Single cell, battery screening system and battery screening method

Abstract

This application relates to the field of battery technology, providing a single-cell battery, a battery screening system, and a battery screening method. The characteristic parameters of the single-cell battery are less than or equal to preset parameter thresholds. These characteristic parameters are determined at the end of the battery production process by applying and maintaining a preset calibrated pressure on the surface of the single-cell battery using a pressing device, obtaining two-dimensional stress distribution data using a thin-film pressure sensor, and then calculating the two-dimensional stress distribution data. The characteristic parameters characterize the degree of stress non-uniformity. The end of the battery production process refers to the stage after the battery has completed liquid injection, sealing, pre-formation, or formation, but before entering the aging or capacity testing process. This application enables early, non-destructive, and rapid online full inspection of internal defects in battery products at the end of the battery production process, thereby screening out qualified products for subsequent production processes and significantly improving the safety level and consistency of battery products.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to single cells, battery screening systems, and battery screening methods. Background Technology

[0002] With the development of technology, lithium-ion batteries have become a key power source for electronic devices, electric vehicles, and energy storage systems. In the large-scale production of lithium-ion batteries, despite increasingly precise process control, it is still difficult to completely avoid internal defects introduced by raw materials, equipment precision, or operational randomness.

[0003] Currently, there is a lack of rapid, non-destructive, online full inspection methods for internal defect diagnosis at the end of the battery production process. This makes it difficult to accurately and efficiently screen out qualified products without internal defects from the batteries on the production line, which may result in qualified products being missed or misjudged as defective products, thus affecting subsequent production processes. Summary of the Invention

[0004] This application aims to address at least one of the technical problems existing in the related art. To this end, one aspect of this application proposes a single-cell battery that enables early, non-destructive, and rapid online full inspection of internal defects of battery products on the production line at the end of the battery manufacturing process. This allows for timely, efficient, and accurate screening of qualified products without internal defects at the source of production, while rejecting defective products with internal defects, thereby significantly improving the safety level and consistency of battery products.

[0005] Another aspect of this application proposes a battery screening system.

[0006] Another aspect of this application proposes a battery screening method.

[0007] Another aspect of this application proposes a battery pack.

[0008] Another aspect of this application proposes a battery pack.

[0009] Another aspect of this application proposes an electric vehicle.

[0010] Another aspect of this application proposes an electrical appliance.

[0011] According to the embodiments of this application, the characteristic parameters of the single battery are less than or equal to a preset parameter threshold. The characteristic parameters are determined at the end of the battery production process, after a pressing device contacts the surface of a single cell and applies and maintains a preset calibrated pressure on the surface of the single cell, and then a two-dimensional stress distribution data is obtained using a thin-film pressure sensor. The characteristic parameters are used to characterize the degree of stress non-uniformity. The final stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation, or formation, but before it has entered the aging or capacity testing process.

[0012] The battery sorting system according to an embodiment of this application includes: A thin-film pressure sensor is used at the end of the battery manufacturing process to collect two-dimensional stress distribution data by contacting the surface of a single cell with a clamping device and applying and maintaining a preset calibrated pressure on the surface of the single cell. The end of the battery manufacturing process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. The controller is configured to: The two-dimensional stress distribution data are calculated to determine characteristic parameters; these characteristic parameters are used to characterize the degree of stress non-uniformity. If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

[0013] The battery screening method according to embodiments of this application includes: Two-dimensional stress distribution data collected by a thin-film pressure sensor is obtained. The two-dimensional stress distribution data is collected at the end stage of the battery production process, after the pressing device contacts the surface of the single cell and applies and maintains a preset calibration pressure on the surface of the single cell. The end stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. The two-dimensional stress distribution data are calculated to determine characteristic parameters; these characteristic parameters are used to characterize the degree of stress non-uniformity. If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

[0014] The battery pack according to an embodiment of this application includes at least two individual cells as described above, and each individual cell is electrically connected to the other.

[0015] A battery pack according to an embodiment of this application includes a housing and at least two battery packs as described above, each battery pack being disposed within the housing and electrically connected to each other.

[0016] The electric vehicle according to an embodiment of this application includes the battery pack described above.

[0017] The electrical device according to the embodiments of this application includes the aforementioned single battery cell.

[0018] The above technical solution has the following advantages or beneficial effects: By using a clamping device to contact the surface of a single battery cell at the end of the battery manufacturing process and applying and maintaining a preset calibration pressure on the battery surface, a thin-film pressure sensor collects two-dimensional stress distribution data of the battery under pressure. Based on the two-dimensional stress distribution data, characteristic parameters for characterizing the degree of stress non-uniformity are determined. By screening out single batteries whose characteristic parameters are less than or equal to a preset parameter threshold, qualified products without internal defects can be obtained. The screening process only requires applying the preset calibration pressure to the single battery cell, achieving non-destructive screening. The screening process can be implemented immediately at the end of the battery manufacturing process, enabling early diagnosis. The screening process does not require sampling or offline testing, achieving rapid online full inspection of battery products on the production line. Therefore, this application can be applied to various types of batteries, enabling early, non-destructive, and rapid online full inspection of internal defects of battery products on the production line at the end of the battery manufacturing process. This allows for timely, efficient, and accurate screening of qualified products without internal defects at the source of production, while rejecting defective products with internal defects, significantly improving the safety level and consistency of battery products.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application and are not considered as limitations on this application. Moreover, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of a single battery provided in an embodiment of this application.

[0022] Figure 2 This is a schematic diagram of the battery screening system provided in the embodiments of this application.

[0023] Figure 3 This is one of the flowcharts of the battery screening method provided in the embodiments of this application.

[0024] Figure 4 This is the second flowchart of the battery screening method provided in the embodiments of this application.

[0025] Figure 5 This is a schematic diagram of the battery pack structure provided in the embodiments of this application.

[0026] Figure 6 This is a schematic diagram of the battery pack structure provided in the embodiments of this application.

[0027] Figure 7 This is a schematic diagram of the battery pack structure provided in the embodiments of this application.

[0028] Figure 8 This is a schematic diagram of the electrical equipment structure provided in the embodiments of this application. Detailed Implementation

[0029] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0030] The following is combined with Figures 1 to 5 This application describes the single cell, the battery screening system, and the battery screening method.

[0031] In the mass production of lithium-ion batteries, despite increasingly precise process control, it is still difficult to completely avoid internal defects introduced by raw materials, equipment precision, or operational randomness. Typical internal defects may include: fragments of active material falling off the edges of the electrode, tearing of the electrode or separator during winding / stacking, accompanied by folding, etc.

[0032] If the above defects are not detected, the following technical problems will occur: (1) Safety hazards: The electrode may puncture the separator during the battery charge and discharge cycle, causing micro short circuit or even thermal runaway, leading to battery fire and explosion.

[0033] (2) Accelerated performance degradation: Local stress concentration areas will accelerate the growth of lithium dendrites or cause damage to the active material structure, resulting in a rapid drop in battery capacity and an abnormal increase in internal resistance.

[0034] Existing methods for detecting battery defects mainly include X-ray inspection, electrochemical inspection, and appearance and thickness inspection. However, these methods have the following limitations: (1) X-ray detection: It is not sensitive to non-metallic foreign objects (such as electrode fragments and diaphragm fragments), has blind spots, and has low detection efficiency, high equipment cost, and radiation risk.

[0035] (2) Electrochemical testing (such as EIS (Electrochemical Impedance Spectroscopy) testing): This needs to be carried out after the battery has been left to stand or formed. The testing equipment is expensive and cannot achieve immediate, 100% full inspection at the end of the battery production process. It also cannot locate the defect.

[0036] (3) Appearance and thickness inspection: It is impossible to detect subtle abnormalities in the electrode stacking structure.

[0037] Therefore, how to simultaneously achieve early, non-destructive, and rapid online full inspection of all battery products on the production line during the battery production process, so as to accurately and efficiently screen out qualified products without internal defects, is an urgent problem to be solved.

[0038] Figure 1 This is a schematic diagram of a single battery cell provided in an embodiment of this application. (Refer to...) Figure 1 This application provides a single-cell battery, wherein the characteristic parameters of the single-cell battery are less than or equal to a preset parameter threshold. The characteristic parameters are determined at the end of the battery production process, after a pressing device contacts the surface of a single cell and applies and maintains a preset calibrated pressure on the surface of the single cell, and then a two-dimensional stress distribution data is obtained using a thin-film pressure sensor. The characteristic parameters are used to characterize the degree of stress non-uniformity. The final stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation, or formation, but before it has entered the aging or capacity testing process.

[0039] The embodiments of this application are applicable to the internal defect diagnosis of single cells of various forms, such as pouch, prismatic, and cylindrical cells, so as to screen out qualified products without internal defects at the end of the battery production process, ensuring that qualified batteries enter the subsequent production process.

[0040] In the embodiments of this application, internal defects of batteries can be diagnosed based on the characteristic parameters of individual cells at the end stage of the battery production process (i.e., after the battery has completed liquid injection, sealing, pre-formation or final formation, and before entering the aging or capacity testing process). This allows batteries with internal defects to be identified in real time and in advance before they are put into the high-cost aging and capacity testing processes, thus preventing batteries with internal defects from being put into subsequent processes and ensuring that only qualified products enter the subsequent production processes, thereby significantly saving subsequent manufacturing costs.

[0041] In this embodiment, a high-sensitivity thin-film pressure sensor can be used to capture localized stress concentrations caused by internal structural folds, which are extremely difficult to detect macroscopically. Compared to traditional appearance or thickness detection methods, the high-sensitivity thin-film pressure sensor is extremely sensitive to anomalies in the battery's internal structure, enabling highly sensitive and accurate diagnosis of internal battery defects. This allows for accurate screening of qualified products at the end of the battery production process, ensuring that only qualified products proceed to subsequent production stages.

[0042] In some embodiments, the effective detection area of ​​the high-sensitivity thin-film pressure sensor can be greater than or equal to the area of ​​a single large surface of the battery under test. The high-sensitivity thin-film pressure sensor can be connected to the controller via a data acquisition line to transmit the acquired two-dimensional stress distribution data of the entire single large surface of the battery to the controller for characteristic parameter calculation. Based on the characteristic parameters, qualified products without internal defects are determined.

[0043] Here, the large surface on one side can refer to the outer surface with the largest area of ​​a single battery cell. When collecting two-dimensional stress distribution data under battery pressure, a thin-film pressure sensor can be attached to the large surface on one side of the battery. The two-dimensional stress distribution data collected at this time best reflects the overall uniformity of the internal electrode stacking or winding structure, and the area is large enough to facilitate the arrangement of a sensor array to cover the entire effective area.

[0044] In this embodiment, a preset calibration pressure can be applied to a single battery cell to amplify the abnormal surface stress distribution caused by internal defects. Defect-free areas exhibit uniform stress, while defective areas show localized stress concentration or stress deficiency. This embodiment utilizes a clamping device to contact the surface of a single battery cell, applying and maintaining a preset calibration pressure on the cell surface. Two-dimensional stress distribution data of the battery under pressure is then collected. Based on this data, internal defect diagnosis is performed, allowing qualified products without internal defects to be screened at the end of the battery production process for subsequent steps. This method has a wide range of applications. Compared to electrochemical detection methods, this application is completely independent of the positive electrode (lithium iron / ternary), negative electrode material, or electrolyte state (liquid, semi-solid, solid) within the battery. It is a purely physical and mechanical detection method with extremely high universality. Compared to X-ray detection methods, this application can simultaneously detect various internal battery defects such as metallic foreign objects, non-metallic foreign objects, electrode fragments, and torn or folded electrode / separator sheets, overcoming the insensitivity of X-rays to low-density foreign objects.

[0045] In some embodiments, the preset calibration pressure applied to the surface of a single cell can refer to a pressure that enables a high-sensitivity thin-film pressure sensor to achieve complete and tight physical contact with the large surface of the cell without causing any plastic deformation or damage to the internal structure of the cell (i.e., the preset calibration pressure is much lower than the yield strength of the cell), thus not damaging the cell and enabling non-destructive detection of internal defects in the cell, thereby achieving non-destructive screening of cells on the production line.

[0046] The clamping device can consist of an upper clamp and a lower clamp, and has controllable pressure application and pressure maintenance functions. A diaphragm pressure sensor can be fixed to the inner surface of the upper clamp or the inner surface of the lower clamp, and connected to the controller via a data acquisition cable.

[0047] In some embodiments, the individual battery cells can be conveyed to the testing station via a conveyor belt or a robotic arm, allowing them to be stably placed on the lower clamping plate. After ensuring that the large surface of the individual battery cell is parallel and aligned with the plane of the thin-film pressure sensor, the clamping device can be activated to drive the upper clamping plate downwards at a constant speed until the upper clamping plate contacts the large surface of the battery. A preset, uniform calibration pressure P0 is then applied and maintained. After the preset calibration pressure P0 is stabilized, the two-dimensional stress distribution data of the individual battery cell under pressure can be obtained by scanning and acquiring data using the thin-film pressure sensor.

[0048] In this embodiment, the shape of the clamping plate of the clamping device can be adjusted based on the battery shape of the individual battery. For example, for cylindrical batteries, the clamping plate of the clamping device can be designed as an arc-shaped clamp. Therefore, this embodiment can be applied to the internal defect diagnosis of batteries of different shapes, and has a wide range of applications.

[0049] In this embodiment, the preset calibration pressure applied to the battery under test can be less than the battery damage threshold, so as not to damage the battery and thus achieve non-destructive screening.

[0050] Two-dimensional stress distribution data can refer to the data distributed across the entire battery surface according to spatial coordinates. Recorded Stress matrix Two-dimensional stress distribution data is stored in the form of a pixel array, which quantifies the real-time pressure value experienced by each tiny area on the battery surface.

[0051] Stress non-uniformity refers to the extent to which stress deviates from a uniform distribution on the battery surface. This non-uniformity can be characterized by characteristic parameters, which can be statistical quantities or composite indices extracted from two-dimensional stress distribution data to quantify the degree of stress non-uniformity. A larger characteristic parameter indicates a more non-uniform stress distribution on the battery surface, while a smaller characteristic parameter indicates a more uniform stress distribution.

[0052] In this embodiment, calculations can be performed based on two-dimensional stress distribution data to determine characteristic parameters characterizing the degree of stress non-uniformity. Based on the comparison between these characteristic parameters and preset parameter thresholds, individual cells on the production line can be screened. If the characteristic parameters of a single cell are less than or equal to the preset parameter threshold, it indicates that the cell is a qualified product without internal defects and can proceed to subsequent production processes. If the characteristic parameters of a single cell are greater than the preset parameter threshold, it indicates that the cell is a defective product with internal defects and cannot proceed to subsequent production processes.

[0053] This application's embodiments, at the end of the battery manufacturing process, utilize a clamping device to contact the surface of a single battery cell, apply and maintain a preset calibration pressure on the battery surface, and then use a thin-film pressure sensor to collect two-dimensional stress distribution data of the battery under pressure. Based on the two-dimensional stress distribution data, characteristic parameters characterizing the degree of stress non-uniformity are determined. By screening out single batteries whose characteristic parameters are less than or equal to a preset parameter threshold, qualified products without internal defects can be obtained. The screening process only requires applying the preset calibration pressure to the single battery cell, achieving non-destructive screening. The screening process can be implemented immediately at the end of the battery manufacturing process, enabling early diagnosis. The screening process does not require sampling or offline testing, achieving rapid online full inspection of battery products on the production line. Therefore, this application can be applied to various battery types, enabling early, non-destructive, and rapid online full inspection of internal defects in battery products on the production line at the end of the battery manufacturing process. This allows for timely, efficient, and accurate screening of qualified products without internal defects at the source of production, while rejecting defective products with internal defects, significantly improving the safety level and consistency of battery products.

[0054] Based on any of the above embodiments, the characteristic parameters include at least one of stress range, stress variance, and stress standard deviation.

[0055] In some embodiments, the characteristic parameter can be at least one of stress range, stress standard deviation, and stress variance. Different preset parameter thresholds may correspond to different characteristic parameters.

[0056] In some embodiments, a comprehensive screening can be performed based on the comparison results of multiple characteristic parameters with their respective preset parameter thresholds to determine whether a single cell is a qualified cell. By using multiple stress characteristic parameters for comprehensive screening, the limitations of screening qualified products based on a single characteristic parameter can be avoided, which is conducive to improving the accuracy of internal defect diagnosis of batteries. This allows for more precise screening of qualified products without internal defects, preventing defective products from entering subsequent production processes.

[0057] Based on any of the above embodiments, the stress range is calculated in the following manner: Determine the maximum and minimum stress values ​​in the two-dimensional stress distribution data; The stress range is calculated based on the maximum and minimum stress values.

[0058] When defects such as localized protrusions, voids, or electrode wrinkles exist inside a battery, the area containing these defects will experience significant stress anomalies under external pressure. For example, stress concentration (local maximum values) may occur at protrusions, while stress may be absent (local minimum values) at voids or gaps. The stress range is thus significantly amplified, and its value directly reflects the degree of localized stress concentration caused by the uniformity of the battery's internal structure. Therefore, the characteristic parameter of this application embodiment can be the stress range, thereby screening qualified batteries based on the stress range at the end of the production process. If the battery's stress range is less than or equal to a preset range threshold, the battery is considered qualified and can proceed to subsequent production processes; if the battery's stress range is greater than the preset range threshold, the battery is considered defective and cannot proceed to subsequent production processes.

[0059] In some embodiments, when the characteristic parameter is the stress range, the characteristic parameter can be calculated using the following formula. : ; in, This is two-dimensional stress distribution data. This represents the maximum stress value in the two-dimensional stress distribution data. This represents the minimum stress value in the two-dimensional stress distribution data. These are characteristic parameters.

[0060] This application embodiment calculates the stress range based on two-dimensional stress distribution data. At the end of the production process, qualified batteries are screened based on the stress range. The calculation method is simple and fast, making it suitable for online rapid initial screening of battery products on the production line. Moreover, it is very sensitive to local extreme internal defects such as hard points, foreign objects, and obvious bulges. It can effectively detect local abnormal stress concentration points that are easily smoothed out by other characteristic parameters, thereby reducing the risk of missing defective products.

[0061] Based on any of the above embodiments, the stress variance is calculated in the following manner: Based on the two-dimensional stress distribution data, the average stress is calculated; Based on the two-dimensional stress distribution data and the average stress, the stress variance is calculated.

[0062] When a battery has distributed defects such as wavy wrinkles, uneven expansion, or localized loosening within the electrode, the stress is no longer uniform. Stress measurements at various locations on the battery surface will deviate to varying degrees, increasing the stress variance. Stress variance is sensitive to overall dispersion and can capture cumulative non-uniformity. It measures the sum of squares of the deviations of stress values ​​at all points on the entire battery surface from the average value. Therefore, the characteristic parameter in this embodiment can be stress variance, allowing for the screening of qualified batteries at the end of the production process. If the battery's stress variance is less than or equal to a preset variance threshold, the battery is considered qualified and can proceed to subsequent production processes; if the battery's stress variance is greater than the preset variance threshold, the battery is considered defective and cannot proceed to subsequent production processes.

[0063] In some embodiments, two-dimensional stress distribution data may refer to the data distributed across the entire battery surface according to spatial coordinates. Recorded Stress matrix The stress value matrix records The stress values ​​at each measuring point can be summed and divided by the total number of measuring points to obtain the average stress. The difference between the stress value at each measuring point and the average stress can be calculated point by point. The square of each difference is then summed, and the sum of all squares is divided by the total number of measuring points to obtain the stress variance.

[0064] This application embodiment calculates the stress variance based on two-dimensional stress distribution data. At the end of the production process, qualified batteries are screened based on the stress variance. Compared with screening qualified batteries based on stress range, the stress variance is less susceptible to interference from single-point outliers and can better reflect the overall uniformity of stress distribution on the entire battery surface, thereby reducing the risk of missing defective products.

[0065] Based on any of the above embodiments, the stress standard deviation is calculated in the following manner: Based on the two-dimensional stress distribution data, the stress variance is calculated; Based on the stress variance, the stress standard deviation is calculated.

[0066] When a battery has distributed defects such as wavy wrinkles, uneven expansion, or localized porosity in its internal electrode plates, the stress is no longer uniform. Stress measurements at various locations on the battery surface will deviate to varying degrees, and the stress standard deviation will increase accordingly. The stress standard deviation characterizes the average deviation of stress from the mean stress at all points across the entire battery surface. Therefore, the characteristic parameter in this embodiment can be the stress standard deviation, allowing for the screening of qualified batteries at the end of the production process. If the battery's stress standard deviation is less than or equal to a preset standard deviation threshold, the battery is considered qualified and can proceed to subsequent production processes; if the battery's stress standard deviation is greater than the preset standard deviation threshold, the battery is considered defective and cannot proceed to subsequent production processes.

[0067] In some embodiments, after calculating the stress variance based on two-dimensional stress distribution data, the square root of the stress variance can be calculated to obtain the stress standard deviation.

[0068] This application embodiment calculates the stress standard deviation based on two-dimensional stress distribution data. At the end of the production process, qualified batteries are screened based on the stress standard deviation. Compared with screening qualified batteries based on stress range, the stress standard deviation is less susceptible to interference from single-point outliers and can better reflect the overall uniformity of stress distribution on the entire battery surface, thereby reducing the risk of missing defective products.

[0069] Based on any of the above embodiments, the preset parameter thresholds include a preset stress range threshold, a preset stress variance threshold, and a preset stress standard deviation threshold; if the stress range is less than or equal to the preset stress range threshold, or the stress variance is less than or equal to the preset stress variance threshold, or the stress standard deviation is less than or equal to the preset stress standard deviation threshold, the single cell is a qualified product.

[0070] In this embodiment of the application, a variety of characteristic parameters can be used to screen qualified batteries. As long as any characteristic parameter is less than or equal to its corresponding threshold, the single battery can be determined to be a qualified product.

[0071] Specifically, if the stress range is less than or equal to the preset stress range threshold, or the stress variance is less than or equal to the preset stress variance threshold, or the stress standard deviation is less than or equal to the preset stress standard deviation threshold, then the single cell can be determined to be a qualified product.

[0072] If the stress range is greater than the preset stress range threshold, the stress variance is greater than the preset stress variance threshold, and the stress standard deviation is greater than the preset stress standard deviation threshold, then the single cell can be determined to be a defective product.

[0073] This application embodiment determines that a single cell is a qualified product when any one of the characteristic parameters, stress range, stress variance, and stress standard deviation, is less than or equal to the corresponding threshold. This can reduce the false rejection of qualified products and prevent defective products from entering subsequent production processes.

[0074] Based on any of the above embodiments, the preset parameter thresholds include a preset stress range threshold, a preset stress variance threshold, and a preset stress standard deviation threshold; when the stress range is less than or equal to the preset stress range threshold, the stress variance is less than or equal to the preset stress variance threshold, and the stress standard deviation is less than or equal to the preset stress standard deviation threshold, the single cell is a qualified product.

[0075] In the embodiments of this application, multiple characteristic parameters can be used to screen qualified batteries. Only when each characteristic parameter is less than or equal to its corresponding threshold is the single cell determined to be a qualified product.

[0076] Specifically, if the stress range is less than or equal to the preset stress range threshold, the stress variance is less than or equal to the preset stress variance threshold, and the stress standard deviation is less than or equal to the preset stress standard deviation threshold, then the single cell can be determined to be a qualified product.

[0077] In another embodiment, when screening qualified batteries using multiple characteristic parameters, a single battery can be determined as a qualified product if at least two characteristic parameters are less than or equal to their respective thresholds. For example, assuming the stress range is less than a preset range threshold and the stress variance is greater than a preset variance threshold, it can be determined that the single battery has internal defects and is a defective product.

[0078] In some embodiments, a critical threshold that can distinguish between batteries with internal defects (i.e., defective products) and batteries without internal defects (i.e., qualified products) can be pre-calibrated through experiments, and the critical threshold is used as a preset parameter threshold.

[0079] This application embodiment determines whether a single cell is a qualified product without internal defects by comparing the characteristic parameters with preset parameter thresholds, thereby achieving automated and quantitative screening of qualified products and eliminating subjective errors caused by human experience.

[0080] This application embodiment determines that only batteries with uniform stress distribution across multiple characteristic dimensions are qualified products. This avoids the limitations of diagnosis based on a single characteristic parameter, eliminates any form of defective battery to the greatest extent, avoids the risk of missing defective products, and improves the consistency and safety level of batteries leaving the factory.

[0081] Based on any of the above embodiments, the single battery cell is a prismatic battery or a pouch battery; When the battery is a prismatic battery, the preset calibration pressure is 0.5~5 kPa; When the battery is a pouch cell, the preset calibration pressure is 1~15 kPa.

[0082] In this embodiment, the preset calibration pressure can be less than the battery damage threshold, so the screening process does not need to damage the battery, thereby achieving non-destructive screening of qualified batteries.

[0083] In this embodiment, the range of the preset calibration pressure can be determined based on the battery packaging form, and the specific value of the preset calibration pressure can be determined through calibration experiments.

[0084] For pouch batteries, the preset calibration pressure P0 can range from 0.5 to 5 kPa. Because the pouch battery casing is flexible, it is easier to transmit the mechanical response of internal defects. Therefore, a higher calibration pressure (1 to 15 kPa) can be used to ensure that the sensor is in close contact with the battery surface without damaging the internal structure.

[0085] For prismatic batteries, the preset calibration pressure P0 can be set between 1 and 15 kPa. Since the prismatic battery has a relatively high shell rigidity, the surface stress changes caused by internal defects are relatively weak. Therefore, a lower calibration pressure (0.5 to 5 kPa) can be used to avoid insufficient sensor contact due to insufficient pressure, while also preventing excessive pressure from masking subtle local stress differences.

[0086] In some embodiments, the specific value of the preset calibration pressure can be determined through calibration experiments.

[0087] This application embodiment sets predetermined calibration pressure ranges for batteries with different packaging forms, which can maximize the excitation and transmission effect of internal defects on stress distribution signals while ensuring battery safety. This is beneficial to improving the sensitivity of internal defect detection, avoiding missed detection of defective batteries, and improving the accuracy of battery screening.

[0088] Based on any of the above embodiments, the single cell is a solid-state battery, a semi-solid-state battery, or a liquid battery.

[0089] The embodiments of this application can be uniformly applied to the internal defect diagnosis of solid-state, semi-solid-state and liquid batteries, thereby enabling the screening of qualified batteries with different electrolyte forms without changing the detection equipment or algorithm, and has good versatility.

[0090] Figure 2 This is a schematic diagram of the battery screening system provided in an embodiment of this application. (Refer to...) Figure 2 This application provides a battery screening system, including: The thin-film pressure sensor 210 is used to collect two-dimensional stress distribution data after contacting the surface of a single cell with a clamping device at the end stage of the battery production process and applying and maintaining a preset calibrated pressure on the surface of the single cell. The end stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. Controller 220, the controller being configured to: The two-dimensional stress distribution data are calculated to determine characteristic parameters; these characteristic parameters are used to characterize the degree of stress non-uniformity. If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

[0091] Based on any of the above embodiments, the controller is further configured to: If the characteristic parameter is greater than a preset parameter threshold, the single cell is determined to be defective.

[0092] In this embodiment of the application, if the characteristic parameter is greater than the preset parameter threshold, it can indicate that the unevenness of the two-dimensional stress distribution of the single cell under pressure exceeds the normal fluctuation range, and there is a defect inside the cell that causes stress concentration or loss. Thus, the single cell is determined to be a defective product, realizing the automatic identification and rejection of defective products.

[0093] The embodiments of this application can quickly and accurately identify batteries with internal defects from the production line, preventing defective products from flowing into subsequent high-cost processes, thereby reducing manufacturing costs and improving the safety of outgoing products.

[0094] Based on any of the above embodiments, after determining that the single battery cell is defective, the controller is further configured to: Based on the two-dimensional stress distribution data, areas of abnormal stress distribution are identified; Based on the abnormal stress distribution area, the location of the internal defect in the defective product is determined.

[0095] Two-dimensional stress distribution data can refer to the data distributed across the entire battery surface according to spatial coordinates. Recorded Stress matrix The stress value matrix records The stress value at each measuring point. In some embodiments, a normal range of stress values ​​can be set, abnormal measuring points whose stress values ​​are not within the normal range can be identified, and the location of these abnormal measuring points can be defined as an abnormal stress distribution area, thereby determining the location of internal defects in the defective product based on the abnormal stress distribution area.

[0096] In some embodiments, the normal range of stress values ​​can be set based on the mean stress and the standard deviation of stress. For example, the normal range of stress values ​​can be [mean stress - k times the standard deviation of stress, mean stress + k times the standard deviation of stress]. Here, k can be a positive number.

[0097] This application embodiment determines the stress distribution anomaly region based on two-dimensional stress distribution data. The stress distribution anomaly region can intuitively display the location of stress concentration (i.e., the coordinates of the local highest stress point), which can provide accurate spatial positioning information for subsequent internal battery defect analysis, facilitating process traceability and improvement.

[0098] Based on any of the above embodiments, after determining that the single cell is a defective product, the controller can also be configured to: determine the type of internal defect based on the two-dimensional stress distribution data.

[0099] In some embodiments, a finite element simulation model of the battery structure can be established, and the geometric parameters of different types of internal defects in the battery can be input to simulate the surface stress distribution characteristics of the battery corresponding to different types of internal defects. During the battery production process, the simulated surface stress distribution characteristics of the battery can be matched with the real-time acquired two-dimensional stress distribution data to achieve internal defect type identification.

[0100] In another embodiment, the acquired two-dimensional stress distribution data (numerical matrix) can be converted into a stress distribution image, with different stress values ​​corresponding to different colors. A deep learning-based visual detection algorithm is used to train the model on stress distribution images corresponding to a large number of batteries with known defect types, enabling it to automatically learn the spatial stress pattern features corresponding to different defects from the stress distribution images. After training, the stress distribution image of a single battery cell can be input into the model, and the model can output defect type classification results, achieving end-to-end detection of all internal defect types.

[0101] Specifically, the visual inspection model can employ a convolutional neural network (CNN) model. A large number of sample stress distribution images of batteries can be pre-acquired, labeled with corresponding internal defect type tags. Based on the sample data and the corresponding internal defect type tags, the CNN model is trained to obtain a pre-trained internal defect type recognition model. During battery production, the real-time stress distribution image of a single battery cell can be directly input into the pre-trained internal defect type recognition model to obtain the internal defect type output by the model, achieving end-to-end determination of battery internal defect types without the need for manually setting parameter thresholds. The internal defect type tags can include tags for no internal defect, as well as tags for various internal defect types such as active material fragments falling off the electrode edges, and tears accompanied by folding during the winding / stacking process of electrodes or separators.

[0102] This application embodiment determines the type of internal defects based on two-dimensional stress distribution data. Without disassembly or additional means such as X-rays, it can quickly provide specific battery internal defect category information for production traceability, which is beneficial for guiding process improvement and accurate sorting.

[0103] Based on any of the above embodiments, the system further includes a sorting device; the controller is further configured to: The sorting device is controlled to sort qualified and defective products.

[0104] In this embodiment, the downstream sorting device can be controlled to automatically separate batteries determined to have internal defects (defective products) and batteries determined to have no internal defects (qualified products) into different channels, thereby achieving the sorting of qualified and defective products in the battery production process and preventing defective products from flowing into subsequent production processes.

[0105] Based on any of the above embodiments, the system further includes a re-inspection device; the controller is further configured to: The re-inspection device is controlled to re-inspect the defective product, and the preset parameter threshold is adjusted based on the re-inspection results.

[0106] In this embodiment of the application, a second precise inspection can be performed on batteries (i.e. defective products) that have been initially determined to have internal defects by a re-inspection device to obtain the true internal defect diagnosis results, thereby verifying whether the battery screening results based on feature parameters are accurate, and optimizing the preset parameter thresholds.

[0107] In some embodiments, the false detection rate of qualified products under the current preset parameter threshold can be statistically analyzed over a period of time; if the false detection rate is greater than the preset false detection rate threshold, the current preset parameter threshold can be optimized and adjusted to improve the accuracy of subsequent diagnosis.

[0108] This application embodiment controls a re-inspection device to re-inspect defective products, and adjusts the preset parameter threshold based on the re-inspection results, which helps to gradually improve the accuracy of defective product identification in the battery production process.

[0109] To enable those skilled in the art to better understand the embodiments of this application, a specific embodiment is described below.

[0110] Figure 3 This is one of the flowcharts illustrating the battery screening method provided in this application. (Refer to...) Figure 3 This application provides a battery screening method, which may specifically include the following steps: Step 301: Obtain two-dimensional stress distribution data collected by a thin-film pressure sensor; the two-dimensional stress distribution data is collected at the end stage of the battery production process, after the pressing device contacts the surface of the single cell and applies and maintains a preset calibration pressure on the surface of the single cell; the end stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. Step 302: Calculate the two-dimensional stress distribution data to determine characteristic parameters; the characteristic parameters are used to characterize the degree of stress non-uniformity. Step 303: If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

[0111] This application's embodiments, at the end of the battery manufacturing process, utilize a clamping device to contact the surface of a single battery cell, apply and maintain a preset calibration pressure on the battery surface, and then use a thin-film pressure sensor to collect two-dimensional stress distribution data of the battery under pressure. Based on the two-dimensional stress distribution data, characteristic parameters characterizing the degree of stress non-uniformity are determined. By screening out single batteries whose characteristic parameters are less than or equal to a preset parameter threshold, qualified products without internal defects can be obtained. The screening process only requires applying the preset calibration pressure to the single battery cell, achieving non-destructive screening. The screening process can be implemented immediately at the end of the battery manufacturing process, enabling early diagnosis. The screening process does not require sampling or offline testing, achieving rapid online full inspection of battery products on the production line. Therefore, this application can be applied to various battery types, enabling early, non-destructive, and rapid online full inspection of internal defects in battery products on the production line at the end of the battery manufacturing process. This allows for timely, efficient, and accurate screening of qualified products without internal defects at the source of production, while rejecting defective products with internal defects, significantly improving the safety level and consistency of battery products.

[0112] Figure 4 This is a second schematic flowchart of the battery screening method provided in this application embodiment. (Refer to...) Figure 4 In one specific embodiment, the battery screening method may include the following steps: Step 1: Preparation of the testing station.

[0113] At the end of the battery manufacturing process (i.e., after the battery has completed electrolyte filling, sealing, pre-formation, or final formation, and before entering the aging or capacity testing process), a dedicated internal defect inspection station is set up. This inspection station includes: Clamping device: Composed of an upper clamping plate and a lower clamping plate, it has the function of controllable pressure application and holding.

[0114] High-sensitivity thin-film pressure sensor: The effective detection area of ​​the thin-film pressure sensor is greater than or equal to the large surface area of ​​one side of the battery under test. The thin-film pressure sensor is fixed to the inner surface of the upper or lower clamping plate and connected to the data processing unit (computer or embedded system) of the controller via a data acquisition line.

[0115] Step 2: Battery positioning and initial contact.

[0116] The battery to be tested (applicable to prismatic, pouch, solid / semi-solid / liquid batteries) is transported to the testing station via a conveyor belt or robotic arm, and the battery to be tested is placed stably on the lower clamping plate, ensuring that the large surface of the battery to be tested is parallel and aligned with the plane where the thin-film pressure sensor is located.

[0117] Step 3: Apply the calibrated pressure.

[0118] Start the clamping device and drive the upper clamping plate to move downwards at a constant speed until it contacts the large surface of the battery. Continue to apply and maintain a preset, uniform calibration pressure P0. The setting principle of the calibration pressure P0 can be: (1) sufficient to achieve complete and tight physical contact between the thin film pressure sensor and the large surface of the battery. (2) not to cause any plastic deformation or internal structural damage to the battery (i.e., the pressure value is much lower than the yield strength of the battery).

[0119] Typical value range: For pouch cells, P0 is 0.5-5 kPa; for prismatic cells, P0 is 1-15 kPa. Specific values ​​can be determined through calibration experiments.

[0120] Step 4: Collect stress distribution data across the entire field.

[0121] After maintaining the calibrated pressure P0 stable, the data processing unit controls a high-sensitivity thin-film pressure sensor to scan and acquire two-dimensional matrix data of stress distribution across the entire battery surface. This data, presented in pixel form, quantifies the real-time pressure values ​​experienced by each tiny area on the battery surface.

[0122] Step 5: Calculation of stress characteristic parameters.

[0123] The data processing unit processes the acquired stress distribution matrix. Perform calculations to extract characteristic parameters that can characterize the degree of stress non-uniformity. .

[0124] For example, in the feature parameters Under extreme stress conditions, characteristic parameters The calculation formula can be: ; in, This is two-dimensional stress distribution data. This represents the maximum stress value in the two-dimensional stress distribution data. This represents the minimum stress value in the two-dimensional stress distribution data. For characteristic parameters. The stress range can directly reflect the degree of local stress concentration caused by the uniformity of the battery's internal structure.

[0125] In other example schemes, feature parameters Stress variance or stress standard deviation can also be used.

[0126] Step Six: Threshold Comparison and Defect Judgment.

[0127] The calculated feature parameters With a preset parameter threshold obtained through a large number of qualified and internally defective battery samples. Comparison: like If the internal structure of the battery is uniform and there are no significant defects, it is considered a qualified product.

[0128] like If the battery has internal defects (such as foreign objects, torn or folded electrodes / separators), it is considered a suspected defective product.

[0129] Step 7: Result Output and Sorting.

[0130] Based on the judgment results, the downstream sorting device automatically separates qualified products from suspected defective products into different channels. For suspected defective products, further disassembly analysis or X-ray verification is performed to verify the accuracy of the diagnostic results and optimize the preset parameter thresholds. .

[0131] Compared with the prior art, the technical solution provided in this application has the following significant advantages: (1) Non-destructive and early detection: The internal defect diagnosis process applies pressure far below the battery damage threshold without damaging the battery. The diagnosis process can be completed at the end of the battery production process, identifying batteries with internal defects before they undergo high-cost aging and capacity testing processes, thus significantly saving subsequent manufacturing costs.

[0132] (2) High sensitivity and accuracy: High-sensitivity thin-film pressure sensors are used to capture local stress concentration phenomena that are extremely difficult to detect macroscopically, caused by tiny internal foreign objects or structural folds. The stress difference index has a clear physical meaning and is extremely sensitive to abnormalities in the internal structure of the battery, with a diagnostic accuracy rate superior to traditional appearance or thickness detection methods.

[0133] (3) Extremely wide range of applications: Applicable to various battery types: This application is applicable to various battery types, including pouch cells and prismatic cells, requiring only adjustment of the clamping plate shape. For cylindrical cells, the clamping plate shape can be designed as an arc-shaped clamp.

[0134] Independent of chemical system: This application is completely independent of the positive electrode (lithium iron / ternary), negative electrode material or electrolyte form (liquid, semi-solid, solid) inside the battery. It belongs to a pure physical and mechanical testing method and has strong universality.

[0135] Capable of identifying various types of internal defects: This application can simultaneously detect a variety of battery internal defects such as metallic foreign objects, non-metallic foreign objects, electrode fragments, and torn and folded electrode / separator, overcoming the disadvantage that X-rays are not sensitive to low-density foreign objects.

[0136] (4) Fast and online full inspection capability: The data acquisition time of a single data acquisition is usually within 0.1-1 seconds. The data acquisition time of the data acquisition equipment can be matched with the cycle time of the battery production line, realizing 100% online full inspection without sampling or offline.

[0137] (5) Location and traceability: Two-dimensional stress distribution data It can intuitively display the location of stress concentration (i.e., the coordinates of the local highest stress point), which can provide accurate spatial positioning information for subsequent defect analysis, facilitating process traceability and improvement.

[0138] Two specific examples are provided below.

[0139] Example 1: Detection of aluminum foil fragments inside a square-shell lithium iron phosphate battery.

[0140] Battery type: 100Ah prismatic lithium iron phosphate (LFP) battery, which has completed electrolyte filling and pre-formation.

[0141] Detection parameters: A high-sensitivity thin-film pressure sensor with an effective area of ​​200mm × 150mm was used. The calibration pressure P0 was set to 8kPa. The preset parameter thresholds were determined through calibration experiments using 500 sets of qualified samples and 100 sets of known defective samples (containing 1mm × 2mm fragments inside). =4.2kPa.

[0142] Testing process: The battery to be tested is transferred to the workstation, where it is supported by the lower clamp.

[0143] Press down the upper clamping plate to maintain a pressure of 8 kPa.

[0144] A thin-film sensor collects two-dimensional stress distribution data. A qualified battery exhibits uniform stress distribution, with a maximum value of approximately 5.1 kPa and a minimum value of approximately 2.0 kPa. Calculations show D = 3.1 kPa ≤ 4.2 kPa, thus classifying the battery as qualified.

[0145] The data collected from a certain battery under test showed that the maximum stress value was 9.8 kPa, located in the center-left region of the battery, and the minimum stress value was 1.5 kPa at the edge. The calculated stress D = 8.3 kPa > 4.2 kPa.

[0146] Result: The system automatically marked the battery as defective and rejected it. Subsequent disassembly and verification of the battery revealed a fragment of aluminum foil, approximately 1.5mm × 2.5mm, at the location corresponding to the maximum stress, confirming the effectiveness of the method.

[0147] Example 2: Detection of tearing and folding of the separator in a soft-pack ternary lithium battery.

[0148] Battery subject: 50Ah soft-pack ternary lithium battery (NCM622), which has completed final formation.

[0149] Detection parameters: A thin-film sensor with an effective area of ​​150mm × 120mm was used. The calibration pressure was set to P0 = 3kPa. This was determined through calibration experiments. =2.5kPa.

[0150] Testing process: The pouch battery is placed flat on the lower clamping plate, and a pressure of 3 kPa is applied to the upper clamping plate.

[0151] Data collection shows that the stress range D of qualified products is usually between 1.0 and 2.0 kPa.

[0152] A battery indicator shows that there is a linear high-stress band near the tab side, with a maximum stress of 5.1 kPa, a minimum stress of 1.2 kPa, and a stress range D of 3.9 kPa, which exceeds the preset parameter threshold.

[0153] Result: The system automatically marked the battery as defective and rejected it. Subsequent disassembly revealed a tear in the separator in the area corresponding to the maximum stress, with the tear edge folded over, causing this area to be significantly higher than the surrounding area. This method successfully detected the defect.

[0154] Figure 5 This is a schematic diagram of the battery pack structure provided in an embodiment of this application. (Refer to...) Figure 5 This application provides a battery pack 500, which includes at least two individual cells 510, and each individual cell 510 is electrically connected to each other.

[0155] Figure 6 This is a schematic diagram of the battery pack structure provided in an embodiment of this application. (Refer to...) Figure 6This application provides a battery pack 600, which includes a housing 610 and at least two battery packs 620. Each battery pack 620 is disposed inside the housing 610 and is electrically connected to each other.

[0156] Figure 7 This is a schematic diagram of the battery pack structure provided in an embodiment of this application. (Refer to...) Figure 7 This application provides an electric vehicle 700, which includes a battery pack 600.

[0157] Figure 8 This is a schematic diagram of the electrical equipment structure provided in an embodiment of this application. (Refer to...) Figure 8 This application provides an electrical device 800, which includes the aforementioned single battery 810.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate this application and are not intended to limit this application. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application and should be covered within the scope of the claims of this application.

Claims

1. A single-cell battery, characterized in that, The characteristic parameters of the individual battery cell are less than or equal to a preset parameter threshold. The characteristic parameters are determined by calculating the two-dimensional stress distribution data obtained by a thin-film pressure sensor after the surface of a single cell is contacted by a clamping device at the end of the battery production process and a preset calibrated pressure is applied and maintained on the surface of the single cell. The characteristic parameters are used to characterize the degree of stress non-uniformity; The final stage of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation, or formation, but before it has entered the aging or capacity testing process.

2. The single-cell battery according to claim 1, characterized in that, The characteristic parameters include at least one of stress range, stress variance, and stress standard deviation.

3. The single-cell battery according to claim 2, characterized in that, The stress range is calculated in the following way: Determine the maximum and minimum stress values ​​in the two-dimensional stress distribution data; The stress range is calculated based on the maximum and minimum stress values.

4. The single-cell battery according to claim 2, characterized in that, The stress variance is calculated in the following way: Based on the two-dimensional stress distribution data, the average stress is calculated; Based on the two-dimensional stress distribution data and the average stress, the stress variance is calculated.

5. The single-cell battery according to claim 2, characterized in that, The stress standard deviation is calculated in the following way: Based on the two-dimensional stress distribution data, the stress variance is calculated; Based on the stress variance, the stress standard deviation is calculated.

6. The single-cell battery according to any one of claims 2-5, characterized in that, The preset parameter thresholds include preset stress range threshold, preset stress variance threshold, and preset stress standard deviation threshold; The individual cell is considered a qualified product if the stress range is less than or equal to the preset stress range threshold, or the stress variance is less than or equal to the preset stress variance threshold, or the stress standard deviation is less than or equal to the preset stress standard deviation threshold.

7. The single-cell battery according to any one of claims 2-5, characterized in that, The preset parameter thresholds include preset stress range threshold, preset stress variance threshold, and preset stress standard deviation threshold; The individual cell is considered qualified if the stress range is less than or equal to the preset stress range threshold, the stress variance is less than or equal to the preset stress variance threshold, and the stress standard deviation is less than or equal to the preset stress standard deviation threshold.

8. The single-cell battery according to claim 1, characterized in that, The individual battery is a prismatic battery or a pouch battery. When the battery is a prismatic battery, the preset calibration pressure is 0.5~5 kPa; When the battery is a pouch cell, the preset calibration pressure is 1~15 kPa.

9. The single-cell battery according to claim 1, characterized in that, The individual battery is a solid-state battery, a semi-solid-state battery, or a liquid battery.

10. A battery sorting system, characterized in that, include: A thin-film pressure sensor is used at the end of the battery manufacturing process to collect two-dimensional stress distribution data by contacting the surface of a single cell with a clamping device and applying and maintaining a preset calibrated pressure on the surface of the single cell. The end of the battery manufacturing process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. The controller is configured to: The two-dimensional stress distribution data are calculated to determine characteristic parameters; these characteristic parameters are used to characterize the degree of stress non-uniformity. If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

11. The battery sorting system according to claim 10, characterized in that, The controller is also configured to: If the characteristic parameter is greater than a preset parameter threshold, the single cell is determined to be defective.

12. The battery sorting system according to claim 11, characterized in that, After determining that the individual battery cell is defective, the controller is further configured to: Based on the two-dimensional stress distribution data, areas of abnormal stress distribution are identified; Based on the abnormal stress distribution area, the location of the internal defect in the defective product is determined.

13. The battery sorting system according to claim 11, characterized in that, After determining that the individual battery cell is defective, the controller is further configured to: Based on the two-dimensional stress distribution data, the type of internal defect is determined.

14. The battery sorting system according to claim 11, characterized in that, The system also includes a re-inspection device; the controller is further configured to: The re-inspection device is controlled to re-inspect the defective product, and the preset parameter threshold is adjusted based on the re-inspection results.

15. The battery sorting system according to any one of claims 11-14, characterized in that, The system also includes a sorting device; the controller is further configured to: The sorting device is controlled to sort qualified and defective products.

16. A battery screening method, characterized in that, include: Acquire two-dimensional stress distribution data collected by a thin-film pressure sensor; The two-dimensional stress distribution data is collected at the end of the battery production process by using a clamping device to contact the surface of a single cell and applying and maintaining a preset calibrated pressure on the surface of the single cell. The end of the battery production process is the stage after the battery has completed liquid injection, sealing, pre-formation or formation, but before it has entered the aging or capacity testing process. The two-dimensional stress distribution data are calculated to determine characteristic parameters; these characteristic parameters are used to characterize the degree of stress non-uniformity. If the characteristic parameter is less than or equal to a preset parameter threshold, the single cell is determined to be a qualified product.

17. A battery pack, characterized in that, It includes at least two individual cells as described in any one of claims 1 to 9 above, and each of the individual cells is electrically connected to the other.

18. A battery pack, characterized in that, It includes a housing and at least two battery packs as described in claim 17, each battery pack being disposed within the housing and electrically connected to each other.

19. An electric vehicle, characterized in that, Includes the battery pack described in claim 18.

20. An electrical appliance, characterized in that, The single cell includes any one of claims 1-9 above.

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