An interface bonding failure test method, system, storage medium and program product

Abstract

An interface bonding failure test method, system, storage medium and program product, relate to the field of testing or analyzing materials by means of determining chemical or physical properties of materials, in the method, the interface bonding state between the pole piece coating and the current collector is evaluated by performing a single loading and unloading cycle. In the loading stage, a first resistance value is measured when the pressure reaches a preset target detection pressure, and then the pressure is continuously increased to a preset peak pressure (the pressure is greater than the target detection pressure but less than the yield strength of the current collector). In the unloading stage, a second resistance value is measured when the pressure decreases back to the preset target detection pressure. By comparing the difference between the two resistance values with a preset hysteresis threshold, the interface bonding state is determined: if the difference is greater than the threshold, it is determined that there is interface bonding failure. The present application is used to reduce the difficulty of identifying overpressure risk and defining the best roll pressure process window.

Description

Technical Field

[0001] This application belongs to the field of testing or analyzing materials by measuring their chemical or physical properties, and particularly relates to a method, system, storage medium, and program product for testing interface bonding failure. Background Technology

[0002] The evaluation of the adhesion of the separator has a significant impact on the research and development of separator coatings, the design of separator introduction processes, and the actual performance of the battery cells. Accurately evaluating the adhesion in actual application scenarios is of great significance for battery cell design and production.

[0003] Traditional lithium-ion battery separator adhesion testing uses a tensile testing machine to perform a one-sided peel test on the disassembled cell separator and electrode. However, this method has poor stability and is disconnected from the bending stress scenario during actual cell extrusion, making it difficult to accurately simulate real-world conditions. To quantitatively evaluate the conductivity of the electrode, the two-probe method is widely used in related technologies. This technique uses two gold-plated flat-head probes to clamp the electrode under constant pressure, testing by observing the continuity between the upper and lower probes. However, this traditional two-probe method measures the total resistance of the electrode, making it difficult to measure the interface resistance separately. It requires complex calculations or additional steps, making it difficult to accurately distinguish the contribution of coating resistance and interface contact resistance, increasing the difficulty of identifying overvoltage risks and defining the optimal rolling process window.

[0004] More importantly, during the actual processing or stress application of the electrode, excessive pressure can lead to microscopic peeling or damage between the coating and the current collector, resulting in interfacial bonding failure. Relevant constant-pressure resistance testing methods can only obtain a single resistance value of the electrode under a static pressure, making it difficult to reflect irreversible structural damage during stress changes (loading and unloading). Due to the lack of dynamic monitoring of the changes in electrical properties after the electrode rebounds under pressure, related technologies struggle to accurately determine whether latent interfacial bonding failure has occurred between the coating and the current collector. This increases the difficulty of identifying overpressure risks and defining the optimal rolling process window for the electrode. Summary of the Invention

[0005] This application provides an interface-based failure testing method, system, storage medium, and program product to reduce the difficulty of identifying overpressure risks and defining the optimal rolling process window.

[0006] In the first aspect, this application provides an interface-based failure testing method, which controls the testing device to perform a single loading and unloading cycle on the electrode under test;

[0007] During the loading phase of the loading and unloading cycle, when the pressure applied to the electrode under test reaches the preset target detection pressure, the first resistance value of the electrode under test is collected.

[0008] Continue to increase the pressure applied to the electrode under test until the preset peak pressure is reached. The preset peak pressure is configured to be greater than the preset target detection pressure and less than the yield strength of the current collector of the electrode under test.

[0009] During the unloading phase of the loading / unloading cycle, the pressure applied to the electrode under test is reduced from the preset peak pressure.

[0010] When the pressure during the unloading phase drops back to the preset target detection pressure, the second resistance value of the electrode under test is collected.

[0011] Calculate the difference between the second resistance value and the first resistance value;

[0012] If the difference is greater than the preset hysteresis threshold, it is determined that there is an interfacial bonding failure between the coating of the electrode under test and the current collector.

[0013] By employing the above technical solution, two resistance values ​​of the electrode under test are collected under the same preset target detection pressure during the loading and unloading cycle, and their difference is calculated. This difference is then combined with a preset hysteresis threshold for judgment, effectively identifying electrode interface bonding failure. When interface bonding failure exists between the coating and the current collector, plastic deformation or interface delamination of the coating occurs during pressurization, resulting in a significant change in resistance value during unloading compared to loading. By controlling the preset peak pressure within a range lower than the yield strength of the current collector, permanent damage to the current collector is avoided, improving the reliability of the test results. This method can complete the assessment of the interface bonding state in a single loading and unloading cycle, reducing testing time and improving production efficiency. Since the resistance difference at the same pressure point is used as the judgment criterion, the impact of pressure control accuracy fluctuations on the test results is reduced, thereby lowering the difficulty of identifying overpressure risks and defining the optimal rolling process window.

[0014] In conjunction with some implementations of the first aspect, in some implementations, the test device is controlled to perform a single loading and unloading cycle on the electrode under test, specifically including:

[0015] Send a step-by-step pressurization command to the drive unit of the test device to drive the test device to apply pressure to the electrode under test in a stepped manner at a preset pressure step.

[0016] During each pressure step, the instantaneous resistance change rate of the electrode under test is monitored in real time at a preset high-frequency sampling rate.

[0017] The instantaneous rate of change of resistance is compared with a preset rheological equilibrium threshold, which is configured as the upper limit of the resistance fluctuation rate characterizing the completion of stress relaxation state of the polymer binder of the electrode.

[0018] If the instantaneous resistance change rate is less than the preset rheological equilibrium threshold, it is determined that the electrode state under the current pressure step has reached rheological equilibrium, and the step-by-step pressurization command of the next pressure step is triggered or the step of real-time monitoring of the instantaneous resistance change rate of the electrode under test at a preset high-frequency sampling rate is executed until a single loading and unloading cycle is completed.

[0019] By adopting the above technical solution, employing a step-by-step pressurization method and monitoring the resistance change rate in real time during each pressure step, and comparing it with a preset rheological equilibrium threshold to determine whether the electrode has reached rheological equilibrium, the impact of the stress relaxation effect of the polymer binder in the electrode on the test results can be reduced. Because the polymer binder has viscoelastic characteristics, stress relaxation occurs under pressure, leading to fluctuations in resistance values. By waiting for the resistance change rate to fall below the preset rheological equilibrium threshold before proceeding to the next pressure loading or data acquisition step, the stability of the resistance measurement data is improved. Adaptively adjusting the pressure holding time avoids the problems of low testing efficiency or insufficient testing accuracy that may result from a fixed holding time, thus improving the overall efficiency and accuracy of the testing process.

[0020] In conjunction with some implementations of the first aspect, in some implementations, the test device is controlled to perform a single loading and unloading cycle on the electrode under test, specifically including:

[0021] Obtain the coating design thickness and coating porosity parameters of the electrode to be tested;

[0022] Based on the coating design thickness and coating porosity parameters, a loading rate that matches the actual breathing conditions of the battery is calculated using a preset strain rate conversion model.

[0023] The control testing device applies continuously varying pressure to the electrode under test according to the loading rate;

[0024] When applying continuously varying pressure, the relationship between the second derivative of pressure and displacement is monitored in real time.

[0025] When the second derivative of pressure and displacement suddenly becomes negative, an overload protection signal is generated and the single loading and unloading cycle is immediately terminated.

[0026] By adopting the above technical solution, based on the coating design thickness and porosity parameters of the electrode under test, a loading rate matching the actual operating conditions of the battery is calculated using a preset strain rate conversion model. Furthermore, by monitoring the second derivative relationship between pressure and displacement in real time during the application of continuously varying pressure, the characterization capability of the electrode interface bonding state during testing can be improved. Since the loading rate affects the strain response characteristics of the coating, using a loading rate matching actual operating conditions can more accurately reflect the interface bonding state of the electrode under real-world usage. By monitoring the second derivative relationship between pressure and displacement and promptly terminating the test upon the occurrence of a sudden negative value, the risk of electrode damage due to overloading is reduced, improving the safety of the testing process and the electrode yield.

[0027] In some embodiments of the first aspect, after determining that there is interfacial bonding failure between the coating of the electrode under test and the current collector, the method further includes:

[0028] Extract the first resistance-pressure data sequence during the loading phase, from the preset target detection pressure to the preset peak pressure, and the second resistance-pressure data sequence during the unloading phase, from the preset peak pressure to the preset target detection pressure.

[0029] By fitting and calculating the first resistance-pressure data sequence and the second resistance-pressure data sequence using the power function relationship, the loading power law exponent, which characterizes the contact characteristics of the loading process, and the unloading power law exponent, which characterizes the contact characteristics of the unloading process, are obtained.

[0030] Calculate the exponential deviation of the unloading power law exponent from the loading power law exponent;

[0031] If the index deviation is less than or equal to the preset deformation judgment threshold, the electrode under test is determined to be in the state of plastic densification of the coating, and the judgment result of interface bonding failure is corrected to interface bonding qualified.

[0032] If the index deviation is greater than the preset deformation judgment threshold, the electrode under test is confirmed to be in a state of physical layering at the interface.

[0033] By employing the above technical solution, and extracting the resistance-pressure data sequences during the loading and unloading stages and fitting them with a power function, the power-law exponents for loading and unloading are obtained. The exponent deviation is calculated and compared with a preset deformation judgment threshold, which can accurately distinguish between the plastic densification state and the physical delamination state of the electrode coating. In the plastic densification state, due to irreversible compaction of the coating particles, the resistance value in the unloading stage is relatively higher than that in the loading stage, but the pressure-resistance relationship still maintains similar power-law characteristics, resulting in a smaller exponent deviation. In the physical delamination state, due to the separation of the coating and the current collector interface, the pressure-resistance relationship in the unloading stage changes significantly, leading to a larger exponent deviation. This reduces the misjudgment rate of the test results and improves the accuracy of the interface bonding state determination.

[0034] In conjunction with some implementations of the first aspect, in some implementations, the method further includes, before calculating the exponential deviation of the unloading power law exponent from the loading power law exponent:

[0035] Obtain the first goodness of fit for the loading process and the second goodness of fit for the unloading process;

[0036] Determine whether both the first and second goodness-of-fit scores are greater than the preset linear correlation threshold;

[0037] If either the first goodness of fit or the second goodness of fit is less than or equal to the preset linear correlation threshold, an abnormal data alarm signal will be output.

[0038] If the first goodness of fit and the second goodness of fit are both greater than the preset linear correlation threshold, then the step of calculating the exponential deviation of the unloading power law exponent relative to the loading power law exponent is performed.

[0039] By adopting the above technical solution and introducing a goodness-of-fit judgment mechanism, the data fitting quality during the loading and unloading process can be evaluated. This allows for the identification of abnormal data caused by interference during the testing process, equipment malfunctions, or sample anomalies. When the goodness-of-fit is lower than a preset linear correlation threshold, it indicates a significant deviation between the measured data and the theoretical model. Timely output of alarm signals helps to eliminate invalid test data, improves the reliability of test results, and reduces the probability of misjudgment due to data anomalies.

[0040] In conjunction with some implementations of the first aspect, in some implementations, obtaining a first goodness-of-fit for the loading process and a second goodness-of-fit for the unloading process specifically includes:

[0041] Perform double logarithmic coordinate transformation on the first resistance-pressure data sequence and the second resistance-pressure data sequence respectively to obtain the first data sequence and the second data sequence;

[0042] The first coefficient of determination for the first data sequence and the second coefficient of determination for the second data sequence are calculated using the least squares method.

[0043] The first coefficient of determination is determined as the first goodness of fit, and the second coefficient of determination is determined as the second goodness of fit.

[0044] By employing the above technical solution, a double logarithmic coordinate transformation is performed on the resistance-pressure data sequence to convert the power function relationship into a linear relationship. The coefficient of determination is then calculated using the least squares method as a goodness-of-fit index, allowing for an accurate assessment of the degree of agreement between the data and the theoretical model. The double logarithmic transformation eliminates the influence of differences in data magnitude, resulting in better numerical stability in the fitting calculation and improving the accuracy and objectivity of the goodness-of-fit assessment.

[0045] In a second aspect, embodiments of this application provide an interface bonding failure testing system, which includes: one or more processors and a memory; the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0046] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0047] Fourthly, embodiments of this application provide a computer program product that, when run on a system, causes the system to execute the method described in any possible implementation of the first aspect.

[0048] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0049] 1. This application provides a method for testing interface bonding failure. By collecting two resistance values ​​of the electrode under test at the same preset target detection pressure during loading and unloading cycles and calculating their difference, combined with a preset hysteresis threshold, interface bonding failure of the electrode can be effectively identified. When interface bonding failure exists between the coating and the current collector, plastic deformation or interface delamination of the coating will occur during pressurization, resulting in a significant change in the resistance value at unloading compared to loading. By controlling the preset peak pressure within a range lower than the yield strength of the current collector, permanent damage to the current collector is avoided, improving the reliability of the test results. This method can complete the assessment of the interface bonding state in a single loading and unloading cycle, reducing test time and improving production efficiency. Since the resistance difference at the same pressure point is used as the judgment criterion, the influence of pressure control accuracy fluctuations on the test results is reduced, thereby reducing the difficulty of identifying overpressure risks and defining the optimal rolling process window.

[0050] 2. This application provides a method for testing interface bonding failure. By extracting the resistance-pressure data sequences during loading and unloading phases and performing power function fitting, the power-law exponents for loading and unloading are obtained. The exponent deviation is calculated and compared with a preset deformation judgment threshold, which can accurately distinguish between the plastic densification state and the physical delamination state of the electrode coating. In the plastic densification state, due to irreversible compaction of the coating particles, the resistance value in the unloading phase is relatively higher than that in the loading phase, but the pressure-resistance relationship still maintains a similar power-law characteristic, so the exponent deviation is small. In the physical delamination state, due to the separation of the coating and the current collector interface, the pressure-resistance relationship in the unloading phase changes significantly, resulting in a larger exponent deviation. This reduces the false judgment rate of the test results and improves the accuracy of interface bonding state determination. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating an interface-based failure testing method in an embodiment of this application.

[0052] Figure 2 This is another flowchart illustrating an interface-based failure testing method in an embodiment of this application.

[0053] Figure 3 This is a schematic diagram of the physical device structure of an interface-based failure testing system provided in an embodiment of this application. Detailed Implementation

[0054] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0055] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0056] The following example is used in conjunction with Figure 1 The following describes an interface-based failure testing method in an embodiment of this application:

[0057] Please see Figure 1 This is a flowchart illustrating an interface-based failure testing method in an embodiment of this application.

[0058] S101, Control the test device to perform a single loading and unloading cycle on the electrode under test;

[0059] The system control test device performs a single loading / unloading cycle on the electrode under test. The electrode under test refers to the battery electrode to be tested for interfacial bonding failure, which typically consists of a current collector and an active material coating on the surface of the current collector. A single loading / unloading cycle refers to the complete process in which the system control test device applies pressure to the electrode under test, increasing the pressure from an initial state to a certain peak value, and then reducing the pressure from that peak value back to the initial state or close to the initial state. The drive unit refers to the power mechanism in the test device used to generate displacement or pressure, such as a servo motor, piezoelectric ceramic actuator, or pneumatic / hydraulic cylinder. The step-pressurization command refers to the control signal sent by the system to the drive unit, instructing the drive unit to pressurize according to a preset discrete pressure increment. The preset pressure step size refers to the fixed value or predetermined sequence of values ​​for each pressure increase during the step-pressurization process. The preset high-frequency sampling rate refers to the data acquisition frequency used by the system when monitoring resistance changes. This frequency is high enough to capture transient resistance fluctuations caused by changes in the microstructure inside the electrode, such as a sampling frequency greater than 1 kHz. Instantaneous resistance change rate refers to the ratio of the change in resistance of the tested electrode to the time interval within a very short time interval, or the percentage change in resistance relative to the previous moment. The preset rheological equilibrium threshold is a pre-set numerical standard used to determine whether the electrode has completed the stress relaxation process under the action of the polymer binder, i.e., whether the resistance value has stabilized. The coating design thickness refers to the target coating thickness value specified in the electrode manufacturing process document. The coating porosity parameter refers to the percentage of pore volume within the coating to the total volume, reflecting the density of the coating. The preset strain rate conversion model is a mathematical model or algorithm used to establish the mapping relationship between the battery's volume expansion / contraction rate (breathing condition) during actual operation and the loading rate of the pressure applied by the testing device. The loading rate refers to the rate at which the testing device applies pressure, which can be a constant rate of pressure change or a rate of displacement change. The overload protection signal is an emergency control signal generated when the system detects an abnormal situation (such as excessive pressure or material failure), used to trigger a safety mechanism. The second derivative relationship between pressure and displacement reflects the rate of change of material stiffness, used to identify abrupt changes in material properties. This step can be achieved in at least the following two ways:

[0060] The system can send a step-by-step pressurization command to the drive unit of the testing device to drive the testing device to apply pressure to the electrode under test in a stepped manner at a preset pressure step. During each pressure step, the instantaneous resistance change rate of the electrode under test is monitored in real time at a preset high-frequency sampling rate. The instantaneous resistance change rate is compared with a preset rheological equilibrium threshold, which is configured as the upper limit of the resistance fluctuation rate characterizing the completion of stress relaxation of the polymer binder of the electrode. If the instantaneous resistance change rate is determined to be less than the preset rheological equilibrium threshold, it is determined that the electrode state at the current pressure step has reached rheological equilibrium, and the system triggers the step-by-step pressurization command for the next pressure step or executes the step of monitoring the instantaneous resistance change rate of the electrode under test in real time at a preset high-frequency sampling rate, until a single loading and unloading cycle is completed. The system first initializes the test parameters and sends the first step-by-step pressurization command to the drive unit. The drive unit responds to the command by increasing the pressure applied to the electrode under test by a preset pressure step. During the pressure holding phase, the system uses a high-precision resistance measurement module to continuously acquire voltage and current data of the electrode under test at a preset high-frequency sampling rate, calculates the instantaneous resistance value, and further calculates the instantaneous resistance change rate. The system compares the calculated instantaneous resistance change rate with a preset rheological equilibrium threshold stored in the database in real time. If the instantaneous resistance change rate is greater than or equal to the preset rheological equilibrium threshold, it indicates that the polymer binder inside the electrode has not yet completed stress relaxation, and the resistance is still fluctuating significantly. The system continues to maintain the current pressure and continuously monitors. Once it is determined that the instantaneous resistance change rate is less than the preset rheological equilibrium threshold, the system determines that the electrode state under the current pressure step has reached rheological equilibrium, and then triggers the pressurization command for the next pressure step, repeating the above process until the loading phase is completed, and then enters the unloading phase to complete the cycle.

[0061] The system can also acquire the coating design thickness and porosity parameters of the electrode under test; based on the coating design thickness and porosity parameters, it uses a preset strain rate conversion model to calculate a loading speed that matches the actual breathing conditions of the battery; it controls the testing device to apply continuously varying pressure to the electrode under test according to the loading speed; while applying continuously varying pressure, it monitors the second derivative relationship between pressure and displacement in real time; when the second derivative of pressure and displacement suddenly becomes negative, it generates an overload protection signal and immediately terminates the single loading and unloading cycle. The system first acquires the coating design thickness and porosity parameters of the electrode under test through the user interface or production management system. The system calls the preset strain rate conversion model to convert the rate of change in electrode thickness (i.e., breathing conditions) caused by lithium-ion insertion and extraction during battery charging and discharging into the loading speed of the testing device. This model considers the mechanical properties of porous media, ensuring that the testing process can realistically simulate the internal stress conditions of the battery. The system controls the testing device to apply continuously varying pressure to the electrode under test according to the calculated loading speed. During loading, the system simultaneously collects data from pressure and displacement sensors and calculates the second derivative of pressure with respect to displacement in real time. The system continuously monitors the second derivative value. Once a sudden negative change in the second derivative is detected, which usually means that the electrode structure has yielded or micro-fractured, the system immediately generates an overload protection signal, instructing the drive unit to stop pressurizing and unload quickly, thereby terminating the single loading and unloading cycle and preventing equipment damage or complete sample destruction.

[0062] S102. During the loading phase of the loading and unloading cycle, when the pressure applied to the electrode under test reaches the preset target detection pressure, the first resistance value of the electrode under test is collected.

[0063] The loading phase refers to the process in which the pressure applied to the electrode under test gradually increases from its initial value (usually zero or preload) during a single loading and unloading cycle. The preset target detection pressure is a key pressure point specified in the test plan. This pressure point is typically selected to reflect the interlayer contact pressure under normal battery operation, or the typical pressure value experienced by the electrode during the rolling process. The first resistance value refers to the penetration resistance or interface resistance of the electrode under test measured by the system when the real-time monitored pressure value first equals or is extremely close to the preset target detection pressure during the loading phase. The core of this step is to accurately capture the resistance state under a specific pressure as a benchmark for subsequent comparisons.

[0064] The system can implement this step in two ways. The first method uses pressure-triggered synchronous acquisition technology. The system is equipped with a high-frequency pressure sensor and a high-precision resistance measurement unit. During loading, the system's main control unit polls the pressure sensor's output signal at extremely short intervals (e.g., microseconds). The system sets a pressure trigger window centered on a preset target detection pressure, with a very small upper and lower tolerance range. When the real-time pressure signal falls into this trigger window, the main control unit immediately sends an acquisition command to the resistance measurement unit. Upon receiving the command, the resistance measurement unit freezes the current voltage and current readings, calculates the resistance value using Ohm's law, marks it as the first resistance value, and stores it in a cache. To prevent false triggering due to noise interference, the system can use a moving average filtering algorithm to preprocess the pressure signal. The second method uses timestamp alignment technology based on the data stream. During the loading phase, the system independently records the pressure data stream and resistance data stream at a fixed high sampling rate, and assigns a precise timestamp to each data point. After the loading phase ends, the system performs post-processing analysis on the acquired data streams. The system traverses the pressure data stream, searching for the data point closest to the preset target detection pressure and recording its corresponding timestamp. Then, the system searches the resistance data stream for data points with the same or closest timestamps, and determines the resistance value at that point as the first resistance value. If the sampling times of the two data streams do not completely overlap, the system uses linear interpolation or spline interpolation algorithms to calculate the precise resistance value corresponding to the target timestamp based on the resistance data from adjacent time points.

[0065] S103. Continue to increase the pressure applied to the electrode under test until the preset peak pressure is reached;

[0066] The system continues to increase the pressure applied to the electrode under test until a preset peak pressure is reached. This preset peak pressure is configured to be greater than the preset target detection pressure but less than the yield strength of the current collector in the electrode under test. The preset peak pressure refers to the maximum pressure value that the system is allowed to apply to the electrode under test in a single loading / unloading cycle. This value is strictly configured to be greater than the preset target detection pressure to ensure that the test covers the mechanical behavior after the target pressure point; simultaneously, this value must be less than the yield strength of the current collector in the electrode under test. The yield strength of the current collector refers to the critical stress value at which the current collector material (such as copper foil or aluminum foil) undergoes plastic deformation. If the applied pressure exceeds this value, the current collector will undergo irreversible tensile stress or rupture, resulting in a destructive test and distorted results. The purpose of this step is to further compress the coating without damaging the current collector, inducing any potential interfacial bonding defects.

[0067] The system can implement this step in two ways. The first method is closed-loop PID control based on force feedback. The system sets a preset peak pressure as the target setpoint for the PID controller. After acquiring the first resistance value, the system continues to send a pressurization signal to the drive mechanism. The pressure sensor provides real-time feedback of the current pressure value as a process variable. The PID controller calculates the error between the target setpoint and the process variable, and adjusts the control output to the drive mechanism according to the proportional, integral, and derivative parameters, ensuring the pressure smoothly and quickly approaches the preset peak pressure. To ensure that the pressure does not exceed the yield strength of the current collector, a hard limit is set in the PID control logic. Once the feedback pressure reaches the preset peak pressure, the position of the drive mechanism is immediately locked or switched to a pressure-holding mode to prevent overshoot. The second method is predictive control based on a displacement-pressure model. The system pre-stores a typical compression curve model of the electrode under test. After reaching the preset target detection pressure, the system predicts the remaining displacement required to reach the preset peak pressure based on the model. The system controls the drive motor to move this remaining displacement according to the planned speed curve. During the movement, the system continuously monitors the pressure value as a safety redundancy. If the pressure reaches the preset peak pressure before the predicted displacement is reached due to electrode thickness tolerance, the system prioritizes responding to the pressure signal and immediately stops the motor. This method has higher execution efficiency on production lines with good electrode consistency.

[0068] S104. During the unloading phase of the loading and unloading cycle, the pressure applied to the electrode under test is reduced from the preset peak pressure.

[0069] The unloading phase refers to the process in a single loading / unloading cycle where the pressure applied to the electrode under test gradually decreases from a preset peak pressure back to its initial state or a lower pressure level. This process simulates the rebound behavior of the battery electrode after external pressure is released. Pressure reduction refers to the driving unit reversing its movement or releasing the load, causing a decrease in the pressure value on the electrode. This step is a crucial part of the interface resistance hysteresis effect test. By releasing the pressure, it is observed whether the electrode resistance can return to the level of the loading phase, thereby determining the strength of the interface bonding.

[0070] The system can implement this step in two ways. The first method is a controlled linear unloading strategy. The system control drive unit releases pressure at a constant unloading rate (e.g., 1 MPa per second). The system adjusts the exhaust valve opening (for pneumatic systems) or motor reversal speed (for electric systems) through closed-loop control to ensure a linear pressure decrease over time. This method ensures the smoothness of the unloading process, avoiding instantaneous oscillations in the electrode's internal structure caused by sudden pressure drops, thus obtaining more stable resistance rebound data. The system continuously records the pressure-time curve during unloading to verify the linearity of the unloading rate. The second method is a staged release strategy. The system divides the range from the preset peak pressure to zero pressure into several sub-ranges. The system control device first rapidly reduces the pressure to the first intermediate node, holds it briefly (e.g., 0.5 seconds) to allow the electrode's microstructure to initially rebound, and then rapidly reduces it to the next node. This stepped unloading method allows the transient rebound characteristics of the electrode to be observed at different pressure levels. Although the main purpose is to reduce pressure, the stepped release helps to distinguish the effects of elastic deformation recovery and residual plastic deformation on resistance.

[0071] S105. When the pressure during the unloading stage drops back to the preset target detection pressure, the second resistance value of the electrode under test is collected.

[0072] The pressure drop during the unloading phase refers to the process of the pressure value gradually decreasing from its peak value. When the real-time pressure value is equal to the preset target detection pressure set in step S202 again, the system triggers the acquisition action. The second resistance value refers to the resistance value of the electrode under test measured at the exact same pressure point (preset target detection pressure) as the loading phase during the unloading process. Due to the viscoelasticity and plasticity of the electrode material, the contact state of its internal conductive network may change after being pressurized to the peak value and then unloaded, and the second resistance value is usually different from the first resistance value.

[0073] The system can implement this step in two ways. The first method uses a hysteresis comparison acquisition method. During unloading, the system continuously reads the pressure sensor values. A comparison logic is set up so that when the real-time pressure value crosses the preset target detection pressure from high to low, an interrupt signal is triggered. This interrupt signal directly activates the resistance measurement circuit for sampling. To eliminate multiple triggers caused by signal jitter, a single-trigger latch mechanism is set up. That is, during a single unloading process, once the resistance value corresponding to the target pressure is successfully acquired, the function is locked until the next test cycle resets. The resistance value recorded by the system is the second resistance value. The second method uses curve fitting interpolation. Throughout the unloading process, the system continuously records pressure and resistance data pairs at a high frequency, forming a complete unloading curve dataset. After the unloading process is completed, the system uses the least squares method or other fitting algorithms to perform function fitting on the pressure-resistance data of the unloading stage, obtaining an analytical expression or a high-precision discrete correspondence between resistance and pressure. The system substitutes the preset target detection pressure into this fitting function or performs interpolation calculations in the data table to accurately calculate the resistance value corresponding to that pressure point as the second resistance value. This method avoids hardware delay errors in real-time capture of transient points.

[0074] S106. Calculate the difference between the second resistance value and the first resistance value;

[0075] The calculation of the difference refers to the subtraction operation performed by the system's internal processor between the second resistance value obtained in step S205 and the first resistance value obtained in step S202. Specifically, it usually involves subtracting the first resistance value from the second resistance value, or calculating the absolute value of the difference between the two, depending on the specific judgment logic definition. This difference quantifies the irreversible change in the resistivity of the electrode during the process of being pressurized to its peak value and then unloaded back to its original pressure point. This difference directly reflects the bonding state between the coating and the current collector interface, as well as the integrity of the conductive network inside the coating.

[0076] S107. If the difference is greater than the preset hysteresis threshold, it is determined that there is an interfacial bonding failure between the coating of the electrode under test and the current collector.

[0077] The preset hysteresis threshold is a pre-defined numerical limit used to distinguish between normal resistance rebound fluctuations and abrupt resistance changes caused by abnormal interface failures. This threshold is typically derived from statistical analysis of test data from a large number of high-quality electrode sheets and represents the maximum irreversible resistance increment allowed for a qualified product during loading and unloading cycles. Interface bonding failure refers to the disruption of the physical connection between the coating and the current collector, manifested as delamination, peeling, or a significant reduction in contact area, leading to impaired electron transport. Macroscopically, this results in a significantly higher resistance after unloading compared to the resistance during loading. The judgment process is the core of the system's logical comparison and determines the final test conclusion.

[0078] The system can implement this step in two ways. The first method is a binary judgment based on a single fixed threshold. The system directly compares the resistance difference (or relative rate of change) calculated by S206 with a fixed preset hysteresis threshold stored in the configuration parameters. If the difference is significantly greater than the threshold, the system immediately marks the test result of the current electrode under test as unqualified and outputs a diagnostic code of "interface bonding failure." Conversely, if the difference is less than or equal to the threshold, the system marks it as qualified. This method is logically simple, executes quickly, and is suitable for rapid screening in mass production. The second method is a fuzzy judgment based on dynamic graded thresholds. The system sets multiple levels of hysteresis thresholds (e.g., slight hysteresis threshold, severe hysteresis threshold). The system assigns different levels of failure ratings based on the range of the difference. If the difference exceeds the severe hysteresis threshold, it is judged as a severe interface failure; if the difference is between slight and severe, it is judged as a potential interface risk; if it is below the slight threshold, it is judged as "good interface." The system combines other parameters of the electrode (such as thickness and weight) with a fuzzy logic algorithm to give a final judgment. This approach provides a more detailed quality assessment and helps process engineers analyze the severity of failures.

[0079] In the above embodiments, by collecting two resistance values ​​of the electrode under test at the same preset target detection pressure during the loading and unloading cycle and calculating their difference, and combining this with a preset hysteresis threshold for judgment, the interface bonding failure of the electrode can be effectively identified. When there is an interface bonding failure between the coating and the current collector, the coating will undergo plastic deformation or interface delamination during pressurization, resulting in a significant change in the resistance value at unloading compared to that at loading. By controlling the preset peak pressure within a range less than the yield strength of the current collector, permanent damage to the current collector is avoided, improving the reliability of the test results. This method can complete the evaluation of the interface bonding state in a single loading and unloading cycle, reducing test time and improving production efficiency. Since the resistance difference at the same pressure point is used as the judgment criterion, the influence of pressure control accuracy fluctuations on the test results is reduced, thereby reducing the difficulty of identifying overpressure risks and defining the optimal rolling process window.

[0080] In the above embodiments, the interface bonding state can be preliminarily determined by analyzing the resistance difference at the same pressure point. However, relying solely on single-point data may not fully reflect the dynamic changes in the electrode interface throughout the loading and unloading process. To further improve the reliability of interface bonding state determination, the following embodiments provide a more in-depth analysis of the test data. The following is a combination of... Figure 2 Another interface-based failure testing method is described in the embodiments of this application:

[0081] Please see Figure 2 This is another flowchart illustrating an interface-based failure testing method in an embodiment of this application.

[0082] S201. Extract the first resistance-pressure data sequence from the preset target detection pressure to the preset peak pressure during the loading phase, and the second resistance-pressure data sequence from the preset peak pressure to the preset target detection pressure during the unloading phase;

[0083] The first resistance-pressure data sequence refers to the set of ordered data points recorded by the system during a single loading / unloading cycle. These data points cover the range from the preset target detection pressure to the preset peak pressure. Each data point in this sequence contains a pressure value and a corresponding resistance value at a given moment. The second resistance-pressure data sequence refers to the set of ordered data points recorded by the system during the unloading process, as the pressure decreases from the preset peak pressure back to the preset target detection pressure. These two sequences represent the dynamic resistance response characteristics of the electrode under test during the pressure densification process and the pressure release and rebound process, respectively. The extraction operation refers to the process by which the system filters, extracts, and reconstructs these two specific segments from the original full-process test data stream based on pressure threshold conditions. This step is the basis for subsequent nonlinear fitting analysis and requires the data to have a high degree of time synchronization and numerical accuracy. The system needs to ensure that the extracted data points are dense enough to accurately reflect the shape of the curve, while also removing outliers caused by equipment vibration or electromagnetic interference.

[0084] The system can implement this step in two ways. The first method is based on real-time caching and event-triggered extraction technology. The system allocates two independent circular buffers in memory to store data for the loading and unloading segments, respectively. During testing, the system monitors the pressure sensor values ​​in real time. When the pressure first reaches the preset target detection pressure, the system triggers a "load recording start" event, beginning to write the real-time collected pressure and resistance data to the first buffer. When the pressure reaches the preset peak pressure, the system triggers "load recording stop" and "unloading recording start" events, stopping writing to the first buffer and locking the data, while simultaneously starting to write data to the second buffer. When the pressure drops back to the preset target detection pressure, the "unloading recording stop" event is triggered. Finally, the system exports the data from the two buffers into independent data sequence files.

[0085] The second approach is based on timestamp-based post-processing extraction technology for the entire dataset. Throughout the testing period, the system records all sensor data (pressure, displacement, resistance, time) indiscriminately into the raw database at a fixed high frequency (e.g., 10kHz). After the test, the system executes a query algorithm, first retrieving key timestamp nodes in the raw data where the pressure value equals the preset target detection pressure and the preset peak pressure. Then, based on these timestamp nodes, the system slices and extracts data within the same time period from the raw database as the first sequence, and extracts data within the same time period as the second sequence. After extraction, the system performs linear interpolation on the data to ensure a uniform distribution of data points along the pressure axis.

[0086] S202. The first resistance-pressure data sequence and the second resistance-pressure data sequence are fitted and calculated using the power function relationship to obtain the loading power law index characterizing the contact characteristics of the loading process and the unloading power law index characterizing the contact characteristics of the unloading process.

[0087] By fitting and calculating the first and second resistance-pressure data sequences using power function relationships, the loading power law exponent, which characterizes the contact characteristics during the loading process, and the unloading power law exponent, which characterizes the contact characteristics during the unloading process, are obtained. The power function relationship is as follows:

[0088] ;

[0089] in, This is the resistance value. This is the pressure value. These are the fitting coefficients, which are mainly related to the material's basic resistivity, surface roughness, and the initial geometry of the contact points; The power-law exponent reflects the rate at which the contact area expands with increasing pressure, i.e., the sensitivity of the resistance to pressure.

[0090] This model is based on contact mechanics theory (such as Holm contact theory) and is used to describe how the contact resistance between rough surfaces changes with pressure.

[0091] S203. Calculate the exponential deviation of the unloading power law exponent relative to the loading power law exponent.

[0092] The exponential deviation is a quantitative indicator used to measure the degree of change in the resistivity-pressure response characteristics during the unloading process relative to the loading process. Since the loading process involves a mixture of plastic and elastic deformation of the coating, while the unloading process is primarily dominated by elastic recovery, the power-law exponents of the two processes are usually unequal. The purpose of calculating the exponential deviation is to identify anomalies in the interfacial bonding state by comparing these two exponents and separating the resistance change caused solely by geometric deformation (change in contact area). This deviation can be the difference between the two exponents, their ratio, or a relative rate of change. The system performs this calculation step through its internal arithmetic logic unit, transforming the two independent physical parameters obtained in S302 into a single criterion.

[0093] The system can implement this step in two ways. The first way is to calculate the relative rate of change percentage. The system reads the loaded power-law exponent (denoted as...) stored in memory. ) and unloading power-law exponent (denoted as System execution formula ,in The first method is to calculate the index deviation. This calculation method normalizes the deviation, eliminating the influence of fluctuations in the absolute value of the index caused by differences in the base materials of different batches of electrodes, thus making the judgment standard more widely applicable. The second method is to calculate the weighted absolute difference. The system takes into account that the absolute value of the index is also important in some high-voltage application scenarios, so it uses a formula... This considers not only the power-law exponent. The difference was also considered, and the fitting coefficient was introduced. The difference, and through weighting coefficients and Adjustments are made. The system defines the calculated overall difference value as the exponential deviation. This method captures the overall drift in the basic conductivity of the contact interface, in addition to the rate of change of contact area, providing a more comprehensive description of the difference.

[0094] S204. If the index deviation is less than or equal to the preset deformation judgment threshold, the electrode to be tested is determined to be in the state of plastic densification of the coating, and the judgment result of interface bonding failure is corrected to interface bonding qualified.

[0095] The preset deformation judgment threshold is a pre-defined numerical limit used to define the boundary between normal plastic deformation and abnormal interface delamination. This threshold is usually determined based on a large amount of experimental data and represents the maximum allowable range of power-law exponential changes caused solely by coating compaction (densification) under good interface bonding conditions. Coating plastic densification refers to a state where, after the electrode is subjected to pressure, the voids between coating particles are compressed, and the particles undergo irreversible displacement and rearrangement, resulting in a decrease in coating thickness and an increase in density, but the coating and current collector remain tightly connected. Correcting the interface bonding failure judgment result means that if a previous step (such as S107 based on single-point resistance difference) initially judged it as "failure" due to a large change in absolute resistance value, but this step's analysis finds that this change conforms to the physical laws of densification (i.e., small exponential deviation), the system will overwrite the previous conclusion and re-mark the test result as "qualified." This step is crucial for intelligent error correction, avoiding misjudging increased compaction density as interface damage.

[0096] The system can implement this step in two ways. The first method uses a conditional logic overriding mechanism. The system sets a priority logic in the judgment module. First, the system checks if the exponential deviation is less than or equal to a preset deformation judgment threshold. If so, the system generates a "densification confirmation" flag. Then, the system reads the status in the final output register. If the current status is "interface bonding failure" (generated by S107), the system uses the "densification confirmation" flag to force a rewrite of the register, updating it to "interface bonding qualified (densification)," and noting in the test report that "resistance hysteresis originates from plastic deformation." The second method uses a weighted scoring correction mechanism. The system does not directly perform binary overriding but calculates a comprehensive health score. The system assigns a deduction weight to the single-point resistance difference and a compensation weight to the exponential deviation. If the exponential deviation is very small, the system will give a very high compensation score to offset the deduction caused by the resistance difference. When the final comprehensive score is higher than the passing line, the system judges it as qualified. This method allows the system to handle situations on the edge, providing a smoother judgment transition.

[0097] S205. If the index deviation is greater than the preset deformation judgment threshold, confirm that the electrode under test is in the state of physical layering at the interface.

[0098] When the calculated exponential deviation exceeds the preset deformation threshold, it means that the resistance-pressure response characteristics during loading and unloading have undergone a fundamental change, no longer merely a matter of geometric compression. Interface physical delamination refers to the inability of the adhesion between the coating and the current collector to resist rebound or shear stress, leading to separation at the microscopic or macroscopic level. This separation cuts off or significantly reduces the electron transport path, manifested as a drastically different resistance sensitivity to pressure (power-law exponent) during unloading compared to loading (typically, the unloading exponent increases significantly because the contact breaks down rapidly with a slight decrease in pressure). The confirmation operation refers to the system finally locking in the test conclusion, ruling out the possibility of plastic deformation, and qualitatively classifying the electrode as a product with structural defects.

[0099] The system can implement this step in two ways. The first method is multi-level alarm and classification recording. When the system detects an exponential deviation greater than a threshold, it first locks the test result as "NG - Interface Delamination". Then, the system performs a secondary classification based on the magnitude of the deviation exceeding the threshold: if the deviation is within 20%, it is marked as "Slight Delamination Risk," and the system controls the sorting machine to send the electrode to the re-inspection channel; if the deviation is greater than 20%, it is marked as "Severe Physical Delamination," and the system controls the sorting machine to directly send it to the scrap channel, simultaneously triggering an audible and visual alarm to prompt the operator to check the coating or rolling process parameters. The second method is triggering a related microscopic verification process (if the hardware supports it). When the system determines that there is interface physical delamination, it automatically sends a command to the integrated microscopic vision inspection module, requesting high-magnification photography of the electrode area. The system packages and stores the abnormal power-law exponential curve obtained from the test along with the captured microscopic crack or delamination images, generating a complete failure analysis report containing electrical data and visual evidence. This not only confirms the results but also provides intuitive evidence for subsequent failure mechanism research.

[0100] In the above embodiments, by extracting the resistance-pressure data sequences during the loading and unloading stages and performing power function fitting, the power-law exponents for loading and unloading are obtained. The exponent deviation is calculated and compared with a preset deformation judgment threshold, which can accurately distinguish between the plastic densification state and the physical delamination state of the electrode coating. In the plastic densification state, due to irreversible compaction of the coating particles, the resistance value in the unloading stage is relatively higher than that in the loading stage, but the pressure-resistance relationship still maintains similar power-law characteristics, thus the exponent deviation is small. In the physical delamination state, due to the separation of the coating and the current collector interface, the pressure-resistance relationship in the unloading stage changes significantly, resulting in a larger exponent deviation. This reduces the misjudgment rate of the test results and improves the accuracy of the interface bonding state determination.

[0101] Furthermore, before step S203 of the above embodiment, the system may also obtain the first goodness of fit of the loading process and the second goodness of fit of the unloading process;

[0102] Determine whether both the first and second goodness-of-fit scores are greater than the preset linear correlation threshold;

[0103] If either the first goodness of fit or the second goodness of fit is less than or equal to the preset linear correlation threshold, an abnormal data alarm signal will be output.

[0104] If the first goodness of fit and the second goodness of fit are both greater than the preset linear correlation threshold, then the step of calculating the exponential deviation of the unloading power law exponent relative to the loading power law exponent is performed.

[0105] Specifically, obtaining the first goodness of fit for the loading process and the second goodness of fit for the unloading process includes: performing double logarithmic coordinate transformation on the first resistance-pressure data sequence and the second resistance-pressure data sequence to obtain the first data sequence and the second data sequence; calculating the first coefficient of determination of the first data sequence and the second coefficient of determination of the second data sequence based on the least squares method; determining the first coefficient of determination as the first goodness of fit, and determining the second coefficient of determination as the second goodness of fit.

[0106] The first goodness of fit refers to the statistical measure of the degree of matching between the first resistance-pressure data sequence and the preset power function model during the loading phase. Its value typically ranges between zero and one; the closer the value is to one, the more closely the data points surround the fitted curve, reflecting that the physical contact process better matches theoretical expectations. The second goodness of fit refers to the statistical measure of the degree of matching between the second resistance-pressure data sequence and the power function model during the unloading phase. Its physical meaning is the same as the first goodness of fit, but it applies to the stress release process. The preset linear correlation threshold is a scalar limit set internally by the system to determine whether the fitting quality is acceptable. This threshold can be a single fixed value, such as 0.95 or 0.98, or it can be a dynamically adjusted value based on historical data. However, in this embodiment, it is usually used as the minimum standard for determining data validity. Both the first and second goodness of fit must be compared with the same preset linear correlation threshold. Alternatively, the system can set different thresholds for the loading and unloading processes respectively. If different thresholds are set, the first goodness of fit must be greater than the first threshold, and the second goodness of fit must be greater than the second threshold. In this step, the system first receives the raw resistance and pressure data from the loading and unloading processes. To assess the quality of this nonlinear data, the system performs a double logarithmic coordinate transformation, converting the curves, which were originally power-law distributed in Cartesian coordinates, into a linear distribution in double logarithmic coordinates. Subsequently, the system uses statistical algorithms to calculate the coefficient of determination, i.e., the goodness of fit, characterizing the strength of this linear relationship. The system then logically compares the calculated first and second goodness of fits with a preset linear correlation threshold. This comparison is a logical AND operation; only when the goodness of fit for both the loading and unloading processes is strictly greater than the threshold is the system considered valid, indicating that the contact behavior of the electrode sample has not been significantly affected by nonlinear interference or equipment malfunction, thus allowing the system to proceed to the subsequent exponential deviation calculation step. Conversely, if any goodness of fit value is less than or equal to the threshold, the system determines the data to be unreliable. This could stem from electromagnetic noise in the testing environment, poor probe contact, or structural defects in the sample itself. In this case, the system immediately triggers an abnormal data alarm signal, terminating subsequent calculations to prevent erroneous conclusions about electrode delamination or densification based on incorrect data.

[0107] Regarding the specific implementation of obtaining the goodness of fit in the above steps, namely the process of performing double logarithmic coordinate transformation on the data and calculating the coefficient of determination based on the least squares method, the system can adopt the following two specific technical methods. The first method is based on a variance decomposition-based calculation path: The system first takes the natural logarithm of each value in the collected resistance and pressure sequences to construct the transformed logarithmic resistance and logarithmic pressure sequences. Next, the system calculates the arithmetic mean of the logarithmic resistance sequences and the sum of squares of the differences between each logarithmic resistance value and this mean, obtaining the total sum of squares of deviations, which represents the total degree of data variation. Simultaneously, the system uses the principle of least squares to determine the slope and intercept of the best-fit line by minimizing the sum of squares of errors, and uses this line equation to calculate the predicted logarithmic resistance value corresponding to each pressure point. The system further calculates the sum of squares of the differences between the actual and predicted logarithmic resistance values ​​to obtain the residual sum of squares, which represents the variation that the model cannot explain. Ultimately, the system calculates the coefficient of determination by subtracting the ratio of the sum of squared residuals to the sum of squared total deviations, and directly assigns this coefficient as the goodness of fit. The second approach is based on the Pearson correlation coefficient: the system first performs a logarithmic transformation on the original resistance and pressure data, resulting in two new linear data vectors. Then, the system calculates the covariance between these two vectors, reflecting the overall trend and direction of change for both variables. Simultaneously, the system calculates the standard deviations of the logarithmic resistance and pressure vectors, reflecting the dispersion of their respective data. The system divides the calculated covariance by the product of the two standard deviations to obtain the Pearson correlation coefficient. Since the coefficient of determination in simple linear regression is numerically equal to the square of the Pearson correlation coefficient, the system squares this coefficient, and the result is the required coefficient of determination, which is then used to determine the goodness of fit. These two methods are mathematically equivalent, but the choice can be made flexibly based on hardware resources for optimizing library function calls or computational efficiency in the system algorithm implementation.

[0108] In the above embodiments, by introducing a goodness-of-fit judgment mechanism, the data fitting quality during the loading and unloading processes is evaluated, which can identify abnormal data caused by interference, equipment failure, or sample anomalies during the testing process. When the goodness-of-fit is lower than a preset linear correlation threshold, it indicates that there is a significant deviation between the measured data and the theoretical model. Timely output of alarm signals helps to eliminate invalid test data, improves the reliability of test results, and reduces the probability of misjudgment caused by data anomalies.

[0109] The system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of an interface-based failure testing system provided in an embodiment of this application.

[0110] It should be noted that, Figure 3 The structure of the system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0111] like Figure 3 As shown, the system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0112] The following components are connected to I / O interface 305: input section 306 including a camera, infrared sensor, etc.; output section 307 including a liquid crystal display (LCD) and speakers, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0113] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0114] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0116] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of a system, cause the system to implement the methods provided in the above embodiments.

[0117] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0118] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0119] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0120] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for testing interface-based failures, characterized in that, include: The control and testing device performs a single loading and unloading cycle on the electrode under test. During the loading phase of the loading and unloading cycle, when the pressure applied to the electrode under test reaches the preset target detection pressure, the first resistance value of the electrode under test is collected. Continue to increase the pressure applied to the electrode under test until a preset peak pressure is reached. The preset peak pressure is configured to be greater than the preset target detection pressure and less than the yield strength of the current collector of the electrode under test. During the unloading phase of the loading and unloading cycle, the pressure applied to the electrode under test is controlled to decrease from the preset peak pressure. When the pressure during the unloading phase drops back to the preset target detection pressure, the second resistance value of the electrode under test is collected. Calculate the difference between the second resistance value and the first resistance value; If the difference is greater than a preset hysteresis threshold, it is determined that there is an interfacial bonding failure between the coating of the electrode under test and the current collector. Extract the first resistance-pressure data sequence from the preset target detection pressure to the preset peak pressure during the loading phase, and the second resistance-pressure data sequence from the preset peak pressure to the preset target detection pressure during the unloading phase; The first resistance-pressure data sequence and the second resistance-pressure data sequence are fitted and calculated using the power function relationship to obtain the loading power law index, which characterizes the contact characteristics of the loading process, and the unloading power law index, which characterizes the contact characteristics of the unloading process. Calculate the exponential deviation of the unloading power law exponent relative to the loading power law exponent; If the index deviation is less than or equal to the preset deformation judgment threshold, the electrode under test is determined to be in the state of plastic densification of the coating, and the judgment result of interface bonding failure is corrected to interface bonding qualified. If the index deviation is determined to be greater than the preset deformation determination threshold, the electrode under test is confirmed to be in a state of physical layering at the interface.

2. The method according to claim 1, characterized in that, The control and testing device performs a single loading and unloading cycle on the electrode under test, specifically including: Send a step-by-step pressurization command to the drive unit of the test device to drive the test device to apply pressure to the electrode under test in a stepped manner with a preset pressure step. During each pressure step duration, the instantaneous resistance change rate of the electrode under test is monitored in real time at a preset high-frequency sampling rate. The instantaneous resistance change rate is compared with a preset rheological balance threshold, which is configured as the upper limit of the resistance fluctuation rate characterizing the completion of stress relaxation state of the electrode polymer binder. If the instantaneous resistance change rate is less than the preset rheological balance threshold, it is determined that the electrode state under the current pressure step has reached rheological balance, and the step-by-step pressurization command of the next pressure step is triggered or the step of monitoring the instantaneous resistance change rate of the electrode under test in real time with a preset high-frequency sampling rate is executed until the single loading and unloading cycle is completed.

3. The method according to claim 1, characterized in that, The control and testing device performs a single loading and unloading cycle on the electrode under test, specifically including: Obtain the coating design thickness and coating porosity parameters of the electrode to be tested; Based on the designed coating thickness and the coating porosity parameters, a loading rate that matches the actual breathing conditions of the battery is calculated using a preset strain rate conversion model. The testing device is controlled to apply continuously varying pressure to the electrode under test according to the loading speed; When applying continuously varying pressure, the relationship between the second derivative of pressure and displacement is monitored in real time. When the second derivative of the pressure and displacement suddenly becomes negative, an overload protection signal is generated and the single loading and unloading cycle is immediately terminated.

4. The method according to claim 1, characterized in that, Before calculating the exponential deviation of the unloading power law exponent relative to the loading power law exponent, the method further includes: Obtain the first goodness of fit of the loading process and the second goodness of fit of the unloading process; Determine whether both the first goodness of fit and the second goodness of fit are greater than a preset linear correlation threshold; If either the first goodness of fit or the second goodness of fit is less than or equal to a preset linear correlation threshold, an abnormal data alarm signal is output. If both the first goodness of fit and the second goodness of fit are greater than the preset linear correlation threshold, the step of calculating the exponential deviation of the unloading power law exponent relative to the loading power law exponent is performed.

5. The method according to claim 4, characterized in that, The process of obtaining the first goodness of fit of the loading process and the second goodness of fit of the unloading process specifically includes: Perform double logarithmic coordinate transformation on the first resistance-pressure data sequence and the second resistance-pressure data sequence respectively to obtain the first data sequence and the second data sequence; The first coefficient of determination for the first data sequence and the second coefficient of determination for the second data sequence are calculated using the least squares method. The first coefficient of determination is determined as the first goodness of fit, and the second coefficient of determination is determined as the second goodness of fit.

6. An interface-based failure testing system, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-5.

7. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-5.

8. A computer program product, characterized in that, When the computer program product is run on the system, it causes the system to perform the method as described in any one of claims 1-5.

Images