A method for generating and reconstructing porous media for positive and negative electrode coatings

Abstract

The present invention relates to the technical field of lithium battery positive and negative electrode coating analysis. A method for generating and reconstructing porous media for positive and negative electrode coatings is disclosed. The method includes establishing models of the porous media using a four-parameter random generation method based on the confidence intervals and dimensionless transformation of the pore size distributions of the positive and negative electrode coatings. The method also employs a Cartesian background grid-based coloring method to address dead zones in the models. This method ensures that the macroscopic parameters of the porous media for the positive and negative electrode coatings meet requirements while efficiently addressing the dead zone issue in the pores of the positive and negative electrode coatings.

Description

Technical Field

[0001] The present invention relates to the technical field of analysis of positive and negative electrode coatings of lithium batteries, and in particular to a method for generating and reconstructing modeling of porous media of positive and negative electrode coatings. Background Art

[0002] Lithium batteries have found widespread application as energy storage devices in the aerospace industry. The positive and negative electrode coatings of lithium batteries are porous media, and thermal and mechanical analyses require modeling of these porous media. Reconstructing these porous media is a key pre-processing step for simulations.

[0003] The most commonly used and important macroscopic parameter of the porous media of the positive and negative electrode coatings is porosity With hole size ,in Certainty is given based on statistics; Due to the random nature of the distribution, only a given distribution is usually possible. The pore size distribution (PSD) is determined by the distribution probability density function. The application of existing methods is constrained by statistical data, and each established lithium battery positive and negative electrode coating requires verification and revision based on size and flow. Existing methods have poor versatility and suffer from dead zone issues. The present invention provides a universal modeling method for porous media in lithium battery positive and negative electrode coatings that eliminates the dead zone issue. Summary of the Invention

[0004] In response to the above-mentioned deficiencies in the prior art, the present invention provides a method for generating and reconstructing modeling of porous media in positive and negative electrode coatings, which can not only ensure that the macroscopic parameters of the porous media in the positive and negative electrode coatings meet the requirements, but also efficiently deal with the dead zone problem in the pores of the positive and negative electrode coatings.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] A method for generating and reconstructing a model of a porous medium for positive and negative electrode coatings comprises the following steps:

[0007] According to the confidence interval and dimensionless process of the pore size distribution of the positive and negative electrode coatings, a four-parameter random generation method is used to establish the porous medium model of the positive and negative electrode coatings.

[0008] The dead zone of the porous medium model of the positive and negative electrode coatings is processed using a coloring method based on the Cartesian background grid.

[0009] Furthermore, a four-parameter random generation method is used to establish the porous medium model of the positive and negative electrode coatings, including:

[0010] Set the number range and grid size of the Cartesian background grid;

[0011] Determine the aperture and corresponding probability density of each cell on the Cartesian background grid;

[0012] Initialize the labels of each cell on the Cartesian background grid;

[0013] For the unit marked as 1, grow toward the adjacent unit in the corresponding direction according to the growth probability;

[0014] Calculate the current porosity based on the number of cells marked as 1 and iterate with the current porosity as the iteration submission.

[0015] Furthermore, determining the aperture and corresponding probability density of each cell on the Cartesian background grid includes:

[0016] Generate a random number in [0,1] for each cell on the Cartesian background grid;

[0017] Search for the pore size distribution interval number of the positive and negative electrode coatings that meets the following formula :

[0018] Where N is the number of pore size distribution intervals of the positive and negative electrode coatings, is a random number, For unit The aperture, The first Aperture value, For unit The probability density of for The corresponding probability density function value;

[0019] Pick .

[0020] Furthermore, initializing the labels of each cell on the Cartesian background grid includes:

[0021] Generate a random number in [0,1] for each cell on the Cartesian background grid;

[0022] If satisfied:

[0023] in, is a random number, For unit The probability density of the positive and negative electrode coatings is , and N is the number of pore size distribution intervals.

[0024] Furthermore, the growth probability is the ratio of the unit aperture to the growth coefficient in each direction.

[0025] Furthermore, growing the unit marked as 1 toward the adjacent unit in the corresponding direction according to the growth probability includes:

[0026] Determine whether the cell mark of the adjacent cells in each direction is 1;

[0027] If so, skip the adjacent unit in that direction;

[0028] Otherwise, generate a random number in [0,1] on the adjacent cells in the corresponding direction;

[0029] If the random number is less than the growth probability, the adjacent unit in that direction is marked as 1;

[0030] Otherwise, there is no growth in this direction.

[0031] Furthermore, the current porosity is the ratio of the number of cells marked as 1 to the total number of cells in the Cartesian background grid in three-dimensional coordinates.

[0032] Furthermore, the dead zone processing of the positive and negative electrode coating porous medium model is performed using a coloring method based on a Cartesian background grid, including:

[0033] Relabel the cells marked as 1 on the regional boundaries of the positive and negative electrode coating porous media models to -1;

[0034] Initialize the access flags of each unit of the positive and negative electrode coating porous medium model;

[0035] Traverse the cells with a cell mark of -1 and a visit mark of 0, and determine whether the adjacent cells on the same plane as the cell satisfy the cell mark of 1 and the visit mark of 0; if so, mark the adjacent cell as -1, otherwise do not process it. When the adjacent cell is processed, mark the visit mark of the cell back to 1;

[0036] Traverse all the units of the positive and negative electrode coating porous medium model and remark the units marked as 1 to 0.

[0037] The present invention has the following beneficial effects:

[0038] The present invention solves the dead zone problem in the modeling of porous media with positive and negative electrode coatings through dimensionless processing of a four-parameter random generation method and a coloring method based on a Cartesian grid to quickly identify units inside and outside the hole. It has good versatility and, because there is no dead zone, its accuracy is much higher than that of existing modeling methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Schematic diagram of the process flow for generating a reconstruction modeling method for a porous medium with positive and negative electrode coatings.

[0040] Figure 2 Schematic diagram for initialization unit labeling.

[0041] Figure 3 Schematic diagram of unit growth in the x and y directions in two dimensions.

[0042] Figure 4 Label the schematic for the final unit.

[0043] Figure 5 Schematic diagram of the initial staining state.

[0044] Figure 6 Schematic diagram of the dyeing state after one iteration.

[0045] Figure 7 Schematic diagram of the final dyeing state. DETAILED DESCRIPTION

[0046] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0047] like Figure 1 As shown, an embodiment of the present invention provides a method for generating and reconstructing a model of a positive and negative electrode coating porous medium, comprising the following steps S1 and S2:

[0048] S1. Based on the confidence interval and dimensionless process of the pore size distribution of the positive and negative electrode coatings, a four-parameter random generation method is used to establish the porous medium model of the positive and negative electrode coatings;

[0049] In an optional embodiment of the present invention, the pore sizes of the positive and negative electrode coatings may vary by orders of magnitude, so a dimensionless process is required for universality to obtain a generation algorithm that is independent of specific size. The upper and lower limits of the pore size within the confidence interval are determined based on the distribution. , the aperture within the confidence interval is normalized as follows: (where no ambiguity is caused, the subscript is ignored. )

[0050] Obviously, the normalized d is Satisfy the same type of distribution (only the parameters or coefficients are different).

[0051] Will[ ] is divided into N intervals, and the midpoint of each interval is recorded as , after normalization to :

[0052] by The probability density function is approximated by a broken line with this as the endpoint Obviously, the larger N is, the more accurate the approximation is. In order to simplify the notation, express .

[0053] When generating the porous media of the positive and negative electrode coatings, it is hoped that the grid size can distinguish the smallest pore size (ie, d1), while at the same time the scale of each direction of the region can contain as many largest pore sizes as possible (ie, ), so the requirements for the Cartesian background grid required by the generation method are:

[0054] (1) Cartesian grid size (The dimensions in each direction are taken to be consistent)

[0055] (2) The Cartesian grid area contains at least K maximum apertures in each direction , so the scale L in each direction of the grid area (take the scale in each direction to be consistent) should satisfy

[0056] The number of grid cells M in each direction of the background Cartesian grid should satisfy

[0057] Desirable

[0058] The total number of Cartesian grids in the three-dimensional case is Obviously, if N and K are very large, the background grid size will be unacceptably large. Therefore, in order to reduce the amount of calculation as much as possible, N=10 and K=5 are usually taken, or adjusted appropriately according to the accuracy requirements.

[0059] In an optional embodiment of the present invention, establishing the positive and negative electrode coating porous medium model using a four-parameter random generation method includes:

[0060] Set the number range and grid size of the Cartesian background grid;

[0061] Determine the aperture and corresponding probability density of each cell on the Cartesian background grid;

[0062] Initialize the labels of each cell on the Cartesian background grid;

[0063] For the unit marked as 1, grow toward the adjacent unit in the corresponding direction according to the growth probability;

[0064] Calculate the current porosity based on the number of cells marked as 1 and iterate with the current porosity as the iteration submission.

[0065] The dimensionless four-parameter random generation method used in this embodiment is as follows:

[0066] (1) Set the Cartesian background grid Number range, i.e. , and the grid size is ;

[0067] (2) Give an aperture to each cell on the background grid and the corresponding probability density , the values ​​of the two are One of them; it can be randomly given by such a rule, that is, a random number in [0,1] is generated on each unit , if for a certain

[0068] have

[0069] Then take ;

[0070] (3) Initialize the mark of the background grid cell (The marking rule is that if the cell is identified as to be grown, it is marked as 1, otherwise it is marked as 0). The initialization process is to generate a random number in (0,1) for each cell. ,

[0071] like

[0072] Initialize ,otherwise ;like Figure 2 As shown;

[0073] (4) For Each unit of The three directions have the following growth probabilities

[0074] The adjacent units grow in the corresponding direction, such as Figure 3 shown; for The growth coefficient of the direction; the growth rule is: if the adjacent unit is marked as 1, skip it, otherwise give a random number r in (0,1), if

[0075] Then the adjacent unit is also marked as 1;

[0076] (5) Calculate current porosity , that is, statistics The number of units is N1, then

[0077] like Not less than the specified porosity ,Right now

[0078] Then the iteration is stopped, and the final obtained positive and negative electrode coating porous media are as follows Figure 4 Otherwise, repeat step (4).

[0079] S2. The dead zone of the positive and negative electrode coating porous medium model is processed using a coloring method based on the Cartesian background grid.

[0080] In an optional embodiment of the present invention, the dead zone processing of the positive and negative electrode coating porous medium model using a coloring method based on a Cartesian background grid includes:

[0081] Relabel the cells marked as 1 on the regional boundaries of the positive and negative electrode coating porous media models to -1;

[0082] Initialize the access flags of each unit of the positive and negative electrode coating porous medium model;

[0083] Traverse the cells with a cell mark of -1 and a visit mark of 0, and determine whether the adjacent cells on the same plane as the cell satisfy the cell mark of 1 and the visit mark of 0; if so, re-mark the cell to -1 and re-mark the visit mark of the cell to 1;

[0084] Traverse all the units of the positive and negative electrode coating porous medium model and remark the units marked as 1 to 0.

[0085] The coloring method based on the Cartesian background grid adopted in this embodiment is as follows:

[0086] (1) Consider the final mark given by the porous media generation algorithm , the region boundary The unit is relabeled as ,like Figure 5 As shown;

[0087] (2) Introducing new tags for each unit , called "access mark" (if "not visited" ,otherwise ), since all non-porous areas do not need to be “visited”, initially all non-porous units, i.e. The "access flag" of the unit is set to the "visited" state, that is, ; The pore unit is The "access flag" of each unit is initially set to the "unvisited" state, that is, ;

[0088] (3) Traversal and unit; examine all adjacent units that are coplanar with it ,like and Then set ; After all coplanar adjacent units are processed, the "visit mark" of the current unit is set to "visited", that is, ;like Figure 6 As shown;

[0089] (4) Repeat step (3) until no more conditions are met at the same time. and Unit;

[0090] (5) Traverse the grid cells, if (i.e., dead zone unit), relabel it as The resulting porous medium is marked as the pore zone unit The non-porous area (solid area) unit ;like Figure 7 shown.

[0091] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0092] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0094] Specific embodiments are used in the present invention to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

[0095] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A method for generating and reconstructing a model of a porous medium for positive and negative electrode coatings, characterized in that: The following steps are involved: According to the confidence interval and dimensionless process of the pore size distribution of the positive and negative electrode coatings, a four-parameter random generation method is used to establish a positive and negative electrode coating porous medium model; wherein, the four-parameter random generation method is used to establish the positive and negative electrode coating porous medium model, including: setting the number range and grid size of the Cartesian background grid; Determining the aperture and corresponding probability density of each cell on a Cartesian background grid, generating a random number in the range [0, 1] for each cell on the Cartesian background grid; Search for the pore size distribution interval number n of the positive and negative electrode coatings that satisfies the following formula: Where N is the number of pore size distribution intervals of the positive and negative electrode coatings, r (i，j，k) is a random number, d (i，j，k) is the aperture of unit (i, j, k), d n The nth aperture value after the aperture range is divided into N segments, p (i，j，k) is the probability density of unit (i, j, k), p n d n The corresponding probability density function value; Take d (i，j，k) =d n , p (i，j，k) =p n ; Initialize the mark of each cell on the Cartesian background grid, and generate a random number in [0,1] for each cell on the Cartesian background grid; If satisfied: Among them, r (i，j，k) is a random number, p (i，j，k) is the probability density of unit (i, j, k), N is the number of pore size distribution intervals of positive and negative electrode coatings; The unit marked as 1 grows towards the adjacent unit in the corresponding direction according to the growth probability, where the growth probability is the ratio of the unit aperture to the growth coefficient in each direction; Calculate the current porosity based on the number of cells marked as 1, and iterate using the current porosity as the iteration submission; The dead zone of the porous medium model of the positive and negative electrode coatings is processed using a coloring method based on the Cartesian background grid.

2. A method for generating and reconstructing a model of a positive and negative electrode coating porous medium according to claim 1, characterized in that: The growth of the unit marked as 1 toward the adjacent unit in the corresponding direction according to the growth probability includes: Determine whether the cell mark of the adjacent cells in each direction is 1; If so, skip the adjacent unit in that direction; Otherwise, generate a random number in [0,1] on the adjacent cells in the corresponding direction; If the random number is less than the growth probability, the adjacent unit in that direction is marked as 1; Otherwise, there is no growth in this direction.

3. The method for generating and reconstructing a model of a porous medium for positive and negative electrode coatings according to claim 2, characterized in that: The current porosity is the ratio of the number of cells marked as 1 to the total number of cells in the Cartesian background grid in 3D coordinates.

4. The method for generating and reconstructing a model of a positive and negative electrode coating porous medium according to claim 1, characterized in that: The dead zone treatment of the positive and negative electrode coating porous medium model using a coloring method based on Cartesian background grid includes: Relabel the cells marked as 1 on the regional boundaries of the positive and negative electrode coating porous media models to -1; Initialize the access flags of each unit of the positive and negative electrode coating porous medium model; Traverse the cells with a cell mark of -1 and a visit mark of 0, and determine whether the adjacent cells on the same plane as the cell satisfy the cell mark of 1 and the visit mark of 0; if so, mark the adjacent cell as -1, otherwise do not process it. When the adjacent cell is processed, mark the visit mark of the cell back to 1; Traverse all the units of the positive and negative electrode coating porous medium model and remark the units marked as 1 to 0.

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