A method and system for testing performance of ternary lithium battery pole piece

Abstract

The application provides a ternary lithium battery pole piece performance test method and system, and belongs to the field of battery performance test. The method comprises the following steps: performing multi-position thickness test on a target pole piece to obtain a thickness sequence, performing positive and negative error analysis to obtain a negative error degree and a positive error degree; configuring the porosity and conductivity test quantity according to the error degree, performing confidence analysis to obtain a first porosity confidence and a first conductivity confidence, and respectively testing to obtain a porosity sequence and a conductivity sequence, so as to obtain a second porosity confidence and a second conductivity confidence; and calculating three performance uniformity parameters according to the three sequences, and combining multiple confidences to calculate a final performance uniformity parameter. The application solves the technical problem of low accuracy of ternary lithium battery pole piece performance uniformity detection in the prior art, and achieves the technical effects of improving the accuracy and reliability of ternary lithium battery pole piece performance uniformity detection.

Description

Technical Field

[0001] This invention relates to the field of battery performance testing, and in particular to a method and system for testing the performance of ternary lithium battery electrodes. Background Technology

[0002] As a core component of new energy vehicles and energy storage systems, the performance and safety of ternary lithium batteries largely depend on the manufacturing quality of the battery electrodes. During the production of ternary lithium battery electrodes, due to the influence of processes such as coating, compaction, and slitting, the electrodes often suffer from uneven thickness, inconsistent porosity distribution, and differences in conductivity, resulting in poor electrode performance uniformity.

[0003] The uniformity of electrode performance directly affects the charge-discharge performance, cycle life, and safety of a battery. When there are significant differences in key parameters such as thickness, porosity, and conductivity at different locations on the electrode, it can cause uneven current distribution within the battery, leading to localized overheating. This, in turn, accelerates battery capacity decay, increases internal resistance, and in severe cases, may even cause thermal runaway and other safety issues. Currently, the methods for detecting the uniformity of ternary lithium battery electrode performance mainly employ single-parameter testing or simple multi-point sampling, which are insufficient to accurately reflect the true uniformity of the electrode performance, resulting in low accuracy in the detection of ternary lithium battery electrode performance uniformity. Summary of the Invention

[0004] This invention addresses the technical problem of low accuracy in detecting the uniformity of ternary lithium battery electrode performance in existing technologies by providing a method and system for testing the performance of ternary lithium battery electrodes.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0006] In a first aspect, the present invention provides a method for testing the performance of a ternary lithium battery electrode, comprising: performing thickness tests at multiple locations on a target electrode to obtain an electrode thickness sequence; performing positive and negative error analysis on the electrode thickness to obtain a negative error degree and a positive error degree, wherein the target electrode is a ternary lithium battery electrode; configuring and obtaining a number of porosity tests and a number of conductivity tests based on the negative and positive error degrees; performing test confidence analysis to obtain a first porosity confidence degree and a first conductivity confidence degree; and performing tests respectively to obtain a porosity sequence and a conductivity sequence. The sequence; Performance deviation analysis is performed on the porosity sequence and conductivity sequence to obtain porosity deviation and conductivity deviation. Combining the negative error and positive error, a second porosity confidence level and a second conductivity confidence level are calculated. Based on the electrode thickness sequence, porosity sequence, and conductivity sequence, a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter are calculated. Combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level, a performance uniformity parameter is calculated as the test result.

[0007] Secondly, the present invention provides a ternary lithium battery electrode performance testing system, comprising: a thickness error analysis module, used to perform thickness tests at multiple locations on a target electrode to obtain an electrode thickness sequence, perform positive and negative error analysis on the electrode thickness to obtain negative and positive error degrees, wherein the target electrode is a ternary lithium battery electrode; and a test configuration execution module, used to configure the number of porosity tests and conductivity tests based on the negative and positive error degrees, perform test confidence analysis to obtain a first porosity confidence degree and a first conductivity confidence degree, and perform tests respectively to obtain a porosity sequence and conductivity sequence. The system includes a porosity sequence and a performance deviation analysis module, used to perform performance deviation analysis calculations on the porosity sequence and conductivity sequence to obtain porosity deviation and conductivity deviation. Combining the negative and positive error values, a second porosity confidence level and a second conductivity confidence level are calculated. A uniformity calculation module, based on the electrode thickness sequence, porosity sequence, and conductivity sequence, calculates a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter. Combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level, a performance uniformity parameter is calculated as the test result.

[0008] The beneficial effects of this invention are:

[0009] Thickness tests were conducted at multiple locations on the target electrode to obtain an electrode thickness sequence. Positive and negative error analyses were performed to obtain the negative and positive error degrees. The target electrode was a ternary lithium battery electrode. Multi-point thickness testing provides a comprehensive understanding of the electrode thickness distribution, while positive and negative error analyses quantify the degree to which the electrode thickness deviates from the standard value, providing a basis for subsequent test parameter configuration. Based on the negative and positive error degrees, the number of porosity and conductivity tests was configured. Test confidence analysis was performed to obtain the first porosity confidence degree and the first conductivity confidence degree, and tests were conducted separately to obtain porosity and conductivity sequences. Configuring the number of tests based on thickness error ensures the relevance and sufficiency of the tests, while test confidence analysis provides a quantitative assessment of the reliability of the test results.

[0010] Performance deviation analysis is performed on the porosity and conductivity sequences to obtain porosity deviation and conductivity deviation. Combining negative and positive error values, a second porosity confidence score and a second conductivity confidence score are calculated. Performance deviation analysis quantifies the uniformity of porosity and conductivity distribution. Combining this with thickness error values ​​for confidence score calculation verifies the accuracy of the thickness influence analysis and improves the reliability of the test results. Based on the electrode thickness, porosity, and conductivity sequences, a first, second, and third performance uniformity parameter are calculated. Combining the first porosity confidence score, the first conductivity confidence score, the second porosity confidence score, and the second conductivity confidence score, a performance uniformity parameter is calculated as the test result. Weighted calculation of the three performance uniformity parameters using multiple confidence scores comprehensively considers the reliability of various test results, ultimately obtaining accurate and reliable electrode performance uniformity evaluation parameters.

[0011] The above technical solutions can accurately identify and quantify the non-uniformity of electrode performance distribution, effectively improving the accuracy and reliability of ternary lithium battery electrode performance uniformity detection, and providing reliable technical support for ternary lithium battery electrode quality control and process optimization. Attached Figure Description

[0012] Figure 1 A flowchart illustrating a method for testing the performance of ternary lithium battery electrodes provided by this invention;

[0013] Figure 2 This is a schematic diagram of the structure of a ternary lithium battery electrode performance testing system provided by the present invention.

[0014] In the attached diagram, the components represented by each number are as follows:

[0015] Thickness error analysis module 11, test configuration execution module 12, performance deviation analysis module 13, uniformity calculation module 14. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] In the description of this invention, 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 invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0018] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention 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 herein.

[0019] Example 1, as Figure 1 As shown, this embodiment of the invention provides a method for testing the performance of ternary lithium battery electrodes, including:

[0020] S1. Perform thickness tests at multiple locations on the target electrode to obtain an electrode thickness sequence. Perform positive and negative error analysis on the electrode thickness to obtain the negative error degree and the positive error degree. The target electrode is a ternary lithium battery electrode.

[0021] Specifically, the first step is to perform multi-point thickness measurements on the ternary lithium battery electrode to be tested (the target electrode). Specifically, multiple locations are selected on the surface of the target electrode according to a predetermined testing plan, and the thickness is measured at each location using a precision thickness measuring instrument (such as a micrometer or laser thickness gauge), thereby obtaining a set of thickness data, i.e., the electrode thickness sequence. This electrode thickness sequence contains the thickness values ​​of the target electrode at different locations and reflects the spatial distribution characteristics of the electrode thickness. Due to the influence of factors such as coating and compaction processes during the manufacturing process, the thickness at different locations often varies, and this thickness non-uniformity directly affects the uniformity of the electrode's electrochemical performance.

[0022] After obtaining the electrode thickness sequence, the data in the sequence are classified and analyzed using the standard electrode thickness as a benchmark. Data less than or equal to the standard electrode thickness are classified as negative thickness deviations, while data greater than the standard electrode thickness are classified as positive thickness deviations. The negative error degree is obtained by calculating the mean absolute error of the negative thickness deviations; the positive error degree is obtained by calculating the mean absolute error of the positive thickness deviations. The negative error degree reflects the degree of deviation when the electrode thickness is lower than the standard electrode thickness, while the positive error degree reflects the degree of deviation when the electrode thickness is higher than the standard electrode thickness. Thickness deviation is closely related to the porosity and conductivity of the electrode. This bidirectional error analysis provides important guidance for the subsequent development of porosity and conductivity testing strategies.

[0023] S2. Based on the negative error degree and the positive error degree, configure the number of porosity tests and the number of conductivity tests, perform test confidence analysis, obtain the first porosity confidence degree and the first conductivity confidence degree, and perform tests respectively to obtain the porosity sequence and the conductivity sequence.

[0024] Specifically, when the electrode thickness is less than the standard electrode thickness, the material density is relatively high, leading to a reduction in pore space and a decrease in porosity. Conversely, when the electrode thickness is greater than the standard electrode thickness, the material density is relatively low, resulting in a decrease in the connectivity of the conductive path and a decrease in conductivity. Based on this physical mechanism, the magnitude of the negative error directly affects the importance of porosity testing, while the magnitude of the positive error directly affects the importance of conductivity testing.

[0025] Therefore, based on the ratio of negative error degree to average negative error degree, the preset porosity test quantity is adjusted. When the negative error degree is large, the number of porosity tests is increased to improve test accuracy; when the negative error degree is small, the number of porosity tests is appropriately reduced to improve test efficiency. The average negative error degree refers to the average value obtained through statistical analysis of the negative error degree of each electrode based on statistical data from a large number of ternary lithium battery electrode samples, reflecting the general level of negative thickness deviation of the same type of electrode under manufacturing process conditions. The preset porosity test quantity refers to the number of porosity test points pre-set according to test accuracy requirements, test cost control, and statistical principles, determined based on empirical data and statistical confidence intervals.

[0026] Similarly, based on the ratio of the positive error degree to the average positive error degree, the preset conductivity test quantity is adjusted accordingly to obtain the conductivity test quantity. The average positive error degree refers to the average value obtained through statistical analysis of the positive error degree of each electrode based on statistical data from a large number of ternary lithium battery electrode samples, reflecting the general level of positive thickness deviation of the same type of electrode under manufacturing process conditions. The preset conductivity test quantity refers to the number of conductivity test points pre-set according to test accuracy requirements, test cost control, and statistical principles, determined based on empirical data and statistical confidence intervals.

[0027] By comparing the current error of the target electrode with the corresponding average error, it is possible to effectively identify whether the deviation characteristics of the electrode exceed the normal range, thereby reasonably adjusting the allocation of testing resources and achieving the optimal balance between testing accuracy and testing efficiency.

[0028] After determining the number of porosity and conductivity tests, the ratio of the number of porosity tests to the preset number of porosity tests is further analyzed to obtain the first porosity confidence level; the ratio of the number of conductivity tests to the preset number of conductivity tests is analyzed to obtain the first conductivity confidence level. These first porosity and first conductivity confidence levels reflect the reliability of the testing strategy formulated based on thickness error analysis. Subsequently, according to the determined number of porosity and conductivity tests, the target electrode is actually measured using appropriate testing equipment and methods to obtain porosity and conductivity sequences. For example, corresponding test locations are selected on the target electrode according to the number of porosity tests, and porosity tests are performed using methods such as mercury intrusion porosimetry or gas adsorption to obtain the porosity sequence; corresponding test locations are selected on the target electrode according to the number of conductivity tests, and conductivity tests are performed using methods such as the four-probe method or AC impedance method to obtain the conductivity sequence. Obtaining the porosity and conductivity sequences provides a data foundation for subsequent performance deviation analysis.

[0029] S3. Perform performance deviation analysis on the porosity sequence and conductivity sequence to obtain porosity deviation and conductivity deviation. Combine the negative error and positive error to calculate the second porosity confidence and the second conductivity confidence.

[0030] Specifically, firstly, standard porosity and standard conductivity are obtained as benchmark parameters. Standard porosity refers to the ideal porosity value that a ternary lithium battery electrode sheet prepared under standard process conditions should possess; standard conductivity refers to the ideal conductivity value that a ternary lithium battery electrode sheet prepared under standard process conditions should possess.

[0031] Subsequently, the absolute deviation of each porosity within the porosity sequence from the standard porosity is calculated, and the arithmetic mean of all absolute deviations is taken to obtain the porosity deviation. Similarly, the absolute deviation of each conductivity within the conductivity sequence from the standard conductivity is calculated, and the arithmetic mean of all absolute deviations is taken to obtain the conductivity deviation. The porosity deviation and conductivity deviation reflect the degree of deviation of the actual porosity and conductivity of the target electrode from the standard values, respectively.

[0032] Next, the second porosity confidence level was obtained by calculating the similarity between the porosity deviation and the negative error; the second conductivity confidence level was obtained by calculating the similarity between the conductivity deviation and the positive error. Specifically, when the porosity deviation and the negative error have a high similarity, it indicates a strong correlation between the negative thickness error and the porosity deviation, verifying the accuracy of the physical mechanism that a smaller thickness leads to a decrease in porosity, thus obtaining a high second porosity confidence level. Similarly, when the conductivity deviation and the positive error have a high similarity, it indicates a strong correlation between the positive thickness error and the conductivity deviation, verifying the accuracy of the physical mechanism that a larger thickness leads to a decrease in conductivity, thus obtaining a high second conductivity confidence level.

[0033] The second porosity confidence and second conductivity confidence obtained through the above analysis can quantitatively evaluate the effectiveness of the porosity and conductivity testing strategy guided by thickness error analysis, and provide a reliable confidence basis for subsequent performance uniformity parameter calculations.

[0034] S4. Based on the electrode thickness sequence, porosity sequence, and conductivity sequence, calculate the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter. Combine the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level to calculate the performance uniformity parameter, which is used as the test result.

[0035] Specifically, the standard deviation of the electrode thickness sequence is calculated to obtain the first performance uniformity parameter, which reflects the dispersion of the target electrode thickness distribution; the standard deviation of the porosity sequence is calculated to obtain the second performance uniformity parameter, which reflects the dispersion of the target electrode porosity distribution; and the standard deviation of the conductivity sequence is calculated to obtain the third performance uniformity parameter, which reflects the dispersion of the target electrode conductivity distribution. A smaller standard deviation indicates a more uniform distribution of the corresponding performance parameter.

[0036] Subsequently, the three performance uniformity parameters are weighted and calculated by combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level. Specifically, firstly, a preset thickness weight and a weight to be assigned are obtained; then, the porosity confidence level is calculated based on the first and second porosity confidence levels, and the conductivity confidence level is calculated based on the first and second conductivity confidence levels; based on the numerical values ​​of the porosity and conductivity confidence levels, the weights to be assigned are calculated to obtain the porosity weight and conductivity weight; then, based on the preset thickness weight, porosity weight, and conductivity weight, the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter are weighted and calculated to obtain the performance uniformity parameter. This performance uniformity parameter comprehensively reflects the uniformity level of the target electrode in the three dimensions of thickness, porosity, and conductivity. Performance parameters with higher confidence levels have a larger weight in the final result, thereby ensuring the reliability and accuracy of the test results. This performance uniformity parameter, as the final test result, provides an important basis for the quality assessment and process optimization of ternary lithium battery electrodes.

[0037] Furthermore, thickness measurements are performed at multiple locations on the target electrode to obtain an electrode thickness sequence. Negative and positive error analyses of the electrode thickness are then conducted to obtain the negative and positive error values, including:

[0038] S11. Randomly select multiple thickness test locations for the target electrode and perform thickness tests on each location to obtain the electrode thickness sequence.

[0039] S12. Obtain the standard electrode thickness;

[0040] S13. Identify and filter electrode thicknesses within the electrode thickness sequence that are less than or equal to or greater than the standard electrode thickness to obtain negative electrode thickness sequences and positive electrode thickness sequences. Perform negative error analysis and positive error analysis to obtain negative error degree and positive error degree.

[0041] In one feasible implementation, firstly, multiple thickness testing locations are randomly selected on the target electrode, and thickness tests are performed at each location to obtain an electrode thickness sequence. Specifically, random sampling is used to select testing locations on the surface of the target electrode to avoid systematic bias caused by regular point selection. The number of multiple thickness testing locations is determined based on the electrode size, testing accuracy requirements, and statistical principles, typically no fewer than 10 testing locations to ensure the statistical validity of the data. Thickness measurements are then performed at each selected testing location using a precision thickness measuring device, and the thickness values ​​from all testing locations are arranged in the testing order to form an electrode thickness sequence.

[0042] Subsequently, the standard electrode thickness is obtained. This standard electrode thickness refers to the ideal thickness value that a ternary lithium battery electrode should have under standard process conditions. This value is determined based on the electrode design requirements, material properties, and process parameters, and serves as a benchmark reference value for subsequent error analysis.

[0043] Then, using the standard electrode thickness as a dividing point, the thickness data within the electrode thickness sequence are filtered and judged. Thickness values ​​less than or equal to the standard electrode thickness are selected to form a negative electrode thickness sequence; thickness values ​​greater than the standard electrode thickness are selected to form a positive electrode thickness sequence. Next, negative error analysis is performed on the negative electrode thickness sequence, calculating the absolute error between each thickness value and the standard electrode thickness and taking the average value to obtain the negative error degree; positive error analysis is performed on the positive electrode thickness sequence, calculating the absolute error between each thickness value and the standard electrode thickness and taking the average value to obtain the positive error degree.

[0044] The above steps can accurately quantify the bidirectional deviation characteristics of the target electrode thickness distribution, providing precise data support for the formulation of subsequent porosity and conductivity testing strategies.

[0045] Furthermore, negative and positive error analyses are performed to obtain the negative and positive error values, including:

[0046] S131. Randomly select several negative electrode thicknesses within the negative electrode thickness sequence, calculate the absolute error amplitude between the negative electrode thickness and the standard electrode thickness, and calculate the average value to obtain the negative error degree.

[0047] S132. Randomly select several positive electrode thicknesses within the positive electrode thickness sequence, calculate the absolute error amplitude between them and the standard electrode thickness, and calculate the average value to obtain the positive error degree.

[0048] In a preferred embodiment, firstly, several negative electrode thicknesses are randomly selected from the negative electrode thickness sequence. The absolute error amplitude compared to the standard electrode thickness is calculated, and the mean is calculated to obtain the negative error degree. Specifically, several thickness values ​​are selected from the negative electrode thickness sequence using random sampling. The number of these selected values ​​is determined based on the total number of negative electrode thickness sequences and the statistical precision requirements, typically not less than 30% of the total number of negative electrode thickness sequences to ensure the representativeness of the sampling. For each selected negative electrode thickness, the absolute value of its difference from the standard electrode thickness is calculated, i.e., the absolute error amplitude. The absolute error amplitudes of all selected thicknesses are arithmetically averaged to obtain the negative error degree. This negative error degree quantitatively reflects the average deviation of the target electrode thickness from the standard value.

[0049] Simultaneously, several positive electrode thicknesses are randomly selected from the positive electrode thickness sequence. The absolute error amplitude compared to the standard electrode thickness is calculated, and the mean is calculated to obtain the positive error degree. Specifically, using the same random sampling principle as in step S131, several positive electrode thicknesses are selected from the positive electrode thickness sequence. For each selected positive electrode thickness, the absolute value of its difference from the standard electrode thickness is calculated, i.e., the absolute error amplitude. The arithmetic mean of the absolute error amplitudes of all selected thicknesses is then used to obtain the positive error degree. This positive error degree quantitatively reflects the average deviation of the target electrode thickness from the standard value.

[0050] By using the above-mentioned random sampling method for error analysis, we can avoid the objectivity of the analysis results due to selection bias, improve computational efficiency, and ensure the accuracy and representativeness of negative and positive error measures.

[0051] Furthermore, based on the negative and positive error degrees, the number of porosity tests and conductivity tests are configured and obtained. Test confidence analysis is performed to obtain a first porosity confidence degree and a first conductivity confidence degree. Tests are then conducted separately to obtain a porosity sequence and a conductivity sequence, including:

[0052] S21. Obtain the preset number of porosity tests and the preset number of conductivity tests;

[0053] S22. Calculate the ratio of the negative error degree to the average negative error degree, and perform a correction calculation on the preset porosity test quantity to obtain the porosity test quantity.

[0054] S23. Calculate the ratio of the positive error degree to the average positive error degree, and perform a correction calculation on the preset conductivity test quantity to obtain the conductivity test quantity.

[0055] S24. Based on the number of porosity tests and conductivity tests, analyze and obtain the first porosity confidence level and the first conductivity confidence level;

[0056] S25. Perform porosity and conductivity tests on the target electrode according to the number of porosity tests and conductivity tests respectively, and obtain porosity sequence and conductivity sequence.

[0057] In a preferred embodiment, firstly, a preset number of porosity test points and a preset number of conductivity test points are obtained. The preset number of porosity test points refers to the number of porosity test points predetermined based on testing accuracy requirements, testing cost control, and statistical principles, and is typically determined based on empirical data and statistical confidence intervals. The preset number of conductivity test points refers to the number of conductivity test points predetermined based on testing accuracy requirements, testing cost control, and statistical principles, and is typically determined based on empirical data and statistical confidence intervals.

[0058] Then, the ratio of the negative error degree to the average negative error degree is calculated, and the preset porosity test quantity is corrected to obtain the final porosity test quantity. Specifically, when the negative error degree is greater than the average negative error degree, the ratio is greater than 1, indicating that the negative deviation of the target electrode thickness is significant. In this case, the number of porosity tests needs to be increased to improve test accuracy. When the negative error degree is less than the average negative error degree, the ratio is less than 1, indicating that the negative deviation of the target electrode thickness is relatively small. In this case, the number of porosity tests can be appropriately reduced to improve test efficiency. For example, multiplying the ratio of the negative error degree to the average negative error degree by the preset porosity test quantity achieves a correction calculation of the preset porosity test quantity, obtaining a porosity test quantity suitable for the characteristics of the target electrode. Similarly, the ratio of the positive error degree to the average positive error degree is calculated, and the preset conductivity test quantity is corrected to obtain the final conductivity test quantity. The correction principle is the same as in step S22. The preset number of conductivity tests is adjusted according to the relative magnitude of the positive error to obtain a conductivity test number suitable for the characteristics of the target electrode. Subsequently, based on the number of porosity tests and the number of conductivity tests, a first porosity confidence level and a first conductivity confidence level are obtained. These first porosity confidence levels and first conductivity confidence levels reflect the reliability of the testing strategy formulated based on thickness error analysis.

[0059] Subsequently, porosity and conductivity tests were performed on the target electrode according to the number of porosity tests and conductivity tests, respectively, to obtain porosity sequences and conductivity sequences. On the target electrode, corresponding test locations were selected according to the determined number of tests, and appropriate testing methods were used to obtain the porosity and conductivity values ​​at each test location, forming porosity sequences and conductivity sequences. For example, for porosity testing, a corresponding number of test locations are randomly selected on the target electrode according to the number of porosity tests required, and electrode samples with a specification of 5mm×5mm are cut from each test location. When using the mercury intrusion porosimetry method for porosity testing, the electrode sample is placed in the sample cell of the mercury intrusion apparatus, and mercury is injected into the pores of the electrode under different pressures. The porosity value is calculated using the Washburn equation based on the relationship between the amount of mercury intrusion and the intrusion pressure. Alternatively, when using the gas adsorption method for porosity testing, the electrode sample is placed in a BET surface area and porosity analyzer, and the porosity value is calculated based on the BJH theory or DFT theory by measuring the adsorption-desorption isotherm of nitrogen on the electrode. A porosity value is obtained for each test location, and the porosity values ​​of all test locations are arranged in the test order to form a porosity sequence. For conductivity testing, a corresponding number of test locations are randomly selected on the target electrode according to the conductivity test requirements. When using the four-probe method for conductivity testing, four equally spaced probes are perpendicularly contacted with the electrode surface. A constant DC current I is passed through the two outer probes, and the voltage V is measured on the two inner probes. The conductivity σ = 1 / (ρ×t) is calculated according to Ohm's law and geometric correction factor, where ρ is the resistivity and t is the electrode thickness. Alternatively, when using the AC impedance method for conductivity testing, the electrode sample is made into an electrode sheet and assembled into a test cell. A small-amplitude AC voltage signal is applied using an electrochemical workstation, and the corresponding current response is measured. The conductivity value is calculated through impedance spectroscopy analysis. Each test location yields a conductivity value, and the conductivity values ​​of all test locations are arranged in the test order to form a conductivity sequence.

[0060] Furthermore, based on the number of porosity tests and conductivity tests, the first porosity confidence level and the first conductivity confidence level are analyzed and obtained, including:

[0061] S241. Calculate the ratio of the number of porosity tests to the preset number of porosity tests to obtain the first porosity confidence level;

[0062] S242. Calculate the ratio of the number of conductivity tests to the preset number of conductivity tests to obtain the first conductivity confidence level.

[0063] First, the ratio of the number of porosity tests to the preset number of porosity tests is calculated to obtain the first porosity confidence level. Specifically, the number of porosity tests is used as the numerator, and the preset number of porosity tests is used as the denominator, and a division operation is performed to obtain the ratio. When this ratio is greater than 1, it indicates that the negative error analysis determines that the number of porosity tests needs to be increased. In this case, the first porosity confidence level is high, reflecting a high expectation of the reliability of the porosity test results. When this ratio is less than 1, it indicates that the negative error analysis determines that the number of porosity tests can be reduced. In this case, the first porosity confidence level is relatively low, but it still meets the basic test accuracy requirements. The first porosity confidence level quantitatively reflects the credibility of the porosity testing strategy formulated based on the thickness negative error.

[0064] Simultaneously, the ratio of the number of conductivity tests to the preset number of conductivity tests is calculated to obtain the first conductivity confidence level. Specifically, the number of conductivity tests is used as the numerator, and the preset number of conductivity tests is used as the denominator, and a division operation is performed to obtain the ratio. The meaning of this ratio is the same as that in step S241: when the ratio is greater than 1, the first conductivity confidence level is high; when the ratio is less than 1, the first conductivity confidence level is relatively low. The first conductivity confidence level quantitatively reflects the reliability of the conductivity testing strategy formulated based on the thickness positive error.

[0065] The above ratio calculations provide an intuitive and quantitative assessment of the rationality of the test quantity configuration, offering fundamental parameters for subsequent comprehensive confidence analysis.

[0066] Furthermore, performance deviation analysis is performed on the porosity sequence and conductivity sequence to obtain porosity deviation and conductivity deviation. Combining the negative error and positive error, a second porosity confidence level and a second conductivity confidence level are calculated, including:

[0067] S31. Obtain standard porosity and standard conductivity;

[0068] S32. Calculate the absolute deviation of each porosity in the porosity sequence from the standard porosity, and calculate the mean value to obtain the porosity deviation degree.

[0069] S33. Calculate the absolute deviation of each conductivity in the conductivity sequence from the standard conductivity, and calculate the mean value to obtain the conductivity deviation.

[0070] S34. Calculate the similarity between the porosity deviation and the negative error to obtain the second porosity confidence level;

[0071] S35. Calculate the similarity between the conductivity deviation and the positive error to obtain the second conductivity confidence level.

[0072] In a preferred embodiment, firstly, standard porosity and standard conductivity are obtained. Standard porosity refers to the ideal porosity value that a ternary lithium battery electrode prepared under standard process conditions should possess, and is typically determined based on electrode design requirements, active material characteristics, and battery performance indicators. Standard conductivity refers to the ideal conductivity value that a ternary lithium battery electrode prepared under standard process conditions should possess, and is typically determined based on the conductive agent ratio, electrode structure design, and conductivity requirements.

[0073] Then, the absolute deviation of each porosity value in the porosity sequence from the standard porosity is calculated, and the mean value is calculated to obtain the porosity deviation degree. Specifically, the difference between each porosity value in the porosity sequence and the standard porosity is calculated, and the absolute value is taken to obtain the absolute deviation amplitude; all absolute deviation amplitudes are arithmetically averaged to obtain the porosity deviation degree. This porosity deviation degree quantitatively reflects the average deviation of the actual porosity of the target electrode from the standard porosity. Simultaneously, the absolute deviation of each conductivity value in the conductivity sequence from the standard conductivity is calculated, and the mean value is calculated to obtain the conductivity deviation degree. The calculation method is the same as in step S32, and this conductivity deviation degree quantitatively reflects the average deviation of the actual conductivity of the target electrode from the standard conductivity.

[0074] Subsequently, the similarity between the porosity deviation and the negative error was calculated to obtain the second porosity confidence score. This similarity calculation employed numerical correlation analysis, specifically using the formula: Similarity = 1 - |Porosity Deviation - Negative Error| / max(Porosity Deviation, Negative Error). When the porosity deviation and negative error values ​​are close, the absolute value of their difference is small, and the similarity is close to 1, indicating a strong correlation between the thickness negative error and the porosity deviation. This verifies the accuracy of the physical mechanism that a smaller thickness leads to increased density and consequently reduced porosity, thus obtaining a high second porosity confidence score. Conversely, when the difference between the two values ​​is large, the similarity is low, indicating a weaker correlation and a lower second porosity confidence score. Simultaneously, the similarity between the conductivity deviation and the positive error was calculated to obtain the second conductivity confidence score. The same similarity calculation method as in step S34 is used, and the calculation formula is: similarity = 1 - |conductivity deviation - positive error| / max(conductivity deviation, positive error). This is used to verify the correlation between thickness positive error and conductivity deviation, and to evaluate the accuracy of the physical mechanism that excessive thickness leads to reduced density and thus reduced conductivity.

[0075] The second porosity confidence and second conductivity confidence obtained through the above analysis can be used to quantitatively evaluate the effectiveness of predicting porosity and conductivity deviations based on thickness error analysis.

[0076] Furthermore, based on the electrode thickness sequence, porosity sequence, and conductivity sequence, a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter are calculated, including:

[0077] S41. Calculate the standard deviation based on the electrode thickness sequence to obtain the first performance uniformity parameter;

[0078] S42. Based on the porosity sequence and conductivity sequence, calculate the second performance uniformity parameter and the third performance uniformity parameter.

[0079] In a preferred embodiment, firstly, statistical analysis is performed on all thickness values ​​in the electrode thickness sequence. Specifically, the arithmetic mean of the electrode thickness sequence is calculated first, then the deviation of each thickness value from the arithmetic mean is calculated, all deviations are squared, the sum of the squared deviations is divided by the sample size minus 1, and finally the square root is taken to obtain the standard deviation, which serves as the first performance uniformity parameter. This parameter quantitatively reflects the dispersion of the target electrode thickness distribution; the smaller the standard deviation, the more uniform the electrode thickness distribution and the better the thickness consistency.

[0080] Then, using the same standard deviation calculation method as in step S41, statistical analysis is performed on the porosity sequence to calculate the standard deviation of the porosity sequence, obtaining the second performance uniformity parameter. This parameter quantitatively reflects the dispersion of the porosity distribution of the target electrode. Similarly, statistical analysis is performed on the conductivity sequence to calculate the standard deviation of the conductivity sequence, obtaining the third performance uniformity parameter. This parameter quantitatively reflects the dispersion of the conductivity distribution of the target electrode. The smaller the standard deviation value, the more uniform the spatial distribution of the corresponding performance parameter, and the better the performance consistency.

[0081] By calculating the standard deviation mentioned above, the uniformity level of the target electrode in the three key performance dimensions of thickness, porosity and conductivity can be objectively quantified, providing basic data for subsequent comprehensive performance evaluation.

[0082] Furthermore, by combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level, performance uniformity parameters are calculated and used as test results, including:

[0083] S41. Obtain the preset thickness weight and the weight to be assigned;

[0084] S42. Based on the first pore confidence, the first conductivity confidence, the second pore confidence, and the second conductivity confidence, calculate the pore confidence and conductivity confidence, and perform allocation calculation on the weights to be assigned to obtain the pore weight and conductivity weight.

[0085] S43. Based on the preset thickness weight, porosity weight, and conductivity weight, the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter are weighted and calculated to obtain the performance uniformity parameter, which is used as the test result.

[0086] In a preferred embodiment, firstly, a preset thickness weight and a weight to be assigned are obtained. The preset thickness weight refers to a weighting coefficient pre-set for the first performance uniformity parameter in the performance uniformity parameter calculation. This weight is determined based on the fundamental and reliable nature of thickness testing and is typically a fixed value. The weight to be assigned refers to the remaining weights, excluding the preset thickness weight, that need to be allocated between the porosity weight and the conductivity weight, ensuring that the sum of all weighting coefficients is 1, thus satisfying the mathematical requirements of weighted calculation.

[0087] Then, based on the first pore confidence level, the first conductivity confidence level, the second pore confidence level, and the second conductivity confidence level, the pore confidence level and conductivity confidence level are calculated. These are then used to allocate the weights to obtain the pore weight and conductivity weight. Specifically, by comprehensively considering the first and second pore confidence levels, a weighted average or optimal combination method is used to calculate the comprehensive pore confidence level. Similarly, by comprehensively considering the first and second conductivity confidence levels, a comprehensive conductivity confidence level is calculated. Subsequently, based on the relative magnitude of the pore and conductivity confidence levels, the weights are proportionally allocated, with performance parameters having higher confidence levels receiving larger weights, thus obtaining the pore weight and conductivity weight.

[0088] For example, assuming a preset thickness weight of 0.4 and a weight to be assigned of 0.6, the calculated confidence levels for the first pore are 0.8 and the second pore are 0.9. Therefore, the overall pore confidence level can be calculated using a weighted average: (0.8 + 0.9) / 2 = 0.85. Similarly, assuming a first conductivity confidence level of 0.7 and a second conductivity confidence level of 0.6, the overall conductivity confidence level is (0.7 + 0.6) / 2 = 0.65. Based on the relative magnitudes of the pore confidence level (0.85) and the conductivity confidence level (0.65), the weight to be assigned (0.6) is proportionally allocated: pore weight = 0.6 × 0.85 / (0.85 + 0.65) = 0.34, conductivity weight = 0.6 × 0.65 / (0.85 + 0.65) = 0.26. At this point, the preset weights are 0.4 for thickness, 0.34 for porosity, and 0.26 for conductivity. The sum of these three weights is 1.0, which meets the requirements for weighted calculation.

[0089] Then, based on preset thickness weight, porosity weight, and conductivity weight, the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter are weighted and calculated to obtain the performance uniformity parameter, which serves as the test result. The specific calculation formula is: Performance uniformity parameter = Preset thickness weight × First performance uniformity parameter + Porosity weight × Second performance uniformity parameter + Conductivity weight × Third performance uniformity parameter. This performance uniformity parameter comprehensively reflects the overall uniformity level of the target electrode across the three key performance dimensions of thickness, porosity, and conductivity, providing an important basis for the quality assessment and process optimization of ternary lithium battery electrodes.

[0090] Example 2, as Figure 2 As shown, based on the same inventive concept as the ternary lithium battery electrode performance testing method provided in Embodiment 1, this embodiment of the invention also provides a ternary lithium battery electrode performance testing system, comprising:

[0091] The thickness error analysis module 11 is used to perform thickness tests at multiple locations on the target electrode to obtain the electrode thickness sequence, perform positive and negative error analysis on the electrode thickness, and obtain the negative error degree and the positive error degree, wherein the target electrode is a ternary lithium battery electrode.

[0092] The test configuration execution module 12 is used to configure the number of porosity tests and the number of conductivity tests based on the negative error degree and the positive error degree, perform test confidence analysis to obtain the first porosity confidence degree and the first conductivity confidence degree, and perform tests respectively to obtain the porosity sequence and the conductivity sequence.

[0093] The performance deviation analysis module 13 is used to perform performance deviation analysis calculations on the porosity sequence and conductivity sequence to obtain the porosity deviation degree and conductivity deviation degree. Combining the negative error degree and positive error degree, the second porosity confidence degree and the second conductivity confidence degree are calculated.

[0094] The uniformity calculation module 14 calculates a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter based on the electrode thickness sequence, porosity sequence, and conductivity sequence. It then combines the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level to calculate the performance uniformity parameter as the test result.

[0095] Furthermore, the thickness error analysis module 11 includes the following execution steps:

[0096] Multiple thickness test locations are randomly selected for the target electrode, and thickness tests are performed at each location to obtain the electrode thickness sequence.

[0097] Obtain the standard electrode thickness;

[0098] The electrode thicknesses within the selected electrode thickness sequence that are less than or equal to or greater than the standard electrode thickness are identified to obtain negative electrode thickness sequences and positive electrode thickness sequences. Negative error analysis and positive error analysis are then performed to obtain negative error degree and positive error degree.

[0099] Furthermore, the thickness error analysis module 11 also includes the following execution steps:

[0100] Randomly select several negative electrode thicknesses within the negative electrode thickness sequence, calculate the absolute error magnitude between them and the standard electrode thickness, and calculate the average value to obtain the negative error degree.

[0101] Several positive electrode thicknesses are randomly selected from the positive electrode thickness sequence, and the absolute error amplitude between them and the standard electrode thickness is calculated. The mean value is then calculated to obtain the positive error degree.

[0102] Furthermore, the test configuration execution module 12 includes the following execution steps:

[0103] Obtain the preset number of porosity tests and the preset number of conductivity tests;

[0104] Calculate the ratio of the negative error degree to the average negative error degree, and correct the preset porosity test quantity to obtain the porosity test quantity.

[0105] Calculate the ratio of the positive error degree to the average positive error degree, and correct the preset conductivity test quantity to obtain the conductivity test quantity;

[0106] Based on the number of porosity tests and conductivity tests, the first porosity confidence level and the first conductivity confidence level are obtained through analysis.

[0107] The target electrode is subjected to porosity and conductivity tests according to the specified number of porosity tests and conductivity tests, respectively, to obtain porosity sequences and conductivity sequences.

[0108] Furthermore, the test configuration execution module 12 also includes the following execution steps:

[0109] Calculate the ratio of the number of porosity tests to the preset number of porosity tests to obtain the first porosity confidence level;

[0110] Calculate the ratio of the number of conductivity tests to the preset number of conductivity tests to obtain the first conductivity confidence level.

[0111] Furthermore, the performance deviation analysis module 13 includes the following execution steps:

[0112] Obtain standard porosity and standard conductivity;

[0113] Calculate the absolute deviation of each porosity in the porosity sequence from the standard porosity, and calculate the mean value to obtain the porosity deviation degree;

[0114] Calculate the absolute deviation of each conductivity in the conductivity sequence from the standard conductivity, and calculate the mean value to obtain the conductivity deviation degree;

[0115] Calculate the similarity between the porosity deviation and the negative error to obtain the second porosity confidence level;

[0116] The similarity between the conductivity deviation and the positive error is calculated to obtain the second conductivity confidence level.

[0117] Furthermore, the uniformity calculation module 14 includes the following execution steps:

[0118] Based on the electrode thickness sequence, the standard deviation is calculated to obtain the first performance uniformity parameter;

[0119] Based on the porosity sequence and conductivity sequence, the second performance uniformity parameter and the third performance uniformity parameter are calculated.

[0120] Furthermore, the uniformity calculation module 14 includes the following execution steps:

[0121] Obtain the preset thickness weights and the weights to be assigned;

[0122] Based on the first pore confidence level, the first conductivity confidence level, the second pore confidence level, and the second conductivity confidence level, the pore confidence level and conductivity confidence level are calculated, and the weights to be assigned are calculated to obtain the pore weights and conductivity weights.

[0123] Based on the preset thickness weight, porosity weight, and conductivity weight, the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter are weighted and calculated to obtain the performance uniformity parameter, which is used as the test result.

[0124] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0125] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0127] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0128] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0129] Although preferred embodiments of the invention have been described, those skilled in the art, once they have learned the basic inventive concept, can make other changes and modifications to these embodiments.

[0130] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for testing the performance of ternary lithium battery electrodes, characterized in that, The method includes: Thickness tests are performed at multiple locations on the target electrode to obtain an electrode thickness sequence. Positive and negative error analyses are then performed on the electrode thickness to obtain the negative and positive error degrees. The target electrode is a ternary lithium battery electrode. Based on the negative and positive error values, the number of porosity tests and conductivity tests are configured and obtained. Test confidence analysis is performed to obtain a first porosity confidence value and a first conductivity confidence value. Tests are then conducted separately to obtain porosity sequences and conductivity sequences, including: Obtain the preset number of porosity tests and the preset number of conductivity tests; Calculate the ratio of the negative error degree to the average negative error degree, and correct the preset porosity test quantity to obtain the porosity test quantity. Calculate the ratio of the positive error degree to the average positive error degree, and correct the preset conductivity test quantity to obtain the conductivity test quantity; Based on the number of porosity tests and conductivity tests, the first porosity confidence level and the first conductivity confidence level are obtained through analysis, including: Calculate the ratio of the number of porosity tests to the preset number of porosity tests to obtain the first porosity confidence level; Calculate the ratio of the number of conductivity tests to the preset number of conductivity tests to obtain the first conductivity confidence level; The target electrode was subjected to porosity and conductivity tests according to the specified number of porosity tests and conductivity tests, respectively, to obtain porosity sequences and conductivity sequences. Performance deviation analysis is performed on the porosity and conductivity sequences to obtain porosity deviation and conductivity deviation. Combining the negative and positive error values, a second porosity confidence level and a second conductivity confidence level are calculated, including: Obtain standard porosity and standard conductivity; Calculate the absolute deviation of each porosity in the porosity sequence from the standard porosity, and calculate the mean value to obtain the porosity deviation degree; Calculate the absolute deviation of each conductivity in the conductivity sequence from the standard conductivity, and calculate the mean value to obtain the conductivity deviation degree; Calculate the similarity between the porosity deviation and the negative error to obtain the second porosity confidence level; Calculate the similarity between the conductivity deviation and the positive error to obtain the second conductivity confidence level; Based on the electrode thickness sequence, porosity sequence, and conductivity sequence, a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter are calculated. Combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level, a performance uniformity parameter is calculated as the test result, including: Based on the electrode thickness sequence, the standard deviation is calculated to obtain the first performance uniformity parameter; Based on the porosity sequence and conductivity sequence, the second performance uniformity parameter and the third performance uniformity parameter are calculated. Obtain the preset thickness weights and the weights to be assigned; Based on the first pore confidence level, the first conductivity confidence level, the second pore confidence level, and the second conductivity confidence level, the pore confidence level and conductivity confidence level are calculated, and the weights to be assigned are calculated to obtain the pore weights and conductivity weights. Based on the preset thickness weight, porosity weight, and conductivity weight, the first performance uniformity parameter, the second performance uniformity parameter, and the third performance uniformity parameter are weighted and calculated to obtain the performance uniformity parameter, which is used as the test result.

2. The method for testing the performance of ternary lithium battery electrodes according to claim 1, characterized in that, Thickness measurements were performed at multiple locations on the target electrode to obtain an electrode thickness sequence. Negative and positive error analyses of the electrode thickness were then conducted to obtain the negative and positive error values, including: Multiple thickness test locations are randomly selected for the target electrode, and thickness tests are performed at each location to obtain the electrode thickness sequence. Obtain the standard electrode thickness; The electrode thicknesses within the selected electrode thickness sequence that are less than or equal to or greater than the standard electrode thickness are identified to obtain negative electrode thickness sequences and positive electrode thickness sequences. Negative error analysis and positive error analysis are then performed to obtain negative error degree and positive error degree.

3. The method for testing the performance of ternary lithium battery electrodes according to claim 2, characterized in that, Perform negative and positive error analysis to obtain the negative error margin and positive error margin, including: Randomly select several negative electrode thicknesses within the negative electrode thickness sequence, calculate the absolute error magnitude between them and the standard electrode thickness, and calculate the average value to obtain the negative error degree. Several positive electrode thicknesses are randomly selected from the positive electrode thickness sequence, and the absolute error amplitude between them and the standard electrode thickness is calculated. The mean value is then calculated to obtain the positive error degree.

4. A ternary lithium battery electrode performance testing system, characterized in that, The system is used to implement the ternary lithium battery electrode performance testing method as described in any one of claims 1 to 3, the system comprising: The thickness error analysis module is used to perform thickness tests at multiple locations on the target electrode to obtain the electrode thickness sequence, perform positive and negative error analysis on the electrode thickness, and obtain the negative error degree and positive error degree. The target electrode is a ternary lithium battery electrode. The test configuration execution module is used to configure the number of porosity tests and the number of conductivity tests based on the negative error degree and the positive error degree, perform test confidence analysis to obtain the first porosity confidence degree and the first conductivity confidence degree, and perform tests respectively to obtain the porosity sequence and the conductivity sequence. The performance deviation analysis module is used to perform performance deviation analysis calculations on the porosity sequence and conductivity sequence to obtain the porosity deviation degree and conductivity deviation degree. Combining the negative error degree and positive error degree, the second porosity confidence degree and the second conductivity confidence degree are calculated. The uniformity calculation module calculates a first performance uniformity parameter, a second performance uniformity parameter, and a third performance uniformity parameter based on the electrode thickness sequence, porosity sequence, and conductivity sequence. Combining the first porosity confidence level, the first conductivity confidence level, the second porosity confidence level, and the second conductivity confidence level, the module calculates the performance uniformity parameter as the test result.

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