Methods, devices, equipment, storage media, and software products for identifying elastic parameters

Abstract

This application relates to a method, apparatus, device, storage medium, and program product for elastic parameter identification. The control device for the elastic parameter identification system includes a control unit, a data acquisition unit, and an excitation device. The control unit is connected to both the excitation device and the data acquisition unit. The excitation device is used to excite vibration of a target battery under the control of the control unit. The method includes: controlling the excitation device to excite vibration of the target battery under different states of charge; for each state of charge, receiving vibration signals sent by the data acquisition unit and determining the modal parameters of the target battery based on the vibration signals; for each state of charge, determining the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio. This method can reduce damage to the battery structure when determining elastic parameters.

Description

Technical Field

[0001] This application relates to the field of vibration technology, and in particular to a method, apparatus, device, storage medium, and program product for identifying elastic parameters. Background Technology

[0002] The safety, reliability, and lifespan of new batteries depend on further research and exploration of various battery performance parameters. Among these, the mechanical performance testing of batteries is a key indicator, and Young's modulus and Poisson's ratio, as important parameters of material elasticity, play a vital role in understanding the mechanical behavior of batteries.

[0003] In existing technologies, compression tests or tensile tests are typically used to identify the Young's modulus and Poisson's ratio of a battery. The compression test involves using equipment such as a compression testing machine to compress individual battery cells, and by collecting stress-strain data, the Young's modulus and Poisson's ratio of the battery are calculated.

[0004] However, due to the complex and fragile internal structure of batteries, traditional compression or tensile tests are likely to cause structural damage to the batteries, affecting their performance and even causing dangers such as battery leakage and explosion. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, device, storage medium, and program product for identifying elastic parameters that can avoid damage to the battery structure, in order to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides an elastic parameter identification method for use in the control device of an elastic parameter identification system. The elastic parameter identification system includes a control device, a data acquisition device, and an excitation device. The control device is connected to both the excitation device and the data acquisition device. The excitation device is used to excite the vibration of a target battery under the control of the control device. The method includes:

[0007] Under different states of charge of the target battery, the excitation device is controlled to stimulate the vibration of the target battery;

[0008] For each state of charge, the vibration signal sent by the receiving and acquisition device is used to determine the modal parameters of the target battery based on the vibration signal.

[0009] For each state of charge, the elastic parameters of the target battery under the state of charge are determined based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

[0010] In one embodiment, the modal parameters include natural frequencies of each order. Determining the elastic parameters of the target battery under the state of charge based on the modal parameters and the identification model includes:

[0011] Based on the natural frequencies of each order, a first parameter is determined, wherein the first parameter is at least one of the natural frequencies of each order; the first parameter is input into the identification model, and the elastic parameters of the target battery under the state of charge are determined based on the output of the identification model.

[0012] In one embodiment, the identification model is determined based on an equation with Young's modulus and Poisson's ratio as variables. The first parameter includes any two of the natural frequencies. The first parameter is input into the identification model, and the elastic parameters of the target battery under the state of charge are determined based on the output of the identification model, including:

[0013] Obtain the physical parameters of the target battery, including density, length in the X direction, and length in the Y direction. Determine the first equation based on the product of Young's modulus and a second parameter, the product of the square of Poisson's ratio and a third parameter, and a fourth parameter. The second parameter is determined based on the physical parameters. The third and fourth parameters are determined based on the physical parameters and a first natural frequency, where the first natural frequency is any one of the first parameters. Determine the second equation based on the product of Young's modulus and a second parameter, the product of the square of Poisson's ratio and a fifth parameter, and a sixth parameter. The fifth and sixth parameters are determined based on the physical parameters and a second natural frequency, where the second natural frequency is any other natural frequency among the first parameters. Determine the Young's modulus and Poisson's ratio based on the first and second equations.

[0014] In one embodiment, the excitation device is a hammer, and the excitation device is controlled to excite the target battery to vibrate under different states of charge of the target battery, including:

[0015] A control hammer strikes one or more points on the target battery to induce vibration in the target battery.

[0016] In one embodiment, receiving vibration signals from a data acquisition device and determining the modal parameters of the target battery based on the vibration signals includes:

[0017] The vibration signal is preprocessed; the preprocessed vibration signal is then subjected to frequency domain analysis, and the modal parameters of the target battery are determined based on the spectrum of the vibration signal.

[0018] In one embodiment, the method further includes:

[0019] An elastic parameter mapping table is determined based on each state of charge and elastic parameter. The elastic parameter mapping table is used to store the correspondence between different states of charge and elastic parameters.

[0020] Secondly, this application also provides an elastic parameter identification device, disposed in the control device of an elastic parameter identification system. The elastic parameter identification system includes a control device, a data acquisition device, and an excitation device. The control device is connected to both the excitation device and the data acquisition device. The excitation device is used to excite the target battery to vibrate under the control of the control device. The device includes:

[0021] The excitation module is used to control the excitation device to excite the target battery to vibrate under different states of charge of the target battery;

[0022] The receiving module is used to receive vibration signals sent by the acquisition device for each state of charge and determine the modal parameters of the target battery based on the vibration signals.

[0023] The identification module is used to determine the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

[0024] In one embodiment, the modal parameters include natural frequencies of each order. The identification module is specifically used to determine a first parameter based on the natural frequencies of each order, wherein the first parameter is at least one of the natural frequencies of each order; input the first parameter into the identification model, and determine the elastic parameters of the target battery under the state of charge based on the output of the identification model.

[0025] In one embodiment, the identification model is determined based on an equation with Young's modulus and Poisson's ratio as variables. The first parameter includes any two of the natural frequencies of each order. The identification module is specifically used to acquire the physical parameters of the target battery, including density, length dimension of the target battery in the X direction, and length dimension in the Y direction. The first equation is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the third parameter, and the fourth parameter. The second parameter is determined based on the physical parameters. The third and fourth parameters are determined based on the physical parameters and the first natural frequency, where the first natural frequency is any one of the first parameters. The second equation is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the fifth parameter, and the sixth parameter. The fifth and sixth parameters are determined based on the physical parameters and the second natural frequency, where the second natural frequency is any of the other natural frequencies of the first parameters. The Young's modulus and Poisson's ratio are determined based on the first and second equations.

[0026] In one embodiment, the excitation device is a hammer and an excitation module, specifically used to control the hammer to strike one or more parts of the target battery to stimulate vibration of the target battery.

[0027] In one embodiment, the receiving module is specifically used to preprocess the vibration signal; perform frequency domain analysis on the preprocessed vibration signal, and determine the modal parameters of the target battery based on the spectrum of the vibration signal.

[0028] In one embodiment, the identification module is further configured to determine an elastic parameter mapping table based on each state of charge and elastic parameter, the elastic parameter mapping table being used to store the correspondence between different states of charge and elastic parameters.

[0029] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the methods described in the first aspect above.

[0030] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the methods described in the first aspect above.

[0031] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the methods described in the first aspect above.

[0032] The aforementioned method, apparatus, device, storage medium, and program product for identifying elastic parameters work by controlling an excitation device to stimulate vibration of the target battery under different states of charge. Then, for each state of charge, vibration signals sent by a data acquisition device are received, and the modal parameters of the target battery are determined based on these signals. Finally, for each state of charge, the elastic parameters of the target battery under each state of charge are determined based on the modal parameters and an identification model. These elastic parameters include Young's modulus and Poisson's ratio. In this way, by controlling the vibration of the target battery, modal parameters of the target battery under different states of charge can be obtained, and Young's modulus and Poisson's ratio can be determined based on these modal parameters and the identification model. Unlike existing technologies that use compression or tensile tests, the method in this application reduces damage to the battery structure when determining elastic parameters. Furthermore, once the elastic parameters for different states of charge are determined, subsequent applications only require determining the battery's state of charge to obtain the corresponding elastic parameters. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a diagram illustrating the application environment of an elastic parameter identification method in one embodiment.

[0035] Figure 2This is a flowchart illustrating an elastic parameter identification method in one embodiment;

[0036] Figure 3 This is a flowchart illustrating the steps for determining elastic parameters in one embodiment;

[0037] Figure 4 This is a flowchart illustrating the steps of determining elasticity parameters based on the output of an identification model in one embodiment.

[0038] Figure 5 This is a flowchart illustrating the steps for determining the modal parameters of a target battery in one embodiment;

[0039] Figure 6 This is a flowchart illustrating the elastic parameter identification method in another embodiment;

[0040] Figure 7 This is a structural block diagram of an elastic parameter identification device in one embodiment;

[0041] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0043] With the rapid development of technology, batteries, as energy storage devices, have penetrated numerous industries and are widely used in electric vehicles, aircraft, and portable electronic devices. At the same time, this has placed higher demands on the specific energy of batteries. To meet industry needs, new types of batteries, such as lithium metal batteries, are constantly being researched and developed. In this process, the safety, reliability, and lifespan of these new batteries depend on further exploration and research into their various performance characteristics. Among these, the mechanical performance testing of batteries is a key indicator, and Young's modulus and Poisson's ratio, as important parameters of material elastic properties, play a crucial role in understanding the mechanical behavior of batteries.

[0044] To identify the Young's modulus and Poisson's ratio of a battery, traditional methods typically employ compression or tensile tests. Compression tests use equipment such as compression testing machines to compress individual battery cells, collecting stress-strain data to calculate the Young's modulus and Poisson's ratio. Tensile tests are similar, using tensile testing machines to perform tensile tests on individual battery cells; the stress-strain parameters obtained during the tensile process are also used as the basis for calculating the battery's Young's modulus and Poisson's ratio.

[0045] However, the aforementioned Young's modulus and Poisson's ratio identification schemes have significant limitations in application at the individual battery cell level. Batteries have complex and fragile internal structures, and traditional compression or tensile tests are likely to cause structural damage, affecting battery performance and even leading to dangers such as leakage and explosion. This is especially true for lithium metal batteries, which this patent focuses on; their danger level is even higher. Once the lithium metal negative electrode is exposed to air, it is highly susceptible to explosion, making traditional compression and tensile tests unsuitable for identifying the Young's modulus and Poisson's ratio of lithium metal batteries.

[0046] In view of this, embodiments of this application provide an elastic parameter identification method that can avoid damage to the battery structure. The elastic parameter identification method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the elastic parameter identification system 10 may include a control device 11, a data acquisition device 12, and an excitation device 13. The control device 11 is connected to both the excitation device 13 and the data acquisition device 12. The excitation device 13 is used to excite the target battery to vibrate under the control of the control device 11. The data acquisition device 12 is connected to the target battery and is used to acquire the vibration signal of the target battery and send the acquired vibration signal to the control device 11. The control device 11 is used to control the excitation device 13 to excite the target battery to vibrate under different states of charge of the target battery. For each state of charge, it receives the vibration signal sent by the data acquisition device 12, determines the modal parameters of the target battery based on the vibration signal, and determines the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio. The control device 11 may be a computer device, such as an industrial control computer or a computer. The type of control device 11 is not limited in this embodiment.

[0047] In one exemplary embodiment, such as Figure 2 As shown, a method for identifying elastic parameters is provided, which can be applied to... Figure 1 Taking the control device 11 as an example, the description includes the following steps 201 to 203. Wherein:

[0048] S201, under different states of charge of the target battery, control the excitation device to excite the target battery to vibrate.

[0049] Optionally, the target battery can be a lithium metal battery or a lead-acid battery, etc. The target battery can be multiple batteries of the same model that are not used, or it can be a single battery. In this embodiment of the application, the number of target batteries is not limited.

[0050] Optionally, the state of charge can be the ratio of the amount of charge currently stored in the target battery to the amount of charge that the target battery can store when fully charged. It reflects the energy storage level of the electrochemical energy inside the battery and is a key indicator for measuring the remaining capacity of the battery.

[0051] Optionally, the current state of charge of the target battery can be obtained before the excitation device is used to excite the target battery to vibrate, and then the target battery can be excited to vibrate under different states of charge.

[0052] Optionally, the state of charge of the target battery can be determined by methods such as current integration or open-circuit voltage method. This application does not limit the method for determining the state of charge of the target battery.

[0053] Optionally, the excitation device can be a vibrator, such as an electromagnetic vibrator or a hammer. An electromagnetic vibrator can generate a controllable and stable excitation force, while a hammer can flexibly strike the target battery.

[0054] S202, for each state of charge, receive the vibration signal sent by the acquisition device, and determine the modal parameters of the target battery based on the vibration signal.

[0055] Optionally, the acquisition device can be an accelerometer and a data acquisition system. The vibration signal can be vibration acceleration. The accelerometer can be placed on the surface of the target battery to measure the vibration acceleration of the target battery. The data acquisition system is connected to the accelerometer and can record the vibration signal acquired by the accelerometer.

[0056] Optionally, an accelerometer with appropriate sensitivity and range can be selected based on the size of the battery and the expected vibration frequency range. For example, for small batteries and high-frequency vibration testing, a sensor with high sensitivity and a small range is required; for large batteries and situations where large vibration amplitudes may occur, a sensor with a larger range is required.

[0057] Optionally, for each state of charge, the vibration signal of the target battery in that state of charge is acquired, and then the modal parameters of the target battery corresponding to that state of charge are determined.

[0058] Optionally, if the target battery consists of multiple batteries of the same model, the vibration signals of each battery can be acquired separately, the modal parameters can be determined separately, and each modal parameter can be processed. The processed result can be used as the modal parameters of the target battery. The processing can include verifying each modal parameter and taking the average or median of the data that meets the requirements.

[0059] Optionally, the target battery can be excited multiple times or at multiple locations to obtain multiple vibration signals. Then, the modal parameters corresponding to each vibration signal can be determined, and the multiple modal parameters can be processed to obtain the processed results as the modal parameters of the target battery.

[0060] Optionally, the modal parameters of the target cell may include one or more of the natural frequency, damping ratio, and mode shape.

[0061] In one possible approach, the modal parameters of the target battery can be determined by performing time-domain analysis on the vibration signal. For example, by obtaining the vibration amplitude and period of the vibration signal, the intensity and frequency of the vibration of the target battery under excitation can be determined. Alternatively, when the target battery is excited by pulse excitation, information such as the modal damping of the target battery can be obtained by analyzing the vibration signal.

[0062] In another possible approach, the modal parameters of the target battery can be determined by frequency domain analysis of the vibration signal. For example, the vibration signal can be Fourier transformed to obtain its spectrum, and the natural frequencies of the target battery can be determined based on the spectrum. Alternatively, the modal parameters of the battery can be determined by peak picking or least squares methods after frequency domain transformation.

[0063] S203, for each state of charge, determine the elastic parameters of the target battery under the state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

[0064] Optionally, the input to the identification model can be modal parameters, and the output can be elastic parameters. For each state of charge of the target battery, the modal parameters corresponding to that state of charge can be input into the identification model to determine the elastic parameters of the target battery under that state of charge.

[0065] Optionally, the identification model can be a pre-trained neural network model or a mathematical model, and the embodiments of this application do not limit it.

[0066] Optionally, Young's modulus can be a physical quantity describing a material's resistance to deformation, defined as the ratio of stress (force on a single area) to strain (the degree of deformation of the material) within the elastic limit; Poisson's ratio can be a proportional relationship describing the relationship between lateral contraction and axial tension of a material, defined as the ratio of the absolute values ​​of lateral strain to axial strain when the material is under uniaxial tension or compression.

[0067] The aforementioned elastic parameter identification method involves controlling an excitation device to stimulate vibration of the target battery under different states of charge. Then, for each state of charge, the method receives vibration signals from a data acquisition device and determines the modal parameters of the target battery based on these signals. Finally, for each state of charge, the method determines the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. These elastic parameters include Young's modulus and Poisson's ratio. In this way, by controlling the vibration of the target battery, modal parameters under different states of charge can be obtained, and Young's modulus and Poisson's ratio can be determined based on these modal parameters and the identification model. Unlike existing technologies that use compression or tensile tests, the method in this application reduces damage to the battery structure when determining elastic parameters. Furthermore, once the elastic parameters for different states of charge are determined, subsequent applications only require determining the state of charge of the target battery to obtain the corresponding elastic parameters.

[0068] In one exemplary embodiment, optionally, such as Figure 3 As shown, the modal parameters include the natural frequencies of each order. The elastic parameters of the target battery under the state of charge are determined based on the modal parameters and the identification model, including the following steps 301 to 302. Wherein:

[0069] S301, determine the first parameter based on the natural frequencies of each order.

[0070] The first parameter is at least one of the natural frequencies of each order.

[0071] Optionally, each natural frequency can be the frequency of free vibration of the target battery when there is no external damping. There can be multiple natural frequencies, such as the first natural frequency, the second natural frequency, and the third natural frequency.

[0072] Optionally, at least one of the natural frequencies can be selected as the first parameter.

[0073] S302, input the first parameter into the identification model, and determine the elastic parameters of the target battery under the state of charge based on the output of the identification model.

[0074] In one possible implementation, the first parameter can be any natural frequency. The identification model can include an equation with Young's modulus as a variable and an equation with Poisson's ratio as a variable. The physical parameters of the target battery can be obtained, such as mass, density, length of the target battery in the X direction, and length of the target battery in the Y direction. Then, the physical parameters are substituted into the equation with Young's modulus as a variable to determine Young's modulus. After determining Young's modulus, the physical parameters and Young's modulus are substituted into the equation with Poisson's ratio as a variable to determine Poisson's ratio. In the embodiments of this application, the specific forms of the equation with Young's modulus as a variable and the equation with Poisson's ratio as a variable are not limited.

[0075] In another possible implementation, such as Figure 4 As shown, the identification model is determined based on an equation with Young's modulus and Poisson's ratio as variables. The first parameter includes any two of the natural frequencies of each order. The first parameter is input into the identification model, and the elastic parameters of the target battery under the state of charge are determined based on the output of the identification model, including the following steps 401 to 404. Wherein:

[0076] S401, Obtain the physical parameters of the target battery.

[0077] The physical parameters include density, the length of the target battery in the X direction, and the length in the Y direction.

[0078] Alternatively, the equation with Young's modulus and Poisson's ratio as variables can be expressed by the following equation:

[0079]

[0080] Where E is Young's modulus, v is Poisson's ratio, and f is... ij These are the natural frequencies corresponding to different orders of the target battery. The vibration modes of the target battery are determined by i and j. That is, a combination of i and j corresponds to a vibration mode order. For example, the first-order natural frequency can be represented by f. 10 In this representation, ρ is the density, L and W are the length dimensions of the battery in the X and Y directions, and R is the density. x and R y Let be the radius of gyration of the thin rod with a rectangular cross-section, and P(i) and Q(j) be the roots of the following equation:

[0081] tan[ωL / (2V x )]=±tanh{ωL / (2V x )]

[0082] tan[ωL / (2V y )]=±tanh{ωL / (2V y )]

[0083] ωL / (2V x ) = P(i), i = 0, 1, 2, 3, ...,

[0084] ωL / (2V y ) = Q(j), j = 0, 1, 2, 3, ...,

[0085] Among them, V x V y ω is the equivalent sound velocity of the bending vibration of the thin rod, and ω is the angular frequency of the bending vibration of the thin rod.

[0086] It should be noted that the identification model can also be determined through other variations or equivalent equations of the above equations. In the above equations, the equivalent sound velocity, angular frequency and other physical quantities of the bending vibration of the thin rod are also predetermined. In the identification model, after inputting the first parameter into the above equations, two equations can be obtained, and then the elastic parameters can be determined.

[0087] S402, the first equation is determined by the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the third parameter, and the fourth parameter.

[0088] The second parameter is determined based on the physical parameters, and the third and fourth parameters are determined based on the physical parameters and the first natural frequency, where the first natural frequency is any one of the first parameters.

[0089] Optionally, the second parameter can be obtained through... The third parameter can be calculated through... The fourth parameter can be calculated through... In calculating the third and fourth parameters, the first natural frequency can be substituted into f. ij .

[0090] Alternatively, the first equation can be expressed in the following simplified form:

[0091] C1E+C2v 2 =C3

[0092] S403, the second equation is determined by the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the fifth parameter, and the sixth parameter.

[0093] Among them, the fifth and sixth parameters are determined based on the physical parameters and the second natural frequency, which is the other natural frequencies in the first parameter.

[0094] Optionally, the fifth parameter can be obtained through... The sixth parameter can be calculated through... In calculating the fifth and sixth parameters, the second natural frequency can be substituted into f. ij .

[0095] Alternatively, the second equation can be expressed in the following simplified form:

[0096] C1E+C4v 2 =C5

[0097] S404. Based on the first and second equations, determine Young's modulus and Poisson's ratio.

[0098] Optionally, a system of two equations can be formed based on the first and second equations, and Young's modulus and Poisson's ratio can be determined by solving the system of two equations.

[0099] Optionally, for each state of charge, a seventh parameter can be determined based on each natural frequency, and then the elastic parameters of the target battery in that state of charge can be determined based on the seventh parameter and the methods of steps 401 to 404. The seventh parameter is different from the natural frequency in the first parameter. For example, the first parameter may include the first natural frequency and the second natural frequency, and the seventh parameter may include the second natural frequency and the third natural frequency.

[0100] It is understood that, under a state of charge, the elastic parameters of the target battery determined by the first parameter and the seventh parameter should be the same. Therefore, the elastic parameters can be calculated using the first parameter and the seventh parameter respectively to verify the accuracy of the elastic parameter identification method provided in the embodiments of this application, thereby improving the accuracy of the elastic parameter identification method.

[0101] The above method determines the first parameter based on the natural frequencies of each order, inputs the first parameter into the identification model, and determines the elastic parameters of the target battery under the state of charge based on the output of the identification model. The elastic parameters of the target battery under the state of charge can be accurately determined by the identification model and the obtained natural frequencies of each order.

[0102] In one exemplary embodiment, optionally, the excitation device is a force hammer, and controlling the excitation device to excite vibration of the target battery under different states of charge of the target battery includes:

[0103] A control hammer strikes one or more points on the target battery to induce vibration in the target battery.

[0104] Optionally, the hammer can be connected to the controller via a mechanical device, which can be a robotic arm or a positioning clamp, etc.

[0105] Optionally, the controller can control the striking force of the hammer according to a preset force value, making the striking force controllable. Under the control of the controller, the mechanical device drives the hammer to strike the target device, which can cause the target battery to vibrate.

[0106] Optionally, by tapping the target battery at multiple points, various vibration modes of the target battery can be excited, resulting in richer vibration signals.

[0107] In one exemplary embodiment, optionally, such as Figure 5 As shown, the method of receiving vibration signals sent by the acquisition device and determining the modal parameters of the target battery based on the vibration signals includes the following steps 501 to 502.

[0108] in:

[0109] S501 performs preprocessing on the vibration signal.

[0110] Optionally, preprocessing the vibration signal can include noise reduction or data normalization, which can improve the accuracy of subsequent analysis. For example, noise in the vibration signal can be removed by wavelet denoising or adaptive denoising.

[0111] S502 performs frequency domain analysis on the preprocessed vibration signal and determines the modal parameters of the target battery based on the spectrum of the vibration signal.

[0112] Optionally, the vibration signal can be processed by Fast Fourier Transform to convert it into a frequency domain signal. In the spectrum of the target battery, the frequency corresponding to the peak is the natural frequency of the battery. Therefore, the natural frequencies of the target battery can be determined by the spectrum of the vibration signal.

[0113] In one exemplary embodiment, optionally, the elasticity parameter identification method further includes:

[0114] An elastic parameter mapping table is determined based on each state of charge and elastic parameter. The elastic parameter mapping table is used to store the correspondence between different states of charge and elastic parameters.

[0115] Optionally, after determining the elastic parameters of the target battery under different states of charge, an elastic parameter mapping table can be obtained. In subsequent applications, after determining the state of charge of the target battery, the Young's modulus and Poisson's ratio of the target battery can be quickly determined by querying the elastic parameter mapping table.

[0116] As an optional implementation method, such as Figure 6 As shown, the elastic parameter identification method provided in this application embodiment may include the following specific steps:

[0117] S601, under different states of charge of the target battery, controls the hammer to strike one or more parts of the target battery to excite the target battery to vibrate.

[0118] S602 receives vibration signals from the acquisition device for each state of charge and preprocesses the vibration signals.

[0119] S603, for each state of charge, performs frequency domain analysis on the preprocessed vibration signal, and determines the modal parameters of the target battery based on the spectrum of the vibration signal.

[0120] The modal parameters include the natural frequencies of each order.

[0121] S604 determines the first parameter for each state of charge based on the natural frequency of each order.

[0122] The first parameter includes any two of the natural frequencies of each order.

[0123] S605, obtain the physical parameters of the target battery.

[0124] The physical parameters include density, the length of the target battery in the X direction, and the length in the Y direction.

[0125] S606, the first equation for each charged state is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the third parameter, and the fourth parameter.

[0126] The second parameter is determined based on the physical parameters, and the third and fourth parameters are determined based on the physical parameters and the first natural frequency, where the first natural frequency is any one of the first parameters.

[0127] S607, the second equation for each charged state is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the fifth parameter, and the sixth parameter.

[0128] Among them, the fifth and sixth parameters are determined based on the physical parameters and the second natural frequency, which is the other natural frequencies in the first parameter.

[0129] S608, for each state of charge, determine the elastic parameters according to the first equation and the second equation.

[0130] Among them, the elastic parameters include Young's modulus and Poisson's ratio.

[0131] S609, determine the elastic parameter mapping table based on each state of charge and elastic parameters.

[0132] The elastic parameter mapping table is used to store the correspondence between different states of charge and elastic parameters.

[0133] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0134] Based on the same inventive concept, this application also provides an elastic parameter identification device for implementing the elastic parameter identification method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more elastic parameter identification device embodiments provided below can be found in the limitations of the elastic parameter identification method described above, and will not be repeated here.

[0135] In one exemplary embodiment, such as Figure 7 As shown, an elastic parameter identification device is provided, including: an excitation module 701, a receiving module 702, and an identification module 703, wherein:

[0136] The excitation module 701 is used to control the excitation device to excite the target battery to vibrate under different states of charge of the target battery.

[0137] The receiving module 702 is used to receive vibration signals sent by the acquisition device for each state of charge, and determine the modal parameters of the target battery based on the vibration signals.

[0138] The identification module 703 is used to determine the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

[0139] In an exemplary embodiment, the modal parameters include natural frequencies of each order. The identification module 703 is specifically used to determine a first parameter based on the natural frequencies of each order, wherein the first parameter is at least one of the natural frequencies of each order; input the first parameter into the identification model; and determine the elastic parameters of the target battery under the state of charge based on the output of the identification model.

[0140] In an exemplary embodiment, the identification model is determined based on an equation with Young's modulus and Poisson's ratio as variables. The first parameter includes any two of the natural frequencies of each order. The identification module 703 is specifically used to acquire the physical parameters of the target battery, including density, length dimension of the target battery in the X direction, and length dimension in the Y direction. The first equation is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the third parameter, and the fourth parameter. The second parameter is determined based on the physical parameters. The third and fourth parameters are determined based on the physical parameters and the first natural frequency, where the first natural frequency is any one of the first parameters. The second equation is determined based on the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the fifth parameter, and the sixth parameter. The fifth and sixth parameters are determined based on the physical parameters and the second natural frequency, where the second natural frequency is any of the other natural frequencies of the first parameters. The Young's modulus and Poisson's ratio are determined based on the first and second equations.

[0141] In an exemplary embodiment, the excitation device is a hammer, and the excitation module 701 is specifically used to control the hammer to strike one or more parts of the target battery to excite the target battery to vibrate.

[0142] In an exemplary embodiment, the receiving module 702 is specifically used to preprocess the vibration signal; perform frequency domain analysis on the preprocessed vibration signal, and determine the modal parameters of the target battery based on the spectrum of the vibration signal.

[0143] In an exemplary embodiment, the identification module 703 is further configured to determine an elastic parameter mapping table based on each state of charge and elastic parameter, wherein the elastic parameter mapping table is used to store the correspondence between different states of charge and elastic parameters.

[0144] Each module in the aforementioned elastic parameter identification device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0145] In one exemplary embodiment, a computer device is provided, which may be a computer, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a flexible parameter identification method.

[0146] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0147] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps described in any of the above method embodiments.

[0148] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps described in any of the above method embodiments.

[0149] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps described in any of the above method embodiments.

[0150] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0152] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for identifying elastic parameters, characterized in that, In a control device for an elastic parameter identification system, the elastic parameter identification system includes a control device, a data acquisition device, and an excitation device. The control device is connected to both the excitation device and the data acquisition device. The excitation device is used to excite the target battery to vibrate under the control of the control device. The method includes: Under different states of charge of the target battery, the excitation device is controlled to excite the target battery to vibrate; For each of the stated states of charge, the vibration signal sent by the acquisition device is received, and the modal parameters of the target battery are determined based on the vibration signal; For each of the stated states of charge, the elastic parameters of the target battery under the stated states of charge are determined based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

2. The method according to claim 1, characterized in that, The modal parameters include natural frequencies of each order. Determining the elastic parameters of the target battery under the state of charge based on the modal parameters and the identification model includes: Based on the natural frequencies of each order, a first parameter is determined, wherein the first parameter is at least one of the natural frequencies of each order; The first parameter is input into the identification model, and the elastic parameter of the target battery under the state of charge is determined based on the output of the identification model.

3. The method according to claim 2, characterized in that, The identification model is determined based on an equation with Young's modulus and Poisson's ratio as variables. The first parameter includes any two of the natural frequencies. The step of inputting the first parameter into the identification model and determining the elastic parameters of the target battery under the state of charge based on the output of the identification model includes: Obtain the physical parameters of the target battery, including density, length of the target battery in the X direction, and length of the target battery in the Y direction; The first equation is determined by the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the third parameter, and the fourth parameter. The second parameter is determined based on the physical parameter. The third and fourth parameters are determined based on the physical parameter and the first natural frequency. The first natural frequency is any one of the first parameters. The second equation is determined by the product of Young's modulus and the second parameter, the product of the square of Poisson's ratio and the fifth parameter, and the sixth parameter. The fifth parameter and the sixth parameter are determined based on the physical parameter and the second natural frequency. The second natural frequency is the other natural frequencies in the first parameter. The Young's modulus and the Poisson's ratio are determined based on the first equation and the second equation.

4. The method according to claim 1, characterized in that, The excitation device is a force hammer, and controlling the excitation device to excite the target battery to vibrate under different states of charge of the target battery includes: The hammer is controlled to strike one or more points on the target battery to induce vibration in the target battery.

5. The method according to claim 2, characterized in that, Receiving vibration signals sent by the acquisition device and determining the modal parameters of the target battery based on the vibration signals includes: The vibration signal is preprocessed; Frequency domain analysis is performed on the preprocessed vibration signal, and the modal parameters of the target battery are determined based on the spectrum of the vibration signal.

6. The method according to claim 1, characterized in that, The method further includes: An elastic parameter mapping table is determined based on each of the stated states of charge and the stated elastic parameters. The elastic parameter mapping table is used to store the correspondence between different states of charge and elastic parameters.

7. An elastic parameter identification device, characterized in that, The elastic parameter identification system is configured in a control device, which includes a control device, a data acquisition device, and an excitation device. The control device is connected to both the excitation device and the data acquisition device. The excitation device is used to excite the target battery to vibrate under the control of the control device. The device includes: An excitation module is used to control the excitation device to excite the target battery to vibrate under different states of charge of the target battery; A receiving module is used to receive vibration signals sent by the acquisition device for each of the states of charge, and to determine the modal parameters of the target battery based on the vibration signals. The identification module is used to determine the elastic parameters of the target battery under each state of charge based on the modal parameters and the identification model. The elastic parameters include Young's modulus and Poisson's ratio.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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