Discontinuity detection in battery cells

Abstract

A system for evaluating a battery cell, the system comprising an imaging device configured to acquire a first image of at least a portion of the battery cell when the battery cell is in a first deformed state and to acquire a second image of at least a portion of the battery cell when the battery cell is in a second deformed state. The system further comprises a processor configured to analyze the first image and the second image; identify a first region of the first image indicative of a suspected discontinuity, the first region corresponding to a portion of the battery cell; compare the first region of the first image to a second region of the second image, the second region corresponding to the portion of the battery cell; and determine, based on a difference between the first region and the second region, that the suspected discontinuity is an actual discontinuity.

Description

Detection of discontinuities in battery cells Technical Field

[0001] This topic relates to batteries, and more specifically to the detection of discontinuities in battery cells. Background Technology

[0002] Pouch cells are used in a variety of applications, such as automotive applications (e.g., in electric and hybrid vehicles). Tearing and other discontinuities can occur in components of the battery cell, such as the anode and cathode foils. Such discontinuities can lead to short circuits and other malfunctions. It is important to inspect the battery cell and its components to ensure proper functioning and to detect discontinuities before they can negatively impact such cells. Summary of the Invention

[0003] In one exemplary embodiment, a system for evaluating a battery cell includes an imaging device configured to acquire a first image of at least a portion of the battery cell when the battery cell is in a first deformed state, and to acquire a second image of at least a portion of the battery cell when the battery cell is in a second deformed state. The system also includes a processor configured to acquire the first and second images. The processor is configured to analyze the first and second images and identify a first region of the first image representing a suspected discontinuity, the first region corresponding to a portion of the battery cell. The processor is further configured to compare the first region of the first image with a second region of the second image, the second region corresponding to a portion of the battery cell; and to determine, based on the difference between the first and second regions, that the suspected discontinuity is an actual discontinuity.

[0004] In addition to one or more features described herein, the first and second images were acquired using direct x-ray radiography.

[0005] In addition to one or more features described herein, at least one of the first deformation state and the second deformation state is achieved by elastically deforming the components of the battery cell.

[0006] In addition to one or more features described herein, at least one of the first deformation state and the second deformation state is achieved by bending the tabs of the battery cell.

[0007] In addition to one or more of the features described herein, the battery cell is a pouch cell.

[0008] In addition to one or more features described herein, a portion of a battery cell includes at least one of the following: a foil of the battery cell, a stack of foils of the battery cell, a soldering area, and an area including solder lines.

[0009] In addition to one or more features described herein, analysis is performed on the first and second images to increase at least one of the contrast and visibility of the suspected discontinuity.

[0010] In addition to one or more features described herein, analyzing the first and second images includes performing at least one of digital filtering and histogram weighting.

[0011] In addition to one or more features described herein, the identification of the first region is based on an automated machine vision discontinuity detection process.

[0012] In one exemplary embodiment, a method for evaluating a battery cell includes: acquiring a first image of at least a portion of the battery cell when the battery cell is in a first deformed state; acquiring a second image of at least a portion of the battery cell when the battery cell is in a second deformed state; analyzing the first image and the second image, and identifying a first region of the first image representing a suspected discontinuity, the first region corresponding to a portion of the battery cell. The method further includes comparing the first region with a second region of the second image, the second region corresponding to a portion of the battery cell; and determining, based on the difference between the first region and the second region, that the suspected discontinuity is an actual discontinuity.

[0013] In addition to one or more features described herein, the first and second images were acquired using direct X-ray radiography.

[0014] In addition to one or more features described herein, at least one of the first deformation state and the second deformation state is achieved by elastically deforming the components of the battery cell.

[0015] In addition to one or more of the features described herein, the battery cell is a pouch cell.

[0016] In addition to one or more features described herein, the second region also represents a suspected discontinuity, and comparing the first region with the second region includes comparing the geometry of the suspected discontinuity in the first region with the geometry of the suspected discontinuity in the second region.

[0017] In addition to one or more features described herein, determining a suspected discontinuity to be an actual discontinuity is based on the fact that the suspected discontinuity is visible in a first region of a first image and is not visible in a second region of a second image.

[0018] In addition to one or more features described herein, the identification of the first region is based on an automated machine vision discontinuity detection process.

[0019] In one exemplary embodiment, a computer program product includes a computer-readable storage medium having instructions executable by a computer processor to cause the computer processor to perform a method. The method includes: acquiring a first image of at least a portion of a battery cell when the battery cell is in a first deformed state; acquiring a second image of at least a portion of the battery cell when the battery cell is in a second deformed state; analyzing the first and second images and identifying a first region of the first image representing a suspected discontinuity, the first region corresponding to a portion of the battery cell. The method further includes comparing the first region with a second region of the second image, the second region corresponding to a portion of the battery cell; and determining, based on the difference between the first and second regions, that the suspected discontinuity is an actual discontinuity.

[0020] In addition to one or more features described herein, at least one of the first deformation state and the second deformation state is achieved by elastically deforming the components of the battery cell.

[0021] In addition to one or more features described herein, the battery cell is a pouch cell, and a portion of the battery cell includes at least one of the following: a foil of the battery cell, a stack of foils of the battery cell, a soldering area, and an area including solder lines.

[0022] In addition to one or more features described herein, analysis is performed on the first and second images to increase at least one of the contrast and visibility of the suspected discontinuity.

[0023] The present invention also discloses the following technical solutions:

[0024] 1. A system for evaluating battery cells, the system comprising:

[0025] An imaging device configured to acquire a first image of at least a portion of the battery cell when the battery cell is in a first deformed state, and to acquire a second image of the at least a portion of the battery cell when the battery cell is in a second deformed state; and

[0026] A processor configured to acquire the first image and the second image, and configured to execute:

[0027] Analyze the first image and the second image to identify a first region in the first image that represents a suspected discontinuity, the first region corresponding to a portion of the battery cell;

[0028] The first region of the first image is compared with the second region of the second image, the second region corresponding to the portion of the battery cell; and

[0029] The suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

[0030] 2. The system according to technical solution 1, wherein the first image and the second image are acquired using direct X-ray radiography.

[0031] 3. The system according to technical solution 1, wherein at least one of the first deformation state and the second deformation state is achieved by elastically deforming a component of the battery cell.

[0032] 4. The system according to technical solution 3, wherein at least one of the first deformation state and the second deformation state is achieved by bending the tabs of the battery cell.

[0033] 5. The system according to technical solution 1, wherein the battery cell is a pouch battery cell.

[0034] 6. The system according to technical solution 5, wherein the portion of the battery cell includes at least one of the following: the foil of the battery cell, the foil stack of the battery cell, the welding area, and the area including the welding line.

[0035] 7. The system according to technical solution 1, wherein the analysis of the first image and the second image is performed to increase at least one of the contrast and visibility of the suspected discontinuity.

[0036] 8. The system according to technical solution 7, wherein analyzing the first image and the second image includes performing at least one of digital filtering and histogram weighting.

[0037] 9. The system according to technical solution 1, wherein the identification of the first region is based on an automatic machine vision discontinuity detection process.

[0038] 10. A method for evaluating battery cells, the method comprising:

[0039] A first image of at least a portion of the battery cell is acquired when the battery cell is in a first deformed state;

[0040] A second image of at least a portion of the battery cell is acquired when the battery cell is in a second deformed state;

[0041] Analyze the first image and the second image to identify a first region in the first image that represents a suspected discontinuity, the first region corresponding to a portion of the battery cell;

[0042] The first region is compared with a second region of the second image, the second region corresponding to the portion of the battery cell; and

[0043] The suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

[0044] 11. The method according to technical solution 10, wherein the first image and the second image are acquired using direct X-ray radiography.

[0045] 12. According to the method of technical solution 10, at least one of the first deformation state and the second deformation state is achieved by elastically deforming the components of the battery cell.

[0046] 13. The method according to technical solution 10, wherein the battery cell is a pouch battery cell.

[0047] 14. The method according to technical solution 13, wherein the second region also represents the suspected discontinuity, and comparing the first region with the second region includes comparing the geometry of the suspected discontinuity in the first region with the geometry of the suspected discontinuity in the second region.

[0048] 15. The method according to technical solution 10, wherein determining that the suspected discontinuity is an actual discontinuity is based on the fact that the suspected discontinuity is visible in the first region of the first image and the suspected discontinuity is not visible in the second region of the second image.

[0049] 16. The method according to technical solution 10, wherein identifying the first region is based on an automatic machine vision discontinuity detection process.

[0050] 17. A computer program product comprising a computer-readable storage medium having instructions executable by a computer processor to cause the computer processor to perform a method, the method comprising:

[0051] A first image of at least a portion of the battery cell is acquired when the battery cell is in a first deformed state;

[0052] A second image of at least a portion of the battery cell is acquired when the battery cell is in a second deformed state;

[0053] Analyze the first image and the second image to identify a first region in the first image that represents a suspected discontinuity, the first region corresponding to a portion of the battery cell;

[0054] The first region is compared with a second region of the second image, the second region corresponding to the portion of the battery cell; and

[0055] The suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

[0056] 18. The computer program product according to technical solution 17, wherein at least one of the first deformed state and the second deformed state is achieved by elastically deforming a component of the battery cell.

[0057] 19. The computer program product according to technical solution 17, wherein the battery cell is a pouch battery cell, and the portion of the battery cell includes at least one of the following: a foil of the battery cell, a foil stack of the battery cell, a welding area, and a region including welding lines.

[0058] 20. The computer program product according to technical solution 17, wherein the analysis of the first image and the second image is performed to increase at least one of the contrast and visibility of the suspected discontinuity.

[0059] The above-described features and advantages of this disclosure, as well as other features and advantages, will become clear from the following detailed description when considered in conjunction with the accompanying drawings. Attached Figure Description

[0060] Other features, advantages, and details are presented in the following detailed description by way of example only, with reference to the following figures, wherein:

[0061] Figure 1 depicts an example of a pouch cell;

[0062] Figure 2 depicts the battery cell of Figure 1 in a deformed state;

[0063] Figures 3A-3C depict examples of imaging and deformation systems used to evaluate battery cells;

[0064] Figure 4 depicts the X-ray source and detector of the system in Figures 3A-3C;

[0065] Figure 5 illustrates an example of battery cell deformation;

[0066] Figure 6 depicts an example of a portion of the battery cell in Figure 5 when the battery cell is in a deformed state by bending the tabs of the battery cell.

[0067] Figure 7 depicts an example of a portion of the battery cell in Figures 5 and 6 when the battery cell is brought to another deformed state by bending the tabs.

[0068] Figures 8A and 8B depict examples of images of a portion of a battery cell in a deformed state, which have been processed to increase the visibility of suspicious discontinuities;

[0069] Figure 9 is a flowchart depicting various aspects of methods for evaluating battery cells and / or detecting discontinuities in battery cells;

[0070] Figure 10 depicts an example image of a portion of the battery cell used in the method of Figure 9; and

[0071] Figure 11 depicts a computer system according to an exemplary embodiment. Detailed Implementation

[0072] The following description is exemplary in nature only and is not intended to limit this disclosure, its application, or use. It should be understood that in all the drawings, corresponding reference numerals denote the same or corresponding parts and features.

[0073] According to one or more exemplary embodiments, methods, apparatus, and systems are provided for evaluating battery cells and / or non-destructively detecting discontinuities in battery cells. Embodiments include methods for detecting discontinuities in pouch cells or other types of battery cells based on images of the battery cells acquired in various deformation states.

[0074] Embodiments of the method include acquiring multiple images of portions of a battery cell in multiple different deformation states. One or more images may be acquired for each deformation state. For example, a first image of a portion of the battery cell may be acquired when the battery cell is in a first deformation state, and a second image of the portion may be acquired when the battery cell is in a second deformation state. Deformation states include, for example, an undeformed state and various types and / or degrees of deformation (e.g., an undeformed state, a state in which the battery tabs are deformed to one degree, and a state in which the tabs are deformed to another degree). In embodiments, tomography techniques such as direct X-ray radiography are used to acquire the images.

[0075] Optionally, the first and second images (and any additional images acquired) are processed (e.g., to increase brightness, visibility, contrast, etc.) and then analyzed to identify one or more suspected discontinuities, such as foil tears or folds. Image regions representing suspected discontinuities are compared to determine if differences exist between them.

[0076] If the difference between suspected discontinuities in the images is large enough (e.g., greater than a threshold difference), the method includes determining that the suspected discontinuity is an actual discontinuity. In response to the detection of an actual discontinuity, additional actions may be performed, such as performing additional imaging and / or inspection, or remedial measures such as repairing or replacing a battery cell or its components.

[0077] It should be noted that suspected discontinuities may not be easily identifiable or visible in all deformed states. For example, a first image of a portion of a battery cell may show a discontinuity, while a second image may not (i.e., the discontinuity is hidden). In this example, a comparison is made between the location or region showing the suspected discontinuity in the first image and the corresponding location or region in the second image (where the location or region in the two images shows substantially the same part of the battery cell).

[0078] The embodiments described herein present numerous advantages and technical effects. The embodiments provide an improved evaluation method capable of detecting discontinuities that are difficult to detect using other techniques. The embodiments also simplify the evaluation process by allowing detection without disassembling or removing the battery cells.

[0079] Figure 1 illustrates an example of a pouch cell 10 that can be examined or analyzed using the systems and methods described herein. It should be noted that the systems and methods are not limited to the specific example in Figure 1 or any other particular battery type.

[0080] The battery cell 10 includes a flexible envelope or pouch 12 that seals multiple stacked cell units (cell stacks). The pouch 12 may be aluminum laminate foil or other suitable pouch material. Each cell unit includes a negative electrode or anode 14 and a positive electrode or cathode 16. The anode and cathode are made of a selected conductive material and constructed as thin sheets or foils. Each cell unit also includes a separator 18 made of an electrically insulating material such as polymer or ceramic. An active material 20, such as lithium, is disposed between the various layers of the cell units within the pouch 12.

[0081] As shown in Figure 1, each anode 14 (also referred to as an anode foil) extends away from the cell, and the anode foils 14 are attached together as a foil stack 22. The foil stack 22 welds the foils together, for example, by a single ultrasonic welding. The foil stack 22 is then attached to the conductive tab 24 by a weld 26. The weld 26 may be a solid weld joint formed by ultrasonic welding or a fusion weld joint formed by laser welding, although other metal-to-metal joining processes may be used. In this example, the tab 24 is the negative terminal tab. The cathode foil 16 may be similarly welded to the positive terminal tab (not shown) extending outside the pouch 12.

[0082] The embodiments include a method for non-destructively detecting discontinuities and other defects in a pouch cell, such as cell 10. The method includes imaging portions of the battery cell in multiple deformed states and analyzing the resulting images to detect one or more discontinuities. For example, a first image is acquired when the battery cell is in an undeformed state, and the first image is analyzed to identify potential tears or other discontinuities (also referred to as “suspected discontinuities”). The battery cell is then placed in a deformed state, wherein the tabs or other components of the battery cell elastically deform. While the battery cell is in the deformed state, a second image of the portion is acquired and analyzed. The images are compared to determine whether any tears or other discontinuities (actual discontinuities) that should be addressed are present.

[0083] To deform a battery cell, force of a chosen magnitude and direction is applied to the component, causing it to elastically deform. The applied force makes the deformation elastic, and the component returns to its previous state when the force is removed.

[0084] In an embodiment, the battery cell 10 is deformed by bending, twisting, pulling, or otherwise deforming the tab 24. Figure 2 depicts an example of such deformation, where the tab 24 is deformed by bending. The tab 24 is bendable such that it extends in a direction that forms an angle with respect to the undeformed axis of the tab 24 and / or the battery cell 10 (e.g., the longitudinal axis or z-axis of the cell shown in Figures 1 and 2). For example, the tab 24 may be bent at approximately 10 degrees.

[0085] Note that any desired component or part of the battery cell can be deformed. For example, the battery cell 10 can be deformed by applying force to the pouch material, the casing, and / or by applying force to one or more foils (e.g., between the cell and the tab 24).

[0086] Battery cells, such as cell 10, can be imaged in various deformed states using any desired imaging technique. For example, tomography techniques such as X-ray radiography, magnetic resonance imaging (MRI), microwave tomography, and neutron tomography can be used to image the battery cells. X-ray tomography includes direct radiography and X-ray computed tomography (CT). Other types of imaging that can be used include optical, radar, and ultrasound imaging.

[0087] In this embodiment, direct radiography is used to image the battery cell. Direct radiography is relatively fast and provides sufficient resolution for detecting discontinuities. X-ray CT tomography may not be suitable due to resolution and cycle time limitations. It is known that both X-ray CT and direct radiography (DR) have difficulty detecting discontinuities in battery cells, such as foil tears, including tears at or near weld lines. Discontinuities in battery cell foil due to cracks and tears are difficult to detect because the changes in X-ray attenuation between discontinuous and continuous areas are relatively small. As discussed further herein, using direct radiography in combination with deformation and / or image processing is effective in increasing the detectability of these discontinuities.

[0088] The acquired image may be post-processed using one or more of various techniques to increase the contrast or visibility of suspected discontinuities, or otherwise make detection easier. Examples of post-processing techniques include digital filtering (e.g., Wallis filters, Emboss filters, edge detection, etc.) and histogram weighting to increase the contrast of discontinuities. In some cases, post-processing may not be necessary or desirable, for example, if the acquired image shows discontinuities with sufficient contrast and visibility.

[0089] After image acquisition and / or post-processing, the image is analyzed to detect any suspicious discontinuities, such as tears, folds, separations, or other damage. This analysis can be automated. In embodiments, one or more machine learning, artificial intelligence, and / or machine vision methods are used to perform image analysis. Examples of methods that can be used for discontinuity detection include object tracking, digital image correlation, neural networks, classifiers, supervised and unsupervised machine learning, image cross-correlation, gradient histograms, etc. Any combination of the above techniques and methods may be employed.

[0090] Based on the detection of one or more suspected discontinuities in one or more acquired images, the acquired images are compared to determine whether any changes exist in the suspected discontinuities, or whether any changes exist in the acquired images as a result of the battery cell being in different deformed states. For example, a suspected discontinuity in a region of an image of a battery cell in one deformed state is compared with a corresponding region in another image of a battery cell in a different deformed state. If a difference exists and the difference is of a sufficient magnitude, the method includes determining that the suspected discontinuity is an actual discontinuity. This difference may be a difference in the size, length, width, shape, or other geometry of the suspected discontinuity between different images. In some cases, the difference lies between an image region where the suspected discontinuity is visible and a corresponding region in another image where the suspected discontinuity is not visible. For example, if the difference in tear length and / or width between images reaches or exceeds a threshold, or if a tear is shown in one deformed state but not visible in another deformed state, the suspected foil tear may be considered an actual foil tear. Image comparison may include one or more of the above-described image processing techniques.

[0091] Figures 3A-3C depict examples of imaging systems 30 that can be used to perform the various functions described herein. Imaging system 30 includes a support structure or retainer 32 for securing a battery cell (e.g., battery cell 10) in a static position. Imaging components such as a direct X-ray tomography assembly 34 are positioned and oriented for imaging at least portions of the battery cell, such as portions including foil stacks, tabs, and welded sections of the cell. Deformation assembly 36 includes a support structure 38 and deformation or bending features, such as a plastic disc 40 connected to an actuator (not shown).

[0092] As shown in Figure 4, the tomography assembly 34 includes an X-ray source 44 and an X-ray detector 42. As shown in Figure 4, images can be acquired from the side of the battery cell 10 (e.g., with the X-ray source guided along the X-axis), or from any desired direction and in any desired orientation.

[0093] Figures 5-7 depict examples of partial deformation of the battery cell 10 and images of the battery cell 10 in different deformation states. The battery cell 10 is placed in two deformation states and imaged in each state. Figure 5 shows an example of how the deformation states are achieved. In this example, the battery cell 10 is in a first deformation state, where the tab 24 is bent at an angle of approximately positive 10 degrees (+10°) relative to the z-axis or longitudinal axis of the battery cell 10; and the battery cell 10 is in a second deformation state, where the tab 24 is bent at an angle of approximately negative 10 degrees (-10º).

[0094] Figure 6 depicts a direct X-ray image 50 (also referred to as an X-ray image) acquired when the battery cell 10 is in a first deformed state (tab bending +10°), and Figure 7 depicts an X-ray image 52 acquired when the battery cell 10 is in a second deformed state (tab bending -10°). Each image depicts a portion of the battery cell 10, including portions of the electrode stack 54 (including various anode foil layers, cathode foil layers, and separators), portions of the anode foil 14, and the weld area 56 (formed by welds 26).

[0095] Each image also shows a discontinuity in the form of a suspected foil fold 58 and a suspected tear 60. As can be seen, the suspected tear 60 has a different width when the tab is bent at +10° (Fig. 6) compared to when the tab is bent at -10° (Fig. 7). Based on this difference, it can be determined that the suspected tear 60 is an actual tear.

[0096] Figures 8A-8B are examples of radiographic images obtained according to the embodiments described herein. These examples illustrate how distortion and post-processing can enhance suspicious discontinuities and make them easier to detect.

[0097] Figure 8A shows an example image 70 of the battery cell 10 in a deformed state before post-processing, and Figure 8B shows an image 72 of the battery cell 10 after post-processing while it is in a deformed state. In this example, image 72 is filtered using a Wallis filter and an Embossing filter. As can be seen, bending and post-processing reveal multiple discontinuities 74 along the weld line at the edge of the weld area 56. Such internal discontinuities cannot be detected by visual inspection or optical imaging, and are difficult to detect by radiography alone.

[0098] Figure 9 illustrates an embodiment of a method 90 for evaluating battery cells and / or detecting discontinuities. Aspects of method 90 may be executed by one or more processors. Note that method 90 may be executed by any suitable processing device or system, or by a combination of processing devices.

[0099] Method 90 includes multiple steps or stages represented by boxes 91-100. Method 90 is not limited to the number or order of steps as described herein, because some steps represented by boxes 91-100 may be performed in a different order than that described below, or fewer than all steps may be performed.

[0100] For illustrative purposes, aspects of the method are discussed in conjunction with the battery cell 10 in a deformed state as shown in Figures 1 and 2. Method 90 is not limited to this and can be used with any type of battery cell and any number of different deformed states.

[0101] In box 91, images of battery cells in different deformable states are acquired. Images can be acquired using X-ray radiography techniques such as direct X-ray radiography or other suitable methods. Examples of other image types include optical images, radar images, ultrasound images, etc.

[0102] For example, the first image of the battery cell 10 is taken in an undeformed state (as shown in Figure 1). The second image of the battery cell 10 is taken in a deformed state, in which the battery cell tab 24 has been bent or otherwise elastically deformed to a selected degree. Additional images may be taken in other deformed states. The number of images that can be obtained, as well as the number and types of deformed states, are not limited to the examples discussed herein.

[0103] Optionally, the images can be processed to increase the visibility of suspected discontinuities and / or other features of the battery cells. For example, in box 92, one or more filters, such as the Wallis filter and / or the Embossing filter, are applied. In another example, in box 93, histogram weighting is applied to each image.

[0104] In box 94, the image is analyzed to search for any suspicious discontinuities. This analysis can be performed through visual inspection of the image and / or through machine learning techniques or other image analysis techniques. In box 95, it is determined whether any suspicious discontinuities were detected. If no suspicious discontinuities were detected, the method is complete (box 96).

[0105] In box 97, if one or more suspected discontinuities are detected, the first and second images are compared to determine whether there is a difference between the suspected discontinuities in the first image and the suspected discontinuities in the second image, or whether there is a difference between corresponding regions in the first and second images (e.g., if the suspected discontinuity is not visible in a given image). For example, an object tracking algorithm can be used to determine whether there is expansion and contraction of suspected tears between images and to what extent they exist. Based on this comparison, it is determined whether the suspected discontinuity is an actual discontinuity (box 98).

[0106] In box 99, if an actual discontinuity is detected, it is classified as a defect. Battery cell 10 can then be replaced or repaired. In box 100, if a suspected discontinuity is not considered an actual discontinuity, other detection algorithms or other inspection methods can be used to confirm whether the suspected discontinuity will adversely affect battery operation or lifespan.

[0107] Figure 10 shows an example of an image 110 acquired at a portion of battery cell 112. Battery cell 112 includes tabs 114, foil stacks 116, solder areas 118, and solder lines 120. Image 110 was acquired using direct X-ray radiography in a deformed state, where the tabs are bent at a selected angle (e.g., 10 degrees). Image 110 is also filtered to increase the contrast and visibility of discontinuities. Image 110 shows multiple suspected discontinuities in the form of suspected tears 122. Additional images in various deformed states may be acquired, processed, and compared according to method 90 to determine whether one or more suspected tears are actual tears.

[0108] The systems and methods described herein can be applied to various types of batteries. In the embodiments, the battery cells evaluated may be cells used in electric and / or hybrid vehicles; however, the systems and methods are not limited thereto.

[0109] Figure 11 illustrates aspects of an embodiment of computer system 140, which can perform various aspects of the embodiments described herein. Computer system 140 includes at least one processing device 142, which typically includes one or more processors, for performing aspects of the image acquisition and analysis methods described herein.

[0110] The components of computer system 140 include processing device 142 (such as one or more processors or processing units), memory 144, and bus 146 connecting the various system components (including system memory 144 to processing device 142). System memory 144 may include a wide variety of computer system readable media. Such media may be any available media accessible to processing device 142, and may include volatile and non-volatile media, as well as removable and non-removable media.

[0111] For example, system memory 144 includes non-volatile memory 148 such as a hard disk drive, and may also include volatile memory 150 such as random access memory (RAM) and / or cache memory. Computer system 140 may also include other removable / non-removable, volatile / non-volatile computer system storage media.

[0112] System memory 144 may include at least one program product having a group of program modules (e.g., at least one) configured to perform the functions of the embodiments described herein. For example, system memory 144 stores various program modules that generally implement the functions and / or methods of the embodiments described herein. One or more modules 152 may be included to perform functions related to image acquisition. Image analysis module 154 may be included for image post-processing and / or image comparison as described herein. System 140 is not limited thereto, as other modules may be included. As used herein, the term "module" refers to processing circuitry, which may include application-specific integrated circuits (ASICs), electronic circuitry, processors (shared, dedicated, or grouped) and memories executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components providing the said functions.

[0113] The processing device 142 can also communicate with one or more external devices 156, such as a keyboard, a pointing device, and / or any device that enables the processing device 52 to communicate with one or more computing devices (e.g., a network card, a modem, etc.). Communication with various devices can be made via input / output (I / O) interfaces 164 and 165.

[0114] Processing device 142 may also communicate with one or more networks 166 via network adapter 168, such as a local area network (LAN), a general wide area network (WAN), a bus network, and / or a public network (e.g., the Internet). It should be understood that, although not shown, other hardware and / or software components may be used in conjunction with computer system 40. Examples include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, and data archive storage systems.

[0115] Although the above disclosure has been described with reference to exemplary embodiments, those skilled in the art will understand that various changes may be made and equivalents may be substituted for elements therein without departing from its scope. Furthermore, many modifications may be made to adapt particular situations or materials to the teachings of this disclosure without departing from its essential scope. Therefore, it is intended that this disclosure be limited to the specific embodiments disclosed, but will include all embodiments falling within its scope.

Claims

1. A system for evaluating battery cells, the system comprising: A deformation assembly configured to elastically deform a tab of a battery cell between a first deformation state and a second deformation state, wherein the tab is elastically deformed to the extent that it causes a detectable change in the actual discontinuity of the tab; and an imaging device configured to acquire a first image of at least a portion of the battery cell when the battery cell is in the first deformation state, and to acquire a second image of the at least a portion of the battery cell when the battery cell is in the second deformation state. The processor is configured to acquire the first image and the second image, and the processor is configured to perform: analyzing the first image and the second image to identify a first region in the first image that represents a suspicious discontinuity, the first region corresponding to a portion of the battery cell; The first region of the first image is compared with the second region of the second image, the second region corresponding to the portion of the battery cell; and the suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

2. The system according to claim 1, wherein, The imaging device is configured to acquire the first image and the second image using direct X-ray radiography.

3. The system according to claim 1, wherein, It also includes a retainer configured to hold the battery cell in a stationary position, the deformable component including a support structure and a bending feature configured to apply a force that bends the tab.

4. The system according to claim 1, wherein, At least one of the first deformation state and the second deformation state is achieved by bending the tabs of the battery cell.

5. The system according to claim 1, wherein, The actual discontinuity is a tear, and the change in the actual discontinuity is the expansion or contraction of the tear.

6. The system according to claim 5, wherein, The portion of the battery cell includes at least one of the following: the foil of the battery cell, the foil stack of the battery cell, the welding area, and the area including the welding line.

7. The system according to claim 1, wherein, Perform analysis on the first and second images to increase at least one of the contrast and visibility of the suspected discontinuity.

8. The system according to claim 7, wherein, Analyzing the first image and the second image includes performing at least one of digital filtering and histogram weighting.

9. The system according to claim 1, wherein, The identification of the first region is based on an automated machine vision discontinuity detection process.

10. A method for evaluating battery cells, the method comprising: A first image of at least a portion of the battery cell is acquired when the battery cell is in a first deformed state; The tabs of a battery cell are elastically deformed from a first deformable state to a second deformable state, wherein the tabs are elastically deformed to the extent that they cause a detectable change in an actual discontinuity of the tabs; a second image of at least a portion of the battery cell is acquired while the battery cell is in the second deformable state; the first image and the second image are analyzed to identify a first region of the first image representing a suspected discontinuity, the first region corresponding to a portion of the battery cell; the first region is compared with a second region of the second image, the second region corresponding to the portion of the battery cell; and the suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

11. The method according to claim 10, wherein, The first and second images were acquired using direct X-ray radiography.

12. The method according to claim 10, wherein, Making the tabs elastically deform includes: stabilizing the battery cell in a stationary position and applying a force that bends the tabs.

13. The method according to claim 10, wherein, The battery cell is a pouch cell.

14. The method according to claim 13, wherein, The second region also represents the suspected discontinuity, and comparing the first region with the second region includes comparing the geometry of the suspected discontinuity in the first region with the geometry of the suspected discontinuity in the second region.

15. The method according to claim 10, wherein, The determination that the suspected discontinuity is an actual discontinuity is based on the fact that the suspected discontinuity is visible in the first region of the first image and is not visible in the second region of the second image.

16. The method of claim 10, wherein, The identification of the first region is based on an automated machine vision discontinuity detection process.

17. A computer program product comprising a computer-readable storage medium having instructions executable by a computer processor to cause the computer processor to perform a method, the method comprising: A first image of at least a portion of the battery cell is acquired when the battery cell is in a first deformed state; The tabs of a battery cell are elastically deformed from a first deformable state to a second deformable state, wherein the tabs are elastically deformed to the extent that they cause a detectable change in an actual discontinuity of the tabs; a second image of at least a portion of the battery cell is acquired while the battery cell is in the second deformable state; the first image and the second image are analyzed to identify a first region of the first image representing a suspected discontinuity, the first region corresponding to a portion of the battery cell; the first region is compared with a second region of the second image, the second region corresponding to the portion of the battery cell; and the suspected discontinuity is determined to be an actual discontinuity based on the difference between the first region and the second region.

18. The computer program product according to claim 17, wherein, At least one of the first deformation state and the second deformation state is achieved by bending the tab.

19. The computer program product according to claim 17, wherein, The battery cell is a pouch cell, and the portion of the battery cell includes at least one of the following: the foil of the battery cell, the foil stack of the battery cell, the welding area, and the area including the welding line.

20. The computer program product according to claim 17, wherein, Perform analysis on the first and second images to increase at least one of the contrast and visibility of the suspected discontinuity.

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