system in ultrasonic metal welding.

Ultrasonic welding is a solid-state joining process that produces joints by the application of high-frequency vibratory energy in the work pieces held together under pressure without melting. In electronic and automotive applications, copper wires are connected to the equipment (alternator/rectifier) by a solid state joining process. For such an application ultrasonic metal welding is useful. The dominant problem faced by industry dealing with ultrasonic metal welding process is the poor weld quality and strength of the weld due to improper selection of weld parameters. In this work welding parameters like welding pressure, weld time and amplitude of the vibration are considered while producing ultrasonically welded joints of copper whose thickness is 0.2 mm. If other modes of joining are used, this size being very small, it may damage the weld. A suitable experimental design based on Taguchi’s robust design methodology was designed and executed for conducting trials. The analysis of variance (ANOVA) and signal to noise ratio analyses are employed to investigate the influence of different welding parameters on the weld strength and to obtain the optimum parameters.

Simulating microstructure evolution of battery tabs during ultrasonic welding

Application of artificial neural network models to predict ultrasonic welding parameters for joining copper to aluminium sheet

When working with thin layers of comparable and/or different metals, resistance welding and conventional welding each have their own set of limits that they must overcome. When the input parameters include a high-frequency vibration, proper weld duration and pressure, ultrasonic metal welding performs at its highest level of efficiency. Ultrasonic welding uses a lot of power, force and energy, and if the right input parameters aren’t chosen, the quality of the weld and its durability suffer. This study takes into account the relationships between the input process parameters of welding pressure, welding time and vibration amplitude and the output responses of power, force and energy in ultrasonic metal welding (UMW). For multilayer AL-8011 foils, the author utilized UMW has experimented with central composite design by design professionals. The response surface approach, often known as RSM, has been used to improve the process parameters to get the best possible welding connections.

Manufacturing of lithium-ion battery packs for electric or hybrid electric vehicles requires a significant amount of joining, such as welding, to meet the desired power and capacity needs. However, conventional fusion welding processes, such as resistance spot welding and laser welding, face difficulties in joining multiple sheets of highly conductive, dissimilar materials to create large weld areas. Ultrasonic metal welding overcomes these difficulties by using its inherent advantages derived from its solid-state process characteristics. Although ultrasonic metal welding is well-qualified for battery manufacturing, there is a lack of scientific quality guidelines for implementing ultrasonic welding in volume production. In order to establish such quality guidelines, this paper first identifies a number of critical weld attributes that determine the quality of welds by experimentally characterizing the weld formation over time using copper-to-copper welding as an example. Samples of different weld quality were cross-sectioned and characterized with optical microscopy, scanning electronic microscopy (SEM), and hardness measurements in order to identify the relationship between physical weld attributes and weld performance. A novel microstructural classification method for the weld region of an ultrasonic metal weld is introduced to complete the weld quality characterization. The methodology provided in this paper links process parameters to weld performance through physical weld attributes.

Manufacturing of lithium-ion battery packs for electric or hybrid electric vehicles requires a significant amount of joining such as welding to meet desired power and capacity needs. However, conventional fusion welding processes such as resistance spot welding and laser welding face difficulties in joining multiple sheets of highly conductive, dissimilar materials with large weld areas. Ultrasonic metal welding overcomes these difficulties by using its inherent advantages derived from its solid-state process characteristics. Although ultrasonic metal welding is well-qualified for battery manufacturing, there is a lack of scientific quality guidelines for implementing ultrasonic welding in volume production. In order to establish such quality guidelines, this paper first identifies a number of critical weld attributes that determine the quality of welds by experimentally characterizing the weld formation over time. Samples of different weld quality were cross-sectioned and characterized with optical microscopy, scanning electronic microscopy (SEM), and hardness measurements in order to identify the relationship between physical weld attributes and weld performance. A novel microstructural classification method for the weld region of an ultrasonic metal weld is introduced to complete the weld quality characterization. The methodology provided in this paper links process parameters to weld performance through physical weld attributes.