Dynamics of Battery Tabs Under Ultrasonic Welding

Metal Welding ◽

Ultrasonic metal welding 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 and equivalent stiffness, of the battery tab and cell pouch interface. This study provides a fundamental understanding of battery tab dynamics during ultrasonic welding and its effects on weld quality, and thus provides useful guidelines for design and welding of battery tabs from tab dynamics point of view.

Dynamic Response of Battery Tabs Under Ultrasonic Welding

10.1115/1.4024535 ◽

2013 ◽

Vol 135 (5) ◽

Cited By ~ 22

Author(s):

Bongsu Kang ◽

Wayne Cai ◽

Chin-An Tan

Keyword(s):

Longitudinal Vibration ◽

Welding Process ◽

Ultrasonic Welding ◽

Structural Vibration ◽

Kinetic Properties ◽

Weld Quality ◽

Equivalent Viscous Damping ◽

Metal 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.

Characterization of Joint Quality in Ultrasonic Welding of Battery Tabs

ASME 2012 International Manufacturing Science and Engineering Conference ◽

10.1115/msec2012-7410 ◽

2012 ◽

Cited By ~ 1

Author(s):

S. Shawn Lee ◽

Tae H. Kim ◽

S. Jack Hu ◽

Wayne W. Cai ◽

Jingjing Li ◽

...

Keyword(s):

Lithium Ion ◽

Ultrasonic Welding ◽

Fusion Welding ◽

Scientific Quality ◽

Weld Quality ◽

Quality Guidelines ◽

State Process ◽

Metal Welding ◽

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.

Characterization of Joint Quality in Ultrasonic Welding of Battery Tabs

10.1115/1.4023364 ◽

2013 ◽

Vol 135 (2) ◽

Cited By ~ 41

Author(s):

S. Shawn Lee ◽

Tae Hyung Kim ◽

S. Jack Hu ◽

Wayne W. Cai ◽

Jeffrey A. Abell ◽

...

Keyword(s):

Lithium Ion ◽

Ultrasonic Welding ◽

Fusion Welding ◽

Scientific Quality ◽

Weld Quality ◽

Quality Guidelines ◽

State Process ◽

Metal Welding ◽

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.

Process Monitoring in Ultrasonic Metal Welding of Lithium Batteries by Power Signals

10.1115/1.4052704 ◽

2021 ◽

pp. 1-22

Author(s):

Xinhua Shi ◽

Lin Li ◽

Suiran Yu ◽

Lingxiang Yun

Keyword(s):

Electric Power ◽

Process Monitoring ◽

Lithium Batteries ◽

Welding Process ◽

Isometric Transformation ◽

Welding Defects ◽

Different Types ◽

Metal Welding ◽

Abstract Ultrasonic metal welding is one of the key technologies in manufacturing lithium batteries, and the welding quality directly determines the battery performance. Therefore, an online welding process monitoring system is critical in identifying abnormal welding processes, detecting defects, and improving battery quality. Traditionally, the peak welding power is used to indicate abnormal process signals in welding process monitoring systems. However, since various factors have complex impacts on the electric power signals of ultrasonic welding processes, the peak power is inadequate to detect different types of welding defects. Therefore, a signal pattern matching method is proposed in this study, which is based on the electric power signal during the entire welding process and thus is capable of identifying abnormal welding processes in various conditions. The proposed method adopts isometric transformation and homogenization as signal pretreatment methods, and Euclidean distance is used to calculate the similarity metric for signal matching. The effectiveness and robustness of the proposed method are experimentally validated under different abnormal welding conditions.

Electronic and Photonic Packaging, Electrical Systems Design and Photonics, and Nanotechnology ◽

Ultrasonic Rapid Manufacturing: Implementation and Thermo-Mechanical Analysis

10.1115/imece2002-39378 ◽

2002 ◽

Author(s):

Shailendra Yadav ◽

Charalabos Doumanidis

Keyword(s):

Temperature Effects ◽

Welding Process ◽

Mechanical Analysis ◽

Ultrasonic Welding ◽

Solid Metal ◽

Rapid Manufacturing ◽

Mechanical Process ◽

Metal Parts ◽

This paper addresses a novel non-thermal Ultrasonic Rapid Manufacturing (URM), for layered parts based on Ultrasonic Metal Welding (USW). Its laboratory implementation, automation and integration are described first. The thermo-mechanical process aspects (i.e. heat generation and resulting temperature effects) during each cycle of ultrasonic welding are then studied. The technical advantages of ultrasonic welding process, including fabrication of dense, full-strength functional solid metal parts, multi-material composites, and active parts with embedded intelligent components and electronic, mechatronic, optic and fluidic structures, are examined.

Analysis of Weld Formation in Multilayer Ultrasonic Metal Welding Using High-Speed Images

10.1115/1.4029787 ◽

2015 ◽

Vol 137 (3) ◽

Cited By ~ 24

Author(s):

S. Shawn Lee ◽

Tae Hyung Kim ◽

S. Jack Hu ◽

Wayne W. Cai ◽

Jeffrey A. Abell

Keyword(s):

High Speed ◽

Lateral Displacement ◽

Welding Process ◽

Lithium Ion ◽

Ultrasonic Welding ◽

Fusion Welding ◽

Tool Geometry ◽

Weld Quality ◽

Weld Formation ◽

One of the major challenges in manufacturing automotive lithium-ion batteries and battery packs is to achieve consistent weld quality in joining multiple layers of dissimilar materials. While most fusion welding processes face difficulties in such joining, ultrasonic welding stands out as the ideal method. However, inconsistency of weld quality still exists because of limited knowledge on the weld formation through the multiple interfaces. This study aims to establish real-time phenomenological observation on the multilayer ultrasonic welding process by analyzing the vibration behavior of metal layers. Such behavior is characterized by a direct measurement of the lateral displacement of each metal layer using high-speed images. Two different weld tools are used in order to investigate the effect of tool geometry on the weld formation mechanism and the overall joint quality. A series of microscopies and bond density measurements is carried out to validate the observations and hypotheses of those phenomena in multilayer ultrasonic welding. The results of this study enhance the understanding of the ultrasonic welding process of multiple metal sheets and provide insights for optimum tool design to improve the quality of multilayer joints.

Characterization of Ultrasonic Metal Welding by Correlating Online Sensor Signals With Weld Attributes

Volume 2: Processing ◽

10.1115/msec2014-4139 ◽

2014 ◽

Author(s):

S. Shawn Lee ◽

Chenhui Shao ◽

Tae Hyung Kim ◽

S. Jack Hu ◽

Elijah Kannatey-Asibu ◽

...

Keyword(s):

Welding Process ◽

Deep Understanding ◽

Lithium Ion ◽

Ultrasonic Welding ◽

Diagnostic Methods ◽

Quality Monitoring ◽

Process Conditions ◽

Bond Density ◽

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.

Characterization of Ultrasonic Metal Welding by Correlating Online Sensor Signals With Weld Attributes

10.1115/1.4028059 ◽

2014 ◽

Vol 136 (5) ◽

Cited By ~ 20

Author(s):

S. Shawn Lee ◽

Chenhui Shao ◽

Tae Hyung Kim ◽

S. Jack Hu ◽

Elijah Kannatey-Asibu ◽

...

Keyword(s):

Welding Process ◽

Deep Understanding ◽

Lithium Ion ◽

Ultrasonic Welding ◽

Diagnostic Methods ◽

Quality Monitoring ◽

Process Conditions ◽

Bond Density ◽

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.

Analysis of Weld Formation in Multilayer Ultrasonic Metal Welding Using High-Speed Images

Volume 1: Processing ◽

10.1115/msec2015-9262 ◽

2015 ◽

Cited By ~ 1

Author(s):

S. Shawn Lee ◽

Tae Hyung Kim ◽

S. Jack Hu ◽

Wayne W. Cai ◽

Jeffrey A. Abell

Keyword(s):

High Speed ◽

Lateral Displacement ◽

Welding Process ◽

Lithium Ion ◽

Ultrasonic Welding ◽

Fusion Welding ◽

Tool Geometry ◽

Weld Quality ◽

Weld Formation ◽

Profile Monitoring and Fault Diagnosis Via Sensor Fusion for Ultrasonic Welding

10.1115/1.4043731 ◽

2019 ◽

Vol 141 (8) ◽

Cited By ~ 2

Author(s):

Weihong (Grace) Guo ◽

Jionghua (Judy) Jin ◽

S. Jack Hu

Keyword(s):

Real Data ◽

Ultrasonic Welding ◽

Profile Data ◽

Monitoring And Diagnosis ◽

Operational Quality ◽

Vector Projection ◽

Sensor Signals ◽

Rich Information ◽

Sensor signals acquired during the manufacturing process contain rich information that can be used to facilitate effective monitoring of operational quality, early detection of system anomalies, and quick diagnosis of fault root causes. This paper develops a method for effective monitoring and diagnosis of multisensor heterogeneous profile data based on multilinear discriminant analysis. The proposed method operates directly on the multistream profiles and then extracts uncorrelated discriminative features through tensor-to-vector projection, and thus, preserving the interrelationship of different sensors. The extracted features are then fed into classifiers to detect faulty operations and recognize fault types. The developed method is demonstrated with both simulated and real data from ultrasonic metal welding.