Ternary lithium battery electrode material interface bonding force testing method and system

Abstract

The invention relates to a ternary lithium battery electrode material interface bonding force test method and system, and relates to the technical field of lithium battery interface test.The method comprises the steps that the interface performance requirements of ternary lithium battery electrodes in batches are obtained, and an interface electrochemical test scheme and an interface mechanical test scheme are configured according to the interface performance requirements; testing the batch of electrodes through an interface electrochemical test scheme to obtain an electrode interface electrochemical test data set; grouping and sampling the batch electrodes based on the data set to obtain a plurality of electrode sampling groups; testing the sampling group through an interface mechanical test scheme to obtain an electrode interface mechanical test data set; and establishing an interface bonding force correlation model by using the two data sets, and finally obtaining an interface bonding force evaluation result of the ternary lithium battery electrodes in batches. According to the method, the problems that in the traditional test, although full-amount detection can be realized, the accuracy is insufficient in nondestructive detection, and although the precision of lossy detection is high, the cost is high, the destructiveness is strong, and the efficiency and the accuracy are difficult to consider in batch electrode interface bonding force test are solved.

Description

Technical Field

[0001] This application relates to the field of lithium battery interface testing, and in particular to a method and system for testing the interfacial bonding strength of ternary lithium battery electrode materials. Background Technology

[0002] With the rapid development of the ternary lithium battery industry, interfacial adhesion testing plays an increasingly prominent role in the quality control of mass electrode production. Existing testing methods have significant limitations: relying on non-destructive testing methods such as resistance testing, while achieving 100% full-volume testing, lacks accuracy; relying on destructive testing methods such as mechanical peel testing, while providing accurate results, is costly and destructive, making it difficult to apply to large-scale testing. This results in a situation where interfacial adhesion testing in mass electrode production cannot balance efficiency and accuracy, failing to meet the actual needs for precise assessment of electrode interface quality. Summary of the Invention

[0003] To address the aforementioned technical issues, this application provides a method and system for testing the interfacial bonding strength of ternary lithium battery electrode materials. This method improves the balance between efficiency and accuracy in batch testing of the interfacial bonding strength of ternary lithium battery electrodes, and overcomes the shortcomings of traditional nondestructive testing, such as insufficient accuracy and high cost and difficulty in batch application of destructive testing.

[0004] The embodiments of this application disclose the following technical solutions: In a first aspect, embodiments of this application provide a method for testing the interfacial bonding strength of ternary lithium battery electrode materials, the method comprising: Obtain the interface performance requirements of batch ternary lithium battery electrodes, and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements; The interface electrochemical test data of the batch of ternary lithium battery electrodes was obtained by performing interface electrochemical tests on the interface electrochemical test scheme. Based on the electrode interface electrochemical test dataset, the batch of ternary lithium battery electrodes were sampled in groups to obtain multiple electrode sampling groups. The interface mechanical testing scheme is used to perform interface mechanical testing on the multiple electrode sampling groups to obtain an electrode interface mechanical test dataset. An interfacial bonding force correlation model was established using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset to obtain the interfacial bonding force evaluation results of the batch ternary lithium battery electrodes.

[0005] Secondly, embodiments of this application provide a system for testing the interfacial bonding strength of ternary lithium battery electrode materials, the system comprising: The performance scheme configuration module is used to obtain the interface performance requirements of batch ternary lithium battery electrodes and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements. The interface electrochemical testing module is used to perform interface electrochemical testing on the batch of ternary lithium battery electrodes using the interface electrochemical testing scheme, and to obtain an electrode interface electrochemical test dataset. An electrochemical grouping sampling module is used to group and sample the batch of ternary lithium battery electrodes based on the electrode interface electrochemical test dataset to obtain multiple electrode sampling groups. The interface mechanical testing module is used to perform interface mechanical testing on the multiple electrode sampling groups through the interface mechanical testing scheme to obtain an electrode interface mechanical test dataset. The bonding force assessment module is used to establish an interface bonding force correlation model using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset to obtain the interface bonding force assessment results of the batch of ternary lithium battery electrodes.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application proposes a method and system for testing the interfacial adhesion of ternary lithium battery electrode materials. By integrating electrochemical and mechanical testing of the electrode interface, it achieves efficient and accurate evaluation of the interfacial adhesion of ternary lithium battery electrode materials. First, the interfacial performance requirements of a batch of electrodes are obtained. Based on these requirements, indicators such as interfacial resistance, interfacial stability, and interfacial peel strength are extracted, and an interfacial electrochemical testing scheme and an interfacial mechanical testing scheme are configured accordingly. After numbering all ternary lithium battery electrodes, electrochemical testing is performed using an interfacial impedance spectroscopy (IIS) detection station to obtain an electrochemical dataset containing impedance spectroscopy data for each electrode. Based on this dataset, multiple electrode sets are divided according to charge transfer resistance deviation, and multiple electrode sampling groups are obtained by differentiated sampling according to risk level. Mechanical peel tests are performed on the sampling groups to obtain interfacial peel strength data and form a mechanical dataset. An interfacial adhesion correlation model is established using the two types of test datasets. This model is used to calculate the interfacial peel strength distribution of all electrodes, and then compared with the interfacial performance requirements to evaluate the pass rate of the interfacial adhesion of the batch of electrodes, thus obtaining the final interfacial adhesion evaluation result.

[0007] This application's technical solution combines the full coverage of electrochemical testing with the precise quantification of mechanical testing. It integrates differentiated sampling in groups with correlation model calculations, solving the problems of high cost, strong destructiveness, and insufficient representativeness of partial sampling in full-scale mechanical testing. This achieves a balance between efficiency and accuracy in testing the bonding force of ternary lithium battery electrode interfaces, providing a reliable technical solution for batch electrode quality testing. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A schematic flowchart illustrating the method for testing the interfacial bonding strength of ternary lithium battery electrode materials provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of the ternary lithium battery electrode material interface bonding force testing system provided in the embodiments of this application.

[0010] The components represented by each number in the attached diagram are explained below: Performance scheme configuration module 01, interface electrochemical testing module 02, electrochemical grouping sampling module 03, interface mechanical testing module 04, and bonding force evaluation module 05. Detailed Implementation

[0011] This application provides a method and system for testing the interfacial bonding strength of ternary lithium battery electrode materials, which solves the technical problem that in the prior art, although non-destructive testing can detect the interfacial bonding strength of ternary lithium battery electrodes in full, its accuracy is insufficient, while destructive testing, although accurate, is difficult to balance in terms of cost, destructiveness, and inability to be applied in batches.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0014] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0015] Example 1, as shown in the appendix Figure 1 As shown, this application provides a method for testing the interfacial bonding strength of ternary lithium battery electrode materials, the method comprising the following steps: S110: Obtain the interface performance requirements of batch ternary lithium battery electrodes, and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements; In this embodiment of the application, in order to achieve accurate and efficient testing of interface bonding during the mass production of ternary lithium battery electrodes, it is necessary to first clarify the testing basis and customize an appropriate testing scheme.

[0016] Specifically, the interface performance requirements of batch ternary lithium battery electrodes are first obtained, and key indicators are extracted from them, including interface resistance performance indicators, interface stability indicators, and interface peel strength indicators. These indicators together constitute the core reference standard for electrochemical testing.

[0017] Furthermore, based on the extracted interfacial resistance performance index and interfacial stability index, a corresponding standard interfacial impedance spectrum is set, and an interfacial electrochemical testing scheme is configured based on this. This scheme will be used for subsequent non-destructive electrochemical characteristic detection of batch electrodes.

[0018] Meanwhile, based on the interface peel strength index, relevant parameters for mechanical peel testing are set, such as the test force range and peel speed, and then an interface mechanical testing scheme is configured to provide an operational basis for subsequent targeted destructive mechanical testing.

[0019] This step, by clarifying performance requirements and customizing two sets of test schemes accordingly, achieves targeted and adaptable testing. It provides an electrochemical testing framework for the rapid initial screening of all ternary lithium battery electrodes and a mechanical testing standard for accurate verification, laying the foundation for the overall testing process.

[0020] Step S110 in the method provided in this application embodiment includes: Based on the interface performance requirements, extract the interface resistance performance index, interface stability index, and interface peel strength index. Based on the interface resistance performance index and interface stability index, a standard interface impedance spectrum is set, and the interface electrochemical testing scheme is configured. Based on the interface peel strength index, mechanical peel test parameters are set, and the interface mechanical test scheme is configured.

[0021] In this embodiment of the application, in order to achieve a precise match between the test scheme and the electrode performance requirements in the interfacial bonding force test of batch ternary lithium battery electrodes, it is necessary to customize the test scheme by extracting core performance indicators and setting standard parameters, so as to provide a basis for subsequent full-scale testing and accurate verification.

[0022] Specifically, three key indicators were first extracted from the obtained performance requirements of the electrode interfaces of batch ternary lithium batteries: interface resistance, interface stability, and interface peel strength. These indicators are the core basis for the subsequent test scheme configuration and are directly related to the core characteristics of interface adhesion.

[0023] For example, if the interface performance requirements of a certain batch of ternary lithium battery electrodes are an interface peel strength greater than 0.5 N / cm, an interface resistance less than 10 Ω·cm², and a peel strength decrease of no more than 20% after 1000 cycles, then the interface resistance performance index extracted from it is "less than 10 Ω·cm²", the interface stability index is "peel strength decrease of no more than 20% after 1000 cycles", and the interface peel strength index is "greater than 0.5 N / cm".

[0024] Furthermore, a standard interface impedance spectrum is established based on the extracted interface resistance performance index and interface stability index.

[0025] Among them, the interfacial impedance spectrum is a key spectrum that reflects the electrochemical characteristics of the electrode interface. It contains impedance information from low frequency to high frequency and can intuitively reflect the electrochemical behavior related to interfacial resistance and stability.

[0026] Specifically, when setting the standard interface impedance spectrum, it is necessary to determine the threshold range of the corresponding resistance parameters in the impedance spectrum in combination with the interface resistance performance index, and at the same time, clarify the limit of change of the impedance spectrum after simulated cyclic testing based on the interface stability index.

[0027] For example, for the index of interface resistance less than 10 Ω·cm², the upper limit of the impedance value at the corresponding frequency is set to 10 Ω·cm² in the standard interface impedance spectrum; for the stability requirement that the peel strength decreases by no more than 20% after 1000 cycles, the characteristic parameters of the impedance spectrum change by no more than 20% after 1000 cycles of simulated testing is set in the standard interface impedance spectrum.

[0028] Furthermore, based on this standard interface impedance spectrum, an interface electrochemical testing scheme is configured to clarify parameters such as the test frequency range, scan rate, and test environment temperature, ensuring that the interface electrochemical testing scheme can accurately obtain electrochemical data reflecting the interface resistance performance and stability.

[0029] Meanwhile, mechanical peel test parameters were set based on the extracted interfacial peel strength index.

[0030] Among them, the mechanical peel test is a destructive test that directly measures the interfacial bonding strength, and the setting of its mechanical peel test parameters directly affects the accuracy and reliability of the test results. These parameters include peel angle, peel speed, and loading force range.

[0031] For example, if the interface peel strength index is greater than 0.5 N / cm, in order to ensure that this strength value can be accurately detected, the peel angle of the mechanical peel test is set to 180° so that the peel force at this angle can more directly reflect the interface bonding strength; the peel speed is 50 mm / min to avoid test errors caused by excessively fast or slow speeds; the loading force range is 0-2 N to cover the force range corresponding to 0.5 N / cm, ensuring that the force sensor can accurately capture the force value change at the moment of peeling during the test.

[0032] Finally, based on these mechanical peel test parameters, an interface mechanical test scheme was configured. By clarifying details such as the clamping method of the test fixture and the force value acquisition frequency, the interface mechanical test scheme was designed to ensure that accurate interface peel strength data could be obtained.

[0033] This step extracts core indicators from interface performance requirements and sets standard interface impedance spectra and mechanical exfoliation test parameters accordingly, enabling customized configuration of interface electrochemical and interface mechanical testing schemes. This configuration method allows the testing scheme to closely match the specific performance requirements of each batch of electrodes.

[0034] For example, when a batch of electrodes requires particularly high interfacial bonding strength, the electrochemical test criteria can be tightened by increasing the threshold requirement of the resistance parameter in the standard interfacial impedance spectrum, while increasing the sampling ratio of mechanical tests. This ensures that the test results can truly reflect the interfacial bonding strength level of the electrodes, laying a precise and suitable foundation for subsequent full-scale electrochemical testing and targeted interfacial mechanical testing.

[0035] S120: Perform interface electrochemical tests on the batch of ternary lithium battery electrodes using the aforementioned interface electrochemical testing scheme to obtain an electrode interface electrochemical test dataset. In this embodiment of the application, in the process of testing the interfacial bonding force of batch ternary lithium battery electrodes, in order to achieve preliminary screening of all electrodes and obtain complete electrochemical characteristic data, it is necessary to complete the full-scale detection through non-destructive interfacial electrochemical testing to provide data support for subsequent group sampling.

[0036] Specifically, each electrode in the batch of ternary lithium battery electrodes is first individually numbered to ensure that each electrode has a unique identifier, so as to facilitate subsequent data association and traceability.

[0037] Furthermore, using the configured interfacial impedance spectroscopy detection station, each numbered ternary lithium battery electrode is sequentially tested according to the preset interfacial electrochemical testing scheme.

[0038] Furthermore, during the testing process, the impedance response of each ternary lithium battery electrode at different frequencies is acquired, forming unique interface impedance spectrum detection data for each electrode. This data contains key information reflecting the interface resistance performance and stability.

[0039] Finally, the number of each ternary lithium battery electrode is associated with its corresponding interfacial impedance spectroscopy detection data and stored to form an electrode interface electrochemical test dataset.

[0040] This associated storage method ensures that the data can be accurately mapped to a specific electrode during subsequent analysis, making it easy to trace the electrochemical characteristics of each electrode.

[0041] This step involves numbering, non-destructively testing, and storing all ternary lithium battery electrodes to construct a complete electrochemical test dataset for the electrode interface. This not only achieves comprehensive coverage of the batch of electrodes but also lays the data foundation for subsequent targeted grouping and sampling based on electrochemical characteristics, ensuring the continuity of the testing process and the integrity of the data.

[0042] Step S120 in the method provided in this application embodiment includes: Each ternary lithium battery electrode in the batch of ternary lithium battery electrodes is assigned an electrode number to obtain the electrode number of each ternary lithium battery electrode. Each ternary lithium battery electrode is sequentially tested using an interface impedance spectroscopy detection station to obtain interface impedance spectroscopy data for each ternary lithium battery electrode. The electrode number of each ternary lithium battery electrode is associated with and stored with the corresponding interfacial impedance spectroscopy detection data to form the electrode interface electrochemical test dataset.

[0043] In this embodiment of the application, in order to achieve accurate recording and traceability of the electrochemical characteristics of all electrodes, it is necessary to construct a complete electrode interface electrochemical test dataset through systematic numbering, detection and data association storage, so as to provide a comprehensive and traceable basis for subsequent group sampling.

[0044] Specifically, each ternary lithium battery electrode in the batch is first assigned an independent electrode number to obtain a unique identifier for each ternary lithium battery electrode.

[0045] This numbering process needs to cover all ternary lithium battery electrodes in the batch, numbering in the thousands or even tens of thousands, to ensure that each electrode has a unique number. For example, they are sequentially marked as "JD-00001", "JD-00002"... "JD-XXXXX" according to the production sequence, laying the foundation for the accurate correspondence between subsequent data and electrodes.

[0046] Furthermore, using the configured interfacial impedance spectroscopy detection station, each numbered ternary lithium battery electrode is sequentially tested according to the preset interfacial electrochemical testing scheme.

[0047] The detection method uses electrochemical impedance spectroscopy, which is a non-destructive testing method that will not damage the structure and performance of the ternary lithium battery electrodes. Therefore, it can achieve 100% full detection of a batch of electrodes to ensure that no electrode is missed.

[0048] Specifically, during the testing process, the equipment records the impedance response of each ternary lithium battery electrode in different frequency ranges, forming unique interface impedance spectrum detection data for each ternary lithium battery electrode. These data contain key information reflecting interface resistance performance and interface stability, such as diffusion impedance in the low-frequency region and charge transfer resistance in the high-frequency region.

[0049] For example, during the testing of the ternary lithium battery electrode numbered "JD-02845", the frequency range recorded by the device covered from 1 mHz to 100 kHz. In the low-frequency region (1 mHz-1 Hz), the diffusion impedance of this electrode was 350 Ω·cm², reflecting the diffusion capability of lithium ions at the electrode interface; in the high-frequency region (1 kHz-100 kHz), its charge transfer resistance was 8.5 Ω·cm², which is directly related to the interface resistance performance.

[0050] Finally, the electrode number of each ternary lithium battery electrode is associated with its corresponding interfacial impedance spectroscopy detection data and stored to form an electrode interface electrochemical test dataset.

[0051] For example, in the interfacial impedance spectroscopy data corresponding to the ternary lithium battery electrode numbered "JD-03612", the impedance value is 120 Ω·cm² at 1 Hz, 25 Ω·cm² at 100 Hz, 9.2 Ω·cm² at 1000 Hz, 5.8 Ω·cm² at 10 kHz, and 3.1 Ω·cm² at 100 kHz. These data are linked to the number "JD-03612" in a spreadsheet. The first column of the spreadsheet records the electrode number, and subsequent columns correspond to the impedance values ​​at various frequency points from 1 mHz to 100 kHz, forming structured data entries and constituting a complete electrode interface electrochemical test dataset.

[0052] This step involves systematically numbering, non-destructively testing, and storing all electrodes to create a comprehensive electrochemical test dataset covering the electrode interface. This not only achieves a complete record of the electrochemical characteristics of a batch of electrodes but also ensures data traceability through numbering and association, guaranteeing the continuity of the testing process and the reliability of the data.

[0053] S130: Based on the electrode interface electrochemical test dataset, the batch of ternary lithium battery electrodes are sampled in groups to obtain multiple electrode sampling groups; In this embodiment of the application, in the process of testing the interfacial bonding force of batch ternary lithium battery electrodes, in order to achieve targeted selection of samples for interfacial mechanical testing, it is necessary to group the samples based on the electrochemical data of the full batch of electrodes, and then perform differentiated sampling according to the risk level, so as to improve the testing efficiency while ensuring the accuracy of the test.

[0054] Specifically, a standard charge transfer resistor is first set based on the standard interface impedance spectrum. This resistor is a key parameter extracted from the standard impedance spectrum and is used to reflect the baseline level of interface charge transfer.

[0055] At the same time, multiple charge transfer resistance deviation thresholds are set as boundaries for classifying electrode risk levels.

[0056] Furthermore, the interfacial impedance spectral data of each ternary lithium battery electrode were extracted from the electrode interface electrochemical test dataset, and the charge transfer test resistance of each electrode was derived from it through mathematical fitting and other methods.

[0057] Among them, the charge transfer test resistor is used to reflect the ease or difficulty of the interface charge transfer process, which is directly related to the interface bonding force.

[0058] Furthermore, based on the standard charge transfer resistance and the charge transfer test resistance of each ternary lithium battery electrode, the charge transfer resistance deviation of each electrode is calculated, thereby measuring the degree of deviation between the actual test value and the standard value.

[0059] Furthermore, based on the charge transfer resistance deviation of each ternary lithium battery electrode and multiple preset charge transfer resistance deviation thresholds, the batch of ternary lithium battery electrodes are divided into multiple ternary lithium battery electrode sets.

[0060] Meanwhile, sampling is performed in groups based on multiple sets of ternary lithium battery electrodes. That is, a higher sampling ratio is set for groups with higher risk levels, and a lower sampling ratio is set for groups with lower risk levels. This ensures that high-risk electrodes can be more fully included in mechanical testing, while reducing the testing volume of low-risk electrodes to reduce costs and losses.

[0061] Ultimately, the multiple electrode sampling groups formed through group sampling not only covered electrode samples of different risk levels, but also achieved a balance between sample representativeness and testing efficiency through differentiated proportions, providing accurate and appropriate test objects for subsequent interface mechanical testing.

[0062] Step S130 in the method provided in this application embodiment includes: The standard charge transfer resistance is set according to the standard interface impedance spectrum, and multiple charge transfer resistance deviation thresholds are set. The interfacial impedance spectrum detection data of each ternary lithium battery electrode is extracted from the electrode interface electrochemical test dataset and converted into the charge transfer test resistance of each ternary lithium battery electrode. Based on the standard charge transfer resistance and the charge transfer test resistance of each ternary lithium battery electrode, the charge transfer resistance deviation of each ternary lithium battery electrode is obtained. Based on the charge transfer resistance deviation of each ternary lithium battery electrode and the multiple charge transfer resistance deviation thresholds, the batch of ternary lithium battery electrodes is divided into multiple ternary lithium battery electrode sets. Based on the multiple sets of ternary lithium battery electrodes, the batch of ternary lithium battery electrodes are sampled in groups to obtain multiple electrode sampling groups.

[0063] In this embodiment of the application, in order to accurately select representative samples from the full amount of electrochemical data for interface mechanical testing, it is necessary to conduct scientific group sampling through key parameter extraction, deviation analysis, classification and differential sampling, so as to reduce the amount of interface mechanical testing while ensuring the representativeness of the samples, so as to balance the accuracy and efficiency of the test.

[0064] First, a standard charge transfer resistance is set based on the standard interfacial impedance spectrum. The charge transfer resistance is a key parameter extracted from the interfacial impedance spectrum through mathematical fitting; it reflects the ease or difficulty of the interfacial charge transfer process and is directly related to the interfacial bonding force.

[0065] Specifically, electrodes with good interfacial bonding facilitate charge transfer and have low charge transfer resistance; electrodes with poor interfacial bonding make charge transfer difficult and have high charge transfer resistance.

[0066] The standard charge transfer resistance is a reference value set based on interface performance requirements, such as 10Ω·cm², which serves as a reference standard for measuring whether the charge transfer characteristics of each electrode meet the standard.

[0067] At the same time, multiple charge transfer resistance deviation thresholds are set, such as 5%, 15%, 30%, and 50%, which will serve as the boundaries for classifying electrode deviation levels.

[0068] Furthermore, based on the standard charge transfer resistance and the charge transfer test resistance of each electrode, the charge transfer resistance deviation of each electrode is calculated. The specific calculation formula is "charge transfer resistance deviation = (charge transfer test resistance - standard charge transfer resistance) / standard charge transfer resistance × 100%".

[0069] For example, if the standard charge transfer resistance is 10 Ω·cm², and the charge transfer test resistance of the "JD-02845" electrode is 8.5 Ω·cm², then its charge transfer resistance deviation is (8.5-10) / 10×100%=-15%; if the charge transfer test resistance of an electrode with the number "JD-05123" is 12 Ω·cm², then its charge transfer resistance deviation is (12-10) / 10×100%=20%.

[0070] Furthermore, based on the charge transfer resistance deviation of each ternary lithium battery electrode and multiple preset charge transfer resistance deviation thresholds, the batch of ternary lithium battery electrodes are divided into multiple ternary lithium battery electrode sets.

[0071] Specifically, electrodes with charge transfer resistance deviations within the range of 0-5% (inclusive) are classified as "Level 1 set"; those with deviations within the range of 5%-15% (inclusive) are classified as "Level 2 set"; those with deviations within the range of 15%-30% (inclusive) are classified as "Level 3 set"; those with deviations within the range of 30%-50% (inclusive) are classified as "Level 4 set"; and those with deviations greater than 50% are classified as "Level 5 set".

[0072] Among them, the higher the charge transfer resistance deviation level, the greater the deviation of the charge transfer characteristics at the electrode interface from the standard value, and the higher the risk of potential interfacial bonding problems.

[0073] Furthermore, the batch electrodes are sampled in groups based on multiple ternary lithium battery electrode sets.

[0074] The method provided in this application embodiment includes the step of "grouping and sampling the batch of ternary lithium battery electrodes based on the multiple ternary lithium battery electrode sets to obtain multiple electrode sampling groups" as follows: Set the overall sampling ratio for batch ternary lithium battery electrodes, and determine the total number of electrode samples based on the overall sampling ratio and the total number of electrodes in the batch ternary lithium battery electrodes; Based on the degree of charge transfer resistance deviation corresponding to the multiple ternary lithium battery electrode sets, multiple deviation levels of the multiple ternary lithium battery electrode sets are obtained, and multiple sampling coefficients are set based on the multiple deviation levels; Multiple sampling coefficients are used as the electrode sampling ratios of multiple ternary lithium battery electrode sets. Combined with the total number of electrode samples, multiple group sampling quantities are obtained. Multiple electrode sampling groups are obtained by randomly selecting electrodes from multiple ternary lithium battery electrode sets based on multiple group sampling quantities.

[0075] In this embodiment of the application, in order to scientifically select representative samples from multiple electrode sets, it is necessary to set the overall sampling ratio, matching deviation level and sampling coefficient, calculate the number of grouped samples and randomly select samples to ensure that high-risk electrodes are covered in a key area while reducing the testing volume of low-risk electrodes, thereby reducing the interface mechanical testing cost while ensuring the representativeness of the samples.

[0076] Specifically, the overall sampling ratio for batch ternary lithium battery electrodes is first determined. This overall sampling ratio needs to consider both testing accuracy requirements and cost control objectives (e.g., set at 6.5%). Based on this overall sampling ratio and the total number of electrodes in the batch, the total number of electrode samples is calculated and determined.

[0077] For example, if the total number of ternary lithium battery electrodes in a batch is 10,000, according to the overall sampling ratio of 6.5%, the total number of electrode samples is 10,000 × 6.5% = 650, that is, 650 samples need to be selected from the full number of electrodes for interface mechanical testing.

[0078] Furthermore, based on the degree of charge transfer resistance deviation corresponding to multiple ternary lithium battery electrode sets, the deviation level corresponding to each set is determined.

[0079] Among them, the deviation level directly reflects the risk level of the electrode interface bonding force. The higher the level, the greater the deviation from the standard value and the higher the potential risk of problems.

[0080] For example, the ternary lithium battery electrode assembly is divided into 5 deviation levels: Level 1 (charge transfer resistance deviation 0-5%), Level 2 (charge transfer resistance deviation 5-15%), Level 3 (charge transfer resistance deviation 15-30%), Level 4 (charge transfer resistance deviation 30-50%), and Level 5 (charge transfer resistance deviation >50%).

[0081] Furthermore, multiple sampling coefficients are set based on these deviation levels, with the higher the deviation level, the larger the corresponding sampling coefficient, in order to achieve accurate coverage of "the higher the risk, the denser the sampling".

[0082] For example, the sampling coefficient for the Level 1 set is 0.02, indicating that the charge transfer resistance deviation of the electrodes in this set is the smallest (0-5%) and the risk of interfacial bonding is the lowest. Therefore, only 2% of the samples need to be drawn to meet the representativeness requirements, and there is no need to conduct too much mechanical testing. The Level 2 set corresponds to 0.05, indicating that its deviation is slightly higher than that of Level 1 (5-15%) and the risk is slightly higher. Therefore, the sampling ratio is appropriately increased.

[0083] Furthermore, the Level 3 set corresponds to 0.15, and due to the deviation reaching 15-30%, the risk of potential interface problems further increases, requiring a 15% sampling ratio to enhance sample coverage; the Level 4 set corresponds to 0.4, and due to the deviation being 30-50%, the risk is relatively high, requiring 40% of the samples to fully capture potential interface bonding defects; the Level 5 set corresponds to 0.7, indicating that its charge transfer resistance deviation is the largest (>50%), which is a high-risk area for interface bonding problems, therefore requiring a high sampling ratio of 70% to ensure that potential problems in this area can be fully detected.

[0084] Furthermore, multiple sampling coefficients are used as the electrode sampling ratios of multiple ternary lithium battery electrode sets. Combined with the total number of electrode samples, multiple group sampling quantities are calculated.

[0085] Specifically, a strategy of "total quantity control and weighted allocation" is adopted to determine the number of samples for each ternary lithium battery electrode set. First, the sampling weight of each set is calculated.

[0086] The sampling weight takes into account the size and risk level of each ternary lithium battery electrode set. The specific calculation formula can be expressed as "set sampling weight = number of electrodes in the set × set sampling coefficient".

[0087] For example, if the Level 1 set contains 9400 electrodes and the sampling coefficient is 0.02, then the sampling weight is 9400 × 0.02 = 188; the Level 2 set contains 500 electrodes and the sampling coefficient is 0.05, so the sampling weight is 500 × 0.05 = 25; the Level 3 set contains 300 electrodes and the sampling coefficient is 0.15, so the sampling weight is 300 × 0.15 = 45; the Level 4 set contains 150 electrodes and the sampling coefficient is 0.4, so the sampling weight is 150 × 0.4 = 60; and the Level 5 set contains 50 electrodes and the sampling coefficient is 0.7, so the sampling weight is 50 × 0.7 = 35.

[0088] Furthermore, based on the obtained sampling weights of each set, the total sampling weight is calculated by summing them up. The specific formula is "Total sampling weight = Σ set sampling weights". For example, in the same example above, the total sampling weight = 188 + 25 + 45 + 60 + 35 = 353.

[0089] Based on this, the total number of electrode samples is allocated to each set according to the sampling weight ratio to obtain the group sampling number of the corresponding set.

[0090] The formula for calculating the number of group samples for each set can be expressed as "Number of group samples = Total number of electrode samples × (Set sampling weight / Total sampling weight)".

[0091] For example, the number of samples in a Level 1 set group is approximately 346 (650 × (188 / 353)); the number of samples in a Level 2 set group is approximately 46 (650 × (25 / 353)); the number of samples in a Level 3 set group is approximately 83 (650 × (45 / 353)); the number of samples in a Level 4 set group is approximately 110 (650 × (60 / 353)); and the number of samples in a Level 5 set group is approximately 65 (650 × (35 / 353)).

[0092] Finally, the last digit is adjusted to ensure that the number of grouped samples precisely matches the total number of electrode samples.

[0093] Since allocating the number of group samples according to the sampling weight ratio may result in decimals in the calculation results, the calculation results are rounded to the nearest integer before specific sampling to ensure the rationality and feasibility of the number of group samples.

[0094] In the same example, the total number of samples across all sets is 346 + 46 + 83 + 110 + 65 = 650, which is exactly equal to the total number of electrode samples, requiring no additional adjustment. If there is a slight difference between the total number of samples and the total number of electrode samples, the difference should be allocated or deducted from the set with the highest risk level.

[0095] This method maintains the correspondence between the sampling density of each set and the risk level, while strictly controlling the total number of samples to be consistent with the total number of electrode samples, thus ensuring the accuracy and operability of the test plan.

[0096] Finally, based on the calculated number of samples for multiple groups, electrodes are randomly selected from multiple ternary lithium battery electrode sets to form multiple electrode sampling groups.

[0097] For example, 188 electrodes are randomly selected from 9400 electrodes in the Level 1 set to form a Level 1 electrode sampling group; and 35 electrodes are randomly selected from 50 electrodes in the Level 5 set to form a Level 5 electrode sampling group.

[0098] The number of samples in each sampling group is matched with the risk level of the corresponding set. For example, the high-risk Level 5 sampling group contains only 50 original electrodes, but selects 35 samples, accounting for 70%, which can fully capture potential interfacial bonding problems; while the low-risk Level 1 sampling group selects only 5% of the samples, which greatly reduces unnecessary testing.

[0099] By randomly sampling according to the sampling ratio, the resulting multiple electrode sampling groups not only cover electrode samples of different risk levels, but also achieve key risk detection and moderate sampling of general risks through differentiated ratios, which significantly improves testing efficiency while ensuring sample representativeness.

[0100] S140: Perform interface mechanical testing on the multiple electrode sampling groups using the interface mechanical testing scheme to obtain an electrode interface mechanical test dataset; In this embodiment of the application, in the process of testing the interfacial bonding force of batch ternary lithium battery electrodes, in order to obtain the interfacial bonding force data of the sampled group electrodes, it is necessary to test the samples obtained by the group sampling through destructive interface mechanical testing, so as to provide a performance reference for the subsequent establishment of an interfacial bonding force correlation model.

[0101] Specifically, mechanical peeling test parameters are first extracted from the interface mechanical testing scheme. These parameters include peeling angle, peeling speed, and loading force range, which are key indicators to ensure the accuracy of the test.

[0102] Furthermore, the interface mechanical test station is configured according to the mechanical peel test parameters to ensure that the tooling clamping method and force value acquisition frequency of the test equipment meet the test requirements, laying the foundation for accurate measurement.

[0103] Furthermore, through the configured interface mechanical testing station, mechanical peeling tests are performed on each ternary lithium battery electrode in multiple electrode sampling groups.

[0104] Among them, the mechanical peel test is a destructive test. By peeling off the electrode coating, the force that causes the coating to detach is directly measured to obtain the interfacial peel strength data of each electrode.

[0105] Finally, the electrode number of each ternary lithium battery electrode in multiple electrode sampling groups is associated with and stored along with the corresponding interface peel strength data to form an electrode interface mechanical test dataset. This associated storage method ensures a one-to-one correspondence between peel strength data and specific electrodes, facilitating subsequent matching and analysis with electrochemical test data.

[0106] This step, through targeted mechanical peeling tests and data storage on the sampled group electrodes, obtained accurate data reflecting the interfacial bonding force. This not only compensates for the inability of electrochemical tests to directly quantify the interfacial bonding force, but also reduces the damage to batch electrodes by testing only the sampled group. This provides experimental evidence for the subsequent establishment of a correlation model between the electrochemical test dataset and the interfacial bonding force.

[0107] Step S140 in the method provided in this application embodiment includes: Extract mechanical peel test parameters from the interface mechanical test scheme, and configure the interface mechanical test station according to the mechanical peel test parameters; The interface mechanical testing station is used to perform a peel test on each ternary lithium battery electrode in multiple electrode sampling groups to obtain the interface peel strength data of each ternary lithium battery electrode in multiple electrode sampling groups. The electrode number of each ternary lithium battery electrode in multiple electrode sampling groups is associated with and stored with the corresponding interface peel strength data to form the electrode interface mechanical test dataset.

[0108] In this embodiment of the application, in order to obtain the interfacial bonding force data of the sampling group electrodes, it is necessary to perform destructive testing on the samples obtained by the group sampling through standardized interfacial mechanical peeling test, so as to provide experimental basis for the subsequent establishment of a correlation model between electrochemical data and interfacial bonding force.

[0109] First, mechanical peeling test parameters are extracted from the interface mechanical testing scheme. These parameters are the core indicators to ensure the accuracy and consistency of the test results.

[0110] Specifically, the mechanical peel test parameters include peel angle, peel speed, and loading force range. Simultaneously, the interface for the mechanical test station is configured based on these parameters, including adjusting the tooling clamping method of the test equipment and setting the force value acquisition frequency, ensuring that the hardware conditions of the test station fully match the test plan requirements, thus laying the foundation for accurate measurement.

[0111] For example, if the mechanical peel test parameters set in the interface mechanical test scheme are peel angle 180°, peel speed 50mm / min, and loading force range 0-2N, then when configuring the interface mechanical test station, the peel angle of the test equipment needs to be adjusted to 180° to ensure that the force direction of the electrode coating remains perpendicular to the substrate during the peel process; the peel speed is set to 50mm / min to balance test efficiency and the accuracy of force value capture; and the loading range of the force sensor is adjusted to 0-2N to ensure that the peak force at the moment of peel is accurately recorded.

[0112] Meanwhile, the clamping device of the tooling was adjusted to ensure that the electrodes were firmly fixed during the test, preventing the peeling direction from shifting due to loosening; the acquisition frequency of the force sensor was set to 100Hz to ensure that the subtle changes in force during the peeling process could be fully captured, providing complete data support for the subsequent calculation of the interface peeling strength.

[0113] Furthermore, through the configured interface mechanical testing station, mechanical peeling tests are performed on each ternary lithium battery electrode in multiple electrode sampling groups.

[0114] Specifically, the mechanical peel test is a destructive test. The electrode coating is peeled off from the substrate at a set angle and speed using a mechanical clamping device. At the same time, the force required during the peeling process is recorded in real time, and finally the interfacial peel strength data of each electrode (in N / cm) is obtained.

[0115] Among them, the obtained electrode interface peel strength data is a direct quantitative representation of the interface bonding force. When the interface peel strength value is larger, it indicates that the coating and the substrate are more firmly bonded and the interface bonding force is stronger; conversely, if the interface peel strength value is smaller, it indicates that the interface bonding is weaker.

[0116] For example, the interfacial peel strength of the "JD-00156" electrode was tested to be 0.8 N / cm from the Level 1 electrode sampling group, while the interfacial peel strength of the "JD-05821" electrode was tested to be 0.3 N / cm from the Level 5 electrode sampling group. The difference between the two directly reflects the interfacial bonding strength of electrodes of different risk levels.

[0117] Similarly, the electrode number of each ternary lithium battery electrode in multiple electrode sampling groups is associated with and stored one by one with the corresponding interface peel strength data to form an electrode interface mechanical test dataset.

[0118] For example, the interface peel strength data corresponding to the ternary lithium battery electrode with the number "JD-02845" is 0.7 N / cm, the interface peel strength data corresponding to the ternary lithium battery electrode with the number "JD-03612" is 0.5 N / cm, and the interface peel strength data corresponding to the ternary lithium battery electrode with the number "JD-05821" is 0.3 N / cm.

[0119] Similarly, these interfacial peel strength data are linked with each electrode number and stored in a spreadsheet. The first column of the spreadsheet records the electrode number, and the second column corresponds to the interfacial peel strength value (in N / cm), forming structured data entries and constituting a complete electrode interface mechanical test dataset.

[0120] This step, through targeted mechanical peel testing and interface peel strength data storage of the sampled electrodes, not only obtains accurate quantitative data reflecting the interfacial bonding force, but also reduces the wear and tear on batch electrodes by performing destructive testing only on the sampled groups, thus controlling testing costs while ensuring data validity.

[0121] S150: Using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset, establish an interface bonding force correlation model to obtain the interface bonding force evaluation results of the batch ternary lithium battery electrodes.

[0122] In this embodiment of the application, in the process of testing the interfacial bonding force of batch ternary lithium battery electrodes, in order to achieve an overall evaluation of the interfacial bonding force of the entire electrode, it is necessary to establish an interfacial bonding force correlation model by correlation analysis of two types of test datasets, and to estimate the interfacial bonding force of the entire electrode based on the measured data of a portion of the samples, so as to finally complete the batch evaluation.

[0123] Specifically, the electrochemical test dataset and the mechanical test dataset of the electrode interface are first subjected to correlation analysis. That is, by matching the interfacial impedance spectroscopy detection data and interfacial peel strength data corresponding to the same electrode number in the two test datasets, the intrinsic relationship between the two is explored, and the correlation between the interfacial impedance spectroscopy detection data and the interfacial peel strength data is established.

[0124] Furthermore, based on the established interfacial bonding force correlation model, the interfacial peeling strength of ternary lithium battery electrodes that have not undergone peeling tests is estimated using the electrode interface electrochemical test dataset.

[0125] Since the electrochemical test covers all electrodes, the electrochemical data of each electrode can be converted into the corresponding predicted value of the interface peel strength through the correlation model, thereby obtaining the interface peel strength distribution of the batch of ternary lithium battery electrodes, so as to fully present the interface bonding force of all electrodes.

[0126] Finally, the distribution of interface peel strength is compared with the interface performance requirements to evaluate the pass rate of interface adhesion of batch ternary lithium battery electrodes, and this is used as the evaluation result of interface adhesion of batch ternary lithium battery electrodes.

[0127] This step, through correlation analysis and model extrapolation, achieves a complete evaluation of the interfacial bonding force of electrodes from partial sample measured data to the full range of electrodes. It avoids the high cost and destructiveness of full-scale destructive testing, and ensures the accuracy of the evaluation results through scientific modeling, providing an efficient and reliable solution for the interfacial bonding force testing of ternary lithium battery electrodes in batches.

[0128] Step S150 in the method provided in this application embodiment includes: The electrochemical test dataset and the mechanical test dataset of the electrode interface are correlated to establish the correlation between the interface impedance spectroscopy detection data and the interface peel strength data. Based on the aforementioned correlation, the interface peel strength of the ternary lithium battery electrodes that have not undergone peel testing is estimated using the electrode interface electrochemical test dataset, thereby obtaining the interface peel strength distribution of the batch of ternary lithium battery electrodes. The interface peel strength distribution is compared with the interface performance requirements to evaluate the interface adhesion qualification rate of the batch ternary lithium battery electrodes, which is used as the interface adhesion evaluation result of the batch ternary lithium battery electrodes.

[0129] In this embodiment of the application, in order to achieve a comprehensive evaluation of the interfacial bonding force of the electrodes in a batch of ternary lithium batteries, it is necessary to establish a mapping relationship by associating two types of test datasets, and to calculate the interfacial bonding force of the entire electrode based on the full amount of electrochemical data, so as to finally complete the batch quality judgment and solve the problems of high cost and strong destructiveness of full-volume destructive testing.

[0130] First, the electrochemical test dataset and the mechanical test dataset of the electrode interface are correlated and analyzed.

[0131] Specifically, by matching the information corresponding to the same electrode number in two datasets, such as the interfacial impedance spectroscopy detection data (including impedance values ​​at each frequency, charge transfer resistance, etc.) of the "JD-02845" electrode with the interfacial peeling strength data (0.7 N / cm), the intrinsic relationship between electrochemical properties and interfacial bonding is explored.

[0132] For example, the analysis revealed a significant negative correlation between charge transfer resistance and interfacial peel strength. Specifically, when the charge transfer resistance was 8.5 Ω·cm², the interfacial peel strength was 0.7 N / cm; when the charge transfer resistance increased to 15 Ω·cm², the interfacial peel strength decreased to 0.3 N / cm, thus establishing a quantitative correlation between interfacial impedance spectroscopy detection data and interfacial peel strength data.

[0133] At the same time, a model for interface integration is trained based on historical sample data.

[0134] Specifically, when collecting sample datasets, it is necessary to cover electrode samples under different performance conditions. This includes interfacial impedance spectroscopy data for different charge transfer resistance ranges (e.g., 5Ω・cm² ​​to 20Ω・cm²), corresponding interfacial peel strength data (e.g., 0.3N / cm to 1.0N / cm), as well as ternary lithium battery electrode samples from different production batches and with different material formulations, to ensure the comprehensiveness and representativeness of the sample dataset.

[0135] Among them, the sample data must meet the actual measurement standard of interface peel strength, that is, obtain accurate values ​​through 180° mechanical peel test, so as to provide a reliable label basis for model training.

[0136] Furthermore, a random forest regression algorithm was selected as the core framework to construct an interface bonding force correlation model. This algorithm, through ensemble learning of multiple decision trees, can effectively handle nonlinear relationships and capture the complex correlation between multiple electrochemical parameters such as charge transfer resistance and diffusion impedance and interface peeling strength.

[0137] Specifically, the model input layer receives key electrochemical parameters of the sample electrodes (such as charge transfer resistance, low-frequency diffusion impedance, etc.), performs feature learning and regression prediction through multiple decision trees, and each decision tree is trained based on different sample subsets and feature subsets. Finally, by integrating the prediction results of each decision tree, the predicted value of the interface peeling intensity is output.

[0138] In the process of training and optimizing the interface binding force correlation model using the sample dataset, the sample data is first divided into a training set and a validation set in an 8:2 ratio. The training set is used for model parameter learning, and the validation set is used to evaluate the model's prediction performance.

[0139] Secondly, during training, mean squared error is used as the loss function to measure the deviation between the model's predicted interface peel strength and the measured value. For example, when the model predicts a sample with an actual peel strength of 0.7 N / cm as 0.5 N / cm, the loss value will increase. Simultaneously, the model's hyperparameters are optimized using a grid search method, such as setting the number of decision trees to 100 and the maximum tree depth to 10, to improve the model's prediction accuracy.

[0140] For example, during the initial training, the model's prediction error for the interface peeling strength of a certain sample was 0.2 N / cm. After 50 rounds of training, the error dropped to 0.08 N / cm. When training continued for 100 rounds, the prediction error for the sample stabilized within 0.05 N / cm, and the overall average error of the validation set was less than 0.06 N / cm.

[0141] Furthermore, when the average error fluctuation of the validation set over 20 consecutive iterations does not exceed 0.01 N / cm, the model prediction error is considered to have converged, at which point the parameter optimization of the interface bonding force correlation model is complete.

[0142] Finally, the trained interfacial bonding force correlation model can receive the electrochemical parameters of the electrode to be predicted as input, and output the predicted value of the interfacial peeling strength through the collaborative calculation of multiple decision trees, providing an efficient estimation tool for the interfacial bonding force assessment of all electrodes.

[0143] For example, if the charge transfer resistance of an input electrode is 10 Ω·cm² and the low-frequency diffusion impedance is 300 Ω·cm², the interface bonding force correlation model predicts that its interface peeling strength is 0.6 N / cm through feature analysis and integrated calculation of each decision tree, which is consistent with the subsequent measured value of 0.6 N / cm for the electrode.

[0144] Furthermore, based on the established interfacial bonding force correlation model, the interfacial peel strength of ternary lithium battery electrodes that have not undergone peel testing is estimated using the electrode interface electrochemical test dataset. This yields the distribution of interfacial peel strength of a batch of ternary lithium battery electrodes, which can fully present the interfacial bonding force of all electrodes, including the number and proportion of electrodes in different strength ranges.

[0145] Finally, the distribution of interface peel strength is compared with the interface performance requirements to evaluate the pass rate of interface adhesion of batch ternary lithium battery electrodes, and this result is used as the final evaluation result of interface adhesion.

[0146] For example, if the interface performance requirement is "interface peel strength > 0.5 N / cm", then the proportion of electrodes with predicted peel strength greater than 0.5 N / cm in the batch is counted. Assuming a batch of 10,000 electrodes, and 9,200 electrodes meet the predicted peel strength requirement, the interface adhesion pass rate is 92% (9,200 / 10,000 × 100%). Simultaneously, the specific numbers, charge transfer resistances, and predicted peel strengths of the 800 non-conforming electrodes can be identified, providing a basis for quality traceability and subsequent improvements.

[0147] This step, through correlation analysis and model extrapolation, realizes the transformation from "partial sample mechanical peel test data" to "full-scale electrode interface bonding force evaluation". It retains the direct quantitative advantage of mechanical peel test on interface bonding force, and also realizes batch evaluation by taking advantage of the full coverage of electrochemical test. While ensuring the accuracy of evaluation, it significantly reduces test costs and electrode loss, and provides a feasible solution for the interface bonding force detection of batch ternary lithium battery electrodes.

[0148] The embodiments of this application, through the specific implementation methods described above, achieve the following technical effects: This application proposes a method for testing the interfacial bonding strength of ternary lithium battery electrode materials. First, the interfacial performance requirements of a batch of ternary lithium battery electrodes are obtained, and interfacial resistance, interfacial stability, and interfacial peel strength indices are extracted. Based on this, electrochemical and mechanical testing schemes are configured to clarify the direction and ensure compatibility, providing accurate basis for subsequent testing. Second, after numbering all electrodes, data is acquired and stored through an interfacial impedance spectroscopy detection station to form an electrochemical dataset, achieving non-destructive full-scale initial screening while preserving complete electrode characteristics. Then, based on this dataset, multiple electrode sampling groups are obtained by dividing the dataset into sets according to standard charge transfer resistance and deviation thresholds, ensuring high-risk coverage and reducing low-risk testing volume, balancing accuracy and efficiency. Mechanical peel tests are then performed on the sampling groups to acquire test data and form a mechanical dataset, supplementing the quantitative interfacial bonding strength data and compensating for the limitations of electrochemical testing. Finally, an interfacial bonding strength correlation model is established using the two types of test datasets to calculate the peel strength distribution of all electrodes, and the pass rate is evaluated by comparing it with the interfacial performance requirements, obtaining the final result and achieving efficient and accurate evaluation of the interfacial bonding strength of batch electrodes.

[0149] The method provided in this application adopts a technical solution of "scheme configuration - electrochemical detection - group sampling - mechanical testing - model evaluation". First, electrochemical testing is used to fully cover the initial screening, then differentiated sampling and mechanical testing are used for precise verification, and finally, model association is used to achieve full evaluation. This method breaks through the limitations of full mechanical testing, while taking into account both testing efficiency and accuracy, and provides a reliable solution for batch electrode interface bonding force detection.

[0150] Example 2, as shown in the appendix Figure 2 As shown, based on the inventive concept of the interfacial bonding force testing method for ternary lithium battery electrode materials provided in Embodiment 1, this application also provides a ternary lithium battery electrode material interfacial bonding force testing system, specifically including: The performance scheme configuration module 01 is used to obtain the interface performance requirements of batch ternary lithium battery electrodes and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements. Interface electrochemical testing module 02 is used to perform interface electrochemical testing on the batch of ternary lithium battery electrodes through the interface electrochemical testing scheme to obtain electrode interface electrochemical test dataset. Electrochemical group sampling module 03 is used to group and sample the batch of ternary lithium battery electrodes based on the electrode interface electrochemical test dataset to obtain multiple electrode sampling groups. Interface mechanical testing module 04 is used to perform interface mechanical testing on the multiple electrode sampling groups through the interface mechanical testing scheme to obtain an electrode interface mechanical testing dataset. The bonding force assessment module 05 is used to establish an interface bonding force correlation model using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset, and to obtain the interface bonding force assessment results of the batch ternary lithium battery electrodes.

[0151] In one embodiment, the performance scheme configuration module 01 is further configured to: Based on the interface performance requirements, extract the interface resistance performance index, interface stability index, and interface peel strength index. Based on the interface resistance performance index and interface stability index, a standard interface impedance spectrum is set, and the interface electrochemical testing scheme is configured. Based on the interface peel strength index, mechanical peel test parameters are set, and the interface mechanical test scheme is configured.

[0152] In one embodiment, the interface electrochemical testing module 02 is further used for: Each ternary lithium battery electrode in the batch of ternary lithium battery electrodes is assigned an electrode number to obtain the electrode number of each ternary lithium battery electrode. Each ternary lithium battery electrode is sequentially tested using an interface impedance spectroscopy detection station to obtain interface impedance spectroscopy data for each ternary lithium battery electrode. The electrode number of each ternary lithium battery electrode is associated with and stored with the corresponding interfacial impedance spectroscopy detection data to form the electrode interface electrochemical test dataset.

[0153] In one embodiment, the electrochemical group sampling module 03 is also used for: The standard charge transfer resistance is set according to the standard interface impedance spectrum, and multiple charge transfer resistance deviation thresholds are set. The interfacial impedance spectrum detection data of each ternary lithium battery electrode is extracted from the electrode interface electrochemical test dataset and converted into the charge transfer test resistance of each ternary lithium battery electrode. Based on the standard charge transfer resistance and the charge transfer test resistance of each ternary lithium battery electrode, the charge transfer resistance deviation of each ternary lithium battery electrode is obtained. Based on the charge transfer resistance deviation of each ternary lithium battery electrode and the multiple charge transfer resistance deviation thresholds, the batch of ternary lithium battery electrodes is divided into multiple ternary lithium battery electrode sets. Based on the multiple sets of ternary lithium battery electrodes, the batch of ternary lithium battery electrodes are sampled in groups to obtain multiple electrode sampling groups.

[0154] In one embodiment, the interface mechanical testing module 04 is also used for: Extract mechanical peel test parameters from the interface mechanical test scheme, and configure the interface mechanical test station according to the mechanical peel test parameters; The interface mechanical testing station is used to perform a peel test on each ternary lithium battery electrode in multiple electrode sampling groups to obtain the interface peel strength data of each ternary lithium battery electrode in multiple electrode sampling groups. The electrode number of each ternary lithium battery electrode in multiple electrode sampling groups is associated with and stored with the corresponding interface peel strength data to form the electrode interface mechanical test dataset.

[0155] In one embodiment, the bonding strength assessment module 05 is also used for: The electrochemical test dataset and the mechanical test dataset of the electrode interface are correlated to establish the correlation between the interface impedance spectroscopy detection data and the interface peel strength data. Based on the aforementioned correlation, the interface peel strength of the ternary lithium battery electrodes that have not undergone peel testing is estimated using the electrode interface electrochemical test dataset, thereby obtaining the interface peel strength distribution of the batch of ternary lithium battery electrodes. The interface peel strength distribution is compared with the interface performance requirements to evaluate the interface adhesion qualification rate of the batch ternary lithium battery electrodes, which is used as the interface adhesion evaluation result of the batch ternary lithium battery electrodes.

[0156] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0157] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0158] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for testing the interfacial bonding strength of ternary lithium battery electrode materials, characterized in that, The method includes: Obtain the interface performance requirements of batch ternary lithium battery electrodes, and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements; The interface electrochemical test data of the batch of ternary lithium battery electrodes was obtained by performing interface electrochemical tests on the interface electrochemical test scheme. Based on the electrode interface electrochemical test dataset, the batch of ternary lithium battery electrodes were sampled in groups to obtain multiple electrode sampling groups. The interface mechanical testing scheme is used to perform interface mechanical testing on the multiple electrode sampling groups to obtain an electrode interface mechanical test dataset. An interfacial bonding force correlation model was established using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset to obtain the interfacial bonding force evaluation results of the batch ternary lithium battery electrodes.

2. The method according to claim 1, characterized in that, Obtain the interface performance requirements for batch ternary lithium battery electrodes, and configure interface electrochemical testing schemes and interface mechanical testing schemes according to the interface performance requirements, including: Based on the interface performance requirements, extract the interface resistance performance index, interface stability index, and interface peel strength index. Based on the interface resistance performance index and interface stability index, a standard interface impedance spectrum is set, and the interface electrochemical testing scheme is configured. Based on the interface peel strength index, mechanical peel test parameters are set, and the interface mechanical test scheme is configured.

3. The method according to claim 2, characterized in that, The interface electrochemical testing of the batch of ternary lithium battery electrodes was performed using the aforementioned interface electrochemical testing scheme to obtain an electrode interface electrochemical test dataset, including: Each ternary lithium battery electrode in the batch of ternary lithium battery electrodes is assigned an electrode number to obtain the electrode number of each ternary lithium battery electrode. Each ternary lithium battery electrode is sequentially tested using an interface impedance spectroscopy detection station to obtain interface impedance spectroscopy data for each ternary lithium battery electrode. The electrode number of each ternary lithium battery electrode is associated with and stored with the corresponding interfacial impedance spectroscopy detection data to form the electrode interface electrochemical test dataset.

4. The method according to claim 3, characterized in that, Based on the aforementioned electrode interface electrochemical test dataset, the batch of ternary lithium battery electrodes were sampled in groups to obtain multiple electrode sampling groups, including: The standard charge transfer resistance is set according to the standard interface impedance spectrum, and multiple charge transfer resistance deviation thresholds are set. The interfacial impedance spectrum detection data of each ternary lithium battery electrode is extracted from the electrode interface electrochemical test dataset and converted into the charge transfer test resistance of each ternary lithium battery electrode. Based on the standard charge transfer resistance and the charge transfer test resistance of each ternary lithium battery electrode, the charge transfer resistance deviation of each ternary lithium battery electrode is obtained. Based on the charge transfer resistance deviation of each ternary lithium battery electrode and the multiple charge transfer resistance deviation thresholds, the batch of ternary lithium battery electrodes is divided into multiple ternary lithium battery electrode sets. Based on the multiple sets of ternary lithium battery electrodes, the batch of ternary lithium battery electrodes are sampled in groups to obtain multiple electrode sampling groups.

5. The method according to claim 4, characterized in that, Based on the multiple sets of ternary lithium battery electrodes, the batch of ternary lithium battery electrodes are sampled in groups to obtain multiple electrode sampling groups, including: Set the overall sampling ratio for batch ternary lithium battery electrodes, and determine the total number of electrode samples based on the overall sampling ratio and the total number of electrodes in the batch ternary lithium battery electrodes; Based on the degree of charge transfer resistance deviation corresponding to the multiple ternary lithium battery electrode sets, multiple deviation levels of the multiple ternary lithium battery electrode sets are obtained, and multiple sampling coefficients are set based on the multiple deviation levels; Multiple sampling coefficients are used as the electrode sampling ratios of multiple ternary lithium battery electrode sets. Combined with the total number of electrode samples, multiple group sampling quantities are obtained. Multiple electrode sampling groups are obtained by randomly selecting electrodes from multiple ternary lithium battery electrode sets based on multiple group sampling quantities.

6. The method according to claim 1, characterized in that, The interface mechanical testing scheme is used to perform interface mechanical testing on the multiple electrode sampling groups to obtain an electrode interface mechanical test dataset. Extract mechanical peel test parameters from the interface mechanical test scheme, and configure the interface mechanical test station according to the mechanical peel test parameters; The interface mechanical testing station is used to perform a peel test on each ternary lithium battery electrode in multiple electrode sampling groups to obtain the interface peel strength data of each ternary lithium battery electrode in multiple electrode sampling groups. The electrode number of each ternary lithium battery electrode in multiple electrode sampling groups is associated with and stored with the corresponding interface peel strength data to form the electrode interface mechanical test dataset.

7. The method according to claim 1, characterized in that, An interfacial bonding force correlation model was established using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset to obtain the interfacial bonding force evaluation results of the batch ternary lithium battery electrodes, including: The electrochemical test dataset and the mechanical test dataset of the electrode interface are correlated to establish the correlation between the interface impedance spectroscopy detection data and the interface peel strength data. Based on the aforementioned correlation, the interface peel strength of the ternary lithium battery electrodes that have not undergone peel testing is estimated using the electrode interface electrochemical test dataset, thereby obtaining the interface peel strength distribution of the batch of ternary lithium battery electrodes. The interface peel strength distribution is compared with the interface performance requirements to evaluate the interface adhesion qualification rate of the batch ternary lithium battery electrodes, which is used as the interface adhesion evaluation result of the batch ternary lithium battery electrodes.

8. A testing system for the interfacial bonding strength of ternary lithium battery electrode materials, characterized in that, The system is used to perform the interfacial bonding strength test method for ternary lithium battery electrode materials according to any one of claims 1-7, and the system comprises: The performance scheme configuration module is used to obtain the interface performance requirements of batch ternary lithium battery electrodes and configure the interface electrochemical test scheme and interface mechanical test scheme according to the interface performance requirements. The interface electrochemical testing module is used to perform interface electrochemical testing on the batch of ternary lithium battery electrodes using the interface electrochemical testing scheme, and to obtain an electrode interface electrochemical test dataset. An electrochemical grouping sampling module is used to group and sample the batch of ternary lithium battery electrodes based on the electrode interface electrochemical test dataset to obtain multiple electrode sampling groups. The interface mechanical testing module is used to perform interface mechanical testing on the multiple electrode sampling groups through the interface mechanical testing scheme to obtain an electrode interface mechanical test dataset. The bonding force assessment module is used to establish an interface bonding force correlation model using the electrode interface electrochemical test dataset and the electrode interface mechanical test dataset to obtain the interface bonding force assessment results of the batch of ternary lithium battery electrodes.

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