Battery monomer equivalent simulation model establishment method and device and storage medium

Abstract

The invention discloses a single battery equivalent simulation model establishment method, device and system and a storage medium. The method comprises the following steps: carrying out modal test on the single battery to determine a first vibration mode and a first modal frequency; establishing a finite element model of the battery monomer; wherein a second vibration mode obtained by performing free modal calculation based on the finite element model is consistent with the first vibration mode; adjusting material parameters of the finite element model until a second modal frequency obtained by carrying out free modal calculation on the adjusted finite element model and the first modal frequency meet a preset condition; and storing the adjusted finite element model as the equivalent simulation model. According to the method for establishing the equivalent simulation model of the single battery disclosed by the invention, during modeling, a homogenization method is adopted to simplify a multilayer structure of an internal battery cell of the single battery, so that the calculated amount is greatly reduced. Meanwhile, through combination of experimental modal testing and finite element analysis, it is ensured that the model reflects the real stiffness characteristic of the battery cell.

Description

Technical Field

[0001] The present application relates to the technical field of battery cell simulation, and particularly to a method, device, system and storage medium for establishing an equivalent simulation model of a battery. Background Art

[0002] With the expansion of the application fields of lithium batteries, accurate prediction of mechanical properties is crucial for the design and reliability of battery cells (including internal battery cores, battery modules and battery packs built from multiple battery cells, etc.). The finite element simulation technology can efficiently analyze the performance and reliability of battery cells under complex conditions, providing a scientific basis for battery design, optimization and safety assessment.

[0003] The structure of a mainstream form of lithium-ion battery mainly consists of an internal battery core, a housing and accessory structures. The core is the internal battery core, which is mostly manufactured by a stacking process or a winding process to form a multi-layer structure, mainly including a positive electrode sheet, a negative electrode sheet, a separator, an electrolyte, etc. The complex multi-layer structure results in the fact that the full-detail modeling of the battery requires a large amount of computing resources and is difficult to meet the requirements of rapid design. Summary of the Invention

[0004] In order to solve the above problems, the present application discloses a method, device, system and storage medium for establishing an equivalent simulation model of a battery cell. When modeling, the method for establishing the equivalent simulation model of the battery cell simplifies the multi-layer structure of the internal battery core of the battery cell by using a homogenization method, greatly reducing the amount of calculation. At the same time, by combining experimental modal testing and finite element analysis, it is ensured that the model reflects the true stiffness characteristics of the battery core.

[0005] The first aspect of the present application provides a method for establishing an equivalent simulation model of a battery cell. The method may include: performing a modal test on the battery cell to determine a first vibration mode; establishing a finite element model of the battery; wherein, a second vibration mode obtained by performing a free modal calculation based on the finite element model is consistent with the first vibration mode; adjusting the material parameters of the finite element model until a second modal frequency obtained by performing a free modal calculation on the adjusted finite element model meets a preset condition; saving the adjusted finite element model as the equivalent simulation model.

[0006] According to some embodiments of the present application, the modal test is performed based on an LMS simulation test system; during the modal test, the battery cell is in a free hanging state.

[0007] According to some embodiments of the present application, establishing the finite element model of the battery cell may include: establishing a previous finite element model based on the structural components of the battery cell and preset material parameters; obtaining a simulation vibration mode by performing a free modal calculation based on the previous finite element model; determining whether the simulation vibration mode is consistent with the first vibration mode; if the simulation vibration mode is not consistent with the first vibration mode, adjusting the preset material parameters until the simulation vibration mode output by the adjusted previous finite element model is consistent with the first vibration mode, and designating the adjusted previous finite element model as the finite element model and the simulation vibration mode as the second vibration mode.

[0008] According to some embodiments of the present application, establishing the previous finite element model based on the structural components and material parameters of the battery cell includes: performing homogenization modeling based on the core structure and core material parameters of the battery cell; performing solid element modeling and / or shell element modeling based on the component structure and component material parameters of the battery cell; establishing the previous finite element model based on the homogenization modeling, the solid element modeling and / or the shell element modeling; wherein, the component structure and component materials include one or more of an outer shell structure and outer shell material parameters, a cover plate structure and cover plate material parameters, a terminal post structure and terminal post material parameters, a tab structure and tab material parameters, and an adapter plate structure and adapter plate material parameters.

[0009] According to some embodiments of the present application, the material parameters at least include the elastic modulus and Poisson's ratio of the core; adjusting the material parameters of the finite element model may include: obtaining the material parameter values corresponding to when the simulation vibration mode is consistent with the first vibration mode; wherein, the material parameters include the elastic modulus and Poisson's ratio of the battery cell; adjusting the elastic modulus under a first constraint condition; adjusting Poisson's ratio under a second constraint condition.

[0010] According to some embodiments of the present application, the first constraint condition may include the adjustment range of the elastic modulus, and the adjustment range is: Eupper = Einit*(1 + 0.5), Elower = Einit*(1 - 0.5); where Einit is the value of the elastic modulus in the material parameter values, and Eupper and Elower are respectively the upper and lower limits of the elastic modulus range during the optimization process; the second constraint condition may limit the value range of Poisson's ratio, and the value range is: 0.01 to 0.1.

[0011] According to some embodiments of the present application, the first modal frequency may include a first first-order modal frequency, a first second-order modal frequency, and a first third-order modal frequency, and the second modal frequency may include a second first-order modal frequency, a second second-order modal frequency, and a second third-order modal frequency; a target function is constructed based on the difference between the modal frequencies of corresponding orders; the preset condition may include that the minimum value of the target function is determined; or, the value of the target function is less than a preset threshold.

[0012] According to some embodiments of the present application, the target function is:

[0013] Response = abs(vm1 - sm1)+abs(vm2 - sm2)+abs(vm3 - sm3), where vm1 is the first first-order modal frequency; sm1 is the second first-order modal frequency; vm2 is the first second-order modal frequency; sm2 is the second second-order modal frequency; vm3 is the first third-order modal frequency; sm3 is the second third-order modal frequency.

[0014] A second aspect of the present application provides an apparatus for establishing an equivalent simulation model of a battery cell. The apparatus may include: a modal testing module configured to perform modal testing on the battery cell to determine a first vibration mode and a first modal frequency; a model establishment module configured to establish a finite element model of the battery cell; wherein, the second vibration mode obtained by performing free modal calculation based on the finite element model is consistent with the first vibration mode; a parameter adjustment module configured to adjust the material parameters of the finite element model until the second modal frequency obtained by performing free modal calculation on the adjusted finite element model satisfies a preset condition; a model designation module configured to save the adjusted finite element model as the equivalent simulation model.

[0015] A third aspect of the present application provides a computing system, which may include: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method for establishing an equivalent simulation model of a battery cell as described above can be implemented.

[0016] A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for establishing an equivalent simulation model of a battery cell as described above can be implemented.

[0017] A fifth aspect of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the method for establishing an equivalent simulation model of a battery cell as described above can be implemented.

[0018] The sixth aspect of the present application provides a device for establishing a battery equivalent simulation model, which may include the device or computing system for the method of establishing a single battery cell equivalent simulation model as described above.

[0019] The method for establishing a single battery cell equivalent simulation model disclosed in the present application combines experimental modal testing and finite element analysis to ensure that the model reflects the true stiffness characteristics of the battery cell. At the same time, the homogenization method is used to simplify the multi-layer structure of the internal battery cells of the single battery cell during modeling, greatly reducing the computational amount. In addition, the adjustment of material parameters improves the simulation accuracy of the model.

[0020] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present application will be further described by way of exemplary embodiments, which will be described in detail through the accompanying drawings. These embodiments are not restrictive. In these embodiments, the same reference numerals represent the same structures, where:

[0022] Figure 1 is an exemplary flowchart of the method for establishing a single battery cell equivalent simulation model according to some embodiments of the present application;

[0023] Figure 2 is an exemplary flowchart of establishing a finite element model according to some embodiments of the present application;

[0024] Figure 3 is an exemplary flowchart of adjusting a finite element model according to some embodiments of the present application;

[0025] Figure 4 is a grid model diagram of a single battery cell equivalent simulation model according to some embodiments of the present application;

[0026] Figure 5 is an exemplary schematic diagram of test sites in modal testing according to some embodiments of the present application;

[0027] Figure 6 is an exemplary schematic diagram of the vibration mode of modal testing according to some embodiments of the present application;

[0028] Figure 7 is an exemplary schematic diagram of another vibration mode of modal testing according to some embodiments of the present application;

[0029] Figure 8 is an exemplary schematic diagram of another vibration mode of modal testing according to some embodiments of the present application;

[0030] Figure 9It is an exemplary schematic diagram of the vibration mode of the simulation according to some embodiments of the present application;

[0031] Figure 10 It is an exemplary schematic diagram of another vibration mode of the simulation according to some embodiments of the present application;

[0032] Figure 11 It is an exemplary schematic diagram of another vibration mode of the simulation according to some embodiments of the present application;

[0033] Figure 12 It is an exemplary module diagram of the battery cell equivalent simulation model establishment device according to some embodiments of the present application;

[0034] Figure 13 It is an exemplary block diagram of a computing device according to some embodiments of the present application. Detailed Embodiments

[0035] To make the above objects, features, and advantages of the present application more apparent and understandable, the following provides a detailed description of the specific embodiments of the present application. Many specific details are set forth in the following description to fully understand the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present application. Therefore, the present application is not limited by the specific embodiments disclosed below.

[0036] Unless otherwise defined, all technical and scientific terms used in the present application have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The terms "including" or "comprising" and the like used in the present application mean that the elements or items appearing before the term cover the elements or items listed after the term and their equivalents, without excluding other elements or items. The term "and / or" used in the present application includes any and all combinations of one or more of the related listed items.

[0037] The terms "including", "having" and their cognates used in the present application are only intended to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing items, and should not be construed as first excluding the existence or adding the possibility of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing items.

[0038] It should be noted that the terms "first", "second", "third", etc. used in this application are only for distinguishing descriptions and cannot be understood as indicating or implying relative importance. When a component is referred to as "fixed to", "mounted on", or "disposed on" another component, it can be directly on the other component or there can be other intermediate components. When a component is considered to be "connected" to another component, it can be directly connected to the other component or there may be other intermediate components at the same time. The terms "vertical", "horizontal", "left", "right", and similar expressions used herein are only for illustrative purposes.

[0039] Some preferred embodiments of the present application will be described below. It should be noted that the following description is for illustrative purposes and is not intended to limit the protection scope of the present application. The steps involved in the present application can be precisely executed in sequence, or, alternatively, various steps can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0040] In view of the deficiencies of the prior art, the present application proposes a method combining experimental modal analysis and finite element calculation to efficiently determine the stiffness characteristics of the battery cell and achieve a good balance between accuracy and efficiency.

[0041] Figure 1 It is an exemplary flowchart of a method for establishing an equivalent simulation model of a battery cell shown in some embodiments of the present application. The battery cell can be the smallest unit (cell) used to form a battery module or a battery pack, and can include, but is not limited to, prismatic batteries (such as square lithium batteries), soft-pack batteries, irregular-shaped batteries, cylindrical batteries, etc. Figure 1 The process 100 shown in can be implemented in a computing device, such as an industrial computer, a server, a computer, a tablet, a smart mobile device, etc. In some embodiments, the process 100 can be stored in a storage device (such as the built-in storage unit or an external storage device of the above computing device) in the form of a program or an instruction, and when the program or instruction is executed, the process 100 can be implemented. As Figure 1 shown, the process 100 can include the following operations.

[0042] Step 110, performing a modal test on the battery cell to determine the first vibration mode and the first modal frequency.

[0043] In some embodiments, the modal test can be carried out using a physical battery cell based on an LMS (Lab Modal Analysis) simulation test system. Taking a prismatic lithium battery as an example of the physical battery cell, an elastic rope is used to hoist the prismatic lithium battery to achieve a free constraint state. For example, the large surface of the prismatic lithium battery (i.e., the surface with the largest area in the prismatic lithium battery) is in a horizontal hanging state. At the same time, sensors are arranged on the prismatic lithium battery to collect measured physical quantities, such as force, displacement, velocity, acceleration, etc. Then the corresponding suitable sensors can be force sensors, displacement sensors, velocity sensors, acceleration sensors, etc. Various sensors such as those with high sensitivity, small mass, environmental adaptability, small influence on resonance frequency, and large dynamic range can be used. Ways such as bonding, bolting, and magnetic attraction can be applied to fix the sensors on the surface of the measured structure (i.e., the prismatic lithium battery) to avoid sliding. Refer to Figure 5 the exemplary test sites in the shown modal test. These test sites can be located at the four corners and the length trisection points of the prismatic lithium battery. In this way, the vibration response can be better measured when using a hammer to apply an impact to the measured structure. Subsequently, an impact hammer is used to strike and excite the measured structure, and the excitation position (i.e., the striking position) can be selected at a position with a high signal-to-noise ratio. For example, at the connection edge between the side and the bottom of the battery. The vibration response signal (such as acceleration, etc.) captured by the sensor when the measured structure is excited and the input signal (such as impact force, etc.) of the excitation hammer (with a built-in force sensor) can be transmitted to the computing device for processing. For example, the LMS software installed on the computing device is used to perform curve fitting on the frequency response function based on the above data. Among them, for the parameter settings of the LMS software, exemplarily, a modal analysis broadband of 4096 Hz and a frequency resolution of 0.5 Hz can be adopted. In addition, a window function such as a force window can be applied to the excitation signal to eliminate the noise of the force signal, and an exponential window can be applied to the response signal to reduce the leakage effect, so that the data processing result is more accurate. After processing, the modal parameters of the measured structure include but are not limited to information such as modal frequency, damping ratio, and vibration mode. For example, the above modal parameters are confirmed through the amplitude spectrum of the frequency response function. At this time, the vibration mode of the battery cell obtained through the above modal test can be designated as the first vibration mode, including several orders of vibration modes, such as the first-order vibration mode, the second-order vibration mode, the third-order vibration mode, etc. Refer to Figures 6 to 8 , which shows a schematic diagram of multiple orders of vibration modes of the modal test, Figure 6 shows the first-order vibration mode, Figure 7 shows the second-order vibration mode, Figure 8 shows the third-order vibration mode. At the same time, the modal frequency of the battery cell obtained through the above modal test can also be designated as the first modal frequency, and it can also include several orders of modal frequencies, such as the first-order modal frequency, the second-order modal frequency, the third-order modal frequency, etc.

[0044] Step 120: Establish a finite element model of the battery cell.

[0045] In some embodiments, the geometric dimensions of each component of the battery cell can be obtained first for geometric modeling. Still taking the square-shell lithium battery as an example, its components may include a housing, a cover plate, a terminal post, a connecting piece, a tab, and an internal battery core, etc. The layer structures of the battery cell can be established according to the actual dimensions of each component. To reduce the computational complexity and modeling time consumption, the battery core of the battery cell (i.e., the aforementioned internal battery core) can be modeled using homogenization and the material parameters of the battery core can be involved in the establishment of the finite element model, simplifying the complex microstructure into an equivalent macroscopic model. At the same time, the remaining components (or called component structures), including one or more of the housing structure, cover plate structure, terminal post structure, connecting piece structure, tab structure, etc., can be modeled using solid elements or shell elements after appropriate geometric simplification in combination with the material parameters of the component structures (for example, one or more of the housing material parameters, cover plate material parameters, terminal post material parameters, connecting piece material parameters, tab material parameters, etc.). For example, the housing, cover plate, and terminal post use solid elements, and the connecting piece uses shell elements. Or, solid elements or shell elements can be determined according to the thickness of each structural component. The present application does not make specific limitations. Subsequently, model assembly definitions can be carried out between the structural components. For example, a Tie binding connection is defined between the surface of the housing (for example, the aforementioned large surface) and the homogenized structure of the internal battery core, and a Tie binding connection is used between the connecting piece and the tab, and a common node connection is used between the connecting piece and the terminal post and between the terminal post and the cover plate. For the definition of material parameters, the housing, cover plate, terminal post, connecting piece, etc. are defined according to elastic materials, and the homogenized material of the internal battery core is defined as an anisotropic material. The defined parameters include physical parameters such as density, elastic modulus, Poisson's ratio, thermal conductivity, specific heat capacity, etc., and electrochemical parameters such as conductivity, ion diffusion coefficient, mass transfer coefficient, etc. The setting of the above material parameters can be based on preset values (for example, empirical values). For example, the values obtained through statistical analysis and other methods based on the actual measurement data of a large number of square-shell lithium batteries can be used for the setting of material parameters. For the battery core of the battery cell, equivalent density, elastic modulus, Poisson's ratio, etc. in the equivalent initial virtual directions (including X, Y, Z) can be defined. The definition of the above virtual directions can be centered on the center of the battery core, with the X-axis as the thickness direction of the battery core, the Z-axis vertically upward, and the Y-axis conforming to the right-hand screw rule. Combining the definition of the virtual directions, the two faces of the battery core perpendicular to the X-axis can be called large surfaces (i.e., the large surfaces mentioned in the foregoing description), the two faces of the battery core perpendicular to the Z-axis are respectively called the upper and lower surfaces, and the two faces of the battery core perpendicular to the Y-axis are the side surfaces. Then, through operations such as mesh generation and boundary condition setting, the finite element model can be preliminarily established. Reference can be made to Figure 5 the exemplary mesh model diagram of the equivalent simulation model of the battery cell shown.

[0046] In some embodiments, the mode shapes obtained by performing free modal calculations on the finite element model (which may also be referred to as the second mode shapes in this application) may be the same as the first mode shapes. The second mode shapes may also include several orders of mode shapes, which are the same as the first mode shapes, and may be that the mode shapes of corresponding orders are all the same. That is to say, the mode shapes of the same order are the same. For example, the first-order mode shape included in the first mode shape is the same as the first-order mode shape included in the second mode shape, the second-order mode shape included in the first mode shape is the same as the second-order mode shape included in the second mode shape, and the third-order mode shape included in the first mode shape is also the same as the third-order mode shape included in the second mode shape. Refer to Figures 9 to 11 , which shows a schematic diagram of mode shapes of multiple orders output from a simulation based on a finite element model, Figure 9 shows the first-order mode shape, Figure 10 shows the second-order mode shape, Figure 11 shows the third-order mode shape. By comparing Figures 6 to 8 , if the mode shapes of corresponding orders are all the same, it can be considered that the second mode shape is the same as the first mode shape.

[0047] The above free modal calculation can also be referred to as model solution. The solution process may be obtained by selecting a suitable solver, setting the time step, and defining the convergence criterion. Suitable eigenvalue solvers (or eigenvalue solution algorithms) such as the Lanczos algorithm, Subspace algorithm, Arnoldi algorithm, Block Lanczos algorithm, Power algorithm, Jacobi-Davidson algorithm, etc. can all be applied to this application. After the free modal calculation, the above mode shapes can be obtained. The second mode shape may be affected by the material parameters set during the establishment of the finite element model, and by changing the material parameters, the results output by the model can be changed. For example, the second mode shape can be changed. The specific parameter correction (or model establishment) process can refer to Figure 2 the relevant content, which will not be elaborated again here.

[0048] In some embodiments, the finite element model can also be established based on an application program (i.e., software) installed on the computing device. Such as COMSOL Multiphysics, ANSYS, Abaqus, LS-DYNA, etc. can all be applied to step 120.

[0049] In step 130, adjust the material parameters of the finite element model until the second modal frequency obtained by performing free modal calculations on the adjusted finite element model meets the preset conditions.

[0050] In some embodiments, performing free modal calculations based on the finite element model can obtain several orders of modal parameters, including not only the modal shapes mentioned above, but also several orders of modal frequencies, such as the first-order modal frequency, the second-order modal frequency, the third-order modal frequency, etc. At the same time, in combination with the foregoing description, the adjustment of the material parameters related to the finite element model can cause changes in the results output by the model. Based on this, in this step, the material parameters can be adjusted (or parameter optimization) to make the output of the finite element model consistent with the results obtained from the modal test. Thus, it is ensured that the established finite element model can truly and accurately reflect the stiffness performance of the measured structure.

[0051] In the present application, the results being consistent does not mean that the data obtained from the modal test is the same as the data obtained from the free-state calculation of the finite element model, but rather that the objective function constructed based on these data satisfies a preset condition. The objective function can be obtained by performing mathematical operations between the modal frequencies of the corresponding orders and then performing statistical analysis operations. For example, the mathematical operation can be subtraction, division, etc., and the statistical analysis operation can be summation, mean calculation, mean square deviation calculation, etc. And satisfying the preset condition can be that the value of the objective function reaches the minimum value, or the value of the objective function is less than a preset threshold. In this way, the performance of the finite element model after adjusting the material parameters (which can also be called simulation accuracy) will be highly similar or consistent with the physical object, and can truly reflect the stiffness performance of the physical object.

[0052] Exemplarily, the material parameters for adjustment can include the elastic modulus and Poisson's ratio of the battery cell in the virtual directions (i.e., the aforementioned X, Y, and Z directions), a total of six parameters. The adjustment of each parameter can be carried out under specific constraint conditions. The first constraint condition is used to limit the adjustment of the elastic modulus, which can be used to restrict the adjustment range of the elastic modulus. For example, parameter search can be carried out within the range of ±10%, ±15%, ±20%, ±25%, ±30%, etc. of the elastic modulus before adjustment to change the magnitude of the elastic modulus. The second constraint condition can be used to limit the adjustment of Poisson's ratio, which can be used to restrict the value range of Poisson's ratio. For example, Poisson's ratio can take values within the range of 0 - 0.05, 0 - 0.07, 0 - 0.1, etc. It should be noted that the adjustment range or value range defined by the above constraint conditions can be changed according to the actual situation, rather than being limited to the above examples. The relevant settings ensure the rationality of the search during parameter adjustment, while maintaining the physical rationality of the model and fully reflecting the influence of material characteristics on the calculation results, all within the scope of the present application. By setting the above constraint conditions, it can be ensured that the parameter change range in the parameter optimization analysis process has sufficient freedom and can converge to the optimal solution, thereby improving the efficiency and accuracy of model parameter optimization.

[0053] Step 140, save the adjusted finite element model as the equivalent simulation model.

[0054] In some embodiments, when the objective function meets the preset conditions, it can be considered that the adjustment of the material parameters is completed. At this time, the finite element model has the same or highly similar performance to the physical object in the corresponding material parameters. Therefore, the adjusted finite element model can be saved and used as the equivalent simulation model of the battery cell to analyze the performance and reliability of the battery cell under various conditions.

[0055] It should be noted that the descriptions of the above Figure 1 for each step are only for illustration and explanation, and do not limit the scope of application of this application. For those skilled in the art, various corrections and changes can be made to the Figure 1 for each step under the guidance of this application. However, these corrections and changes are still within the scope of this application.

[0056] The method for establishing the equivalent simulation model of the battery cell disclosed in this application obtains the frequency response function through LMS experimental modal testing, and performs finite element modeling on the battery cell to obtain the simulation function. Subsequently, modal analysis can be performed according to the frequency response function to obtain the measured mode and vibration mode, and modal calculation can be performed according to the simulation function to obtain the simulated mode and vibration mode. When the measured mode and vibration mode are consistent with the simulated mode and vibration mode, through optimization solution, the homogenized material parameters of the internal battery cells are adjusted to make the simulated mode consistent with the measured mode. The material parameters corresponding to the consistent mode are returned to the finite element model, and the obtained equivalent model has high simulation accuracy and can accurately reflect the performance of the physical battery.

[0057] Figure 2 is an exemplary flowchart of establishing a finite element model according to some embodiments of this application. As Figure 2 shown, process 200 may include the following operations.

[0058] Step 210, establish a previous finite element model based on the structural components and material parameters of the battery cell.

[0059] In some embodiments, the material parameters can be obtained based on the actual parameters of multiple battery cells. It can be understood that in the actual experiment / production process, the relevant parameters of each component of the battery cell (such as the internal battery core and the aforementioned structural components, etc.) can be designed, measured, optimized, inspected, and adjusted multiple times, and can have universality. Moreover, these actual data can be collected and stored during the operation as empirical values. Therefore, when performing finite element modeling, these actual parameters can be used to assign values to the material parameters of the relevant components. Combining with the relevant description in step 120, the material parameters of the components of the square shell lithium battery, including the outer shell, cover plate, pole column, adapter plate, tab, and internal battery core, etc., can be determined by querying the empirical values and selecting from them. The model assembly between the structural components and the coordinate system definition can also refer to step 120. What is obtained after completion is the aforementioned prior finite element model.

[0060] Step 220, perform free modal calculation based on the prior finite element model to obtain the simulated vibration mode.

[0061] Similarly, algorithms such as the Lanczos algorithm, Subspace algorithm, Arnoldi algorithm, Block Lanczos algorithm, Power algorithm, Jacobi - Davidson algorithm, etc. can be used to perform free modal calculation on the prior finite element model to obtain the simulated vibration mode.

[0062] Step 230, determine whether the simulated vibration mode is consistent with the first vibration mode.

[0063] It can be understood that it is only meaningful to optimize the material parameters (that is, step 130) when the vibration modes are consistent. If the vibration modes are different (for example, one is up - and - down vibration and the other is left - and - right vibration), no amount of optimization and adjustment is meaningful. Therefore, the function of step 230 is a preliminary determination. If the simulated vibration mode is consistent with the first vibration mode, it can be considered that the material parameters of the prior finite element model are within a reasonable range at this time, and the material parameters can be adjusted to perform step 130 for the finite element model. At this time, this simulated vibration mode is also called the second vibration mode in the foregoing content. If the simulated vibration mode is not consistent with the first vibration mode, the process 200 can proceed to step 240 to adjust the prior finite element model so that the output simulated vibration mode is consistent with the first vibration mode.

[0064] Step 240, adjust the preset material parameters until the simulated vibration mode output by the adjusted prior finite element model is consistent with the first vibration mode.

[0065] In some embodiments, the adjustment of the material parameters can also be based on the empirical values mentioned in step 210. For example, if it is found that the vibration mode of a certain order is different or the vibration modes of several orders are inconsistent in the vibration mode comparison, new material parameters can be selected again from the empirical values to replace the corresponding material parameters in the previous finite element model, obtaining an adjusted previous finite element model. Subsequently, free modal calculations can be performed based on the adjusted previous finite element model to obtain new simulated vibration modes. Similarly, the new simulated vibration modes will also undergo the aforementioned vibration mode comparison. If the vibration mode of a certain order is inconsistent or the vibration modes of several orders are inconsistent again, the replacement of material parameters can continue. If the vibration modes are consistent (for example, the vibration modes of all three orders are completely consistent), the process of parameter adjustment and vibration mode comparison can be terminated. At this time, the previous finite element model with adjusted parameters can be designated as the finite element model and participate in specific steps in process 100. Also, the latest output simulated vibration mode can be designated as the second vibration mode.

[0066] It should be noted that the descriptions of the above Figure 2 for each step are only for illustration and explanation, and do not limit the scope of application of this application. For those skilled in the art, various corrections and changes can be made to Figure 2 each step under the guidance of this application. However, these corrections and changes are still within the scope of this application.

[0067] Figure 3 is an exemplary flowchart for adjusting a finite element model according to some embodiments of this application. As Figure 3 shown, process 300 can include the following operations.

[0068] Step 310, adjusting the material parameters of the finite element model under constraint conditions.

[0069] In some embodiments, the material parameters used for adjustment in step 310 can be the values of the material parameters corresponding when the simulated vibration mode is consistent with the first vibration mode. The constraint conditions can be the first constraint condition for restricting the adjustment of the elastic modulus and the second constraint condition for restricting the adjustment of the Poisson's ratio in the aforementioned step 130. Exemplarily, the first constraint condition can restrict the adjusted elastic modulus to be ±50% of the initial value. Assuming that the elastic modulus of the finite element model before adjustment is Einit, the first constraint condition can define the adjusted elastic modulus E d∈ ±(1 + 50%)Einit. That is to say, the upper and lower limits of the elastic modulus can be ±50% of Einit. Namely, the upper limit Eupper = Einit * (1 + 0.5), and the lower limit Elower = Einit * (1 - 0.5). The second constraint condition can limit the value range of the adjusted Poisson's ratio. Assuming the Poisson's ratio of the finite element model is μ, the value range of μ can be between 0.01 - 0.1. The first constraint condition and the second constraint condition can jointly limit that the adjusted material parameters do not affect the second vibration mode output by the finite element model, that is, when the material parameters are adjusted within the above limits, the second vibration mode does not change. This not only ensures the freedom of parameter adjustment but also ensures that the basis of parameter adjustment does not change.

[0070] Step 320, determine the objective function corresponding to the adjusted material parameters.

[0071] In some embodiments, the first modal frequencies obtained based on the modal test may include several orders of modal frequencies. Exemplarily, they may be the first first-order modal frequency, the first second-order modal frequency, and the first third-order modal frequency. Correspondingly, the second modal frequencies output by the finite element model based on the adjusted material parameters may also include several orders, such as the second first-order modal frequency, the second second-order modal frequency, and the second third-order modal frequency. The objective function can be constructed based on the difference between the corresponding order modal frequencies. A suitable example is that the objective function can be the sum of the absolute values of the differences between the corresponding order modal frequencies, as shown in the following formula:

[0072] Response = |v m1 - s m1 | + |v m2 - s m2 | + |v m3 - s m3 |

[0073] Wherein, Response represents the objective function, v m1 represents the first first-order modal frequency, v m2 represents the first second-order modal frequency, v m3 represents the first third-order modal frequency, s m1 represents the second first-order modal frequency, s m2 represents the second second-order modal frequency, s m3 represents the second third-order modal frequency.

[0074] Step 330, optimize the objective function until the objective function meets the preset conditions.

[0075] In some embodiments, the objective function can be used as an optimization objective, such as in combination with deterministic methods (e.g., gradient descent method, Newton's method, conjugate gradient method, BFGS algorithm, genetic algorithm, particle swarm optimization algorithm, etc.) or stochastic methods (e.g., random search, gradient-based stochastic optimization, stochastic gradient descent, Monte Carlo sampling, Bayesian optimization, etc.) like the design of experiment (DOE) method, response surface method, etc. for parameter optimization, that is, continuously adjusting the material parameters of the finite element model so that the objective function meets the preset conditions. Exemplarily, minimizing the response of the objective function, that is, when the value is the smallest, can meet the preset conditions. In another example, making the value of the objective function less than a preset threshold can meet the preset conditions. The preset threshold can be 1%, 2%, 3%, 4%, 5%, etc., which can be adjusted according to the actual situation and is not specifically limited in this application.

[0076] This application uses a variety of different optimization algorithms / methods to correct and adjust the material parameters of the finite element model. The parameter optimization is reasonable and accurate, and can make the final performance of the model consistent with the physical object.

[0077] This application also discloses a device for establishing an equivalent simulation model of a battery cell. This device for establishing an equivalent simulation model of a battery cell can be used to execute each step as shown in Figures 1 - 3 and can be specifically referred to the corresponding attached drawings for description. Figure 12 is an exemplary module diagram of a device for establishing an equivalent simulation model of a battery cell according to some embodiments of this application. As shown in Figure 12 the device 1200 for establishing an equivalent simulation model of a battery cell can include a modal testing module 1210, a model building module 1220, a parameter adjustment module 1230, and a model specifying module 1240.

[0078] The modal testing module 1210 can be configured to perform modal testing on the battery cell to obtain first modal parameters. For example, the modal testing module 1210 can call the corresponding modal testing program / software to perform physical modal testing on the battery cell to obtain the first modal parameters. The first modal parameters include but are not limited to the first vibration mode, the first modal frequency, etc.

[0079] The model building module 1220 can be configured to build a finite element model of the battery cell. The model building module 1220 can receive or call the model assembly definitions and material parameters of each component of the battery cell and use existing automatic modeling methods to build the finite element model. In addition, the model building module 1220 can fine-tune the material parameters of the built finite element model to make the output second vibration mode consistent with the first vibration mode.

[0080] The parameter adjustment module 1230 can be configured to adjust the material parameters of the finite element model until the second modal frequency obtained by performing free modal calculation on the adjusted finite element model and the first modal frequency meet a preset condition. The parameter adjustment module 1230 can optimize the material parameters by using DOE, response surface method, etc. in combination with deterministic methods or uncertain methods, and perform parameter adjustment under corresponding constraint conditions, so that the objective function constructed based on the first modal frequency and the second modal frequency meets the preset condition. The parameter adjustment module 1230 can define the objective function as the sum of the absolute values of the differences between the modal frequencies of corresponding orders, and make its response value minimum or its value less than a preset function through continuous parameter optimization to meet the preset condition.

[0081] The model specifying module 1240 can be configured to save the adjusted finite element model as the equivalent simulation model. When the objective function meets the preset condition, it can be considered that the adjustment of the material parameters is completed. At this time, the finite element model has the same or highly similar performance to the physical object under the corresponding material parameters. Therefore, the model specifying module 1240 can save the adjusted finite element model as the equivalent simulation model of the battery for analyzing the performance and reliability of the battery under various conditions.

[0082] Other descriptions of the above components can be referred to Figures 1 - 11 in this application

[0083] It should be understood that Figure 12 the system and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in processor control code, such as providing such code on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application can be implemented not only by a hardware circuit of a programmable hardware device such as a very large scale integrated circuit or a gate array, a semiconductor such as a logic chip or a transistor, or a field programmable gate array or a programmable logic device, but also by software executed by various types of processors, or by a combination of the above hardware circuit and software (for example, firmware).

[0084] Note that the above description of the modules is only for convenience of description and does not limit this application to the scope of the examples given. It can be understood that for those skilled in the art, after understanding the principle of the system, they may, without departing from this principle, make any combination of the various modules, or form a subsystem and connect it to other modules. For example, the various modules can share a storage module, or each module can have its own storage module. Such variations are all within the protection scope of this application.

[0085] This application also provides a computing device. Refer to the Figure 13 exemplary block diagram of a computing device shown in accordance with some embodiments of this application as shown. The computing device 1300 may include any components used to implement the processes (e.g., Figures 1 - 3 the content shown therein) or systems (e.g., Figure 12 the content shown therein) described in the embodiments of this application. Exemplarily, the computing device 1300 may be implemented by hardware, software programs, firmware, or a combination thereof. For convenience, Figure 13 only one computing device is drawn, but the computing functions related to the processes and / or systems / devices described in the embodiments of this application may be implemented in a distributed manner by a group of similar platforms to disperse the processing load of the system.

[0086] In some embodiments, the computing device 1300 may include a processor 1310, a memory 1320, an input / output component 1330, and a communication port 1340. In some embodiments, the processor (e.g., CPU) 1310 may execute program instructions in the form of one or more processors. In some embodiments, the memory 1320 includes different forms of program memory and data memory, such as a hard disk, a read-only memory (ROM), a random access memory (RAM), etc., for storing various data files processed and / or transmitted by a computer. In some embodiments, the input / output component 1330 may be used to support input / output between the computing device 1300 and other components. In some embodiments, the communication port 1340 may be connected to a network for data communication. An exemplary computing device may include program instructions executed by the processor 1310 stored in a read-only memory (ROM), a random access memory (RAM), and / or other types of non-transitory storage media. The methods and / or processes of the embodiments of this application may be implemented in the form of program instructions. The computing device 1300 may also receive the programs and data disclosed in this application through network communication.

[0087] For ease of understanding, Figure 13Only one processor is drawn exemplarily. However, it should be noted that the computing device 1300 in the embodiments of the present application may include multiple processors. Therefore, the operations and / or methods implemented by one processor described in the embodiments of the present application may also be implemented jointly or independently by multiple processors. For example, if in the present application, the processor of the computing device 1300 executes operation A and operation B, it should be understood that operation A and operation B may also be executed jointly or independently by two different processors of the computing device 1300 (for example, the first processor executes operation A, the second processor executes operation B, or the first and second processors jointly execute operation A and operation B).

[0088] The basic concepts of the present application have been described. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to the present application. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to the present application. Such modifications, improvements, and corrections are proposed in the present application, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of the present application.

[0089] At the same time, the present application uses specific terms to describe the embodiments of the present application. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "an embodiment" or "one embodiment" or "an alternative embodiment" mentioned twice or more at different positions in the present application does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the present application may be combined appropriately.

[0090] Similarly, it should be noted that, in order to simplify the description of the present application disclosure and thus help the understanding of one or more embodiments of the invention, in the previous description of the embodiments of the present application, sometimes multiple features are merged into one embodiment or its description. However, this disclosure method does not mean that the features required by the object of the present application are more than those mentioned in the claims. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

[0091] Finally, it should be understood that the embodiments described in the present application are only used to illustrate the principles of the embodiments of the present application. Other variations may also belong to the scope of the present application. Therefore, by way of example and not limitation, alternative configurations of the embodiments of the present application may be considered consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly introduced and described in the present application.

Claims

1. A method for establishing a battery monomer equivalent simulation model, characterized in that: The method comprises: Performing a modal test on the battery cell to determine a first vibration shape and a first modal frequency; Establishing a finite element model of the battery cell; wherein a second vibration mode obtained by performing free modal calculation based on the finite element model is consistent with the first vibration mode; Adjusting material parameters of the finite element model until a second modal frequency obtained by performing free modal calculation on the adjusted finite element model and the first modal frequency meet a preset condition; The adjusted finite element model is saved as the equivalent simulation model.

2. The method for establishing a battery monomer equivalent simulation model according to claim 1, characterized in that: The modal test is performed based on the LMS simulation test system; During the modal test, the battery cell is in a free hanging state.

3. The method for establishing a battery monomer equivalent simulation model according to claim 1, characterized in that: The establishing of the finite element model of the battery cell comprises: Based on the structural components and material parameters of the battery cell, a finite element model is established; Performing free modal calculation based on the previous finite element model to obtain a simulation vibration shape; Determining whether the simulated vibration mode is consistent with the first vibration mode; If the simulation vibration shape is inconsistent with the first vibration shape, the material parameters are adjusted until the simulation vibration shape output by the adjusted previous finite element model is consistent with the first vibration shape, and the adjusted previous finite element model is designated as the finite element model, and the simulation vibration shape is designated as the second vibration shape.

4. The method for establishing a battery monomer equivalent simulation model according to claim 3, characterized in that: The finite element model based on the structural components and material parameters of the battery cell is established, including: Based on the battery cell structure and battery cell material parameters of the battery cell, homogenization modeling is performed; Based on the component structure and component material parameters of the battery cell, perform solid unit modeling and / or shell unit modeling; Based on the homogenization modeling, the solid element modeling and / or the shell element modeling, the previous finite element model is established; The component structure and component material include: one or more of the shell structure and shell material parameters, the cover structure and cover material parameters, the pole structure and pole material parameters, the tab structure and tab material parameters, and the adapter structure and adapter material parameters.

5. The method for establishing a battery monomer equivalent simulation model according to claim 3, characterized in that: The material parameters at least include the elastic modulus and Poisson's ratio of the battery core; the material parameters of the finite element model are adjusted, including: Obtaining the material parameter value corresponding to when the simulation vibration shape is consistent with the first vibration shape; wherein the material parameter includes the elastic modulus and Poisson's ratio of the battery cell; adjusting the elastic modulus under a first constraint condition; The Poisson's ratio is adjusted under the second constraint.

6. The method for establishing a battery monomer equivalent simulation model according to claim 5, characterized in that: The first constraint condition includes an adjustment range of the elastic modulus, and the adjustment range is: Eupper=Einit*(1+0.5), Elower=Einit*(1-0.5); wherein Einit is the value of the elastic modulus in the material parameter value, and Eupper and Elower are the upper limit and lower limit of the elastic modulus range in the optimization process, respectively; The second constraint condition includes a value range of the Poisson's ratio, and the value range is: 0.01 to 0.

1.

7. The method for establishing a battery monomer equivalent simulation model according to claim 1, characterized in that: The first modal frequency includes a first first-order modal frequency, a first second-order modal frequency, and a first third-order modal frequency, and the second modal frequency includes a second first-order modal frequency, a second second-order modal frequency, and a second third-order modal frequency; constructing an objective function based on the difference between the first modal frequency and the modal frequency of the order corresponding to the second modal frequency; The preset condition includes that a minimum value of the objective function is determined; or, the value of the objective function is less than a preset threshold.

8. The method for establishing a battery monomer equivalent simulation model according to claim 7, characterized in that: The objective function is: Response = abs(vm1-sm1)+abs(vm2-sm2)+abs(vm3-sm3), Among them, abs represents absolute value, vm1 is the first first-order modal frequency; sm1 is the second first-order modal frequency; vm2 is the first second-order modal frequency; sm2 is the second second-order modal frequency; vm3 is the first third-order modal frequency; sm3 is the second third-order modal frequency.

9. A battery cell equivalent simulation model establishment device, characterized in that: The device comprises: A modal testing module configured to perform a modal test on the battery cell to determine a first vibration shape and a first modal frequency; A model building module is configured to build a finite element model of the battery cell; wherein a second vibration mode obtained by performing free modal calculation based on the finite element model is consistent with the first vibration mode; a parameter adjustment module configured to adjust material parameters of the finite element model until a second modal frequency obtained by performing free modal calculation on the adjusted finite element model and the first modal frequency meet a preset condition; The model specifying module is configured to save the adjusted finite element model as the equivalent simulation model.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the method for establishing a battery equivalent simulation model as described in any one of claims 1 to 8 are implemented.

Images