Modeling method, device and equipment of battery pack structural adhesive, medium and program product

Abstract

The invention relates to the technical field of battery testing, and discloses a battery pack structural adhesive modeling method, device and equipment, a medium and a program product, and the method comprises the steps: carrying out a sweep frequency test on a battery module comprising a plurality of battery cells, and obtaining a first main frequency, displacement data and acceleration data; constructing an equivalent model comprising a plurality of springs, determining a stiffness coefficient matrix of the plurality of springs according to the displacement data and the acceleration data, and performing sweep frequency simulation on the equivalent model to obtain a second main frequency; calculating an error value between the main frequencies, and adjusting the stiffness coefficient matrix according to the error value until the error value is smaller than a preset error threshold value; and determining an equivalent model according to the adjusted stiffness coefficient matrix. According to the method, the nonlinear mechanical behavior of the structural adhesive can be simulated, so that when the finite element model is constructed, the influence of the nonlinear compression and tension mechanical behavior on the performance of the battery pack is fully considered, the accuracy of the random vibration finite element model of the battery pack is improved, and the reliability of the vibration test of the battery pack is improved.

Description

Technical Field

[0001] The present invention relates to the field of battery testing technology, and in particular to a modeling method, device, equipment, medium and program product for battery pack structural adhesive. Background Art

[0002] Lithium-ion batteries are the most widely used rechargeable batteries in current consumer electronics, electric vehicles, and energy storage systems. The stability and safety of their performance are directly related to the overall performance of the product and user safety. As the core component of the battery system, the structural design and material selection of lithium-ion battery packs are crucial to the overall performance of the battery pack. Among them, structural adhesives are the key materials for connecting and fixing battery cells, and their mechanical properties directly affect the sealing and vibration durability of the battery pack.

[0003] Currently, in the design and analysis process of battery packs, traditional modal analysis and random vibration finite element modeling methods use a solid model structure binding method to simulate the structural adhesive between battery cells. In terms of material settings, the elastic modulus, Poisson's ratio, and density parameters are given to the structural adhesive to define its properties. In terms of structural connection, the structural adhesive is bound to the battery cell and the structural adhesive to the box to simulate the interaction between the two. However, the influence of the nonlinear compression and tensile mechanical behavior of the structural adhesive itself on the performance of the battery pack is ignored, resulting in a large deviation between the simulation results and the actual situation, and a low accuracy of the battery pack vibration test. Summary of the invention

[0004] In view of this, the present invention provides a modeling method, device, equipment, medium and program product for a battery pack structural adhesive to solve the problem of inaccurate finite element modeling of random vibration of the battery pack.

[0005] In a first aspect, the present invention provides a modeling method for a battery pack structural adhesive, the method comprising:

[0006] Performing a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a box of the battery module by structural adhesive;

[0007] Construct an equivalent model containing multiple springs, determine the stiffness coefficient matrix of multiple springs according to the displacement data and acceleration data, and perform frequency sweep simulation on the equivalent model to obtain the second main frequency of the equivalent model, where the spring equivalent corresponds to the structural glue between the battery cell and the box body;

[0008] Calculating an error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold;

[0009] The equivalent model is determined based on the adjusted stiffness coefficient matrix.

[0010] The modeling method of the battery pack structural adhesive provided in the embodiment of the present invention performs a sweep frequency test on the battery module to obtain the first main frequency of the battery module and the displacement data and acceleration data of the multiple battery cells contained therein, constructs an equivalent model containing multiple springs, determines the corresponding stiffness coefficient matrix according to the displacement data and acceleration data, performs a sweep frequency simulation on the equivalent model, obtains the second main frequency, calculates the error value of the first main frequency and the second main frequency, and adjusts the stiffness coefficient matrix according to the error value until the error value falls below a preset error threshold, and then determines the equivalent model according to the adjusted stiffness coefficient matrix. The present invention can simulate the nonlinear mechanical behavior of the structural adhesive by making the structural adhesive between the battery cell and the box body equivalent to multiple springs, so that when constructing the finite element model, the influence of the nonlinear compression-stretching mechanical behavior on the performance of the battery pack is fully considered, the accuracy of the finite element model of random vibration of the battery pack is improved, and the reliability of the vibration test of the battery pack is improved.

[0011] In an optional embodiment, an equivalent model including multiple springs is constructed, and a stiffness coefficient matrix of the multiple springs is determined according to displacement data and acceleration data, including: obtaining the total mass and a first number of multiple battery cells; determining a first coupling node between the battery cells and the structural adhesive, and a second coupling node between the structural adhesive and the box in the battery module; arranging a longitudinal spring set including a second number of springs between the first coupling node and the second coupling node to obtain an equivalent model including the first number of longitudinal spring sets; determining an equivalent total stiffness coefficient of the longitudinal spring set according to the total mass, displacement data and acceleration data, and equally dividing the equivalent total stiffness coefficient into a second number of stiffness coefficients to obtain a stiffness coefficient matrix.

[0012] The present invention constructs an equivalent model including a plurality of longitudinal spring sets by taking the connection points between each battery cell and the structural adhesive, and the connection points between the corresponding structural adhesive and the casing as references. This model can simulate the nonlinear mechanical behavior of the structural adhesive between each battery cell and the casing, so that the constructed equivalent model is closer to the actual battery module structure.

[0013] In an optional embodiment, the error value between the first main frequency and the second main frequency is calculated, and the stiffness coefficient matrix is ​​adjusted according to the error value until the error value is less than a preset error threshold, including: calculating the error value between the first main frequency and the second main frequency, and comparing the error value with the first preset error threshold; if the error value is not less than the first preset error threshold, performing a first-level adjustment on the stiffness coefficient based on the stiffness coefficient matrix, and performing a sweep frequency simulation on the adjusted equivalent model until the error value is less than the first preset error threshold; calculating the error value between the first main frequency and the second main frequency, and comparing the error value with the second preset error threshold; if the error value is not less than the second preset error threshold, performing a second-level adjustment on the stiffness coefficient based on the stiffness coefficient matrix, and performing a sweep frequency simulation on the adjusted equivalent model until the error value is less than the second preset error threshold.

[0014] The present invention can gradually improve the accuracy of each spring stiffness coefficient by performing two-stage adjustment on the stiffness coefficient matrix based on the main frequency error, thereby ensuring the matching degree of the nonlinear mechanical behavior between each longitudinal spring set and the structural adhesive.

[0015] In an optional embodiment, the first-level adjustment of the stiffness coefficient is performed based on the stiffness coefficient matrix, including: taking the stiffness coefficients of the first longitudinal spring set corresponding to the first column in the stiffness coefficient matrix as the first reference parameter, and determining the first ratio coefficient of each longitudinal spring set relative to the first longitudinal spring set based on the displacement data and the acceleration data; converting the stiffness coefficients in each row into the product of the first reference parameter and the first ratio coefficient, and extracting the first ratio coefficient from the stiffness coefficient matrix to obtain a first transformation matrix; adjusting the equivalent total stiffness coefficient of the first longitudinal spring set based on the first transformation matrix, and converting the adjusted total stiffness coefficient into the first transformation matrix; The equivalent total stiffness coefficient is equally divided into a second number of stiffness coefficients; a second-level adjustment is performed on the stiffness coefficient based on the stiffness coefficient matrix, including: taking the first stiffness coefficient corresponding to the first spring in the first longitudinal spring set as the second reference parameter, and determining a second ratio coefficient of the stiffness coefficient matrix in the first longitudinal spring set relative to the first stiffness coefficient; based on the optimal state condition of the structural adhesive, each stiffness coefficient in the first longitudinal spring set is converted into the product of the second reference parameter and the second ratio coefficient, and the second reference parameter is extracted from the first transformation matrix to obtain a second transformation matrix; and the second ratio coefficient is adjusted based on the second transformation matrix.

[0016] The present invention performs matrix transformation according to the displacement and acceleration conditions of different longitudinal spring matrices, and can convert the adjustment of the entire stiffness coefficient matrix into the adjustment of the equivalent total stiffness coefficient corresponding to the first column in the stiffness coefficient matrix, simplifying the parameter adjustment process, thereby adjusting the equivalent total stiffness coefficient of each longitudinal spring set, and preliminarily improving the matching degree of the structural adhesive between different longitudinal spring sets and the battery cell and the box. In addition, the present invention performs matrix transformation again according to the optimal state conditions of the structural adhesive, and can convert the adjustment of the equivalent total stiffness coefficient corresponding to the first column in the stiffness coefficient matrix into the adjustment of the comparison value coefficient, further simplifying the parameter adjustment process, thereby adjusting the stiffness coefficient of each spring, and improving the matching degree of each longitudinal spring set with the corresponding battery cell and the real structural adhesive between the box.

[0017] In some optional embodiments, an equivalent model is determined based on the adjusted stiffness coefficient matrix, including: determining the stiffness coefficient of each spring in the first longitudinal spring set based on the first stiffness coefficient and the adjusted second ratio coefficient; determining the stiffness coefficient of each spring in the stiffness coefficient matrix based on the stiffness coefficient of each spring in the first longitudinal spring set and the first ratio coefficient; and determining the equivalent model based on the stiffness coefficient matrix.

[0018] The present invention can gradually transform the finally determined ratio coefficient into each stiffness coefficient in the stiffness coefficient matrix through matrix inverse transformation, thereby determining the nonlinear mechanical properties of each spring and obtaining an equivalent model matching the real battery module.

[0019] In a second aspect, the present invention provides a modeling device for a battery pack structural adhesive, the device comprising:

[0020] A first test module is used to perform a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a box of the battery module by structural adhesive;

[0021] The second test module is used to construct an equivalent model including multiple springs, determine the stiffness coefficient matrix of multiple springs according to the displacement data and acceleration data, and perform frequency sweep simulation on the equivalent model to obtain the second main frequency of the equivalent model, wherein the spring equivalent corresponds to the structural glue between the battery cell and the box body;

[0022] A coefficient adjustment module, used for calculating an error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold;

[0023] The model determination module is used to determine the equivalent model according to the adjusted stiffness coefficient matrix.

[0024] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the modeling method of the battery pack structural adhesive of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for modeling a battery pack structural adhesive according to the first aspect or any corresponding embodiment thereof.

[0026] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the modeling method of the battery pack structural adhesive of the above-mentioned first aspect or any corresponding embodiment thereof.

[0027] In a sixth aspect, the present invention provides a simulation method for vibration testing of a battery pack, the method comprising: constructing a battery pack model based on the modeling method of the battery pack structural adhesive according to the first aspect or any corresponding embodiment thereof, performing vibration test simulation on the battery pack model, and performing performance evaluation based on the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 is a schematic flow chart of a method for modeling a battery pack structural adhesive according to an embodiment of the present invention;

[0030] Figure 2 is a schematic diagram of an existing structural adhesive model according to a modeling method of a battery pack structural adhesive according to an embodiment of the present invention;

[0031] Figure 3 is a schematic flow chart of another method for modeling a battery pack structural adhesive according to an embodiment of the present invention;

[0032] Figure 4 is a coupling node schematic diagram of another battery pack structural adhesive modeling method according to an embodiment of the present invention;

[0033] Figure 5 is a schematic diagram of a spring connection of another battery pack structural adhesive modeling method according to an embodiment of the present invention;

[0034] Figure 6 is a schematic diagram of an equivalent model of another battery pack structural adhesive modeling method according to an embodiment of the present invention;

[0035] Figure 7 is a flow chart of another method for modeling a battery pack structural adhesive according to an embodiment of the present invention;

[0036] Figure 8 is a structural block diagram of a device for modeling a battery pack structural adhesive according to an embodiment of the present invention;

[0037] Fig. 9 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0039] The embodiment of the present invention is applicable to the scenario of constructing a finite element model to perform performance testing on a battery pack to verify its sealing and vibration durability. The embodiment of the present invention provides a modeling method for a battery pack structural adhesive, which simulates the nonlinear mechanical behavior of the structural adhesive by constructing an equivalent model containing multiple springs to improve the accuracy of the finite element model.

[0040] According to an embodiment of the present invention, an embodiment of a modeling method for a battery pack structural adhesive is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0041] In this embodiment, a modeling method of a battery pack structural adhesive is provided, which can be used in mobile terminals, such as computers, etc. Figure 1 is a flow chart of a modeling method for a battery pack structural adhesive according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0042] Step S101, performing a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a box of the battery module by structural adhesive.

[0043] Specifically, in the embodiment of the present invention, a real battery module is prepared in advance, the battery module includes m battery cells, the total mass of all battery cells is M, and the mass of each battery cell is All battery cells are fixed to the box body by structural adhesive. Among them, the battery cells can be set as equal-mass bodies with uniform mass distribution, without considering the structures such as the tabs and aluminum-plastic films on the battery cells, and displacement sensors and acceleration sensors are installed on each battery cell respectively. The battery module is mounted on a vibration table for actual frequency sweep test. The test frequency range can be set to 0-300Hz based on experience, and the displacement data of each battery cell is measured by a displacement sensor, and the acceleration data of each battery cell is measured by an acceleration sensor to obtain the response curve of displacement and acceleration with frequency. At a certain frequency, the displacement response or acceleration response at most positions will have a response peak, which means that the battery module is determined to resonate at this frequency, and this frequency is used as the main frequency of the battery module. Therefore, the embodiment of the present invention obtains the main frequency f of the battery module in the Z direction z-实际 And the displacement of each cell at that frequency: x1, x2, x3…x m , and the acceleration on each cell: a1, a2, a3…a m .

[0044] Step S102, construct an equivalent model including multiple springs, determine the stiffness coefficient matrix of the multiple springs according to the displacement data and the acceleration data, and perform a sweep frequency simulation on the equivalent model to obtain the second main frequency of the equivalent model, wherein the spring equivalent corresponds to the structural glue between the battery cell and the box body.

[0045] Specifically, in the embodiment of the present invention, if the nonlinear mechanical properties of the structural adhesive are not considered, when constructing the finite element model of the battery module, the elastic modulus, Poisson's ratio, and density parameters are directly assigned to the structural adhesive to define its properties. The constructed finite element model is as follows: Figure 2 As shown, the structural adhesive and the battery cell, as well as the structural adhesive and the casing are mutually bound. But in fact, the structural adhesive itself has nonlinear compression and tension mechanical properties. Therefore, in the embodiment of the present invention, the spring is equivalent to the structural adhesive, and an equivalent model including multiple springs is constructed. The spring has the ability to deform in compression and tension, and its stiffness coefficient describes the ability of the spring to resist elastic deformation when subjected to force. In the actual sweep frequency test, the displacement and acceleration transformation of the battery cell both act on the structural adhesive, which is equivalent to the compression and tension process of the structural adhesive. Therefore, the stiffness coefficient matrix corresponding to the multiple springs is preliminarily determined based on the displacement data and acceleration data of each battery cell, so that the equivalent model and the battery module match to a certain extent. Then, a sweep frequency simulation is performed on the equivalent model to obtain the main frequency f in the Z direction of the equivalent model. z-仿真 .

[0046] Step S103, calculating the error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold.

[0047] Specifically, in the embodiment of the present invention, in the initially constructed equivalent model, the stiffness coefficient matrix is ​​only initially determined based on the displacement data and acceleration data of the battery cell, so there is a certain deviation from the nonlinear mechanical properties of the actual structural adhesive. Therefore, the main frequency f is obtained by calculating the actual sweep frequency test. z-实际 The main frequency f is obtained by simulation frequency sweep z-仿真 The error value between the two is calculated and compared with the preset error threshold. If it is greater than the preset error threshold, the stiffness coefficient matrix is ​​adjusted to obtain a new equivalent model, and the new equivalent model is subjected to frequency sweep simulation. The main frequency f is repeatedly adjusted. z-实际 And the updated main frequency f z-仿真 The error value between them is compared with the preset error threshold until the error value is less than the preset error threshold.

[0048] Step S104, determining an equivalent model according to the adjusted stiffness coefficient matrix.

[0049] Specifically, in the embodiment of the present invention, when the main frequency f z-实际 And the updated main frequency f z-仿真 When the error value between them is less than the preset error threshold, it proves that the nonlinear mechanical characteristics of the multiple springs match the nonlinear mechanical characteristics of the structural adhesive itself. Therefore, the equivalent model is determined by the adjusted stiffness coefficient matrix. At this time, the equivalent model can be used instead of the original one when constructing the finite element model of the battery pack. Figure 2 The structural adhesive shown improves the accuracy of finite element modeling of random vibration of battery packs.

[0050] The modeling method of the battery pack structural adhesive provided in the embodiment of the present invention performs a sweep frequency test on the battery module to obtain the first main frequency of the battery module and the displacement data and acceleration data of the multiple battery cells contained therein, constructs an equivalent model containing multiple springs, determines the corresponding stiffness coefficient matrix according to the displacement data and acceleration data, performs a sweep frequency simulation on the equivalent model, obtains the second main frequency, calculates the error value of the first main frequency and the second main frequency, and adjusts the stiffness coefficient matrix according to the error value until the error value falls below a preset error threshold, and then determines the equivalent model according to the adjusted stiffness coefficient matrix. The present invention can simulate the nonlinear mechanical behavior of the structural adhesive by making the structural adhesive between the battery cell and the box body equivalent to multiple springs, so that when constructing the finite element model, the influence of the nonlinear compression-stretching mechanical behavior on the performance of the battery pack is fully considered, the accuracy of the finite element model of random vibration of the battery pack is improved, and the reliability of the vibration test of the battery pack is improved.

[0051] In this embodiment, a modeling method of a battery pack structural adhesive is provided, which can be used in the above-mentioned mobile terminals, such as computers, etc. Figure 3 is a flow chart of a modeling method for a battery pack structural adhesive according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0052] Step S301, performing a frequency sweep test on a battery module including a plurality of battery cells to obtain the first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to the box of the battery module by structural adhesive. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0053] Step S302, construct an equivalent model including multiple springs, determine the stiffness coefficient matrix of the multiple springs according to the displacement data and the acceleration data, and perform a sweep frequency simulation on the equivalent model to obtain the second main frequency of the equivalent model, wherein the spring equivalent corresponds to the structural glue between the battery cell and the box body.

[0054] Specifically, the above step S302 includes:

[0055] Step S3021, obtaining the total mass and first quantity of the plurality of battery cells.

[0056] Specifically, in the embodiment of the present invention, the equivalent model needs to be based on the real battery module, so the total mass M of all the cells in the battery module and the number m of the cells included are obtained, so the mass of each cell can be determined as

[0057] Step S3022, determining a first coupling node between the battery cell and the structural adhesive, and a second coupling node between the structural adhesive and the box in the battery module.

[0058] Specifically, in the embodiment of the present invention, each battery cell in the battery module is fixed to the external box body by structural adhesive, so the bottom of the battery cell and all nodes of the contact surface of the structural adhesive are connected by degrees of freedom coupling, which is recorded as the first coupling node of the battery cell and the structural adhesive, and then all nodes of the contact surface of the box body and the structural adhesive are connected by degrees of freedom coupling, which is recorded as the second coupling node of the structural adhesive and the box body. Among them, the first coupling node and the second coupling node correspond to each other, and each battery cell corresponds to a pair of first coupling nodes and second coupling nodes, such as Figure 4 Therefore, the number of the first coupling nodes and the second coupling nodes are the same, and their positions correspond to each other, as shown in FIG. Figure 5 shown.

[0059] Step S3023: a longitudinal spring set including a second number of springs is set between the first coupling node and the second coupling node to obtain an equivalent model including the first number of longitudinal spring sets.

[0060] Specifically, in the embodiment of the present invention, a spring with elastic deformation capability is equivalent to a structural adhesive. At the same time, based on the structure of the battery cell in the battery module, a longitudinal spring set including a second number n of springs is arranged between each pair of the first coupling node and the second coupling node, which is equivalent to one battery cell corresponding to one longitudinal spring set, and each longitudinal spring set includes multiple layers of connected springs, such as Figure 5 As shown. Therefore, the structural adhesive between the battery cell and the box is equivalent to an equivalent model consisting of n×m springs with different stiffness. Figure 6 As shown in the figure, n×m springs are arranged in the horizontal and vertical directions respectively. Each cell bottom corresponds to n springs connected in series, which are recorded as the longitudinal spring set. There are m longitudinal spring sets in the horizontal direction, and each spring establishes its own local Cartesian coordinate system. Assuming that the stiffness coefficients of the n×m springs are not completely consistent, the nonlinear behavior between the module and the structural adhesive can be reflected.

[0061] Step S3024, determining the equivalent total stiffness coefficient of the longitudinal spring set according to the total mass, displacement data and acceleration data, and equally dividing the equivalent total stiffness coefficient into a second number of stiffness coefficients to obtain a stiffness coefficient matrix.

[0062] Specifically, in the embodiment of the present invention, since compression and tensile deformation mainly occur between the battery cell and the structural adhesive during the frequency sweep process, it is assumed that the spring is not subjected to torsional torque, and the equivalent total stiffness coefficients of each longitudinal spring set are k1, k2, k3…k m , the stiffness coefficient of each spring in each longitudinal spring set is defined as the following vector:

[0063]

[0064] Therefore, the stiffness coefficient matrix of the equivalent model of the structural adhesive between the battery cell and the box is as follows:

[0065]

[0066] In some optional implementations, in the equivalent model initially constructed in the embodiment of the present invention, since the spring components in the i-th column of the stiffness matrix satisfy the series relationship, k is satisfied. i =k 1i +k 2i +…+k ni According to Newton's second law, the force on the corresponding longitudinal spring set under the i-th cell is: So according to Hooke's law By derivation, the equivalent total stiffness coefficient of the longitudinal spring set in the i-th column can be obtained: where a i is the acceleration data corresponding to the ith battery cell, x iis the displacement data corresponding to the ith battery cell, M is the total mass of all battery cells, and m is the number of battery cells. In addition, because the stiffness of each spring in the initially constructed equivalent model cannot be determined, it is assumed that the stiffness coefficient of each spring is the same, that is, the equivalent total stiffness coefficient is equally divided, that is, for the ith column of longitudinal springs, k 1i =k 2i =…=k ni .

[0067] Step S303, calculate the error value between the first main frequency and the second main frequency, and adjust the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0068] Step S304: Determine the equivalent model according to the adjusted stiffness coefficient matrix. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0069] The modeling method of the battery pack structural adhesive provided in the embodiment of the present invention performs a sweep frequency test on the battery module to obtain the first main frequency of the battery module and the displacement data and acceleration data of the multiple battery cells contained therein, constructs an equivalent model containing multiple springs, determines the corresponding stiffness coefficient matrix according to the displacement data and acceleration data, performs a sweep frequency simulation on the equivalent model, obtains the second main frequency, calculates the error value of the first main frequency and the second main frequency, and adjusts the stiffness coefficient matrix according to the error value until the error value falls below a preset error threshold, and then determines the equivalent model according to the adjusted stiffness coefficient matrix. The present invention can simulate the nonlinear mechanical behavior of the structural adhesive by making the structural adhesive between the battery cell and the box body equivalent to multiple springs, so that when constructing the finite element model, the influence of the nonlinear compression-stretching mechanical behavior on the performance of the battery pack is fully considered, the accuracy of the finite element model of random vibration of the battery pack is improved, and the reliability of the vibration test of the battery pack is improved.

[0070] In this embodiment, a modeling method of a battery pack structural adhesive is provided, which can be used in the above-mentioned mobile terminals, such as computers, etc. Figure 7 is a flow chart of a modeling method for a battery pack structural adhesive according to an embodiment of the present invention. Figure 7 As shown, the process includes the following steps:

[0071] Step S701, performing a frequency sweep test on a battery module including a plurality of battery cells to obtain the first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to the box of the battery module by structural adhesive. Figure 3 Step S301 of the illustrated embodiment will not be described in detail here.

[0072] Step S702: construct an equivalent model including multiple springs, determine the stiffness coefficient matrix of multiple springs according to the displacement data and acceleration data, and perform frequency sweep simulation on the equivalent model to obtain the second main frequency of the equivalent model, wherein the spring is equivalent to the structural glue between the battery cell and the box. For details, please refer to Figure 3 Step S302 of the illustrated embodiment will not be described in detail here.

[0073] Step S703, calculating the error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold.

[0074] Specifically, the above step S703 includes:

[0075] Step S7031, calculating an error value between the first main frequency and the second main frequency, and comparing the error value with a first preset error threshold.

[0076] Specifically, in the embodiment of the present invention, the stiffness coefficient matrix is ​​assigned to the equivalent model, and the modal simulation calculation is performed on the equivalent model to obtain the main frequency f in the Z direction of the equivalent model. z-仿真 The modal simulation results are compared with the experimental test results, and the actual sweep frequency test is calculated to obtain the main frequency f z-实际 The main frequency f is obtained by simulation frequency sweep z-仿真 The error between them is used to determine whether the modal simulation calculation result is within the range of a first preset error threshold, wherein the first preset error threshold can be set to 10%, which is only used as an example and is not limited to this.

[0077] Step S7032, if the error value is not less than the first preset error threshold, the stiffness coefficient is adjusted in the first level based on the stiffness coefficient matrix, and a sweep frequency simulation is performed on the adjusted equivalent model until the error value is less than the first preset error threshold.

[0078] Specifically, in the embodiment of the present invention, if the error value exceeds 10%, the stiffness coefficient in the stiffness coefficient matrix is ​​adjusted at the first level until the error value is less than 10%. The calculation formula and judgment are shown as follows:

[0079]

[0080] In some optional implementations, the above step S7032 includes:

[0081] Step a1, taking the stiffness coefficients of the first longitudinal spring set corresponding to the first column in the stiffness coefficient matrix as the first reference parameter, and determining the first ratio coefficient of each longitudinal spring set relative to the first longitudinal spring set based on the displacement data and the acceleration data.

[0082] Step a2: convert each stiffness coefficient in each row into the product of the first reference parameter and the first ratio coefficient, and extract the first ratio coefficient from the stiffness coefficient matrix to obtain a first transformation matrix.

[0083] Step a3: adjusting the equivalent total stiffness coefficient of the first longitudinal spring set based on the first transformation matrix, and equally dividing the adjusted equivalent total stiffness coefficient into a second number of stiffness coefficients.

[0084] Specifically, in the embodiment of the present invention, the stiffness coefficient matrix is ​​mathematically transformed, and the stiffness coefficients of the first longitudinal spring set corresponding to the first column in the stiffness coefficient matrix are used as the first reference parameters of the stiffness coefficients of this row, and the first ratio coefficient β of each row of stiffness coefficients relative to the first reference parameter is calculated. Because the equivalent total stiffness coefficient of each longitudinal matrix set is The first reference parameter corresponding to the first longitudinal spring set is therefore

[0085] In some optional implementations, each stiffness coefficient in each row is converted into the product of the first reference parameter and the first ratio coefficient, and the stiffness coefficient matrix is ​​obtained as follows:

[0086]

[0087] The first ratio coefficient is extracted from the above stiffness coefficient matrix to obtain the first transformation matrix:

[0088]

[0089] In some optional embodiments, the adjustment problem of the entire stiffness coefficient matrix is ​​simplified to only adjusting the column matrix [k 11 …k n1 ] T In this case, it is assumed that the stiffness coefficients of each spring in each longitudinal spring set are the same, so only k1 needs to be adjusted, which is equivalent to adjusting k1, k2, k3…k m The embodiment of the present invention uses a PID control adjustment algorithm to adjust k1, and uses a cyclic test to adjust the modal simulation result f z-仿真 The test results f z-实际 Compare and iterate continuously to gradually reduce the maximum error of the simulation results until the maximum error of the simulation results is less than 10%. At this time, the equivalent total stiffness coefficient of the longitudinal spring set is determined as: k1′, k2′, k3′…, k m '. At this time, it is still assumed that the stiffness coefficients of each spring in each longitudinal spring set are the same.

[0090] Step S7033: Calculate the error value between the first main frequency and the second main frequency, and compare the error value with a second preset error threshold.

[0091] Specifically, in the embodiment of the present invention, when the equivalent stiffness coefficient of each longitudinal spring set is adjusted through cyclic iteration, the modal simulation result f z-仿真 The test results f z-实际 When the error value between them is less than 10%, the updated stiffness coefficient matrix is ​​assigned to the equivalent model, and the modal simulation calculation of the equivalent model is continued to obtain the main frequency f in the Z direction of the equivalent model. z-仿真 The modal simulation results are compared with the experimental test results, and the actual sweep frequency test is calculated to obtain the main frequency f z-实际 The main frequency f is obtained by simulation frequency sweep z-仿真 The error between them is used to determine whether the modal simulation calculation result is within the range of a second preset error threshold, wherein the second preset error threshold can be set to 5%, which is only used as an example and is not limited to this.

[0092] Step S7034, if the error value is not less than the second preset error threshold, the stiffness coefficient is adjusted at the second level based on the stiffness coefficient matrix, and a sweep frequency simulation is performed on the adjusted equivalent model until the error value is less than the second preset error threshold.

[0093] Specifically, in the embodiment of the present invention, if the error value exceeds 5%, the stiffness coefficient in the stiffness coefficient matrix is ​​adjusted at the second level until the error value is less than 5%. The calculation formula and judgment are shown as follows:

[0094] In the Z direction:

[0095] In some optional implementations, the above step S7034 includes:

[0096] Step b1, taking the first stiffness coefficient corresponding to the first spring in the first longitudinal spring set as the second reference parameter, and determining a second ratio coefficient of the stiffness coefficient matrix in the first longitudinal spring set relative to the first stiffness coefficient.

[0097] Step b2, based on the optimal state condition of the structural adhesive, convert each stiffness coefficient in the first longitudinal spring set into the product of the second reference parameter and the second ratio coefficient, and extract the second reference parameter from the first transformation matrix to obtain the second transformation matrix.

[0098] Step b3: adjusting the second ratio coefficient based on the second transformation matrix.

[0099] Specifically, in the embodiment of the present invention, the stiffness coefficient matrix is ​​further mathematically changed, and the first stiffness coefficient corresponding to the first spring in the first longitudinal spring set is used as the second reference parameter k of the stiffness coefficient of this column. 11 , calculate the second ratio coefficient α of each stiffness coefficient in the first column relative to the second reference parameter, and the calculation results are as follows:

[0100]

[0101] In some optional implementations, the present invention converts each stiffness coefficient in the first column into the product of the second reference parameter and the second ratio coefficient, that is, k j1 =k 11 α j ,j=1,2,…,n, the column matrix in the first transformation matrix is ​​composed of [k 11 …k n1 ] T Convert to [k 11 α1…k 11 α n ] T , and the second reference parameter k in the column matrix 11 Extract and get:

[0102]

[0103] In some optional embodiments, the embodiments of the present invention transform the above-mentioned column matrix based on the optimal state conditions of the structural adhesive, wherein the optimal state conditions are as follows: (1) It is assumed that during long-term use, the structural adhesive and the bonded object will not experience significant creep or fatigue effects to maintain the stability of the stress state; (2) It is assumed that the bonding interface between the structural adhesive and the bonded object is continuous, without bubbles or unbonded areas, and it is assumed that the forces on both sides of the structural adhesive are symmetrically distributed; (3) The stiffness near the center of the structural adhesive is always greater than that at the boundary of the structural adhesive, so the second ratio coefficients α can be determined. j The relationship between them is:

[0104]

[0105] When n is an odd number, Pick

[0106] In some optional embodiments, it is assumed that after the second stage adjustment, the equivalent total stiffness coefficient of the longitudinal spring set of the first column changes from k1′ to k1″, and in the initial stage, it is assumed that At this time, the stiffness coefficient of the first spring in the first column of longitudinal springs is still recorded as Therefore, the relationship between each second ratio coefficient and the equivalent total stiffness coefficient is as follows:

[0107] (α1+…+α n ) 11 =k1″

[0108]

[0109] The embodiment of the present invention converts the adjustment of the column matrix into the adjustment of each second ratio coefficient, and uses the adaptive PID control adjustment method to fine-tune the stiffness coefficients of other springs in the first column of longitudinal spring sets. The fine-tuning coefficient is This is only an example and is not limited to this. After adjustment, the stiffness coefficients in the first column of longitudinal springs after adjustment are determined based on the second ratio coefficients, and then the stiffness coefficients in the entire stiffness coefficient matrix are determined, and the updated stiffness coefficient matrix is ​​brought into the finite element model for calculation, and the modal simulation results are calculated and compared with the test results. Control simulation results f z-仿真 The test results f z-实际 The error value between them is less than 5%.

[0110] Step S704: determining an equivalent model according to the adjusted stiffness coefficient matrix.

[0111] Specifically, the above step S704 includes:

[0112] Step S7041, determining the stiffness coefficient of each spring in the first longitudinal spring set according to the first stiffness coefficient and the adjusted second ratio coefficient.

[0113] Step S7042, determining the stiffness coefficient of each spring in the stiffness coefficient matrix according to the stiffness coefficient of each spring in the first longitudinal spring set and the first ratio coefficient.

[0114] Step S7043, determining an equivalent model based on the stiffness coefficient matrix.

[0115] Specifically, in the embodiment of the present invention, when the simulation result f z-仿真 The test results f z-实际 When the error value between them is less than 5%, it means that the spring matrix and the structural adhesive are well matched at this time, so the equivalent model is determined according to the parameters at this time. Among them, the second ratio coefficient is finally adjusted through matrix transformation. The first stiffness coefficient k 11 has been determined, so by calculating the first stiffness coefficient k 11 and the adjusted second ratio coefficient The product of determines the stiffness coefficient of each spring in the first longitudinal spring set, that is, determines the column vector [k 11 …kn1 ] T , so that the optimal equivalent total stiffness of the first longitudinal spring matrix can be obtained

[0116] ″″

[0117] Then calculate the optimal equivalent total stiffness coefficient k1 and the first ratio coefficient β i The product of i It has been determined that the optimal equivalent total stiffness coefficients k1″, k2″, k3″…k of each longitudinal spring set in the stiffness coefficient matrix are obtained. m ″, and then determine the stiffness coefficient corresponding to each spring in the stiffness coefficient matrix, so as to assign the stiffness coefficient matrix to the equivalent model and obtain an equivalent model that matches the nonlinear mechanical behavior of the structural adhesive.

[0118] In some optional embodiments, the embodiment of the present invention takes the structural adhesive between the battery cell and the box body in the battery module as an example of 3×3 spring matrices with different stiffnesses, and pre-establishes a module containing 3 battery cells. The displacements of the battery cells are obtained by frequency sweep test, and the accelerations of each battery cell are a1, a2, and a3, respectively. The main vibration frequency f in the Z direction of the battery module is z-实际 Assume that the stiffness coefficients of the 3×3 springs are not completely consistent, reflecting the nonlinear behavior between the battery module and the structural adhesive. Figure 6 As shown in the figure, 3×3 springs are arranged in the horizontal and vertical directions respectively. Three springs are connected in series at the bottom of each battery cell, which are recorded as longitudinal spring sets. There are three longitudinal spring sets in the horizontal direction. Since compression and tension deformation mainly occur between the module and the structural adhesive during the frequency sweep process, it is assumed that the spring is not subjected to torsional torque. The equivalent total stiffness coefficients of each longitudinal spring set are k1, k2, and k3 respectively. The spring stiffness in each longitudinal spring set is defined as the following vector:

[0119]

[0120] Then the stiffness matrix of the equivalent spring between the module and the structural adhesive is:

[0121]

[0122] According to the spring components satisfying the series relationship, Newton's second law, and Hooke's law, the stiffness coefficient matrix of the equivalent model will be determined Convert to in Is a known number.

[0123] Column matrix of the longitudinal spring set for the first column Assume that Assign the above stiffness coefficient matrix to the equivalent model for modal simulation calculation to obtain the main frequency f in the Z direction of the equivalent model. z-仿真 , the modal simulation results f z-仿真 Test results and test results z-实际 Compare and judge whether the modal simulation calculation results are within the error range. The formula is as follows:

[0124]

[0125] The adaptive PID control adjustment method is used to continuously adjust the equivalent total stiffness coefficient k1 of the first column of longitudinal spring sets, and the corresponding stiffness coefficient column matrix after adjustment is brought into the finite element model for calculation until the maximum simulation analysis maximum error of the simulation calculation result is less than 10%. At this time, the equivalent total stiffness coefficient of the initial longitudinal spring set is determined to be k1′, k2′, and k3′.

[0126] The column matrix of the longitudinal spring set of the first column After mathematical transformation, it is transformed into At the same time, let α1=α3=1, we can get:

[0127]

[0128] Adaptive PID control adjustment method is used to further iterate the coefficient α2 to control the simulation results:

[0129]

[0130] The equivalent total stiffness coefficients k1″, k2″, k3″ of the best longitudinal spring set are finally determined through multiple iterations, and then the stiffness coefficients of each spring are determined in turn.

[0131] The modeling method of the battery pack structural adhesive provided in the embodiment of the present invention performs a sweep frequency test on the battery module to obtain the first main frequency of the battery module and the displacement data and acceleration data of the multiple battery cells contained therein, constructs an equivalent model containing multiple springs, determines the corresponding stiffness coefficient matrix according to the displacement data and acceleration data, performs a sweep frequency simulation on the equivalent model, obtains the second main frequency, calculates the error value of the first main frequency and the second main frequency, and adjusts the stiffness coefficient matrix according to the error value until the error value falls below a preset error threshold, and then determines the equivalent model according to the adjusted stiffness coefficient matrix. The present invention can simulate the nonlinear mechanical behavior of the structural adhesive by making the structural adhesive between the battery cell and the box body equivalent to multiple springs, so that when constructing the finite element model, the influence of the nonlinear compression-stretching mechanical behavior on the performance of the battery pack is fully considered, the accuracy of the finite element model of random vibration of the battery pack is improved, and the reliability of the vibration test of the battery pack is improved.

[0132] In this embodiment, a modeling device for a battery pack structural adhesive is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0133] This embodiment provides a modeling device for battery pack structural adhesive, such as Figure 8 As shown, including:

[0134] The first test module 801 is used to perform a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a casing of the battery module by structural adhesive.

[0135] The second test module 802 is used to construct an equivalent model including multiple springs, determine the stiffness coefficient matrix of the multiple springs according to the displacement data and the acceleration data, and perform a sweep frequency simulation on the equivalent model to obtain the second main frequency of the equivalent model, wherein the spring equivalent corresponds to the structural glue between the battery cell and the box body.

[0136] The coefficient adjustment module 803 is used to calculate the error value between the first main frequency and the second main frequency, and adjust the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold.

[0137] The model determination module 804 is used to determine the equivalent model according to the adjusted stiffness coefficient matrix.

[0138] In some optional embodiments, the second test module 802 includes:

[0139] The parameter determination unit is used to obtain the total mass and the first quantity of the plurality of battery cells.

[0140] The coupling node determination unit is used to determine the first coupling node between the battery cell and the structural adhesive and the second coupling node between the structural adhesive and the box in the battery module.

[0141] The equivalent model construction unit is used to set a longitudinal spring set including a second number of springs between the first coupling node and the second coupling node to obtain an equivalent model including the first number of longitudinal spring sets.

[0142] The stiffness coefficient determination unit is used to determine the equivalent total stiffness coefficient of the longitudinal spring set according to the total mass, displacement data and acceleration data, and equally divide the equivalent total stiffness coefficient into a second number of stiffness coefficients to obtain a stiffness coefficient matrix.

[0143] In some optional implementations, the coefficient adjustment module 803 includes:

[0144] The first error comparison unit is used to calculate an error value between the first main frequency and the second main frequency, and compare the error value with a first preset error threshold.

[0145] The first coefficient adjustment unit is used to perform a first-level adjustment on the stiffness coefficient based on the stiffness coefficient matrix if the error value is not less than a first preset error threshold, and perform a sweep frequency simulation on the adjusted equivalent model until the error value is less than the first preset error threshold.

[0146] The second error comparison unit is used to calculate the error value between the first main frequency and the second main frequency, and compare the error value with a second preset error threshold.

[0147] The second order adjustment unit is used to perform a second-level adjustment on the stiffness coefficient based on the stiffness coefficient matrix if the error value is not less than the second preset error threshold, and perform a sweep frequency simulation on the adjusted equivalent model until the error value is less than the second preset error threshold.

[0148] In some optional implementations, the first coefficient adjustment unit includes:

[0149] The first ratio coefficient calculation subunit is used to use the respective stiffness coefficients of the first longitudinal spring set corresponding to the first column in the stiffness coefficient matrix as the first reference parameter, and determine the first ratio coefficient of each longitudinal spring set relative to the first longitudinal spring set based on the displacement data and the acceleration data.

[0150] The first matrix conversion subunit is used to convert each stiffness coefficient in each row into the product of the first reference parameter and the first ratio coefficient, and extract the first ratio coefficient from the stiffness coefficient matrix to obtain a first transformation matrix.

[0151] The first coefficient adjustment subunit is used to adjust the equivalent total stiffness coefficient of the first longitudinal spring set based on the first transformation matrix, and equally divide the adjusted equivalent total stiffness coefficient into a second number of stiffness coefficients.

[0152] In some optional implementations, the second coefficient adjustment unit includes:

[0153] The second ratio coefficient calculation subunit is used to use the first stiffness coefficient corresponding to the first spring in the first longitudinal spring set as the second reference parameter, and determine the second ratio coefficient of the stiffness coefficient matrix in the first longitudinal spring set relative to the first stiffness coefficient.

[0154] The second matrix conversion subunit is used to convert each stiffness coefficient in the first longitudinal spring set into the product of the second reference parameter and the second ratio coefficient based on the optimal state condition of the structural adhesive, and extract the second reference parameter from the first transformation matrix to obtain the second transformation matrix.

[0155] The second coefficient adjustment subunit is used to adjust the second ratio coefficient based on the second transformation matrix.

[0156] In some optional implementations, the model determination module 804 includes:

[0157] A first inverse transformation unit, used to determine the stiffness coefficient of each spring in the first longitudinal spring set according to the first stiffness coefficient and the adjusted second ratio coefficient;

[0158] A second inverse transformation unit, used to determine the stiffness coefficient of each spring in the stiffness coefficient matrix according to the stiffness coefficient of each spring in the first longitudinal spring set and the first ratio coefficient;

[0159] Determine the elements used to determine the equivalent model based on the stiffness coefficient matrix.

[0160] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0161] The modeling device of the battery pack structural adhesive in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0162] The embodiment of the present invention also provides a computer device having the above Figure 8 The modeling device of the battery pack structural adhesive is shown.

[0163] See also Fig. 9 , Fig. 9 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig. 9As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig. 9 A processor 10 is taken as an example.

[0164] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0165] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0166] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0167] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0168] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Fig. 9 The example of connecting through bus is taken in the following.

[0169] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0170] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0171] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0172] The present invention provides a simulation method for battery pack vibration test, the method comprising: based on the above Figure 1 , Figure 3 or Figure 7 The modeling method of the battery pack structural adhesive shown builds a battery pack model, performs vibration test simulation on the battery pack model, and performs performance evaluation based on the simulation results.

[0173] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A modeling method for battery pack structural adhesive, characterized in that: The method comprises: Performing a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a box of the battery module by structural adhesive; Constructing an equivalent model including a plurality of springs, determining a stiffness coefficient matrix of the plurality of springs according to the displacement data and the acceleration data, and performing a frequency sweep simulation on the equivalent model to obtain a second main frequency of the equivalent model, wherein the springs are equivalent to the structural glue between the battery cell and the box body; Calculating an error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold; The equivalent model is determined according to the adjusted stiffness coefficient matrix.

2. The method according to claim 1, characterized in that The constructing an equivalent model including a plurality of springs and determining a stiffness coefficient matrix of the plurality of springs according to the displacement data and the acceleration data comprises: Obtaining a total mass and a first quantity of the plurality of battery cells; Determine a first coupling node between the battery cell and the structural adhesive and a second coupling node between the structural adhesive and the box in the battery module; A longitudinal spring set including a second number of springs is arranged between the first coupling node and the second coupling node to obtain an equivalent model including the first number of longitudinal spring sets; The equivalent total stiffness coefficient of the longitudinal spring set is determined according to the total mass, the displacement data and the acceleration data, and the equivalent total stiffness coefficient is equally divided into the second number of stiffness coefficients to obtain the stiffness coefficient matrix.

3. The method according to claim 1, characterized in that The calculating the error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold, includes: Calculating an error value between the first main frequency and the second main frequency, and comparing the error value with a first preset error threshold; If the error value is not less than the first preset error threshold, the stiffness coefficient is adjusted in the first level based on the stiffness coefficient matrix, and a sweep frequency simulation is performed on the adjusted equivalent model until the error value is less than the first preset error threshold; Calculating an error value between the first main frequency and the second main frequency, and comparing the error value with a second preset error threshold; If the error value is not less than the second preset error threshold, the stiffness coefficient is adjusted at the second level based on the stiffness coefficient matrix, and a sweep frequency simulation is performed on the adjusted equivalent model until the error value is less than the second preset error threshold.

4. The method according to claim 3, characterized in that The first-level adjustment of the stiffness coefficient based on the stiffness coefficient matrix includes: Taking each of the stiffness coefficients of the first longitudinal spring set corresponding to the first column in the stiffness coefficient matrix as a first reference parameter, and determining a first ratio coefficient of each of the longitudinal spring sets relative to the first longitudinal spring set based on the displacement data and the acceleration data; Convert each of the stiffness coefficients in each row into the product of the first reference parameter and the first ratio coefficient, and extract the first ratio coefficient from the stiffness coefficient matrix to obtain a first transformation matrix; The equivalent total stiffness coefficient of the first longitudinal spring set is adjusted based on the first transformation matrix, and the adjusted equivalent total stiffness coefficient is equally divided into a second number of stiffness coefficients The second-level adjustment of the stiffness coefficient based on the stiffness coefficient matrix includes: Taking a first stiffness coefficient corresponding to a first spring in the first longitudinal spring set as a second reference parameter, and determining a second ratio coefficient of the stiffness coefficient matrix in the first longitudinal spring set relative to the first stiffness coefficient; Based on the optimal state condition of the structural adhesive, each of the stiffness coefficients in the first longitudinal spring set is converted into the product of the second reference parameter and the second ratio coefficient, and the second reference parameter is extracted from the first transformation matrix to obtain a second transformation matrix; The second ratio coefficient is adjusted based on the second transformation matrix.

5. The method according to claim 4, characterized in that Determining the equivalent model according to the adjusted stiffness coefficient matrix includes: Determining a stiffness coefficient of each of the springs in the first longitudinal spring set according to the first stiffness coefficient and the adjusted second ratio coefficient; Determining the stiffness coefficient of each of the springs in the stiffness coefficient matrix according to the stiffness coefficient of each of the springs in the first longitudinal spring set and the first ratio coefficient; The equivalent model is determined based on the stiffness coefficient matrix.

6. A modeling device for battery pack structural adhesive, characterized in that: The device comprises: A first test module is used to perform a frequency sweep test on a battery module including a plurality of battery cells to obtain a first main frequency of the battery module and displacement data and acceleration data of the battery cells, wherein the plurality of battery cells are fixed to a box of the battery module by structural adhesive; The second test module is used to construct an equivalent model including a plurality of springs, determine a stiffness coefficient matrix of the plurality of springs according to the displacement data and the acceleration data, and perform a frequency sweep simulation on the equivalent model to obtain a second main frequency of the equivalent model, wherein the spring equivalently corresponds to a structural adhesive between the battery cell and the box body; A coefficient adjustment module, used for calculating an error value between the first main frequency and the second main frequency, and adjusting the stiffness coefficient matrix according to the error value until the error value is less than a preset error threshold; A model determination module is used to determine the equivalent model according to the adjusted stiffness coefficient matrix.

7. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the modeling method of the battery pack structural adhesive according to any one of claims 1 to 5 by executing the computer instructions.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the modeling method of the battery pack structural adhesive according to any one of claims 1 to 5.

9. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the modeling method of the battery pack structural adhesive according to any one of claims 1 to 5.

10. A simulation method for battery pack vibration test, characterized in that: The method comprises: constructing a battery pack model based on the modeling method of the battery pack structural adhesive according to any one of claims 1 to 5, performing a vibration test simulation on the battery pack model, and performing a performance evaluation based on the simulation results.

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