Method and device for determining vibration simulation modeling parameters of battery pack structural adhesive

Abstract

The invention relates to a method and a device for determining vibration simulation modeling parameters of a battery pack structural adhesive. The method comprises: based on a structural adhesive built in a battery pack, obtaining frequency scanning data of the structural adhesive, the frequency scanning data comprising at least two scanning frequencies, and energy storage moduli and loss moduli corresponding to the scanning frequencies; then, determining a relaxation time set based on all scanning frequencies, and determining a fitting modulus set based on the relaxation time set, the frequency scanning data and a preset modulus equation so as to accurately simulate modulus states of the structural adhesive at different frequencies (such as a stress hysteresis phenomenon caused by the fact that molecular movement in a material cannot keep up with rapid change of external force); and then, based on the fitting modulus set, the material type of the structural adhesive and the constant Poisson's ratio, determining a relaxation modulus set, and based on the relaxation modulus set, the relaxation time set and the constant Poisson's ratio, determining vibration simulation modeling parameters of the structural adhesive so as to effectively guarantee the accuracy of a vibration simulation result during subsequent simulation processing.

Description

Technical Field

[0001] The embodiments in this specification belong to the field of battery pack simulation modeling technology, and specifically relate to a method and apparatus for determining vibration simulation modeling parameters of battery pack structural adhesive. Background Technology

[0002] Structural adhesives in battery packs primarily function to bond cells to trays, modules, and the casing to covers. They not only transfer loads, buffer vibrations, and improve overall stiffness, but also provide some sealing and thermal management assistance. Therefore, the finite element modeling process for structural adhesives is particularly important in the current field of battery pack finite element modeling.

[0003] When performing finite element modeling on structural adhesives, two methods are generally used. One method is to directly connect the two bonded components using a contact relationship (such as a tie) to simulate their adhesive relationship. The other method is to create a solid model of the adhesive at the bonding location (such as connecting the adhesive with a finite element mesh) to assign physical parameters for simulation. However, the first method carries the risk of failing to identify structural adhesive failure in advance, while the second method, although effective in predicting whether the structural adhesive will fail, suffers from significant deviations in vibration simulation, leading to poor simulation accuracy. Summary of the Invention

[0004] The embodiments of this disclosure present a method and apparatus for determining vibration simulation modeling parameters of battery pack structural adhesive.

[0005] In a first aspect of this disclosure, a method for determining vibration simulation modeling parameters of a battery pack structural adhesive is provided. The method includes acquiring frequency scan data of the structural adhesive embedded in the battery pack, the frequency scan data including at least two scan frequencies, and the energy storage modulus and loss modulus corresponding to each scan frequency. The method further includes determining a relaxation time set based on all scan frequencies, and determining a fitted modulus set based on the relaxation time set, the frequency scan data, and a preset modulus equation, the relaxation time set including at least two sequentially arranged relaxation times, and the fitted modulus set including the stiffness modulus corresponding to each relaxation time. Furthermore, the method includes determining a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and a constant Poisson's ratio, and determining vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio, the relaxation modulus set including the shear relaxation modulus and volumetric relaxation modulus corresponding to each stiffness modulus.

[0006] In a second aspect of this disclosure, a device for determining vibration simulation modeling parameters of a battery pack structural adhesive is provided. The device includes a data acquisition module configured to acquire frequency scan data of the structural adhesive embedded in the battery pack. The frequency scan data includes at least two scan frequencies, and the storage modulus and loss modulus corresponding to each scan frequency. The device also includes a data fitting module configured to determine a relaxation time set based on all scan frequencies, and to determine a fitted modulus set based on the relaxation time set, the frequency scan data, and a preset modulus equation. The relaxation time set includes at least two relaxation times arranged in sequence, and the fitted modulus set includes the stiffness modulus corresponding to each relaxation time. Furthermore, the device includes a parameter determination module configured to determine a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and a constant Poisson's ratio, and to determine vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. The relaxation modulus set includes the shear relaxation modulus and volumetric relaxation modulus corresponding to each stiffness modulus.

[0007] In a third aspect of this disclosure, a computer program product is provided, comprising a computer program that is executed by a processor to implement the method according to the first aspect.

[0008] In a fourth aspect of this disclosure, a machine-readable storage medium is provided. The machine-readable storage medium stores machine-executable instructions, which are executed by a processor to implement the method provided according to a first aspect of this disclosure.

[0009] It should be understood that the description in the Summary of the Invention section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0010] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0011] Figure 1 A schematic diagram of an example environment in which some embodiments of this disclosure may be implemented is shown;

[0012] Figure 2 A flowchart illustrating a method for determining vibration simulation modeling parameters of a battery pack structural adhesive according to some embodiments of the present disclosure is shown.

[0013] Figure 3 A schematic diagram of a modulus-time correspondence table according to some embodiments of the present disclosure is shown;

[0014] Figure 4A block diagram of a device for determining vibration simulation modeling parameters of a battery pack structural adhesive according to some embodiments of the present disclosure is shown; and

[0015] Figure 5 A block diagram of an electronic device that can implement several embodiments of the present disclosure is shown. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0017] The terms “comprising” and “having”, and any variations thereof, in this specification, claims, and the foregoing drawings are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. Depending on the context, the word “if” as it applies herein may be interpreted as “when”, “when”, “in response to determination”, or “in response to detection”.

[0018] As mentioned above, structural simulation engineers generally use two methods when performing finite element modeling on structural adhesives. One method is to directly connect the two bonded components using a contact relationship (such as a tie) to simulate the adhesive relationship. The other method is to model the adhesive as a solid at the bonding location (such as by connecting the adhesive with a finite element mesh) to assign physical parameters for simulation. The first method is fast and computationally efficient, mainly used to simulate the bonding between two components, but it cannot examine the adhesive unit itself. If the adhesive unit fails, there is a risk that structural adhesive failure cannot be detected in advance.

[0019] The second method is more complex and time-consuming in modeling, requiring meshing and connection establishment for all bonded locations. It can examine the strength of the structural adhesive itself while demonstrating the connection relationships. Furthermore, this method often treats the structural adhesive as a purely elastic body, i.e., inputting fixed simulation modeling parameters such as density, elastic modulus, and Poisson's ratio. In static and transient dynamic analyses, Hooke's law can be used to realistically reflect the deformation and failure modes of the structural adhesive, and failure can be effectively predicted. However, this method often leads to simulation distortion and inaccurate predictions when performing vibration simulations. This is because the structural adhesive itself is not a purely elastic body, but a polymer material (a viscoelastic material between an elastomer and a viscous body). This material exists in a state of matter between an ideal solid and an ideal fluid, and its elastic modulus changes with frequency. In other words, at a fixed temperature, the frequency determines the elastic modulus of the polymer material. However, during vibration simulation, the mechanical properties of the structural adhesive change with the frequency, which in turn changes the stiffness matrix of the connected components and the entire system during vibration, as well as the fatigue accumulation during vibration. If the structural adhesive is treated as a pure elastic body for simulation, a large deviation will occur, and as the error accumulates, the accuracy of the simulation results will be poor.

[0020] To address this, embodiments of this disclosure propose a method for determining vibration simulation modeling parameters for a battery pack structural adhesive. The method includes acquiring frequency scan data of the structural adhesive embedded in the battery pack. The frequency scan data includes at least two scan frequencies, and the energy storage modulus and loss modulus corresponding to each scan frequency. The method further includes determining a relaxation time set based on all scan frequencies, and determining a fitted modulus set based on the relaxation time set, the frequency scan data, and a preset modulus equation. The relaxation time set includes at least two relaxation times arranged in sequence, and the fitted modulus set includes the stiffness modulus corresponding to each relaxation time. Furthermore, the method includes determining a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and a constant Poisson's ratio, and determining vibration simulation modeling parameters for the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. The relaxation modulus set includes the shear relaxation modulus and volumetric relaxation modulus corresponding to each stiffness modulus.

[0021] In this way, the fitted modulus set can be determined based on the frequency scanning data of the structural adhesive and the preset modulus equation, and the relaxation modulus set can be determined by combining the material type of the structural adhesive and the constant Poisson's ratio. This can accurately simulate the modulus state of the structural adhesive at different frequencies (such as the stress hysteresis phenomenon caused by the molecular motion inside the material not keeping up with the rapid change of external force). Furthermore, when using the determined vibration simulation modeling parameters of the structural adhesive for simulation processing, the accuracy of the vibration simulation results can be effectively guaranteed.

[0022] Figure 1 Schematic diagrams are shown illustrating example environments in which some embodiments of this disclosure can be implemented. For example... Figure 1 As shown, the example environment 100 may include a structural adhesive testing device 101, which is used to perform standard testing on structural adhesive samples embedded in the battery pack to obtain corresponding test data. Here, the structural adhesive testing device 101 may be a frequency scanning instrument (such as a DMA or dynamic thermomechanical analyzer), which can measure the dynamic mechanical properties of the structural adhesive sample as a function of frequency, such as storage modulus and loss modulus, under constant temperature and constant strain amplitude. The storage modulus can be understood as the energy stored in the structural adhesive sample due to elastic deformation during deformation (i.e., reflecting the rigidity or solid-like behavior of the structural adhesive), and the loss modulus can be understood as the energy dissipated as frictional heat during deformation (i.e., reflecting the viscosity or damping characteristics of the structural adhesive).

[0023] It is understood that the structural adhesive sample can be a sample with a specified test shape (such as a dumbbell shape) prepared based on the constituent materials of the structural adhesive during the preparation of the structural adhesive embedded in the battery pack. This sample is specifically designed to obtain the performance of the structural adhesive under different test environments through testing. Furthermore, the structural adhesive sample can be placed in the aforementioned structural adhesive testing equipment 101 by a structural simulation engineer before performing finite element modeling of the structural adhesive to obtain corresponding test data, and is not limited to this.

[0024] Of course, the structural adhesive testing equipment 101 in some embodiments of this disclosure may also include a creep testing instrument (such as a lever creep tester or a universal testing machine), which can measure the strain value of the structural adhesive sample over time under constant stress, so as to subsequently determine the material type of the structural adhesive.

[0025] Example environment 100 may further include processing terminal 102, which establishes a communication connection with structural adhesive testing equipment 101 to acquire test data corresponding to the structural adhesive inside the battery pack, such as multiple scanning frequencies and the energy storage modulus and loss modulus corresponding to each scanning frequency. Here, each scanning frequency may be within a specified test frequency range, such as between 0.1 and 100 Hz.

[0026] Furthermore, the processing terminal 102 can determine a relaxation time set based on all scanning frequencies, and determine a fitting modulus set based on the relaxation time set, frequency scanning data, and a preset modulus equation. Here, the relaxation time set can cover all scanning frequency ranges, and it includes multiple uniformly distributed and sequentially arranged relaxation times. The fitting modulus set can be understood as including multiple parameters to be solved in the preset modulus equation, such as multiple stiffness moduli, and each relaxation time has a corresponding stiffness modulus.

[0027] Furthermore, the processing terminal 102 can determine a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, and determine the vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. Here, the relaxation modulus set may include multiple shear relaxation moduli and multiple volumetric relaxation moduli, and each stiffness modulus in the fitted modulus set has a corresponding shear relaxation modulus and volumetric relaxation modulus. It can be understood that the determined vibration simulation modeling parameters of the structural adhesive can be understood as the viscoelastic parameters of the structural adhesive, such as elastic properties represented by instantaneous modulus and Poisson's ratio, and viscous properties represented by multiple shear relaxation moduli, multiple volumetric relaxation moduli, and relaxation time.

[0028] Of course, the vibration simulation modeling parameters of the structural adhesive in some embodiments of this disclosure may also include basic elastic parameters, plastic stress-strain curves, damage initiation criteria, damage evolution parameters, element type and deletion criteria, contact / connection definition parameters and mesh convergence verification parameters, etc. These parameters can all be obtained or defined by technical means well known in the art, but will not be elaborated here.

[0029] In addition, the processing terminal 102 may also be equipped with simulation application software (such as Abaqus simulation software or ANSYS Mechanical simulation software, which are well known in the art) for finite element modeling of the battery pack. This allows structural simulation engineers to perform accurate modeling on the simulation application software based on the three-dimensional model of the battery pack and the tooling built with the battery pack. When modeling the structural adhesive of the battery pack, the vibration simulation modeling parameters of the structural adhesive mentioned above are input, thereby effectively ensuring the accuracy of the vibration simulation results.

[0030] In this way, the fitted modulus set can be determined based on the frequency scanning data of the structural adhesive and the preset modulus equation, and the relaxation modulus set can be determined by combining the material type of the structural adhesive and the constant Poisson's ratio. This can accurately simulate the modulus state of the structural adhesive at different frequencies (such as the stress hysteresis phenomenon caused by the molecular motion inside the material not keeping up with the rapid change of external force). Furthermore, when using the determined vibration simulation modeling parameters of the structural adhesive for simulation processing, the accuracy of the vibration simulation results can be effectively guaranteed.

[0031] It should be understood that the architecture and functionality in example environment 100 are described for illustrative purposes only and do not imply any limitation on the scope of this disclosure. Embodiments of this disclosure can also be applied to other environments with different architectures and / or functionalities.

[0032] Figure 2 This flowchart illustrates a method for determining vibration simulation modeling parameters of a battery pack structural adhesive according to some embodiments of this disclosure. Method 200 may, for example, be derived from... Figure 1The processing terminal in the example environment shown executes. For example... Figure 2 As shown in block 202, method 200 can obtain frequency scan data of the structural adhesive embedded in the battery pack, based on the structural adhesive itself. The frequency scan data includes at least two scan frequencies, and the energy storage modulus and loss modulus corresponding to each scan frequency. Here, the processing terminal can... Figure 1 The example environment shown uses a structural adhesive testing device to acquire frequency scan data of the structural adhesive. This structural adhesive testing device can be a frequency scanning instrument to measure the storage modulus and loss modulus of the structural adhesive sample as a function of frequency at constant temperature and constant strain amplitude, and each scanning frequency is within a specified test frequency range, such as between 0.1 and 100 Hz.

[0033] It is understood that structural adhesive samples can be samples with a specified test shape (such as a dumbbell shape) prepared based on the constituent materials of the structural adhesive during the preparation of the structural adhesive embedded in the battery pack. These samples are specifically used to obtain the performance of the structural adhesive under different test environments through testing. In addition, structural adhesive samples can be placed in the aforementioned structural adhesive testing equipment by structural simulation engineers before performing finite element modeling of the structural adhesive to obtain corresponding frequency scan data, and are not limited to this.

[0034] In box 204, method 200 can determine a relaxation time set based on all scan frequencies, and determine a fitted modulus set based on the relaxation time set, frequency scan data, and a preset modulus equation. Here, the relaxation time set can cover all scan frequency ranges, and it includes multiple uniformly distributed and sequentially arranged relaxation times. The fitted modulus set can be understood as including multiple parameters to be solved in the preset modulus equation, such as multiple stiffness moduli, and each relaxation time has a corresponding stiffness modulus.

[0035] In some implementations, when determining the relaxation time set based on all scan frequencies, the processing terminal can determine the frequency extrema based on all scan frequencies and then determine the relaxation time interval based on the frequency extrema. In one example, the maximum and minimum scan frequencies can be identified from all scan frequencies to determine the maximum and minimum scan frequencies as frequency extrema, and these frequency extrema can be converted into a relaxation time interval based on a fixed conversion relationship between frequency and relaxation time.

[0036] For example, taking a maximum scan frequency of 100 and a minimum scan frequency of 0.1 (in Hertz, Hz) as examples, the maximum and minimum values ​​of the relaxation time interval can be obtained through the fixed transformation relationship expression shown below:

[0037]

[0038] In the above formula, This corresponds to the relaxation time. This corresponds to the scanning frequency. It can be seen that, based on the minimum scanning frequency, the maximum value of the corresponding relaxation time interval is approximately 1.59; based on the maximum scanning frequency, the maximum value of the corresponding relaxation time interval is approximately 0.0016 (in seconds).

[0039] Subsequently, the processing terminal can determine the logarithmic scale interval based on the relaxation time interval, and determine the logarithmic interval based on the logarithmic scale interval and the preset relaxation time number interval. Here, the logarithmic scale interval can be based on 10 as the logarithm base, and it can cover the relaxation time interval when the corresponding minimum time interval is satisfied. For example, when the relaxation time interval is 0.0016 to 1.59, the minimum time interval can be determined to be 0.0001 (i.e., 10 to the power of negative 4) to 10 (i.e., 10 to the power of 1), and then the corresponding logarithmic scale interval can be determined to be -4 to 1.

[0040] Next, the number of relaxation times can be determined based on a preset range of relaxation times. For example, when the preset range of relaxation times is 11 to 15, the median of the preset range of relaxation times can be determined as the number of relaxation times (e.g., 13). Of course, the number of relaxation times can also be any value within the preset range of relaxation times, and is not limited to this.

[0041] Next, the logarithmic interval can be determined by the ratio of the difference between the maximum and minimum values ​​within the logarithmic scale interval to the result of subtracting one from the initial number of relaxation times. For example, when the logarithmic scale interval is -3 to 1 and the initial number of relaxation times is 10, the logarithmic interval can be approximately determined to be 0.444.

[0042] Subsequently, the processing terminal can determine at least two relaxation times based on the logarithmic scale interval and the logarithmic interval, sort all relaxation times, and determine the sorted relaxation times as a relaxation time set. In one example, multiple target logarithms can be determined sequentially based on the minimum value of the logarithmic scale interval and the logarithmic interval. For example, the first target logarithm can be the sum of the minimum value of the logarithmic scale interval and one logarithmic interval, the second target logarithm can be the sum of the minimum value of the logarithmic scale interval and two logarithmic intervals, and the nth target logarithm can be the sum of the minimum value of the logarithmic scale interval and n-1 logarithmic intervals, and the maximum target logarithm does not exceed the maximum value of the logarithmic scale interval.

[0043] Next, based on the logarithm base of 10 and all target logarithms, the relaxation time corresponding to each target logarithm can be determined. For example, when any target logarithm is -2.556, the corresponding relaxation time can be approximately 0.00278, and when any target logarithm is -2.112, the corresponding relaxation time can be approximately 0.00773. All relaxation times are then sorted in ascending order to form a relaxation time set, thereby effectively ensuring the temporal order and uniform distribution of the relaxation time set.

[0044] For example, taking a logarithmic scale interval of -3 to 1 and a relaxation time of 10, all relaxation times in the determined relaxation time set can be represented as 0.001, 0.00278, 0.00773, 0.0215, 0.0599, 0.167, 0.464, 1.29, 3.59 and 10 respectively.

[0045] In some implementations, to further ensure that all relaxation times fall within the relaxation time interval, the processing terminal may, when determining the relaxation time set based on all scan frequencies, filter all relaxation times based on the relaxation time interval after determining at least two relaxation times based on the logarithmic scale interval and logarithmic interval, and count the number of all relaxation times after filtering. In one example, it may be determined whether each relaxation time falls within the relaxation time interval, so that all relaxation times not within the relaxation time interval are eliminated, and the number of remaining relaxation times (i.e., the number of all relaxation times within the relaxation time interval) is counted.

[0046] Subsequently, the processing terminal can determine whether the number of all relaxation times after filtering falls within a preset relaxation time range. It is understandable that when the number of all relaxation times after filtering falls within the preset range, it indicates that the current number of relaxation times meets the modulus fitting requirements, thus ensuring the accuracy of the subsequently determined fitted modulus set. When the number of all relaxation times after filtering does not fall within the preset range, it indicates that the current number of relaxation times does not meet the modulus fitting requirements. If the number of all relaxation times after filtering exceeds the maximum value of the preset relaxation time range, it will increase the overall computational load of modulus fitting; conversely, if the number of all relaxation times after filtering does not exceed the minimum value of the preset relaxation time range, it will affect the accuracy of the fitted modulus set.

[0047] Subsequently, in response to determining that the number of relaxation times after filtering is within a preset range of relaxation times, the processing terminal may sort all the relaxation times after filtering and determine the sorted relaxation times as a relaxation time set.

[0048] Alternatively, the processing terminal may also update the logarithmic interval in response to determining that the number of relaxation times after filtering is not within a preset relaxation time range, and determine the relaxation time set based on the updated logarithmic interval and logarithmic scale range. In one example, if the number of relaxation times after filtering does not exceed the minimum value of the preset relaxation time range, the number of relaxation times can be re-determined based on the preset relaxation time range so that the subsequently re-determined logarithmic interval is smaller than the current logarithmic interval. The current logarithmic interval is then updated based on the re-determined logarithmic interval, and the relaxation time set is re-determined by referring to the above steps until all relaxation times included in the relaxation time set are within the relaxation time range and the number of relaxation times is within the preset relaxation time range.

[0049] In some implementations, when determining the fitting modulus set based on the relaxation time set, frequency scan data, and a preset modulus equation, the processing terminal can perform conversion processing on each scan frequency in the frequency scan data to obtain the corresponding angular frequency. Here, there is a fixed conversion relationship between the scan frequency and the angular frequency, which can be expressed as follows:

[0050]

[0051] In the above formula, Corresponding to angular frequency, This corresponds to the scanning frequency.

[0052] Subsequently, the processing terminal can perform nonlinear least-squares fitting on the preset modulus equations based on the relaxation time set, all angular frequencies, and the storage modulus and loss modulus corresponding to each angular frequency, to obtain the limiting storage modulus and the stiffness modulus corresponding to each relaxation time. Here, the preset modulus equations include the theoretical modulus equations corresponding to the storage modulus and the theoretical modulus equations corresponding to the loss modulus, which can be expressed as the modulus equation expressions shown below:

[0053]

[0054]

[0055] In the above formula, Corresponding to energy storage modulus, This corresponds to the limiting energy storage modulus to be solved. This corresponds to the i-th stiffness modulus to be solved, and n corresponds to the total number of relaxation times. This corresponds to the i-th relaxation time. This corresponds to the angular frequency associated with the energy storage modulus. This corresponds to the loss modulus.

[0056] Understandably, by substituting the relaxation time set, all angular frequencies, and the storage modulus and loss modulus corresponding to each angular frequency into the aforementioned preset modulus equation, and using fitting mathematical software (such as Origin (with a viscoelastic fitting plugin), MATLAB, Python (SciPy), or fitting tools provided by Abaqus) to perform nonlinear least squares fitting, the limiting storage modulus and stiffness modulus corresponding to each relaxation time that can guarantee the minimum error can be obtained.

[0057] The processing terminal can then determine the ultimate energy storage modulus and all stiffness moduli as a set of fitted moduli.

[0058] Of course, the limiting energy storage modulus of some embodiments of this disclosure can also be obtained by technical means well known in the art, by substituting the preset modulus equation mentioned in the above steps and performing nonlinear least squares fitting processing, to obtain the stiffness modulus corresponding to each relaxation time with the minimum error, and is not limited thereto.

[0059] In box 206, method 200 can determine a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and a constant Poisson's ratio, and determine the vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. Here, the relaxation modulus set may include multiple shear relaxation moduli and multiple volumetric relaxation moduli, and each stiffness modulus in the fitted modulus set has a corresponding shear relaxation modulus and volumetric relaxation modulus. It is understood that the determined vibration simulation modeling parameters of the structural adhesive may be the viscoelastic parameters of the structural adhesive, such as elastic properties represented by instantaneous modulus and Poisson's ratio, and viscous properties represented by multiple shear relaxation moduli, multiple volumetric relaxation moduli, and relaxation time.

[0060] Of course, the vibration simulation modeling parameters of the structural adhesive in some embodiments of this disclosure may also include basic elastic parameters, plastic stress-strain curves, damage initiation criteria, damage evolution parameters, element type and deletion criteria, contact / connection definition parameters and mesh convergence verification parameters, etc. These parameters can all be obtained or defined by technical means well known in the art, but will not be elaborated here.

[0061] In some implementations, when determining the relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, the processing terminal can determine the instantaneous modulus based on the limiting storage modulus and all stiffness moduli. Here, the limiting storage modulus and all stiffness moduli can be substituted into the instantaneous modulus calculation formula shown below to obtain the instantaneous modulus:

[0062]

[0063] In the above formula, Corresponding to instantaneous modulus, This corresponds to the limiting energy storage modulus to be solved. This corresponds to the i-th stiffness modulus, and n corresponds to the total number of stiffness moduli.

[0064] The processing terminal can then determine the corresponding shear relaxation modulus based on the instantaneous modulus and various stiffness moduli. Here, the instantaneous modulus and various stiffness moduli can be substituted into the relaxation modulus calculation formula shown below to obtain the corresponding shear relaxation modulus:

[0065]

[0066] In the above formula, This corresponds to the i-th shear relaxation modulus. This corresponds to the i-th stiffness modulus. This corresponds to the instantaneous modulus.

[0067] Subsequently, the processing terminal can determine whether the structural adhesive material type is linear elastic. Here, the structural adhesive material type can be divided into linear elastic, general linear viscoelastic, (near) incompressible, and elastoplastic. When the structural adhesive material type is linear elastic and has a constant Poisson's ratio, based on the fixed conversion relationship between shear relaxation modulus and volume relaxation modulus (that is, a fixed conversion relationship with instantaneous modulus and Poisson's ratio), it can be concluded that the ratio of shear relaxation modulus and volume relaxation modulus to instantaneous modulus remains constant. At this time, the corresponding volume relaxation modulus can be quickly determined based on each shear relaxation modulus.

[0068] Of course, in some embodiments of this disclosure, when the material type of the structural adhesive is determined to be non-linear elastic, for example, using general linear viscoelasticity, it is shown that the shear relaxation modulus and the volume relaxation modulus are independent of each other. In this case, it is necessary to combine other technical means to determine the volume relaxation modulus, such as obtaining the volume strain response curve of the structural adhesive based on hydrostatic relaxation test, and combining nonlinear least square fitting processing to determine the volume relaxation modulus, and is not limited to this.

[0069] Subsequently, in response to determining that the structural adhesive's material type is linear elastic, the processing terminal can determine the shear relaxation modulus corresponding to each stiffness modulus as the corresponding volumetric relaxation modulus. Here, when the structural adhesive's material type is linear elastic and has a constant Poisson's ratio, the shear relaxation modulus corresponding to each stiffness modulus can be defaulted to being the corresponding volumetric relaxation modulus. That is, each relaxation time has the same shear relaxation modulus and volumetric relaxation modulus, and all shear relaxation moduli and all volumetric relaxation moduli corresponding to all stiffness moduli are determined as the relaxation modulus set.

[0070] In some implementations, to ensure that the method for determining the material type of structural adhesive is more convincing and reliable, strain-related test results can be obtained based on structural adhesive testing equipment, and the material type of structural adhesive can be determined by combining the strain-related test results.

[0071] When determining the relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, the processing terminal can also obtain the strain-time curve of the structural adhesive in the step of determining whether the material type of the structural adhesive is linearly elastic, and determine the strain slope corresponding to each time point on the strain-time curve. Here, the structural adhesive testing equipment may also include a creep testing instrument (such as a lever-type creep testing machine or a universal testing machine), which can measure the strain value of the structural adhesive sample changing with time under constant stress, so as to generate a strain-time curve based on the strain value changing with different times and feed it back to the processing terminal. It can be understood that the processing terminal can obtain the strain slope corresponding to the i-th time point by substituting the i-th time point, the strain value corresponding to the i-th time point, the (i+1)-th time point, and the strain value corresponding to the (i+1)-th time point into the slope calculation formula based on multiple time points on the strain-time curve and the strain value corresponding to each time point.

[0072] The processing terminal can then determine whether all strain slopes corresponding to at least two adjacent time points are at a preset slope value. It can be understood that if the preset slope value is set to 0, meaning all strain slopes corresponding to multiple adjacent time points are 0, it indicates that the strain of the structural adhesive remains constant under constant stress, thus confirming that the material type of the structural adhesive is linear elastic. Furthermore, if all strain slopes corresponding to multiple adjacent time points are not 0 and are all within a preset slope range, it indicates that the strain of the structural adhesive increases slowly and continuously under constant stress, thus confirming that the material type of the structural adhesive is general linear viscoelastic.

[0073] Subsequently, the processing terminal can determine that the material type of the structural adhesive is linear elastic by determining that all strain slopes corresponding to at least two adjacent time points are preset slope values. Of course, some embodiments of this disclosure may also use other test results to determine whether the material type of the structural adhesive is linear elastic, and are not limited thereto.

[0074] In some implementations, when determining the vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, relaxation time set, and constant Poisson's ratio, the processing terminal can define the instantaneous modulus and constant Poisson's ratio as elastic properties. It is understood that the elastic properties in the structural adhesive parameter interface of a battery pack generally include the elastic modulus and Poisson's ratio. Here, the instantaneous modulus can be defaulted to the elastic modulus, or the elastic modulus can be obtained by processing the instantaneous modulus, ensuring that the elastic modulus is very close to the instantaneous modulus.

[0075] The processing terminal can then integrate the relaxation modulus set and relaxation time set to obtain a modulus-time mapping table, and define the modulus-time mapping table and time domain as viscous properties. Here, the modulus-time mapping table includes multiple relaxation times arranged in sequence, and each relaxation time's column (or row) also includes the shear relaxation modulus and volume relaxation modulus corresponding to the corresponding relaxation time.

[0076] Please see Figure 3 The diagram shown illustrates a modulus-time correspondence table according to some embodiments of the present disclosure, such as... Figure 3 As shown, the modulus-time correspondence table 300 may include three relaxation times arranged in sequence, and each row of relaxation time also includes the shear relaxation modulus and volume relaxation modulus corresponding to the corresponding relaxation time.

[0077] Subsequently, the processing terminal can determine the elastic and viscous properties as vibration simulation modeling parameters for the structural adhesive. Upon detecting the structural adhesive parameter interface of the battery pack, it inputs these vibration simulation modeling parameters into the interface. Understandably, after determining the elastic and viscous properties as vibration simulation modeling parameters for the structural adhesive, structural simulation engineers can perform simulation modeling on the simulation application software set up on the processing terminal, based on the 3D model of the battery pack and the tooling assembled with it. Upon detecting the structural adhesive parameter interface of the battery pack (such as the Mechanical -> Elasticity -> Elastic dialog box in Abaqus simulation software), it automatically selects Viscoelastic in the Type selection box and automatically inputs the elastic properties. Afterwards, the Viscoelastic area can be found at the bottom of the Elastic dialog box, where Time (i.e., the time domain in the viscous properties) is automatically selected in the Domain selection box, and the modulus-time correspondence table in the viscous properties is automatically input into the table popped up based on the Edit control. Of course, the processing terminal in some embodiments of this disclosure can also display the vibration simulation modeling parameters of the structural adhesive to the structural simulation engineer, so that the structural simulation engineer can manually input the relevant parameters in the structural adhesive parameter interface of the battery pack according to the vibration simulation modeling parameters of the structural adhesive, and is not limited to this.

[0078] This modeling method can accurately simulate the stress hysteresis phenomenon caused by the inability of molecular motion within the structural adhesive to keep up with the rapid changes in external force during dynamic experiments (vibration) due to its polymer properties. This allows for the accurate simulation of the structural adhesive modulus at different frequencies, maintaining the accuracy of vibration simulation results.

[0079] Furthermore, to further ensure the reliability of vibration simulation results, structural simulation engineers, upon receiving the 3D model of the battery pack, should first perform detailed finite element modeling. This includes detailed mesh modeling of the top cover, lower casing, electronic components, modules, or block groups to ensure the mesh quality of each component. Secondly, weld points and weld seams should be modeled using corresponding software elements to ensure consistency with actual weld point sizes and welding methods. Long bolts should be modeled using 3D solid models to ensure accurate reflection of the stiffness of the force transmission path.

[0080] During the overall modeling of the battery pack, features such as rounded corners, chamfers, steps, labels, and minor details that have a minor impact on the overall structure can be geometrically cleaned up. For example, the principles for removing rounded corners should be: rounded corners that do not account for a large proportion of the overall structure; unnecessary rounded corners (such as external rounded corners); rounded corners in areas of no concern, etc. Chamfers, steps, labels, and minor details can be removed using roughly the same principles. For components with a thickness less than 5mm, 2D shell elements should be used for meshing. For components with a thickness greater than 5mm, when using 3D hexahedral meshing, at least four layers of mesh should be ensured in the thickness direction. When using 3D tetrahedral meshing, second-order elements should be used. Finally, when modeling all adhesives in the entire pack using 3D solid modeling, different types of adhesives need to be created into different sets. For example, structural adhesives, thermally conductive structural adhesives, and double-sided adhesives need to be classified differently. Furthermore, for the locations of connected components, relatively regular locations can be modeled using a shared-node approach, while irregular locations can be connected using solid elements to the adhesive components via tie or glue elements.

[0081] Subsequently, when structural simulation engineers accurately model the tooling assembled with the battery pack, the vibration tooling of the battery pack must meet the actual modeling requirements, such as ensuring that the tooling of the battery pack is consistent with the actual way it is installed on the vehicle frame; when modeling the tooling, 3D meshes can be used for accurate modeling, and in principle, significant simplification and simplified modeling of the model are not allowed; finally, the stiffness of the vibration tooling must be guaranteed, and the modal characteristics of the vibration tooling itself must be greater than 200Hz, or the modal characteristic reduction of the battery pack with and without the tooling test must be less than 1Hz.

[0082] It should be noted that the process by which structural simulation engineers accurately model the battery pack using its 3D model and the tooling assembled with it on the simulation application software is a well-known technique in the field and will not be elaborated upon here.

[0083] Figure 4A block diagram of a device for determining vibration simulation modeling parameters of a battery pack structural adhesive according to some embodiments of the present disclosure is shown. The various embodiments in this specification are described in a progressive manner, with reference to each other for similar or identical parts. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. Figure 4 As shown, the vibration simulation modeling parameter determination device 400 for the battery pack structural adhesive may include a data acquisition module 402, configured to acquire frequency scan data of the structural adhesive embedded in the battery pack. The frequency scan data includes at least two scan frequencies, and the energy storage modulus and loss modulus corresponding to each scan frequency. The device 400 also includes a data fitting module 404, configured to determine a relaxation time set based on all scan frequencies, and to determine a fitted modulus set based on the relaxation time set, the frequency scan data, and a preset modulus equation. The relaxation time set includes at least two relaxation times arranged in sequence, and the fitted modulus set includes the stiffness modulus corresponding to each relaxation time. In addition, the vibration simulation modeling parameter determination device 400 for battery pack structural adhesive also includes a parameter determination module 406, which is configured to determine a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, and to determine the vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. The relaxation modulus set includes the shear relaxation modulus and volume relaxation modulus corresponding to each stiffness modulus.

[0084] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0085] Figure 5 Block diagrams of electronic devices that can implement various embodiments of the present disclosure are shown. For example... Figure 5 As shown, the electronic device 500 includes a processor 501, which can perform various appropriate actions and processes based on computer program instructions loaded into random access memory (RAM) 503 according to computer program instructions stored in read-only memory (ROM) 502. The RAM 503 may also store various programs and data required for the operation of the electronic device 500. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0086] The various processes and procedures described above, such as method 200, can be executed by processor 501. For example, in some embodiments, method 200 may be implemented as a software program tangibly contained in a machine-readable medium. In some embodiments, part or all of the software program may be loaded into and / or installed onto electronic device 500 via ROM 502. When the software program is loaded into RAM 503 and executed by processor 501, one or more actions of method 200 described above may be performed.

[0087] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload programmable logic devices (CPLDs), and so on.

[0088] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0089] This disclosure can be a method, apparatus, system, and / or program product. The program product may include a machine-readable storage medium on which machine-readable program instructions for performing various aspects of this disclosure are loaded. The machine-readable program instructions described herein can be downloaded from the machine-readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the machine-readable program instructions from the network and forwards them to the machine-readable storage medium in the respective computing / processing device.

[0090] Machine program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. Machine-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as a standalone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the machine-readable program instructions to implement various aspects of this disclosure.

[0091] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. Furthermore, although operations are depicted in a specific order, this should be understood as requiring that such operations be performed in the specific order shown or in sequential order, or requiring that all illustrated operations be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.

[0092] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for determining vibration simulation modeling parameters of structural adhesive for battery packs, characterized in that, include: Based on the structural adhesive built into the battery pack, frequency scanning data of the structural adhesive is obtained. The frequency scanning data includes at least two scanning frequencies, and the energy storage modulus and loss modulus corresponding to each scanning frequency. A relaxation time set is determined based on all the scanning frequencies, and a fitting modulus set is determined based on the relaxation time set, the frequency scanning data, and the preset modulus equation. The relaxation time set includes at least two relaxation times arranged in sequence, and the fitting modulus set includes stiffness modulus corresponding to each relaxation time. as well as Based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, a relaxation modulus set is determined, and the vibration simulation modeling parameters of the structural adhesive are determined based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. The relaxation modulus set includes the shear relaxation modulus and volume relaxation modulus corresponding to each of the stiffness moduli.

2. The method according to claim 1, characterized in that, The determination of the relaxation time set based on all said scanning frequencies includes: The maximum and minimum frequencies are determined based on all the said scanning frequencies, and the relaxation time interval is determined based on the maximum and minimum frequencies. Based on the relaxation time interval, a logarithmic scale interval is determined, and based on the logarithmic scale interval and a preset relaxation time number interval, a logarithmic interval is determined; and Based on the logarithmic scale interval and the logarithmic interval, at least two relaxation times are determined, all of the relaxation times are sorted, and all of the sorted relaxation times are determined as a relaxation time set.

3. The method according to claim 2, characterized in that, The determination of the relaxation time set based on all said scanning frequencies further includes: Based on the relaxation time interval, all relaxation times are filtered, and the number of all relaxation times after filtering is counted. Determine whether the total number of relaxation times after the filtering process falls within the preset range of relaxation times. In response to determining that the number of all relaxation times after the filtering process falls within the preset range of relaxation times, the relaxation times after the filtering process are sorted, and the sorted relaxation times are determined as a relaxation time set; or In response to determining that the number of relaxation times after the filtering process is not within the preset relaxation time range, the logarithmic interval is updated, and a relaxation time set is determined based on the updated logarithmic interval and the logarithmic scale range.

4. The method according to claim 1, characterized in that, The step of determining the fitted modulus set based on the relaxation time set, the frequency scan data, and the preset modulus equation includes: The scanning frequencies in the frequency scanning data are converted to obtain the corresponding angular frequencies. Based on the relaxation time set, all the angular frequencies, the energy storage modulus corresponding to each angular frequency, and the loss modulus, a nonlinear least squares fitting process is performed on the preset modulus equation to obtain the limiting energy storage modulus and the stiffness modulus corresponding to each relaxation time; and The ultimate energy storage modulus and all the stiffness moduli are determined as a set of fitted moduli.

5. The method according to claim 4, characterized in that, The determination of the relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio includes: Based on the ultimate energy storage modulus and all the stiffness moduli, the instantaneous modulus is determined; Based on the instantaneous modulus and each of the stiffness moduli, the corresponding shear relaxation modulus is determined; Determine whether the material type of the structural adhesive is linear elastic; In response to determining that the material type of the structural adhesive is linearly elastic, the shear relaxation modulus corresponding to each of the stiffness moduli is determined as the corresponding volume relaxation modulus; and The set of relaxation moduli is defined as all the shear relaxation moduli and all the volume relaxation moduli corresponding to all the stiffness moduli.

6. The method according to claim 5, characterized in that, The determination of vibration simulation modeling parameters for the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio includes: The instantaneous modulus and the constant Poisson's ratio are defined as elastic properties; The relaxation modulus set and the relaxation time set are integrated to obtain a modulus-time correspondence table, and the modulus-time correspondence table and the time domain are determined as viscous properties. The elastic and viscous properties are determined as vibration simulation modeling parameters for the structural adhesive, and the vibration simulation modeling parameters are input into the structural adhesive parameter interface when the structural adhesive parameter interface of the battery pack is detected.

7. The method according to claim 5, characterized in that, The step of determining the relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio further includes: Obtain the strain-time curve of the structural adhesive and determine the strain slope corresponding to each time point on the strain-time curve; Determine whether all strain slopes corresponding to at least two adjacent time points are preset slope values; and In response to determining that all strain slopes corresponding to at least two adjacent time points are the preset slope values, the material type of the structural adhesive is determined to be linear elastic.

8. A device for determining vibration simulation modeling parameters of structural adhesive for battery packs, characterized in that, include: The data acquisition module is configured to acquire frequency scanning data of the structural adhesive built into the battery pack, the frequency scanning data including at least two scanning frequencies, and the energy storage modulus and loss modulus corresponding to each scanning frequency; The data fitting module is configured to determine a relaxation time set based on all the scanning frequencies, and to determine a fitting modulus set based on the relaxation time set, the frequency scanning data, and a preset modulus equation. The relaxation time set includes at least two relaxation times arranged in sequence, and the fitting modulus set includes stiffness moduli corresponding to each relaxation time. as well as The parameter determination module is configured to determine a relaxation modulus set based on the fitted modulus set, the material type of the structural adhesive, and the constant Poisson's ratio, and to determine the vibration simulation modeling parameters of the structural adhesive based on the relaxation modulus set, the relaxation time set, and the constant Poisson's ratio. The relaxation modulus set includes the shear relaxation modulus and volume relaxation modulus corresponding to each of the stiffness moduli.

9. A computer-readable storage medium having a computer program stored thereon, the computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform the steps of the method as claimed in any one of claims 1-7.

10. An electronic device, characterized in that, include: One or more processors, and A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method according to any one of claims 1-7.

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