A method, device and equipment for calculating the tortuosity of a battery pole piece and a storage medium

Abstract

The application provides a battery pole piece tortuosity calculation method, device, equipment and storage medium, which comprises the following steps: obtaining the compaction density of a battery pole piece; and obtaining the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density. Since the tortuosity of the battery pole piece is directly calculated according to the compaction density of the battery, and the compaction density of the battery is relatively easier to obtain, such as being directly obtained through the specification parameters of the battery or being measured through a mature and fast detection method, the tortuosity of the battery pole piece under the compaction density can be quickly obtained, and finally, the relevant physical performance of the battery pole piece can be evaluated according to the obtained tortuosity.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery pole piece processing, and particularly relates to a battery pole piece tortuosity calculation method, device, equipment and storage medium. BACKGROUND

[0002] With the increase of battery energy density, the compaction density and thickness of the battery pole piece are gradually increased. However, the higher compaction density and thickness will cause the tortuosity of the battery pole piece to increase, causing the metal ion diffusion in the porous electrode to be difficult, thereby limiting the fast charging performance of the battery.

[0003] In the related art, when calculating the tortuosity of the battery pole piece, the surface and cross-sectional morphology of the battery pole piece is generally obtained by a focused ion beam-scanning electron microscope (FIB-SEM), professional software is used to 3D reconstruct the pictures and manually count the active particles, and then the tortuosity value is further calculated. The device cost is high and the time is long, and the battery pole piece tortuosity and the fast charging performance of the corresponding battery cannot be conveniently and quickly evaluated. SUMMARY

[0004] The main purpose of the present application is to provide a battery pole piece tortuosity calculation method, device, equipment and storage medium, which aims to solve the problem of complicated and time-consuming calculation of battery pole piece tortuosity and high cost in the related art.

[0005] In a first aspect, the present application provides a battery pole piece tortuosity calculation method, which adopts the following technical scheme:

[0006] A battery pole piece tortuosity calculation method, comprising:

[0007] Obtaining the compaction density of the battery pole piece;

[0008] According to the compaction density, the tortuosity of the battery pole piece corresponding to the compaction density is obtained.

[0009] In some embodiments, the step of obtaining the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density comprises the following steps:

[0010] According to a preset calculation model about the compaction density and the tortuosity, the tortuosity of the battery pole piece under the compaction density is calculated; wherein, the calculation model is obtained according to a first model about the compaction density of the battery pole piece and the pore channel inclination angle of the battery pole piece, and a second model about the pore channel inclination angle and the tortuosity, and the pore channel inclination angle is obtained according to the acute angle side included angle formed by the long axis of each particle structure in the battery pole piece and the vertical direction of the thickness direction of the battery pole piece.

[0011] In some embodiments, the first model is obtained according to a plurality of sets of pore channel inclination angle data corresponding to battery pole pieces under different compaction densities, wherein the set of pore channel inclination angle data comprises at least part of the pore channel inclination angles obtained by the battery pole piece under a compaction density.

[0012] In some embodiments, the first model is obtained according to a plurality of sets of pore channel inclination angle data corresponding to battery pole pieces under different compaction densities, comprising the following steps:

[0013] obtaining a plurality of sets of pore channel inclination angle data corresponding to battery pole pieces under different compaction densities, wherein the set of pore channel inclination angle data comprises all pore channel inclination angles of the battery pole piece under a compaction density;

[0014] obtaining a plurality of sets of pore channel inclination angle data corresponding to battery pole pieces under different compaction densities, wherein the set of pore channel inclination angle data comprises all pore channel inclination angles of the battery pole piece under a compaction density;

[0015] establishing a linear or nonlinear first model according to a plurality of compaction densities and the corresponding inclination angle characteristic values.

[0016] In some embodiments, the obtaining a plurality of sets of pore channel inclination angle data corresponding to battery pole pieces under different compaction densities comprises the following steps:

[0017] counting the pore channel inclination angles of all particle structures in the battery pole piece as the candidate inclination angle data of the corresponding battery pole piece;

[0018] In the candidate inclination angle data set, the pore channel inclination angles between the set angle ranges are selected as the effective inclination angles, and the set of pore channel inclination angle data is established and used for subsequent tortuosity calculation.

[0019] In some embodiments, the obtaining the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density comprises the following steps:

[0020] obtaining the tortuosity corresponding to the compaction density according to a preset mapping model of the compaction density and the tortuosity.

[0021] In some embodiments, the mapping model is obtained according to a plurality of standard tortuosities measured by battery pole pieces under different compaction densities, and the standard tortuosity is obtained according to a plurality of tortuosities measured by a set number of battery pole pieces under the same compaction density.

[0022] In a second aspect, the present application also provides a calculation device for the tortuosity of a battery pole piece, which adopts the following technical scheme:

[0023] A calculation device for the tortuosity of a battery pole piece, comprising:

[0024] an acquisition module configured to acquire a compaction density of a battery electrode sheet;

[0025] a calculation module configured to obtain, according to the compaction density, a tortuosity of the battery electrode sheet corresponding to the compaction density.

[0026] In a third aspect, the present application further provides a battery electrode sheet tortuosity calculation device, which adopts the following technical solution:

[0027] A battery electrode sheet tortuosity calculation device, comprising a processor, a memory, and a battery electrode sheet tortuosity calculation program stored in the memory and executable by the processor, wherein the battery electrode sheet tortuosity calculation program, when executed by the processor, implements the steps of the battery electrode sheet tortuosity calculation method as described above.

[0028] In a fourth aspect, the present application further provides a storage medium, which adopts the following technical solution:

[0029] A storage medium, wherein the storage medium stores a battery electrode sheet tortuosity calculation program, and the battery electrode sheet tortuosity calculation program, when executed by a processor, implements the steps of the battery electrode sheet tortuosity calculation method as described above.

[0030] The battery electrode sheet tortuosity calculation method, device, equipment and storage medium provided by the present application directly calculate the tortuosity of the battery electrode sheet according to the compaction density of the battery, and the compaction density of the battery is relatively easier to obtain, such as being directly obtained from the specification parameters of the battery or being measured by a mature and fast detection method, so that the tortuosity of the battery electrode sheet under the compaction density is quickly obtained, and finally the relevant physical performance of the battery electrode sheet can be evaluated according to the obtained tortuosity. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 A hardware structure diagram of the battery electrode sheet tortuosity calculation device involved in the embodiment scheme of the present application;

[0032] Figure 2 A metal ion transmission microcosmic model of the battery electrode sheet in the embodiment scheme of the present application;

[0033] Figure 3 1.50 g / cm 3 Statistical histogram of the θ angle under the compaction density and fitted probability density function curve;

[0034] Figure 4 1.60 g / cm 3 Statistical histogram of the θ angle under the compaction density and fitted probability density function curve;

[0035] Figure 5 1.70 g / cm 3 Statistical histogram of the theta angle under the compaction density and the fitted probability density function curve;

[0036] Figure 6 A specific function relationship diagram between the negative compaction density and the theta angle of the graphite negative electrode material in an embodiment of the present application;

[0037] Figure 7 A schematic table of the estimated and measured values of the tortuosity of the battery electrode sheet under partial compaction density obtained by the embodiment of the present application.

[0038] The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0039] It should be understood that the specific embodiments described herein are merely intended to explain the present application and are not intended to limit the present application.

[0040] With the increase of the energy density of the battery, the compaction density and the thickness of the battery electrode sheet are gradually increased. However, the higher compaction density and thickness will cause the tortuosity of the battery electrode sheet to increase, causing the metal ion diffusion in the porous electrode to be difficult, thereby limiting the fast charging performance of the battery. In the related art, when calculating the tortuosity of the battery electrode sheet, the surface and cross-sectional morphology of the battery electrode sheet is generally obtained by a focused ion beam-scanning electron microscope (FIB-SEM), the pictures are 3D reconstructed by using professional software and the active particles therein are manually counted, and then the tortuosity value is further calculated. The device cost is high and the time is long, and the battery electrode sheet tortuosity and the fast charging performance of the corresponding battery cannot be conveniently and quickly evaluated. Therefore, the present application provides a battery electrode sheet tortuosity calculation method, device, equipment and storage medium to solve the above problems.

[0041] The method, device, equipment and storage medium for calculating the tortuosity of a battery pole piece provided by the present application have the following technical points: the compaction density of the battery pole piece is obtained, and the tortuosity of the battery pole piece is calculated according to the compaction density. It can be understood that the present application establishes a corresponding relationship between the compaction density and the tortuosity, and the corresponding relationship between the two may be different in different embodiments. For example, in some embodiments, the compaction density and the tortuosity of the battery pole piece are directly mapped according to the compaction density and the tortuosity data of the battery pole piece in a certain sample order by using artificial intelligence, forming an empirical mapping model. For another example, the calculation of the tortuosity is realized according to the physical parameters having a certain correlation between the compaction density and the tortuosity, that is, the compaction density and the tortuosity calculation model are established by using the physical parameters having the correlation, forming a calculation model of the tortuosity of the compaction density. Finally, in the process of calculating the tortuosity such as battery fast charging performance evaluation, the direct detection of the tortuosity can be converted into the acquisition of the compaction density, and the tortuosity of the battery pole piece can be calculated more simply and quickly.

[0042] In a first aspect, an embodiment of the present application provides a battery pole piece tortuosity calculation device. The battery pole piece tortuosity calculation device can be a personal computer (PC), a notebook computer, a server, or other device having a data processing function.

[0043] Reference Figure 1 , Figure 1 FIG. 1 is a schematic diagram of the hardware structure of the battery pole piece tortuosity calculation device according to an embodiment of the present application. In the embodiment of the present application, the battery pole piece tortuosity calculation device can include a processor 1001 (for example, a central processing unit (CPU)), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display and an input unit such as a keyboard. The network interface 1004 can optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WI-FI) interface). The memory 1005 can be a high-speed random access memory (RAM) or a stable memory (non-volatile memory) such as a disk memory. The memory 1005 can optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art can understand that the battery pole piece tortuosity calculation device can further include other components necessary for the device to operate, and the components are not described in detail in the present application. Figure 1The hardware structure shown in the foregoing embodiments is not a limitation on the present application, and can include more or fewer components, or combine certain components, or arrange different components.

[0044] With reference to the foregoing Figure 1 , Figure 1 The memory 1005 in the foregoing embodiments can include an operating system, a network communication module, a user interface module, and a battery pole piece tortuosity calculation program. The processor 1001 can invoke the battery pole piece tortuosity calculation program stored in the memory 1005 and execute the battery pole piece tortuosity calculation method provided by the embodiments of the present application.

[0045] In a second aspect, the embodiments of the present application provide a battery pole piece tortuosity calculation method.

[0046] A battery pole piece tortuosity calculation method includes:

[0047] S100, obtaining a compaction density of a battery pole piece;

[0048] S200, obtaining a tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density.

[0049] Specifically, for step S200, it can be understood that the tortuosity is calculated by first establishing a corresponding relationship between the compaction density and the tortuosity. The corresponding relationship between the two can be different in different embodiments. For example, in some embodiments, a direct mapping relationship between the compaction density and the tortuosity can be established by using artificial intelligence according to the compaction density and the tortuosity data of the battery pole piece in a large sample order, forming an empirical mapping model. For another example, the calculation of the tortuosity is realized according to the physical parameters having a certain correlation between the compaction density and the tortuosity, that is, the establishment of the compaction density and the tortuosity calculation model is realized by the physical parameters having the correlation, forming a calculation model of the tortuosity with respect to the compaction density.

[0050] In this way, in the process of calculating the tortuosity such as battery fast charging performance evaluation, the direct detection of the tortuosity can be converted into the acquisition of the compaction density, and finally the tortuosity of the battery pole piece can be calculated more simply and quickly.

[0051] Further, in some preferred embodiments, step S200, obtaining the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density, includes the following steps:

[0052] According to a preset calculation model about the compaction density and the tortuosity, the tortuosity of the battery pole piece under the compaction density is calculated; wherein the calculation model is obtained according to a first model about the compaction density of the battery pole piece and the inclined angle of the pore channel of the battery pole piece, and a second model about the inclined angle of the pore channel of the battery pole piece and the tortuosity.

[0053] Specifically, referring to Figure 2 The first model used when establishing the calculation model about the compaction density and the tortuosity is specifically the physical connection between the compaction density of the battery pole piece and the inclined angle of the pore channel of the battery pole piece, wherein the inclined angle of the pore channel of the battery pole piece is specifically the acute angle side included angle θ between the long axis of the particle structure in the battery pole piece and the vertical direction of the thickness direction of the pole piece. It can be seen that when the compaction density is greater, the thickness of the battery pole piece is smaller, the deflection angle between the long axis direction of the particle structure in the battery pole piece and the vertical direction of the thickness direction of the battery pole piece is smaller, that is, the inclined angle of the pore channel is smaller.

[0054] At the same time, since the standard definition of tortuosity is τ = (L / d) 2 Wherein L is the diffusion length of the pore channel, d is the thickness of the battery pole piece, and d / L is according to Figure 2 It can be seen that it is sinθ, and then the second model about the inclined angle of the pore channel and the tortuosity can be further obtained:

[0055]

[0056] Further, it can be seen that after the first model is established, it can be substituted into the second model to obtain the calculation model about the compaction density and the tortuosity, so that the tortuosity of the battery pole piece can be reflected after the compaction density of the battery pole piece is known, the detection difficulty is effectively reduced, and the accuracy of the calculated tortuosity is more accurate.

[0057] Further, in some preferred embodiments, the first model is obtained according to a plurality of pore channel inclined angle data sets corresponding to the battery pole piece under different compaction densities; wherein the pore channel inclined angle data set includes at least part of the pore channel inclined angle obtained by the battery pole piece under a compaction density.

[0058] The first model about the compaction density and the pore channel inclination angle is fitted by the pore channel inclination angles of the battery pole piece under the selected compaction densities. It is worth noting that the proportion of the selected data in the inclination angle dataset can be different in different embodiments. For example, all the pore channel inclination angles of the battery pole piece under each compaction density are selected as the fitting data. For another example, part of the pore channel inclination angles of the battery pole piece under each compaction density are selected as the fitting data. In the embodiment of selecting part of the pore channel inclination angle data, the selection can be made according to the needs of the detection personnel, such as selecting the pore channel inclination angle data after removing the maximum 10% and the minimum 10% as the fitting data, which is not limited in the present application.

[0059] Further, in some preferred embodiments, the first model is obtained according to the pore channel inclination angle dataset corresponding to the battery pole piece under a plurality of different compaction densities, including the following steps:

[0060] F100, obtaining a plurality of pore channel inclination angle datasets corresponding to the battery pole piece under different compaction densities; wherein the pore channel inclination angle dataset includes all the pore channel inclination angles of the battery pole piece under a compaction density;

[0061] F200, obtaining the inclination angle characteristic value corresponding to the battery pole piece under each compaction density according to the pore channel inclination angle dataset; the inclination angle characteristic value is the mean value, the median value, the mode value or the set function value of the pore channel inclination angle dataset; wherein the set function for calculating the set function value can be established by the technical personnel according to the needs.

[0062] F300, establishing a linear or nonlinear first model according to a plurality of compaction densities and the respective inclination angle characteristic values.

[0063] Further, in step F100, the calibration method for the pore channel inclination angle of the battery pole piece specifically includes the following steps in some preferred embodiments:

[0064] F110, manually selecting and confirming all the particle structures in the battery pole piece and counting;

[0065] F120, identifying the long axis of the particle structure in the battery pole piece;

[0066] F130, translating the long axis of the particle structure in the short axis direction of the particle structure until it is tangent to the outermost edge of the particle structure;

[0067] F140, calculating the acute angle between the long axis of all the particle structures in F130 after translation and the vertical direction of the thickness direction of the battery pole piece as the alternative inclination angle data corresponding to the battery pole piece.

[0068] F150. In the candidate tilt angle dataset, select the pore channel tilt angle within a set angle range as the effective tilt angle. In this embodiment, the set angle range is preferably 45-70°. Establish the pore channel tilt angle dataset and use it for subsequent tortuosity calculation.

[0069] Corresponding to the steps of establishing the first model described above, the embodiments of this application specifically disclose a concentration of 1.50 g / cm³. 3 1.60g / cm 3 and 1.7g / cm 3 Method for establishing the first model of graphite negative electrode sheet under compaction density:

[0070] Corresponding to step F100 above, specifically by collecting and organizing cross-sectional SEM images of graphite negative electrode sheets under multiple compaction densities, this embodiment specifically uses 1.50 g / cm³. 3 1.60g / cm 3 and 1.7g / cm 3 Cross-sectional SEM images of graphite negative electrode sheets under compaction density were used to mark the voids in the electrode sheets within each cross-sectional SEM image. The candidate tilt angle data of each battery electrode sheet under each compaction density were statistically obtained, and the effective tilt angle was selected from them. A pore channel tilt angle dataset was then established using the effective tilt angle.

[0071] Corresponding to step F200 above, hypothesis testing (e.g., the Kolmogorov-Smirnov test) is used to verify the data distribution type of the pore channel tilt angle θ within the pore channel tilt angle dataset. The probability density functions of data distributions such as normal distribution and Weibull distribution are used to describe the statistical value of the pore channel tilt angle θ. The mean of the pore channel tilt angle θ in the pore channel tilt angle dataset is used as the tilt angle characteristic value under the corresponding negative extreme compaction density. For example... Figure 3 , 4 Figures 5 and 6 respectively show the statistical histograms of the pore channel inclination angle θ and the fitted probability density function curves at compaction densities of 1.50 g / cm3, 1.60 g / cm3 and 1.7 g / cm3;

[0072] Corresponding to step F300 above, specifically using the least squares method, a linear fit is performed on the tilt angle characteristic value data at compaction densities of 1.50 g / cm³, 1.60 g / cm³, and 1.7 g / cm³ regarding the compaction density and tilt angle characteristic value, to obtain a linear functional relationship between compaction density (x) and pore channel tilt angle θ (y) (e.g.) Figure 6 ):

[0073] y = -64.329x + 156.44, R 2 =0.9704.

[0074] In addition, the tilt angle characteristic value involved in step F200 is preferably the mean value of the tilt angles of all the pore channels in the above-mentioned embodiments, but can be other arithmetic values obtained from the tilt angles of all the pore channels in other embodiments, such as a median value, a mode value or a set function value; wherein the set function for calculating the set function value can be established by the skilled person according to the actual error, which is not limited herein.

[0075] Referring to Figure 7 For the specific examples of the present application, the results of the tortuosity obtained by the calculation model under some compaction densities, and the measured results of the tortuosity under the same compaction densities are given. It can be seen that the calculated tortuosity and the measured tortuosity are within a reasonable error range, and thus the calculation of the battery pole piece tortuosity provided by the above-mentioned embodiments of the present application can quickly and relatively accurately obtain the tortuosity that can be used smoothly according to the compaction density.

[0076] In addition, in other embodiments, step S200, obtaining the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density, comprises the following steps:

[0077] S210, obtaining the tortuosity corresponding to the compaction density according to a preset mapping model about the compaction density and the tortuosity.

[0078] It can be understood that, unlike the aforementioned type of embodiment, this type of embodiment directly establishes a mapping model of the compaction density and the tortuosity, and then realizes the corresponding relationship between the two without exploring the physical property relationship or the transition physical parameter between the two. For example, the empirical relationship between the two can be obtained through the continuous learning of artificial intelligence for large sample data. Therefore, in the process of establishing the mapping model in this type of embodiment, the tortuosity of the battery pole piece under the corresponding compaction density still needs to be measured in advance, and then the relationship between the two is established.

[0079] Specifically, the mapping model is obtained according to the standard tortuosity of the battery pole piece measured under a plurality of different compaction densities, and the standard tortuosity is obtained according to the tortuosity measured by a set number of battery pole pieces under the same compaction density.

[0080] Wherein, different battery pole pieces under the same compaction density can have different tortuosity, therefore, by selecting the tortuosity measured by a set number of battery pole pieces, the accuracy of the final obtained standard tortuosity value is guaranteed. Specifically, it can be the mean value of different tortuosity under the same compaction density, etc., which is not limited in the present embodiment.

[0081] Thirdly, the present application also provides a battery pole piece tortuosity calculation device.

[0082] In the embodiment, the device for calculating the tortuosity of the battery pole piece comprises:

[0083] an acquisition module configured to acquire the compaction density of the battery pole piece;

[0084] a calculation module configured to obtain the tortuosity of the battery pole piece corresponding to the compaction density according to the compaction density.

[0085] In the device for calculating the tortuosity of the battery pole piece, the functions of each module correspond to the steps in the method for calculating the tortuosity of the battery pole piece, and the functions and implementation processes will not be described here.

[0086] In a fourth aspect, the embodiment of the present application further provides a storage medium.

[0087] The storage medium of the present application stores a program for calculating the tortuosity of the battery pole piece, wherein the program for calculating the tortuosity of the battery pole piece is executed by a processor to realize the steps of the method for calculating the tortuosity of the battery pole piece.

[0088] The method realized by the program for calculating the tortuosity of the battery pole piece can refer to each embodiment of the method for calculating the tortuosity of the battery pole piece of the present application, and will not be described here.

[0089] It should be noted that in this document, the terms "comprising", "containing" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or system. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or system including the element.

[0090] The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0091] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for making a terminal device execute the method described in each embodiment of the present application.

[0092] The above merely describes the preferred embodiments of the present application, and is not intended to limit the patent scope of the present application, and any equivalent structure or equivalent process conversion, or direct or indirect application in other related technical fields, which are made by using the content of the present application specification and drawings, are also included in the patent protection scope of the present application.

Claims

1. A method for calculating the tortuosity of battery electrode sheets, characterized in that, It includes: Obtain the compaction density of the battery electrode sheets; Based on the compaction density, the tortuosity of the battery electrode corresponding to the compaction density is obtained; The step of obtaining the tortuosity of the battery electrode corresponding to the compaction density includes the following steps: calculating the tortuosity of the battery electrode at the compaction density according to a preset calculation model of compaction density and tortuosity; wherein, the calculation model is obtained based on a first model of the compaction density of the battery electrode and the tilt angle of the pore channels of the battery electrode, and a second model of the tilt angle of the pore channels of the battery electrode and tortuosity, and the tilt angle of the pore channels is obtained based on the acute angle formed by the long axis of each particle structure in the battery electrode and the perpendicular direction of the thickness direction of the battery electrode; The first model is specifically obtained based on a dataset of pore channel tilt angles corresponding to battery electrodes under multiple different compaction densities, and includes the following steps: A dataset of pore channel tilt angles corresponding to battery electrodes under multiple different compaction densities is obtained; wherein, the dataset of pore channel tilt angles includes at least a portion of the pore channel tilt angles of the battery electrodes under a certain compaction density; The tilt angle feature values ​​of the battery electrode at various compaction densities are obtained based on the pore channel tilt angle dataset; the tilt angle feature values ​​are the mean, median, mode, or a set function value of the pore channel tilt angle dataset. A first linear or nonlinear model is established based on multiple compaction densities and their corresponding tilt angle characteristic values.

2. The method for calculating the tortuosity of battery electrode sheets as described in claim 1, characterized in that, The pore channel tilt angle dataset includes all pore channel tilt angles of the battery electrode at a compaction density.

3. The method for calculating the tortuosity of battery electrode sheets as described in claim 2, characterized in that, The process of obtaining a dataset of pore channel tilt angles corresponding to multiple battery electrode sheets with different compaction densities includes the following steps: The tilt angles of the pore channels in all particle structures of the battery electrode are statistically analyzed and used as candidate tilt angle data for the corresponding battery electrode. In the candidate tilt angle dataset, the tilt angle of the pore channel within a set angle range is selected as the effective tilt angle, and a pore channel tilt angle dataset is established for subsequent tortuosity calculation.

4. The method for calculating the tortuosity of battery electrode sheets as described in claim 1, characterized in that, The step of obtaining the tortuosity of the battery electrode corresponding to the compaction density further includes the following steps: Based on a pre-defined mapping model of compaction density and tortuosity, the tortuosity corresponding to the compaction density is obtained.

5. The method for calculating the tortuosity of battery electrode sheets as described in claim 4, characterized in that, The mapping model is obtained based on the standard tortuosity measured by battery electrodes under multiple different compaction densities. The standard tortuosity is obtained based on the tortuosity measured by a set number of battery electrodes under the same compaction density.

6. A device for calculating the tortuosity of battery electrode sheets, characterized in that, It includes: The acquisition module is configured to acquire the compaction density of the battery electrode sheets; A calculation module is configured to obtain the tortuosity of the battery electrode corresponding to the compaction density based on the compaction density; The step of obtaining the tortuosity of the battery electrode corresponding to the compaction density further includes: calculating the tortuosity of the battery electrode at the compaction density according to a preset calculation model of compaction density and tortuosity; wherein, the calculation model is obtained based on a first model of the compaction density of the battery electrode and the tilt angle of the pore channels of the battery electrode, and a second model of the tilt angle of the pore channels of the battery electrode and tortuosity, and the tilt angle of the pore channels is obtained based on the acute angle formed by the long axis of each particle structure in the battery electrode and the perpendicular direction of the thickness direction of the battery electrode; The first model is specifically obtained based on a dataset of pore channel tilt angles corresponding to battery electrodes under multiple different compaction densities, and further includes: A dataset of pore channel tilt angles corresponding to battery electrodes under multiple different compaction densities is obtained; wherein, the dataset of pore channel tilt angles includes at least a portion of the pore channel tilt angles of the battery electrodes under a certain compaction density; The tilt angle feature values ​​of the battery electrode at various compaction densities are obtained based on the pore channel tilt angle dataset; the tilt angle feature values ​​are the mean, median, mode, or a set function value of the pore channel tilt angle dataset. A first linear or nonlinear model is established based on multiple compaction densities and their corresponding tilt angle characteristic values.

7. A device for calculating the tortuosity of battery electrode sheets, characterized in that, The device for calculating the tortuosity of the battery electrode includes a processor, a memory, and a program for calculating the tortuosity of the battery electrode stored in the memory and executable by the processor, wherein when the program for calculating the tortuosity of the battery electrode is executed by the processor, the steps of the method for calculating the tortuosity of the battery electrode as described in any one of claims 1 to 5 are implemented.

8. A storage medium, characterized in that, The storage medium stores a calculation program for the tortuosity of battery electrodes, wherein when the calculation program for the tortuosity of battery electrodes is executed by a processor, the steps of the method for calculating the tortuosity of battery electrodes as described in any one of claims 1 to 5 are implemented.

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