A method, apparatus, device and medium for processing electrode particle stacks

Abstract

The application provides a kind of electrode particle stack processing method, device, equipment and medium, comprising: based on the preset electrode size data, the two-dimensional model of the electrode is constructed;According to the electrode size data, the characteristic data of the electrode internal particle is obtained, the characteristic data includes quantity data and radius data;Based on the characteristic data, a plurality of particle units are constructed in the two-dimensional model, and the coordinate data of the particle unit is obtained;In the two-dimensional model, the area where the particle unit is located is created as a filled area, the remaining area is created as a blank area, the area data of the filled area and the blank area is obtained, and the actual density ratio of the two-dimensional model is calculated.A kind of electrode particle stack processing method, device, equipment and medium disclosed by the application can control the degree of overlap and porosity of particles.

Description

Technical Field

[0001] This invention relates to the field of electrode particle modeling technology, and in particular to a method, apparatus, device, and medium for processing stacked electrode particles. Background Technology

[0002] The electrode is composed of near-spherical particles of varying sizes. The particle ratio within the electrode affects not only the compaction density but also its electrochemical performance. An electrode particle model can be established based on the particle distribution density, allowing for better analysis of the electrode's compaction density and electrochemical performance.

[0003] In existing electrode particle models, the degree of overlap between particles is difficult to control when they are stacked, and the electrode density ratio of the stacked model deviates from the particle density ratio of the actual electrode. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a method, apparatus, device and medium for processing electrode particle stacking, which can control the overlap and density ratio of the particles.

[0005] In a first aspect, the present invention provides a method for processing stacked electrode particles, comprising:

[0006] A two-dimensional model of the electrode is constructed based on the preset electrode size data;

[0007] Based on the electrode size data, the characteristic data of the particles inside the electrode are obtained, including quantity data and radius data;

[0008] Based on the feature data, multiple particle units are constructed within the two-dimensional model, and the coordinate data of the particle units are obtained;

[0009] Within the two-dimensional model, the area where the particle unit is located is created as a filled area, and the remaining areas are created as blank areas. The area data of the filled area and the blank area are obtained, and the actual density ratio of the two-dimensional model is calculated.

[0010] The overlap of the particle units is obtained based on the actual density ratio and the preset target electrode density ratio.

[0011] Determine whether the overlap is greater than a preset overlap threshold. If the overlap is greater than the overlap threshold, update the coordinate data of the particle unit and recalculate the overlap.

[0012] When the overlap is not greater than the overlap threshold, the coordinate data of the particle unit is obtained.

[0013] The coordinate data are aggregated to generate coordinate cluster data.

[0014] Secondly, a processing apparatus for stacking electrode particles is provided, comprising:

[0015] The generation module is used to construct a two-dimensional model of the electrode based on preset electrode size data;

[0016] The acquisition module is used to acquire characteristic data of the particles inside the electrode based on the electrode size data, the characteristic data including quantity data and radius data;

[0017] A construction module is used to construct multiple particle units within the two-dimensional model based on the feature data, and to obtain the coordinate data of the particle units;

[0018] The processing module is used to create a filled area where the particle unit is located within the two-dimensional model, create blank areas for the remaining areas, obtain the area data of the filled area and the blank area, and calculate the actual density ratio of the two-dimensional model.

[0019] The calculation module is used to obtain the overlap of the particle units based on the actual density ratio and the preset electrode target density ratio;

[0020] The judgment module is used to determine whether the overlap is greater than a preset overlap threshold. When the overlap is greater than the overlap threshold, the coordinate data of the particle unit is updated and the overlap is recalculated.

[0021] The acquisition module is used to acquire the coordinate data of the particle unit when the overlap is not greater than the overlap threshold.

[0022] The aggregation module is used to aggregate the coordinate data and generate coordinate group data.

[0023] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described electrode particle stacking processing method.

[0024] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described electrode particle stacking processing method.

[0025] As described above, the present invention provides a method, apparatus, device and medium for processing electrode particle stacking, which can control the degree of overlap between particles in the model and reduce the deviation between the density ratio of the stacked model and the density ratio of the actual electrode, thereby increasing the accuracy of the particle model. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 The diagram shown illustrates the application environment of this invention.

[0028] Figure 2 The flowchart shown is a process for processing electrode particle stacking according to the present invention.

[0029] Figure 3 The diagram shown is a flowchart illustrating a specific embodiment of step S10 of the present invention.

[0030] Figure 4 The diagram shown is a flowchart illustrating a specific embodiment of step S20 of the present invention.

[0031] Figure 5 The diagram shown is a flowchart illustrating a specific embodiment of step S40 of the present invention.

[0032] Figure 6 The diagram shown is a flowchart illustrating a specific embodiment of step S50 of the present invention.

[0033] Figure 7 The diagram shown is a flowchart illustrating a specific embodiment of step S51 of the present invention.

[0034] Figure 8 The diagram shown is a flowchart illustrating a specific embodiment of step S60 of the present invention.

[0035] Figure 9 The diagram shown is a schematic representation of a two-dimensional model of the present invention.

[0036] Figure 10 The diagram shown is a structural diagram of the electrode particle stacking processing apparatus of the present invention.

[0037] Figure 11 The diagram shown is a structural schematic of the computer device of the present invention.

[0038] Figure 12 The diagram shown is another structural schematic of the computer device of the present invention.

[0039] Component designation explanation:

[0040] 101. Generation module; 102. Acquisition module; 103. Construction module; 104. Processing module; 105. Calculation module; 106. Judgment module; 107. Acquisition module; 108. Summary module. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] The electrode particle stacking processing method provided in this embodiment of the invention can be applied to, for example... Figure 1 In this application environment, users can use terminal devices to interact with the server via the network to send commands or receive data. The server can construct a two-dimensional model of the electrode based on preset electrode size data from the client; obtain characteristic data of the particles inside the electrode based on the electrode size data, including quantity and radius data; construct multiple particle units within the two-dimensional model based on the characteristic data, and obtain the coordinate data of the particle units; create a filled area for the region where the particle unit is located within the two-dimensional model, and create blank areas for the remaining regions, obtain the area data of the filled area and the blank area, and calculate the actual density ratio of the two-dimensional model; obtain the overlap of the particle units based on the actual density ratio and a preset target electrode density ratio; determine whether the overlap is greater than a preset overlap threshold; if the overlap is greater than the overlap threshold, update the coordinate data of the particle units and recalculate the overlap; if the overlap is not greater than the overlap threshold, obtain the coordinate data of the particle units; and summarize the coordinate data to generate coordinate group data. In this invention, by optimizing the electrode particle stacking model, the degree of overlap between particles in the model can be controlled, and the deviation between the density ratio of the stacked model and the density ratio of the actual electrode can be reduced, thereby increasing the accuracy of the particle model. The client can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, etc. The server can use a separate server or a server cluster composed of multiple servers to perform model analysis and processing, and can feed the processing results back to the terminal device. The invention will be described in detail below through specific embodiments.

[0043] Please see Figure 2 As shown, Figure 2 A schematic flowchart of a method for processing stacked electrode particles according to an embodiment of the present invention includes the following steps:

[0044] Step S10: Construct a two-dimensional model of the electrode based on the preset electrode size data.

[0045] The electrode particle stacking processing method provided by this invention can be applied to server-side applications in various scenarios. The server can receive electrode size information input by the user on the client side, and preset the two-dimensional size data of the electrode based on this information. A two-dimensional model of the electrode can then be built based on this data. For example, when developers need to build a two-dimensional model of the electrode, they can input the electrode size information into the client side. The server can receive this information and preset the electrode size data based on the actual size information to build the two-dimensional model. This ensures that the built model is consistent with the actual electrode, increasing the accuracy of the particle model.

[0046] It's important to understand that the electrode dimension data here refers to the length, width, or thickness of the electrode. The two-dimensional dimension data of the electrode can be its length and thickness, or it can be its width and thickness. For example, developers can input the length and thickness information of a specific electrode from actual production into the client to create a two-dimensional model of the electrode. For instance, ... Figure 3 As shown, step S10, which involves constructing a two-dimensional model of the electrode based on preset electrode size data, includes the following steps:

[0047] Step S11: Preset the size data of the electrode, the size data including length data and thickness data;

[0048] Step S12: Based on the length data and the thickness data, construct a two-dimensional model of the electrode.

[0049] For steps S11-S12, in one application scenario, the server can receive the electrode length and thickness information input by the user on the client, and set the two-dimensional dimension data of the electrode based on the received electrode length and thickness information. The two-dimensional dimension data of the electrode may include length data and thickness data. Based on the two-dimensional dimension data of the electrode, the horizontal axis and the global axis of the two-dimensional model can be set. Specifically, the server can create a two-dimensional model with a horizontal axis and a vertical axis. The length of the electrode can be set as the length of the horizontal axis, and the thickness of the electrode can be set as the length of the vertical axis. For specific application scenarios, the thickness of the electrode can also be set as the length of the horizontal axis, and the length of the electrode can be set as the length of the vertical axis.

[0050] The two-dimensional model of the electrode can form a rectangular region. The length of the horizontal axis can be the length of the rectangular region, and the length of the vertical axis can be the width of the rectangular region. The area of ​​the rectangular region is the two-dimensional area of ​​the electrode. For example, the length of the electrode can be represented by L, the thickness of the electrode can be represented by T, and the two-dimensional area of ​​the electrode can be represented by S. Then, S = L × T.

[0051] Step S20: Based on the electrode size data, obtain the characteristic data of the particles inside the electrode, the characteristic data including quantity data and radius data.

[0052] It is worth noting that the electrode size data here can refer to the two-dimensional size data of the electrode. Based on the preset two-dimensional size data of the electrode, the characteristic data of the particles inside the electrode can be determined, that is, the number of particles inside the electrode of this size and the radius of each particle.

[0053] Specifically, different two-dimensional electrode dimensions correspond to different numbers and radii of particles. For example, the two-dimensional dimensions of an electrode can be represented as follows: the electrode length is L, the electrode thickness is T, and the number of particles inside this electrode can be N, with the radii of the N particles being R1, R2, R3...RN. Wherein, as... Figure 4 As shown, in step S20, that is, based on the electrode size data, the characteristic data of the particles inside the electrode is obtained. The characteristic data includes quantity data and radius data, and includes the following steps:

[0054] Step S21: Based on the electrode size data, query the particle feature data corresponding to the size data in the historical group, wherein the historical group includes multiple electrode size data and corresponding particle feature data;

[0055] Step S22: Obtain the particle feature data corresponding to the electrode size data.

[0056] For steps S21-S22, the electrode size data here can refer to the two-dimensional size data of the electrode. The historical data set stores multiple different electrode size data, along with the particle count and radius data corresponding to each electrode size data. Specifically, based on the preset electrode size data, the corresponding electrode size data can be queried from the historical data set to obtain the particle count and radius data corresponding to this electrode size data.

[0057] For example, the preset two-dimensional dimensions of an electrode can be represented as an electrode length of L and an electrode thickness of T. Based on this two-dimensional dimension data, electrode dimension data with length L and thickness T can be queried from the historical data set. This allows obtaining the number of particles corresponding to this dimension data, and the radius data of each particle. The corresponding number of particles can be N, and the radii of the N particles can be R1, R2, R3...RN.

[0058] Step S30: Based on the feature data, construct multiple particle units within the two-dimensional model and obtain the coordinate data of the particle units.

[0059] After establishing the two-dimensional model of the electrode, a corresponding number of particle units can be constructed within the two-dimensional model to complete the model. For example, the number of particles can be set to N, and the radii of the N particles can be set sequentially as R1, R2, R3...RN. N particles with radii of R1, R2, R3...RN can be randomly generated within the two-dimensional model. Among the N particles, particles with the same radius may exist.

[0060] It is important to note that when randomly generating N particles within a 2D model, the center coordinates of each particle within the model can be initialized. The radius of each particle can be set to RI, the center coordinates of each particle can be set to (X, Y), the horizontal axis length of the 2D model can be set to L, and the vertical axis length of the 2D model can be set to T. Then, the center coordinates of each particle can satisfy RI≦X≦L-RI, RI≦Y≦T-RI.

[0061] It is worth noting that after constructing multiple particle units within a two-dimensional model, the coordinate data of each particle unit can be obtained. This coordinate data can be the center coordinates of each particle unit, and the distribution position of each particle unit within the two-dimensional model can be determined using the center coordinates.

[0062] For example, the radius of one particle unit can be set to 1, and the center coordinates of this particle unit within the 2D model can be set to (X, Y). The horizontal axis length of the 2D model can be set to 100, and the vertical axis length can be set to 80. Then the center coordinates (X, Y) of this particle unit can satisfy 1≦X≦99, 1≦Y≦79. When the center coordinates of this particle unit are randomly set to (2, 30), the coordinate data of this particle unit (2, 30) can be obtained. When the center coordinates of this particle unit are randomly set to (3, 50), the coordinate data of this particle unit (3, 50) can be obtained.

[0063] Step S40: Within the two-dimensional model, create the area where the particle unit is located as the filled area, create the remaining areas as blank areas, obtain the area data of the filled area and the blank area, and calculate the actual density ratio of the two-dimensional model.

[0064] It should be noted that the two-dimensional model as a whole can form a rectangular region. The area where the particle unit is located within the rectangular region can be represented as the filled region, and the area within the rectangular region that is not covered by the particle unit can be represented as the blank region. The sum of the areas of the filled region and the blank region can be the total area of ​​the rectangular region.

[0065] It should be noted that in one application scenario, when obtaining the area data of the filled and blank areas, the area of ​​the rectangular region can be set as S1, the horizontal axis length of the 2D model can be set as L, and the vertical axis length of the 2D model can be set as T. Then, the area of ​​the rectangular region S1 = L × T. When calculating the area of ​​the filled region, the filled region can be filled with fill color number 1, and the blank area can be filled with fill color number 2. The regions of fill color number 1 and fill color number 2 can be identified by an image recognition processor, and the number of pixels of fill color number 1 and fill color number 2 can be obtained. The area of ​​the filled region can be calculated based on the ratio of the number of pixels of fill color number 1 to fill color number 2. Specifically, the number of pixels of fill color number 1 can be set as PA, the number of pixels of fill color number 2 can be set as PB, the area of ​​the rectangular region can be set as S1, and the area of ​​the filled region can be set as S2. Then, the area of ​​the filled region S2 = PA / (PA+PB) × S1.

[0066] It should be noted that the actual density ratio of the 2D model can be set as EPSS_EL, the area of ​​the rectangular region can be set as S1, and the area of ​​the filled region can be set as S2, then EPSS_EL = S2 / S1. Where, for example... Figure 5 As shown, in step S40, that is, within the two-dimensional model, the area where the particle unit is located is created as a filled area, and the remaining areas are created as blank areas. The area data of the filled area and the blank area are obtained, and the actual density ratio of the two-dimensional model is calculated. This includes the following steps:

[0067] Step S41: Identify the regional characteristics of the filled area and the blank area;

[0068] Step S42: Calculate the area data of the filled area and the blank area based on the regional characteristics, and calculate the actual density ratio of the electrode.

[0069] For steps S41-S42, it should be noted that the region feature can be either the number of pixels or the region outline. For example, when the region feature is the number of pixels, the filled area can be filled with fill color #1, and the blank area can be filled with fill color #2. The region feature of the filled area can be the number of pixels in the fill color #1 region, and the region feature of the blank area can be the number of pixels in the fill color #2 region. The image recognition processor can obtain the number of pixels in fill color #1 and fill color #2 to further calculate the area of ​​the filled and blank areas. For example, when the region feature is the region outline, the image recognition processor can extract the outlines of the filled and blank areas respectively, and then calculate the outline area of ​​the filled area and the outline area of ​​the blank area to obtain the area of ​​the filled and blank areas.

[0070] Step S50: Based on the actual density ratio and the preset target electrode density ratio, obtain the overlap of the particle units.

[0071] It should be noted that when all particle units in the two-dimensional model do not overlap, the area covered by the particle units in the two-dimensional model is the sum of the areas of each particle unit. In this case, the distribution of particle units in the two-dimensional model is the target density distribution, that is, the target density ratio of the electrode is the ratio of the sum of the areas of each particle unit to the area of ​​the rectangular region.

[0072] Specifically, the target density ratio of the electrodes is the density ratio when all particle units do not overlap. The closer the actual density ratio of the 2D model is to the target density ratio, the lower the overlap of the particle units in the 2D model, meaning there is less overlapping of the particle units. For example, Figure 6 As shown, step S50, which involves obtaining the overlap of the particle units based on the actual density ratio and the preset target electrode density ratio, includes the following steps:

[0073] Step S51: Obtain the difference data between the actual density ratio and the preset target electrode density ratio;

[0074] Step S52: Obtain the overlap of particles based on the difference data.

[0075] For steps S51-S52, for example, the actual density ratio of the two-dimensional model can be set as EPSS_EL, and the target density ratio of the electrode can be set as EPSS. The difference between the actual density ratio and the target density ratio can be set as EPSS - EPSS_EL. The larger the value of EPSS - EPSS_EL, the more overlapping parts the particle units have, i.e., the higher the overlap of the particle units. The smaller the value of EPSS - EPSS_EL, the smaller the overlapping parts of the particle units, i.e., the lower the overlap of the particle units. For example, Figure 7 As shown, step S51, which involves obtaining the difference between the actual density ratio and the preset target electrode density ratio, includes the following steps:

[0076] Step S511: Obtain the total area data of the particle unit and the area data of the two-dimensional model;

[0077] Step S512: Preset the target density ratio based on the total area data of the particle units and the area data of the two-dimensional model;

[0078] Step S513: Obtain the difference data between the actual density ratio and the target density ratio.

[0079] For steps S511-S513, it should be noted that the radii of the N particle units in the two-dimensional model can be R1, R2, R3...RN, respectively. Then the total area of ​​the N particle units ST = π(R1...RN). 2 +R2 2 +.....+RN2 The horizontal axis length of the two-dimensional model can be set as L, and the vertical axis length can be set as T. Therefore, the area of ​​the rectangular region S1 = L × T. Thus, the target density ratio EPSS = π(R1) 2 +R2 2 +.....+RN 2 ) / (L×T).

[0080] Step S60: Determine whether the overlap is greater than a preset overlap threshold. When the overlap is greater than the overlap threshold, update the coordinate data of the particle unit and recalculate the overlap.

[0081] It should be noted that the overlap threshold can be set to either 0.000001 or 0.00001, and the specific threshold can be set according to the overlap requirements between particle units. Taking an overlap threshold of 0.00001 as an example, when the overlap is greater than the overlap threshold of 0.00001, it indicates that the overlap is too high, that is, there is too much overlap between particle units in the two-dimensional model.

[0082] Specifically, when there is excessive overlap between particle units in a 2D model, the coordinates of these particles can be adjusted to change their positions and thus alter the degree of overlap. After adjusting the coordinates, the overlap can be recalculated to determine if it meets the requirements for particle unit overlap. For example... Figure 8 and Figure 9 As shown, in step S60, that is, determining whether the overlap is greater than a preset overlap threshold, when the overlap is greater than the overlap threshold, the coordinate data of the particle unit is updated and the overlap is recalculated, including the following steps:

[0083] Step S61: When the overlap is greater than the overlap threshold, update the coordinate data of the particle unit;

[0084] Step S62: Based on the updated coordinate data of the particle unit, recalculate the actual density ratio;

[0085] Step S63: Based on the actual density ratio, recalculate the overlap.

[0086] For steps S61-S63, when the overlap is greater than the overlap threshold, there is too much overlap between the particle units in the two-dimensional model, and the coordinates of the particle units in the two-dimensional model can be updated.

[0087] Specifically, based on the initial coordinate data of each particle unit within the two-dimensional model, this coordinate data can be adjusted and updated. After adjusting the coordinates of each particle unit, the distribution position of the particle units changes, and the areas of the filled and blank areas change accordingly. The actual density ratio of the electrode can be set as EPSS_EL, the area of ​​the rectangular region can be set as S1, and the area of ​​the filled region can be set as S2, then EPSS_EL = S2 / S1. When the area of ​​the filled region changes, the actual density ratio of the two-dimensional model changes accordingly. Therefore, the actual density ratio can be recalculated, and the overlap can be recalculated based on the updated actual density ratio. When the overlap is greater than the overlap threshold, the coordinate data of the particle units can be cyclically adjusted and updated, and the overlap can be recalculated until the overlap is no greater than the overlap threshold.

[0088] It's important to note that the coordinate adjustment of granular units can be based on machine learning methods, such as genetic algorithms, neural network algorithms, or other machine learning approaches. In one application scenario, a neural network algorithm can be used to train the coordinate adjustment algorithm. Specifically, the recalculated overlap can be used as the input layer of the neural network model, and the coordinate adjustment data of each granular unit can be used as the output layer. By training the neural network model with multiple sets of overlap and coordinate adjustment data, a neural network model for granular unit coordinate adjustment can be established. Finally, an overlap value not exceeding an overlap threshold can be input into the trained neural network model, which then outputs the corresponding coordinate adjustment data. Based on this coordinate adjustment data, the coordinates of granular units within the 2D model can be adjusted, and the corresponding overlap can be calculated. If the overlap is still greater than the overlap threshold, the neural network model can be further trained, and the coordinates of the granular units can be continuously adjusted until the overlap is no greater than the overlap threshold.

[0089] Step S70: When the overlap is not greater than the overlap threshold, obtain the coordinate data of the particle unit.

[0090] When the overlap is no greater than the overlap threshold, the overlap of the particle units in the two-dimensional model can approach 0. At this time, the distribution of each particle unit is highly similar to the particle distribution of the actual electrode.

[0091] Step S80: Summarize the coordinate data to generate coordinate group data.

[0092] By aggregating the coordinate data of each particle unit, coordinate cluster data can be generated. The distribution of each particle unit in this coordinate cluster data shows a high degree of similarity to the actual particle distribution of the electrode. Therefore, when multiple particle units are distributed based on this coordinate cluster data, the deviation between the actual density ratio and the target density ratio can be reduced.

[0093] It should be noted that the actual density ratio of the 2D model can be the ratio of the area of ​​the filled region to the area of ​​the rectangular region, and the porosity of the 2D model can be the ratio of the area of ​​the blank region to the area of ​​the rectangular region. When the deviation between the actual density ratio and the target density ratio decreases, the similarity between the particle distribution of the filled region and the particle distribution of the actual electrode increases, thus increasing the similarity between the distribution of the blank region and the pore distribution of the actual electrode. This reduces the deviation between the porosity of the 2D model and the porosity of the actual electrode.

[0094] As can be seen, in the above scheme, by optimizing the electrode particle stacking model, the degree of overlap between particles can be controlled, and the deviation between the density ratio of the stacked model and the density ratio of the actual electrode can be reduced. At the same time, the deviation between the porosity of the two-dimensional model and the porosity of the actual electrode can be reduced, thereby increasing the accuracy of the particle model.

[0095] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0096] In one embodiment, a processing apparatus for stacking electrode particles is provided, which corresponds one-to-one with the processing method based on electrode particle stacking in the above embodiments. For example... Figure 10 As shown, the electrode particle stacking processing device includes a generation module 101, a collection module 102, a construction module 103, a processing module 104, a calculation module 105, a judgment module 106, an acquisition module 107, and a summarization module 108. Detailed descriptions of each functional module are as follows:

[0097] The generation module 101 is used to construct a two-dimensional model of the electrode based on preset electrode size data;

[0098] The acquisition module 102 is used to acquire characteristic data of the particles inside the electrode based on the electrode size data, the characteristic data including quantity data and radius data;

[0099] The construction module 103 is used to construct multiple particle units within the two-dimensional model based on the feature data, and to obtain the coordinate data of the particle units;

[0100] The processing module 104 is used to create a filled area in the region where the particle unit is located within the two-dimensional model, create the remaining areas as blank areas, obtain the area data of the filled area and the blank area, and calculate the actual density ratio of the two-dimensional model.

[0101] The calculation module 105 is used to obtain the overlap of the particle units based on the actual density ratio and the preset electrode target density ratio.

[0102] The judgment module 106 is used to determine whether the overlap is greater than a preset overlap threshold. When the overlap is greater than the overlap threshold, the coordinate data of the particle unit is updated and the overlap is recalculated.

[0103] The acquisition module 107 is used to acquire the coordinate data group of the particle unit when the overlap is not greater than the overlap threshold.

[0104] The summarization module 108 is used to summarize the coordinate data and generate coordinate group data.

[0105] In one embodiment, the generation module 101 is specifically used for:

[0106] The electrode dimensions are preset, including length and thickness data.

[0107] Based on the length data and the thickness data, a two-dimensional model of the electrode is constructed.

[0108] In one embodiment, the acquisition module 102 is specifically used for:

[0109] Based on the electrode size data, query the particle feature data corresponding to the size data in the historical group, wherein the historical group includes multiple electrode size data and corresponding particle feature data;

[0110] Obtain the particle feature data corresponding to the electrode size data.

[0111] In one embodiment, the processing module 104 is specifically used for:

[0112] Identify the regional characteristics of the filled area and the blank area;

[0113] Based on the regional characteristics, the area data of the filled area and the blank area are calculated, and the actual density ratio of the electrode is calculated.

[0114] In one embodiment, the calculation module 105 is specifically used for:

[0115] Obtain the difference data between the actual density ratio and the preset target electrode density ratio;

[0116] The overlap of particles is obtained based on the difference data.

[0117] In one embodiment, the calculation module 105 is specifically used for:

[0118] Obtain the total area data of the particle unit and the area data of the two-dimensional model;

[0119] The target density ratio is preset based on the total area data of the particle units and the area data of the two-dimensional model;

[0120] Obtain the difference data between the actual density ratio and the target density ratio.

[0121] In one embodiment, the determination module 106 is specifically used for:

[0122] When the overlap is greater than the overlap threshold, the coordinate data of the particle unit is updated;

[0123] The actual density ratio is recalculated based on the updated coordinate data of the particle units;

[0124] The overlap is recalculated based on the actual density ratio.

[0125] This invention provides a processing device for electrode particle stacking. By optimizing the electrode particle stacking model, the degree of overlap between particles can be controlled, and the deviation between the density ratio of the stacked model and the density ratio of the actual electrode can be reduced. At the same time, the deviation between the porosity of the two-dimensional model and the porosity of the actual electrode can be reduced, thereby increasing the accuracy of the particle model.

[0126] Specific limitations regarding the processing device for electrode particle stacking can be found in the limitations of the intelligent question-answering method described above, and will not be repeated here. Each module in the aforementioned intelligent question-answering processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, 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.

[0127] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 11 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a server-side processing method for electrode particle stacking.

[0128] In one embodiment, a computer device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 12As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing 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 in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements client-side functions or steps of a method for processing stacked electrode particles.

[0129] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0130] A two-dimensional model of the electrode is constructed based on the preset electrode size data;

[0131] Based on the electrode size data, the characteristic data of the particles inside the electrode are obtained, including quantity data and radius data;

[0132] Based on the feature data, multiple particle units are constructed within the two-dimensional model, and the coordinate data of the particle units are obtained;

[0133] Within the two-dimensional model, the area where the particle unit is located is created as a filled area, and the remaining areas are created as blank areas. The area data of the filled area and the blank area are obtained, and the actual density ratio of the two-dimensional model is calculated.

[0134] The overlap of the particle units is obtained based on the actual density ratio and the preset target electrode density ratio.

[0135] Determine whether the overlap is greater than a preset overlap threshold. If the overlap is greater than the overlap threshold, update the coordinate data of the particle unit and recalculate the overlap.

[0136] When the overlap is not greater than the overlap threshold, the coordinate data of the particle unit is obtained;

[0137] The coordinate data are aggregated to generate coordinate cluster data.

[0138] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0139] A two-dimensional model of the electrode is constructed based on the preset electrode size data;

[0140] Based on the electrode size data, the characteristic data of the particles inside the electrode are obtained, including quantity data and radius data;

[0141] Based on the feature data, multiple particle units are constructed within the two-dimensional model, and the coordinate data of the particle units are obtained;

[0142] Within the two-dimensional model, the area where the particle unit is located is created as a filled area, and the remaining areas are created as blank areas. The area data of the filled area and the blank area are obtained, and the actual density ratio of the two-dimensional model is calculated.

[0143] The overlap of the particle units is obtained based on the actual density ratio and the preset target electrode density ratio.

[0144] Determine whether the overlap is greater than a preset overlap threshold. If the overlap is greater than the overlap threshold, update the coordinate data of the particle unit and recalculate the overlap.

[0145] When the overlap is not greater than the overlap threshold, the coordinate data of the particle unit is obtained;

[0146] The coordinate data are aggregated to generate coordinate cluster data.

[0147] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0148] 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, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0149] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0150] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method of processing an electrode particle stack, characterized by, The method comprises the following steps: constructing a two-dimensional model of the electrode based on preset electrode size data; obtaining characteristic data of particles inside the electrode according to the electrode size data, wherein the characteristic data comprises quantity data and radius data; constructing a plurality of particle units in the two-dimensional model based on the characteristic data and obtaining coordinate data of the particle units; creating a filled area where the particle units are located and a blank area in the two-dimensional model, obtaining area data of the filled area and the blank area, and calculating an actual density ratio of the two-dimensional model; obtaining total area data of the particle units and area data of the two-dimensional model; calculating a target density ratio based on a ratio of the total area data of the particle units to the area data of the two-dimensional model; obtaining difference data of the actual density ratio and the target density ratio; obtaining an overlap degree of the particles based on the difference data; determining whether the overlap degree is greater than a preset overlap degree threshold value, and when the overlap degree is greater than the overlap degree threshold value, updating coordinate data of the particle units and recalculating the overlap degree; when the overlap degree is not greater than the overlap degree threshold value, obtaining the coordinate data of the particle units; summarizing the coordinate data to generate coordinate group data.

2. The method of processing an electrode pellet stack of claim 1, wherein, The step of constructing a two-dimensional model of the electrode based on preset electrode size data comprises the following steps: presetting size data of the electrode, wherein the size data comprises length data and thickness data; constructing a two-dimensional model of the electrode based on the length data and the thickness data.

3. The method of processing an electrode pellet stack of claim 1, wherein, The step of obtaining characteristic data of particles inside the electrode according to the electrode size data comprises the following steps: querying particle characteristic data corresponding to the size data in a historical group according to the electrode size data, wherein the historical group comprises a plurality of electrode size data and corresponding particle characteristic data; obtaining particle characteristic data corresponding to the electrode size data.

4. The method of claim 1, wherein the electrode particles are stacked in a plurality of layers. The step of creating a filled area where the particle units are located and a blank area in the two-dimensional model, obtaining area data of the filled area and the blank area, and calculating an actual density ratio of the two-dimensional model comprises the following steps: identifying area features of the filled area and the blank area; calculating area data of the filled area and the blank area based on the area features, and calculating an actual density ratio of the electrode.

5. The method of claim 1, wherein The step of determining whether the overlap degree is greater than a preset overlap degree threshold value, and when the overlap degree is greater than the overlap degree threshold value, updating coordinate data of the particle units and recalculating the overlap degree comprises the following steps: when the overlap degree is greater than the overlap degree threshold value, updating coordinate data of the particle units; recalculating the actual density ratio based on the updated coordinate data of the particle units; recalculating the overlap degree based on the actual density ratio.

6. A processing apparatus of electrode particles, characterized by, The processing device comprises: a generating module configured to construct a two-dimensional model of the electrode based on preset electrode size data; An acquisition module is configured to acquire feature data of the particles inside the electrode according to the electrode size data, the feature data including quantity data and radius data; A construction module is configured to construct a plurality of particle units in the two-dimensional model based on the feature data, and acquire coordinate data of the particle units; A processing module is configured to create a region where the particle units are located as a filled region and create a remaining region as a blank region in the two-dimensional model, acquire area data of the filled region and the blank region, and calculate an actual density ratio of the two-dimensional model; A calculation module is configured to acquire an overlap degree of the particle units based on the actual density ratio and a preset electrode target density ratio; A judgment module is configured to judge whether the overlap degree is greater than a preset overlap degree threshold, and update the coordinate data of the particle units and recalculate the overlap degree when the overlap degree is greater than the overlap degree threshold; An acquisition module is configured to acquire the coordinate data of the particle units when the overlap degree is not greater than the overlap degree threshold; An aggregation module is configured to aggregate the coordinate data to generate coordinate group data.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the processing method of the electrode particle stack according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to implement the steps of the processing method of the electrode particle stack according to any one of claims 1 to 5.

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