Calibration method, apparatus, and computer storage medium for contact parameters of electrode materials

Abstract

This application discloses a method, apparatus, and computer storage medium for calibrating the contact parameters of an electrode material, the method comprising: performing a discrete element simulation test on the electrode material based on the calibration range and calibration model of the contact parameters of the electrode material, when the axial force-displacement curve of the target press sheet of the electrode material satisfies the conformity conditions of the contact model; further obtaining the simulated axial pressure-axial strain relationship based on the target discrete element simulation parameters of the electrode material; determining whether the contact parameters have been successfully calibrated based on this relationship; and, if successful, determining the calibration result of the contact parameters.

Description

Technical Field

[0001] This application claims the priority of a Chinese patent application with an application number of 202410547629.1, which was filed with the Chinese Patent Office on April 30, 2024. All the contents of the above application are incorporated herein by reference.

[0002] This application relates to the technical field of calibrating parameters of electrode materials, and particularly to a calibration method, apparatus, and computer storage medium for contact parameters of electrode materials.

Background Art

[0003] In the manufacture of the positive electrode of a liquid cathode lithium battery, there is an integrated carbon-coated positive electrode. Regarding this, first, through processing steps such as material mixing, fibrillation, and sieving, powders or particles with consistent porosity and particle size are obtained. Further, the powders or particles are pressed, divided, or directly extruded to obtain a positive electrode sheet. However, with such a positive electrode manufacturing process, phenomena such as looseness of powders or particles in the formed electrode sheet and non-uniformity of compacted density in local regions are likely to appear, which affects the performance of the battery.

[0004] Currently, in order to optimize the design of key components of a liquid cathode lithium battery and find the basis for setting electrode sheet forming process parameters, it is generally necessary to apply the discrete element method (DEM), which is an important method for simulating powder / dispersion material numerical values.

Summary of the Invention

Problems to be Solved by the Invention

[0005] Currently, in the process of obtaining discrete element simulation parameters, related contact parameters, such as stiffness, shear modulus, and friction coefficient, are difficult to obtain directly through measurement. Furthermore, the correlation between existing model parameter calibration methods and the application of electrode materials is not strong, resulting in low accuracy in parameter calibration and making it unfavorable to further investigate the manufacturing process of electrode materials. [Means for solving the problem]

[0006] In the first aspect, the present application is: The axial force-displacement curve of the target press sheet of the electrode material is obtained, and based on the axial force-displacement curve, it is determined whether the electrode material satisfies the pre-set contact model compatibility conditions, and the axial force-displacement curve was obtained by performing an unconfined compression test on the target press sheet. If the determination result is that the electrode material satisfies the conformance conditions of a pre-set contact model, the calibration range of multiple contact parameters of the electrode material is determined, and based on the calibration range of all the contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, a discrete element simulation test is performed on the electrode material to obtain target discrete element simulation parameters for the electrode material, and it is determined that the uniaxial lateral-constrained compression calibration model was constructed based on the contact model and the actual application scenario of the electrode material. Based on the target discrete element simulation parameters, a uniaxial lateral-constrained compression simulation test is performed on the electrode material to obtain the simulated axial pressure-axial strain relationship of the electrode material, and based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, it is determined whether all the contact parameters have been successfully calibrated. If it is determined that the calibration has been successful, the calibration results for all the contact parameters are determined based on the target discrete element simulation parameters. This invention provides a method for calibrating the contact parameters of electrode materials.

[0007] In the second aspect, the present application is: An acquisition module used to obtain the axial force-displacement curve of a target press sheet of electrode material, A determination module is used to determine whether the electrode material satisfies the conformity conditions of a pre-set contact model based on the axial force-displacement curve, and to determine whether the axial force-displacement curve was obtained by performing a uniaxial lateral-restraint-free compression experiment on the target press sheet, If the determination result of the determination module is that the electrode material satisfies the conformance conditions of a preset contact model, a determination module is used to determine the calibration range of multiple contact parameters of the electrode material. A first simulation test module is used to perform discrete element simulation tests on the electrode material based on the calibration range of all the contact parameters and a preset uniaxial lateral-constrained compression calibration model, to obtain target discrete element simulation parameters for the electrode material, and to ensure that the uniaxial lateral-constrained compression calibration model is constructed based on the actual application scenario of the contact model and the electrode material. A second simulation test module is used to perform a uniaxial transverse-constrained compression simulation test on the electrode material based on the target discrete element simulation parameters, in order to obtain the simulated axial pressure-axial strain relationship of the electrode material. The determination module is further used to determine whether all contact parameters have been successfully calibrated, based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters. The decision module further determines, if the decision result of the decision module is that all of the contact parameters have been successfully calibrated, the calibration results of all of the contact parameters are used to determine the calibration results of all of the contact parameters based on the target discrete element simulation parameters. This invention provides a calibration device for the contact parameters of electrode materials.

[0008] In the third aspect, the present application is: Memory in which executable program code is stored, The system comprises a processor coupled to the memory, The processor invokes the executable program code stored in the memory to perform a calibration method for the contact parameters of an electrode material relating to the first aspect of the present invention. This invention provides a calibration device for the contact parameters of different electrode materials.

[0009] In the fourth aspect, the present application is: When invoked, a computer instruction used to perform a calibration method for the contact parameters of an electrode material relating to the first aspect of the present application is stored. We provide computer storage media. [Effects of the Invention]

[0010] In this invention, if the axial force-displacement curve of the target press sheet of the electrode material satisfies the compatibility conditions of the contact model, a discrete element simulation test is performed on the electrode material based on the calibration range and calibration model of the contact parameters of the electrode material. Furthermore, the simulated axial pressure-axial strain relationship is obtained based on the target discrete element simulation parameters of the electrode material. Based on this relationship, it is determined whether or not the contact parameters have been successfully calibrated. If it is determined to be successful, the calibration result of the contact parameters is determined. As can be seen from this, the implementation of this invention employs a combined experimental-simulation calibration method to calibrate the contact parameters of the electrode material. In this way, compared to direct measurement methods, it not only simplifies the experimental flow but also increases the certainty and accuracy of the calibration of the contact parameters of the electrode material, providing a good theoretical basis for the manufacturing process of the electrode material. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram of the flow chart of the calibration method for the contact parameters of electrode materials according to an embodiment of the present invention. [Figure 2] This is a schematic diagram of the flow chart of a calibration method for the contact parameters of another electrode material according to an embodiment of the present application. [Figure 3] This is a schematic diagram of the structure of a calibration device for the contact parameters of electrode materials according to an embodiment of the present application. [Figure 4] This is a schematic diagram of the structure of a calibration device for the contact parameters of another electrode material according to an embodiment of the present application. [Modes for carrying out the invention]

[0012] This application discloses a calibration method, apparatus, and computer storage medium for contact parameters of an electrode material, which not only simplifies the experimental flow compared to the direct measurement method, but also enhances the certainty and accuracy of calibration for contact parameters of the electrode material, providing a good theoretical basis for the manufacturing process of the electrode material.

[0013] Example 1 Referring to FIG. 1, FIG. 1 is a schematic diagram of the flow of a method for calibrating contact parameters of an electrode material according to an embodiment of the present application. In some embodiments, the method can be implemented by a calibration device for contact parameters. The calibration device for contact parameters can be integrated into a contact parameter calibration device such as a smart computer, a related electrode material manufacturing device, etc. When the calibration device for contact parameters exists independently, it may be a local server or a cloud server for processing the calibration flow of the contact parameters of the electrode material, and the embodiments of the present application do not limit this. As shown in FIG. 1, the method for calibrating contact parameters of the electrode material may include the following operations.

[0014] In 101, obtain the axial force-displacement curve of the target pressed sheet of the electrode material, and based on the axial force-displacement curve, determine whether the electrode material meets the fitting conditions of a preset contact model.

[0015] In an embodiment of the present application, among them, the axial force-displacement curve is obtained by performing an uniaxial lateral restraint-free compression experiment on a target pressed sheet. For example, first, an electrode material is pressed and formed (for example, pressed into a cylindrical test block with an inner diameter of x mm and a height of y mm) to obtain a target pressed sheet, and then it is pushed downward along the axial direction at a constant speed until the axial stress received by the platen reaches a preset pressure value, then it is returned to the original position at the same speed, and finally, a universal mechanical testing machine is set to apply a load again until the target pressed sheet is destroyed, and the axial force-displacement curves of the two processes are recorded. By analyzing the deformation situation of the target pressed sheet of the electrode material (for example, whether it is plastic deformation or elastic deformation) based on the axial force-displacement curve, the usability compatibility between the electrode material and a preset contact model is determined.

[0016] In 102, when the judgment result is that the electrode material meets the compatibility conditions of the preset contact model, the calibration range of a plurality of contact parameters of the electrode material is determined, and based on the calibration range of all contact parameters and a preset uniaxial lateral restraint compression calibration model, an operation of a discrete element simulation test is performed on the electrode material to obtain the target discrete element simulation parameters of the electrode material.

[0017] In an embodiment of the present application, among them, the uniaxial lateral restraint compression calibration model is obtained by constructing based on the contact model and the actual application scenario of the electrode material, for example, a Hysteretic Spring model, a Hertz-Mindlin no-slip model, etc. In some embodiments, the calibration range of all contact parameters of the electrode material can be determined by the tapping method and the sieving method.

[0018] In some embodiments, based on the calibration range of all contact parameters and a preset uniaxial lateral-constrained compression calibration model, discrete element simulation tests are performed on the electrode material. Before obtaining the target discrete element simulation parameters for the electrode material, a uniaxial lateral-constrained compression experiment is first performed on the electrode material. For example, after filling a container with the particle material of the electrode material, a load is applied at a constant speed using the pressure plate of a universal testing machine. When the displacement reaches a preset displacement parameter, the pressure plate is returned to its original position. The experiment is repeated multiple times, and axial force and displacement data are recorded for each experimental step. The measured axial pressure-axial strain relationship of the electrode material (e.g., measured axial pressure-axial strain curve y=a·x) is then obtained. b This can be obtained by analyzing the specific numerical values ​​of coefficients a and b, the measured compaction density parameters, etc., and by subsequently comparing the measured axial pressure-axial strain relationship of the electrode material with the simulated axial pressure-axial strain relationship, it is possible to determine whether or not the contact parameters of the electrode material have been successfully calibrated.

[0019] In some embodiments, the process of setting up a uniaxial lateral-constrained compression calibration model may involve simulating an actual cylinder using a cylinder of the same dimensions as in the experiment during a simulation test, simulating sponge-like porous carbon cathode particles by employing spherical particles of a corresponding diameter, setting up a particle factory based on the particle size distribution, generating particles with the same mass as in reality, and filling the cylinder with the particles to complete the setup of the uniaxial lateral-constrained compression calibration model.

[0020] In step 103, based on the target discrete element simulation parameters, a uniaxial lateral-constrained compression simulation test is performed on the electrode material to obtain the simulated axial pressure-axial strain relationship of the electrode material. Based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, it is determined whether all contact parameters have been successfully calibrated. If it is determined that the calibration has been successful, the calibration results for all contact parameters are determined based on the target discrete element simulation parameters.

[0021] In some embodiments of the present invention, the method further includes, if it determines that all contact parameters have not yet been successfully calibrated, adjusting the model parameters of the uniaxial lateral-constrained compression calibration model to update the uniaxial lateral-constrained compression calibration model, and triggering the execution of the discrete element simulation test operation on the electrode material based on the calibration range of all contact parameters and the preset uniaxial lateral-constrained compression calibration model in step 102 above to obtain target discrete element simulation parameters for the electrode material.

[0022] As can be seen from the following, the embodiment of the present invention employs a combined experimental-simulation calibration method to calibrate the contact parameters of the electrode material. In this way, compared to direct measurement methods, it not only simplifies the experimental flow but also increases the reliability and accuracy of the calibration of the contact parameters of the electrode material, providing a good theoretical basis for the manufacturing process of the electrode material.

[0023] In some embodiments, determining the calibration range of multiple contact parameters of the electrode material in step 102 is: This involves determining the particle density parameter of the electrode material and the particle size distribution parameter of the electrode material, This includes determining the calibration range of multiple contact parameters of the electrode material based on particle density parameters and particle size distribution parameters.

[0024] In some embodiments, the particle density parameter of the electrode material can be obtained by the tap method, and the particle size distribution parameter includes a particle size parameter and a particle proportion parameter corresponding to the particle size parameter, for example, a percentage parameter of 0.25% of the proportion of particles with a diameter of 1.5 mm, measured by the sieving method. In some embodiments, all contact parameters include at least one of the interparticle restitution coefficient, interparticle static friction coefficient, interparticle rolling friction coefficient, shear modulus coefficient, damping coefficient, stiffness factor parameter, and yield strength parameter, of which the shear modulus coefficient, damping coefficient, stiffness factor parameter, and yield strength parameter are used to indicate the shear modulus coefficient, damping coefficient, stiffness factor parameter, and yield strength parameter between the particle and the wall of the container, respectively.

[0025] As can be seen from the above embodiment, the particle density parameter and particle size distribution parameter of the electrode material can be measured by the tap method and the sieving method to determine the calibration range of the contact parameter of the electrode material. In this way, a reliable simulation parameter reference range can be provided for subsequent discrete element simulation tests, increasing the certainty, accuracy, and effectiveness of the execution of discrete element simulation tests, increasing the certainty and accuracy of subsequent comparisons between experimental and simulation results of the electrode material, and improving the accuracy of determining whether the contact parameter of the electrode material has been successfully calibrated.

[0026] Example 2 Referring to Figure 2, which is a schematic diagram of the flow of a method for calibrating the contact parameters of another electrode material according to an embodiment of the present application. In some embodiments, the method can be implemented by a contact parameter calibration device, which can be integrated into a contact parameter calibration device such as a smart computer or associated electrode material manufacturing equipment, or if the contact parameter calibration device exists independently, it may be a local server or cloud server for processing the electrode material contact parameter calibration flow, and the embodiments of the present application are not limited thereto. As shown in Figure 2, the method for calibrating the contact parameters of the electrode material may include the following operations.

[0027] In step 201, the axial force-displacement curve of the target press sheet of the electrode material is obtained, and based on the axial force-displacement curve, it is determined whether or not the electrode material satisfies the conformance conditions of a pre-set contact model.

[0028] In step 202, if the judgment result is that the electrode material satisfies the conformance conditions of a pre-set contact model, the calibration range of multiple contact parameters of the electrode material is determined, and based on the calibration range of all contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, a compression molding simulation test is performed on the electrode material to determine all significant contact parameters and the regression equations corresponding to all contact parameters.

[0029] In some embodiments of the present invention, in order to improve the accuracy of detecting errors in compression molding simulation tests, the compression molding simulation test can be performed on the electrode material in conjunction with a preset number of virtual parameters based on the calibration range of all contact parameters and a preset uniaxial lateral-constrained compression calibration model.

[0030] In step 203, based on the calibration range and regression equation for all significant contact parameters, the steepest ascent test is performed for all significant contact parameters to obtain the corresponding ascent test results for all significant contact parameters.

[0031] In some embodiments of the present invention, the most prominent contact parameter among all prominent contact parameters is used as the unit of ascent and the direction of the ascent gradient. Based on the calibration range and regression equation of all prominent contact parameters, the steepest ascent test operation is performed for all prominent contact parameters, and ascent test results corresponding to all prominent contact parameters can be obtained.

[0032] In step 204, based on the results of the rise test, the response surface test procedure is performed for all significant contact parameters, and response surface test results corresponding to all significant contact parameters are obtained.

[0033] In some embodiments of the present invention, the operation of the response surface test can be understood as studying the influence of a single variable, an interaction variable, or a squared term variable on the response index.

[0034] In step 205, the regression equation is solved based on the response surface test results to obtain the target discrete element simulation parameters for the electrode material.

[0035] In the embodiment of the present invention, specifically, the regression equation is solved using physical experimental values ​​as the target, and the optimal solution for each contact parameter of the electrode material is obtained as the target discrete element simulation parameter of the electrode material.

[0036] In step 206, based on the target discrete element simulation parameters, a uniaxial lateral-constrained compression simulation test is performed on the electrode material to obtain the simulated axial pressure-axial strain relationship of the electrode material. Based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, it is determined whether all contact parameters have been successfully calibrated. If it is determined that the calibration was successful, the calibration results for all contact parameters are determined based on the target discrete element simulation parameters.

[0037] In the embodiments of this application, for further descriptions of steps 201 and 206, refer to the detailed descriptions of steps 101 and 103 in Example 1, which are not repeated in the embodiments of this application.

[0038] As can be seen below, the embodiment of the present invention involves performing a compression molding simulation test on the electrode material using a uniaxial lateral-constrained compression calibration model, obtaining the significant contact parameters of the electrode material and a regression equation corresponding to the contact parameters, and then performing a steepest rise test and a response surface test on the significant contact parameters of the electrode material to solve the regression equation and obtain the optimal solution for the contact parameters of the electrode material. In this way, the reliability and accuracy of the simulation results of the model, as well as the computational stability of the model, can be ensured, and the efficiency of calibration for the contact parameters of the electrode material can be increased, thereby enabling the calibration model to be applied to the manufacturing process flow of the electrode material.

[0039] In some embodiments, by performing a compression molding simulation test on the electrode material based on the calibration range of all contact parameters and a preset uniaxial transverse-constrained compression calibration model in step 202, all significant contact parameters and the regression equations corresponding to all contact parameters are determined. Based on the calibration range of all contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, the axial strain rate of the electrode material is used as the response index to perform a compression molding simulation test on the electrode material, and the simulation parameters for the axial strain rate of the electrode material at all contact parameters are obtained as the compression molding simulation results of the electrode material. Based on the compression molding simulation results, a parameter screening test stellarity analysis is performed for all contact parameters to obtain the stellarity parameter for each contact parameter. Based on the stellarity parameters of all contact parameters, all significant contact parameters whose stellarity parameter is above a predetermined stellarity threshold are determined from all contact parameters. This includes determining regression equations corresponding to all contact parameters at axial strain rates based on the results of compression molding simulations.

[0040] In some embodiments, for example, a parameter screening test table is created, and using the axial strain rate as the response index, tests are performed in n groups of two levels for a total of seven contact parameters and three virtual parameters: interparticle restitution coefficient A_X1_e, interparticle static friction coefficient B_X2_μs, interparticle rolling friction coefficient C_X3_μr, shear modulus coefficient D_X4_G, damping coefficient E_X5_bn, stiffness factor parameter F_X6_Kn, and yield strength parameter G_X7_Yn, and compression molding simulation results are obtained. At this time, the P value and correlation coefficient R of the model are obtained. 2If the analysis results indicate good relevance and reliability of the model, then, based on the compression molding simulation results, the prominent contact parameters and corresponding regression equations among all contact parameters can be determined.

[0041] As can be seen from the above embodiment, the uniaxial lateral-constrained compression calibration model can be applied to the simulation of the compaction molding process of electrode materials to determine the prominent contact parameters of the electrode material and the regression equations corresponding to the contact parameters. Thus, it is advantageous to increase the certainty and accuracy of the determination of prominent contact parameters and regression equations, to increase the efficiency of subsequent operations for steepest increase tests of prominent contact parameters, and to quickly converge on and accurately obtain the optimal solution for contact parameters.

[0042] In some embodiments, based on the calibration range and regression equation of all significant contact parameters in step 203 above, the steepest rise test operation is performed for all significant contact parameters to obtain rise test results corresponding to all significant contact parameters. Based on the regression equation, we will analyze the effect of the axial strain rate on the most prominent contact parameter where the prominentness parameter is maximized, Based on the influence of the most prominent contact parameter and the corresponding calibration range, the upward unit and upward gradient direction corresponding to each prominent contact parameter are determined. This includes performing the steepest rise test operation for all significant contact parameters based on the rise unit, the corresponding rise gradient direction, and the corresponding calibration range corresponding to all significant contact parameters, and obtaining rise test results corresponding to all significant contact parameters.

[0043] In some embodiments, the influencing effects include either negative or positive effects. Specifically, in the process of performing the steepest rise test operation for all prominent contact parameters, other contact parameters where the prominent parameter is smaller than a preset prominent threshold may be taken from the median of the corresponding calibration range, and all prominent contact parameters are used as test variables to simulate the axial strain rate of the electrode material.

[0044] As can be seen from the above embodiment, the most prominent contact parameter is used as the determination index for the rising unit and the direction of the rising gradient, and the steepest rising test operation is performed for all prominent contact parameters, and rising test results corresponding to all prominent contact parameters can be obtained. Thus, it is advantageous to increase the certainty and accuracy of the execution of the steepest rising test operation for prominent contact parameters, to increase the certainty and effectiveness of the execution of subsequent response surface tests for prominent contact parameters, and to increase the efficiency of solving for the target discrete element simulation parameters of the electrode material.

[0045] In some embodiments, based on the rise test results in step 204, the response surface test operation is performed for all significant contact parameters, and response surface test results corresponding to all significant contact parameters are obtained. To obtain the measured axial pressure-axial strain relationship of the electrode material, This includes determining the response surface test parameter range corresponding to each significant contact parameter based on the results of the upward test, and performing the response surface test operation for all significant contact parameters using the axial strain rate and related numerical values ​​as response indices, based on the response surface test parameter range corresponding to all significant contact parameters and the pre-set variable study targets corresponding to all significant contact parameters, thereby obtaining the response surface test results corresponding to all significant contact parameters.

[0046] In some embodiments, the measured axial pressure-axial strain relationship is obtained by performing a compression experiment with uniaxial transverse constraint (i.e., a physical experiment) on the electrode material. In some embodiments, the measured axial pressure-axial strain relationship is a numerical relationship between the measured axial pressure and measured axial strain experienced by the electrode material in a compression experiment with uniaxial transverse constraint, for example, the measured axial pressure-axial strain curve y = a·x b This includes coefficients a and b in the given expression. In some embodiments, the variable study includes at least one of a single variable study, an interaction variable study, and a square term variable study, for example, a single variable study X1 of the interparticle restitution coefficient A_X1_e, an interaction variable study X1X2 of the interparticle static friction coefficient B_X2_μs, or its square term variable study X1 2 That is the case.

[0047] In some embodiments, during the process of performing response surface testing for all significant contact parameters, it is possible to create tests with significant contact parameters as independent variables and match the values ​​of other contact parameters to the steepest rise test. Furthermore, in some embodiments, once response surface test results corresponding to all significant contact parameters are obtained, analysis of variance can be performed on the model used in the response surface testing to ensure high goodness of fit and response stability of the model, and then the regression equation can be solved based on the response surface test results.

[0048] As can be seen below, the above embodiment determines the response surface test parameter range corresponding to the prominent contact parameter based on the rise test results, and further performs the response surface test operation on the prominent contact parameter using the axial strain rate and related numerical values ​​as response indices, based on the response surface test parameter range corresponding to the prominent contact parameter and the variable study target corresponding to the preset prominent contact parameter. In this way, the reliability and accuracy of the execution of the response surface test operation on the prominent contact parameter are increased, the efficiency of solving the subsequent regression equation is increased, and the efficiency and precision of calibration of the contact parameter of the electrode material are improved.

[0049] In some embodiments, in step 206 above, determining whether all contact parameters have been successfully calibrated based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters is performed as follows: Based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, the target difference parameter of the electrode material is calculated. This includes determining the simulation-measured difference parameters of the electrode material based on the target difference parameters, determining whether the simulation-measured difference parameters are below a preset difference parameter threshold, and if it is determined that the simulation-measured difference parameters are below the preset difference parameter threshold, determining that all contact parameters have been successfully calibrated.

[0050] In some embodiments, the target difference parameter includes at least one of the following: the difference parameter between the simulated axial pressure and the measured axial pressure of the electrode material; the difference parameter between the simulated axial strain and the measured axial strain of the electrode material; and the difference parameter between the simulated compaction density parameter and the measured compaction density parameter of the electrode material. For example, if, based on the simulated axial pressure-axial strain curve, the measured axial pressure-axial strain curve, the simulated compaction density parameter, and the measured compaction density parameter, the average error parameter between the calculated simulated axial pressure and the measured axial pressure is smaller than a preset first error threshold, the integral difference parameter between the simulated axial strain and the measured axial strain is smaller than a preset second error threshold, and the error parameter between the simulated compaction density parameter and the measured compaction density parameter is smaller than a preset third error threshold, then it can be determined that the simulation-measured difference parameter is smaller than a preset difference parameter threshold, that is, all contact parameters can be determined to have been successfully calibrated.

[0051] As can be seen from the above embodiment, the above embodiment can flexibly calculate the target difference parameter of the electrode material based on the simulated axial pressure-axial strain relationship and the measured axial pressure-axial strain relationship of the electrode material, and further calculate the simulated-measured difference parameter of the electrode material based on the target difference parameter, thereby enabling a determination operation on whether or not the contact parameter calibration was successful. In this way, the reliability and accuracy of detecting the simulation-measured difference of the electrode material can be increased, the reliability and accuracy of determining whether or not the calibration of the contact parameter was successful can be increased, ensuring that the construction of the calibration model can provide a good theoretical basis for the subsequent manufacturing process of the electrode material, and providing appropriate parameters for the compaction molding process of the electrode material.

[0052] Example 3 Referring to Figure 3, Figure 3 is a schematic diagram of the structure of a calibration device for the contact parameters of an electrode material according to an embodiment of the present application. As shown in Figure 3, the calibration device for the contact parameters of the electrode material is Acquisition module 301 used to obtain the axial force-displacement curve of the target press sheet of electrode material, A determination module 302 is used to determine whether the electrode material satisfies the conformance conditions of a pre-set contact model based on the axial force-displacement curve, If the determination result of the determination module 302 is that the electrode material satisfies the conformance conditions of a preset contact model, the determination module 303 is used to determine the calibration range of multiple contact parameters of the electrode material, A first simulation test module 304 is used to perform discrete element simulation tests on an electrode material based on the calibration range of all contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, in order to obtain target discrete element simulation parameters for the electrode material. The system may also include a second simulation test module 305 used to perform a uniaxial transverse-constrained compression simulation test on the electrode material based on target discrete element simulation parameters, in order to obtain the simulated axial pressure-axial strain relationship of the electrode material. The judgment module 302 is further used to determine whether all contact parameters have been successfully calibrated, based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters. The decision module 303 is further used to determine the calibration results for all contact parameters based on the target discrete element simulation parameters, if the decision result of the decision module 302 is that all contact parameters have been successfully calibrated.

[0053] In the embodiments of this application, the axial force-displacement curve was obtained by performing a compression experiment without uniaxial lateral constraint on a target press sheet, while the compression calibration model with uniaxial lateral constraint was constructed based on the contact model and the actual application scenario of the electrode material.

[0054] As can be seen below, the implementation of the electrode material contact parameter calibration apparatus described in Figure 3 employs a combined experimental-simulation calibration method to calibrate the electrode material contact parameters. In this way, compared to direct measurement methods, it not only simplifies the experimental flow but also increases the reliability and accuracy of the calibration of the electrode material contact parameters, providing a good theoretical basis for the electrode material manufacturing process.

[0055] In some embodiments, the method by which the determination module 303 determines the calibration range of multiple contact parameters of the electrode material is, specifically, This involves determining the particle density parameter of the electrode material and the particle size distribution parameter of the electrode material, This includes determining the calibration range of multiple contact parameters of the electrode material based on particle density parameters and particle size distribution parameters.

[0056] In some embodiments, the particle size distribution parameter includes a particle size parameter and a particle proportion parameter corresponding to the particle size parameter, and all contact parameters include at least one of the interparticle restitution coefficient, interparticle static friction coefficient, interparticle rolling friction coefficient, shear modulus coefficient, damping coefficient, stiffness factor parameter, and yield strength parameter.

[0057] As can be seen below, the electrode material contact parameter calibration apparatus described in Figure 3 can determine the calibration range of the electrode material contact parameters by measuring the particle density parameter and particle size distribution parameter of the electrode material using the tap method and sieving method. In this way, it can provide a reliable simulation parameter reference range for subsequent discrete element simulation tests, increasing the certainty, accuracy, and effectiveness of the execution of discrete element simulation tests, improving the certainty and accuracy of subsequent comparisons between experimental and simulation results of the electrode material, and increasing the precision of determining whether the electrode material contact parameters have been successfully calibrated.

[0058] In some embodiments, the first simulation test module 304 performs discrete element simulation testing on the electrode material based on the calibration range of all contact parameters and a preset uniaxial lateral-constrained compression calibration model to obtain target discrete element simulation parameters for the electrode material. Specifically, Based on the calibration range of all contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, a compression molding simulation test is performed on the electrode material to determine all significant contact parameters and the corresponding regression equations for all contact parameters. Based on the calibration range and regression equation for all significant contact parameters, the steepest rise test operation is performed for all significant contact parameters, and rise test results corresponding to all significant contact parameters are obtained. Based on the results of the rise test, the response surface test procedure is performed for all significant contact parameters, and response surface test results corresponding to all significant contact parameters are obtained. This includes solving the regression equation based on the response surface test results and obtaining the target discrete element simulation parameters for the electrode material.

[0059] As can be seen below, the calibration apparatus for electrode material contact parameters described in Figure 3 is implemented by performing a compression molding simulation test on the electrode material using a uniaxial lateral constraint compression calibration model, obtaining the significant contact parameters of the electrode material and a regression equation corresponding to the contact parameters, and then performing a steepest rise test and a response surface test on the significant contact parameters of the electrode material to solve the regression equation and obtain the optimal solution for the contact parameters of the electrode material. In this way, the reliability and accuracy of the simulation results of the model, as well as the computational stability of the model, can be ensured, and the efficiency of calibration for electrode material contact parameters can be increased, thereby enabling the application of this calibration model to the manufacturing process flow of electrode materials.

[0060] In some embodiments, the method by which the first simulation test module 304 performs a compression molding simulation test operation on the electrode material based on the calibration range of all contact parameters and a preset uniaxial lateral-constrained compression calibration model to determine all prominent contact parameters and the regression equation corresponding to all contact parameters is as follows: Based on the calibration range of all contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, the axial strain rate of the electrode material is used as the response index to perform a compression molding simulation test on the electrode material, and the simulation parameters for the axial strain rate of the electrode material at all contact parameters are obtained as the compression molding simulation results of the electrode material. Based on the compression molding simulation results, a parameter screening test stellarity analysis is performed for all contact parameters to obtain the stellarity parameter for each contact parameter. Based on the stellarity parameters of all contact parameters, all significant contact parameters whose stellarity parameter is above a predetermined stellarity threshold are determined from all contact parameters. This includes determining regression equations corresponding to all contact parameters at axial strain rates based on the results of compression molding simulations.

[0061] As can be seen from the following, the implementation of the electrode material contact parameter calibration device described in Figure 3 applies a uniaxial lateral-constrained compression calibration model to the simulation of the electrode material compaction process, enabling the determination of the significant contact parameters of the electrode material and the corresponding regression equations. Thus, it is advantageous in increasing the certainty and accuracy of the determination of significant contact parameters and regression equations, improving the efficiency of subsequent operations for steepest increase tests of significant contact parameters, and enabling rapid convergence and accurate acquisition of the optimal solution for contact parameters.

[0062] In some embodiments, the first simulation test module 304 performs the steepest rise test operation for all significant contact parameters based on the calibration range and regression equation of all significant contact parameters, and obtains rise test results corresponding to all significant contact parameters. Specifically, Based on the regression equation, we will analyze the effect of the axial strain rate on the most prominent contact parameter where the prominentness parameter is maximized, Based on the influence of the most prominent contact parameter and the corresponding calibration range, the upward unit and upward gradient direction corresponding to each prominent contact parameter are determined. This includes performing the steepest rise test operation for all significant contact parameters based on the rise unit, the corresponding rise gradient direction, and the corresponding calibration range corresponding to all significant contact parameters, and obtaining rise test results corresponding to all significant contact parameters.

[0063] As can be seen from the following, the calibration apparatus for electrode material contact parameters described in Figure 3 allows for the steepest rise test operation to be performed for all prominent contact parameters, using the most prominent contact parameter as the determination index for the rise unit and rise gradient direction, and obtaining rise test results corresponding to all prominent contact parameters. Thus, it is advantageous to increase the reliability and accuracy of the execution of the steepest rise test operation for prominent contact parameters, to increase the reliability and effectiveness of the execution of subsequent response surface tests for prominent contact parameters, and to increase the efficiency of solving for the target discrete element simulation parameters of electrode materials.

[0064] In some embodiments, the first simulation test module 304 performs response surface testing operations for all significant contact parameters based on the rise test results, and obtains response surface test results corresponding to all significant contact parameters. Specifically, To obtain the measured axial pressure-axial strain relationship of the electrode material, This includes determining the response surface test parameter range corresponding to each significant contact parameter based on the results of the upward test, and performing the response surface test operation for all significant contact parameters using the axial strain rate and related numerical values ​​as response indices, based on the response surface test parameter range corresponding to all significant contact parameters and the pre-set variable study targets corresponding to all significant contact parameters, thereby obtaining the response surface test results corresponding to all significant contact parameters.

[0065] In some embodiments, the measured axial pressure-axial strain relationship is obtained by performing a compression experiment with uniaxial transverse constraint on the electrode material, and the measured axial pressure-axial strain relationship includes the relationship between the measured axial pressure and measured axial strain experienced by the electrode material in the uniaxial transverse constraint compression experiment, and the variable study subject includes at least one of the single variable study subject, interaction variable study subject, and square term variable study subject.

[0066] As can be seen below, the calibration apparatus for electrode material contact parameters described in Figure 3 determines the response surface test parameter range corresponding to the prominent contact parameter based on the results of the rise test. Furthermore, based on the response surface test parameter range corresponding to the prominent contact parameter and the pre-set variable study target corresponding to the prominent contact parameter, the response surface test operation can be performed on the prominent contact parameter using the axial strain rate and related numerical values ​​as response indices. In this way, the reliability and accuracy of the execution of the response surface test operation for the prominent contact parameter are increased, the efficiency of solving the subsequent regression equation is increased, and the efficiency and precision of calibration for electrode material contact parameters are improved.

[0067] In a further preferred embodiment, the method by which the judgment module 302 determines whether all contact parameters have been successfully calibrated based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters is as follows: Based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, the target difference parameter of the electrode material is calculated. This includes determining the simulation-measured difference parameters of the electrode material based on the target difference parameters, determining whether the simulation-measured difference parameters are below a preset difference parameter threshold, and if it is determined that the simulation-measured difference parameters are below the preset difference parameter threshold, determining that all contact parameters have been successfully calibrated.

[0068] In some embodiments, the target difference parameter includes at least one of the following: a difference parameter between the simulated axial pressure and the measured axial pressure of the electrode material; a difference parameter between the simulated axial strain and the measured axial strain of the electrode material; and a difference parameter between the simulated compaction density parameter and the measured compaction density parameter of the electrode material.

[0069] As can be seen below, the electrode material contact parameter calibration apparatus described in Figure 3 can flexibly calculate the target difference parameter of the electrode material based on the simulated axial pressure-axial strain relationship and the measured axial pressure-axial strain relationship of the electrode material, and further calculate the simulated-measured difference parameter of the electrode material based on the target difference parameter. This enables a determination operation to determine whether the contact parameter calibration was successful or not. In this way, the reliability and accuracy of detecting the simulation-measured difference of the electrode material can be increased, the reliability and accuracy of determining whether the contact parameter calibration was successful or not can be increased, ensuring that the construction of the calibration model can provide a good theoretical basis for the subsequent electrode material manufacturing process and provide appropriate parameters for the electrode material compaction molding process.

[0070] Example 4 Referring to Figure 4, Figure 4 is a schematic diagram of the structure of a calibration device for the contact parameters of another electrode material according to an embodiment of the present application. As shown in Figure 4, the calibration device for the contact parameters of the electrode material is Memory 401 where executable program code is stored, The memory 401 may also be coupled to a processor 402, The processor 402 invokes executable program code stored in memory 401 to perform steps in the method for calibrating the contact parameters of electrode materials as described in Embodiment 1 or Embodiment 2 of the present invention.

[0071] Example 5 Embodiments of the present application disclose a computer storage medium in which computer instructions are stored, and when invoked, the computer instructions are used to perform steps in a method for calibrating the contact parameters of an electrode material as described in Embodiment 1 or Embodiment 2 of the present application.

[0072] Example 6 Embodiments of the present application disclose a computer program product comprising a non-temporary computer-readable storage medium in which the computer program is stored, and which, when operated, causes a computer to perform steps in the method for calibrating the contact parameters of electrode materials described in Embodiment 1 or Embodiment 2.

[0073] The embodiments of the apparatus described above are merely illustrative, and the modules described as separate components may or may not be physically separate, and the components referred to as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. The objectives of the embodiments of this model can be achieved by selecting some or all of these modules as needed for practical measurement. Those skilled in the art can understand and implement this without expending any creative effort.

[0074] From the detailed description of the above embodiments, those skilled in the art will understand that each embodiment may be implemented by adding a general-purpose hardware platform necessary for the software, or of course, by hardware. Based on this understanding, the above-mentioned technical embodiments may be embodied in the form of a software product, in which essential parts or parts contributing to the prior art may be stored on a computer-readable storage medium, the storage medium including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disc memory, magnetic disk memory, magnetic tape memory, or any other computer-readable medium that can be used to carry or store data.

Claims

1. The axial force-displacement curve of the target press sheet of the electrode material is obtained, and based on the axial force-displacement curve, it is determined whether the electrode material satisfies the pre-set contact model compatibility conditions, and the axial force-displacement curve was obtained by performing a uniaxial compression experiment without lateral constraint on the target press sheet. If the determination result is that the electrode material satisfies the conformance conditions of a pre-set contact model, the calibration range of multiple contact parameters of the electrode material is determined, and based on the calibration range of all the contact parameters and a pre-set uniaxial lateral-constrained compression calibration model, a discrete element simulation test is performed on the electrode material to obtain target discrete element simulation parameters for the electrode material, and it is determined that the uniaxial lateral-constrained compression calibration model was constructed based on the contact model and the actual application scenario of the electrode material. Based on the target discrete element simulation parameters, a uniaxial lateral-constrained compression simulation test is performed on the electrode material to obtain the simulated axial pressure-axial strain relationship of the electrode material, and based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, it is determined whether all the contact parameters have been successfully calibrated. If it is determined that the calibration has been successful, the calibration results for all the contact parameters are determined based on the target discrete element simulation parameters. A method for calibrating the contact parameters of electrode materials.

2. Determining the calibration range of the multiple contact parameters of the electrode material as described above is: The particle density parameter of the electrode material is determined, and the particle particle size distribution parameter of the electrode material is determined, including the particle particle size parameter and the particle proportion parameter corresponding to the particle particle size parameter. The calibration range of a plurality of contact parameters of the electrode material is determined based on the particle density parameter and the particle size distribution parameter, and all of the contact parameters include at least one of the interparticle restitution coefficient, interparticle static friction coefficient, interparticle rolling friction coefficient, shear modulus coefficient, damping coefficient, stiffness factor parameter, and yield strength parameter. A method for calibrating the contact parameters of an electrode material according to claim 1.

3. Based on the calibration range of all the contact parameters and the preset uniaxial lateral-constrained compression calibration model described above, a discrete element simulation test is performed on the electrode material to obtain the target discrete element simulation parameters for the electrode material. Based on the calibration range of all the contact parameters and a preset uniaxial lateral-constrained compression calibration model, a compression molding simulation test is performed on the electrode material to determine all of the significant contact parameters and the regression equations corresponding to all of the contact parameters. Based on the calibration range of all the aforementioned significant contact parameters and the regression equation, the steepest rise test operation is performed for all the aforementioned significant contact parameters, and rise test results corresponding to all the aforementioned significant contact parameters are obtained. Based on the results of the aforementioned rise test, the response surface test operation is performed for all of the aforementioned significant contact parameters, and response surface test results corresponding to all of the aforementioned significant contact parameters are obtained. This includes solving the regression equation based on the response surface test results and obtaining the target discrete element simulation parameters for the electrode material. A method for calibrating the contact parameters of an electrode material according to claim 1.

4. Based on the calibration range of all the contact parameters and the preset uniaxial lateral-constrained compression calibration model described above, by performing a compression molding simulation test on the electrode material, all of the prominent contact parameters and the regression equations corresponding to all of the contact parameters can be determined. Based on the calibration range of all the contact parameters and a preset uniaxial lateral-constrained compression calibration model, a compression molding simulation test is performed on the electrode material using the axial strain rate of the electrode material as the response index, and the axial strain rate simulation parameters of the electrode material for all the contact parameters are obtained as the compression molding simulation results of the electrode material. Based on the compression molding simulation results, a parameter screening test significance analysis is performed on all the contact parameters to obtain the significance parameter for each contact parameter, and based on the significance parameters of all the contact parameters, all significant contact parameters whose significance parameter is equal to or greater than a preset significance threshold are determined from all the contact parameters. This includes determining regression equations corresponding to all the contact parameters at the axial strain rate based on the compression molding simulation results, A method for calibrating the contact parameters of an electrode material according to claim 3.

5. Based on the calibration range of all the significant contact parameters and the regression equation described above, performing the steepest rise test operation for all the significant contact parameters and obtaining rise test results corresponding to all the significant contact parameters is: Based on the regression equation, the effect of the most prominent contact parameter, where the prominentness parameter is maximized, on the axial strain rate is analyzed, Based on the influence of the most prominent contact parameter and the corresponding calibration range, the upward unit and upward gradient direction corresponding to each prominent contact parameter are determined. This includes performing the steepest rise test operation for all the significant contact parameters based on the rise unit, the corresponding rise gradient direction, and the corresponding calibration range corresponding to all the significant contact parameters, and obtaining rise test results corresponding to all the significant contact parameters. A method for calibrating the contact parameters of an electrode material according to claim 4.

6. Based on the aforementioned rise test results, performing a response surface test operation for all of the significant contact parameters and obtaining response surface test results corresponding to all of the significant contact parameters is: This was obtained by performing a compression experiment with uniaxial transverse constraint on the electrode material, and the measured axial pressure-axial strain relationship of the electrode material is obtained, including the relationship between the measured axial pressure and the measured axial strain experienced by the electrode material in the uniaxial transverse constraint compression experiment. Based on the results of the aforementioned rise test, a response surface test parameter range corresponding to each of the aforementioned significant contact parameters is determined, and based on the response surface test parameter range corresponding to all of the aforementioned significant contact parameters and the pre-set variable study targets corresponding to all of the aforementioned significant contact parameters, the response surface test operation is performed for all of the aforementioned significant contact parameters using the axial strain rate and the relational value as response indices, response surface test results corresponding to all of the aforementioned significant contact parameters are obtained, and the variable study targets include at least one of a single variable study target, an interaction variable study target, and a square term variable study target, and includes: A method for calibrating the contact parameters of an electrode material according to claim 4.

7. Based on the aforementioned simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, it is possible to determine whether all the contact parameters have been successfully calibrated. Based on the simulated axial pressure-axial strain relationship, the previously obtained measured axial pressure-axial strain relationship of the electrode material, and the measured compaction density parameters, the target difference parameter of the electrode material is calculated. The process includes determining the simulation-measured difference parameter of the electrode material based on the target difference parameter, determining whether the simulation-measured difference parameter is below a preset difference parameter threshold, and if it is determined that the simulation-measured difference parameter is below a preset difference parameter threshold, determining that all the contact parameters have been successfully calibrated. A method for calibrating the contact parameters of an electrode material according to any one of claims 1 to 6.

8. The target difference parameter includes at least one of the following: the difference parameter between the simulated axial pressure and the measured axial pressure of the electrode material; the difference parameter between the simulated axial strain and the measured axial strain of the electrode material; and the difference parameter between the simulated compaction density parameter and the measured compaction density parameter of the electrode material. A method for calibrating the contact parameters of an electrode material according to claim 7.

9. Memory in which executable program code is stored, The system comprises a processor coupled to the memory, The processor calls the executable program code stored in the memory to perform the calibration method for the contact parameters of the electrode material according to any one of claims 1 to 8. Calibration device for contact parameters of electrode materials.

10. When invoked, a computer instruction used to perform a calibration method for the contact parameters of an electrode material according to any one of claims 1 to 8 is stored. Computer storage medium.

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