Optimization method and device for lithium battery slurry mixing equipment based on fluid mechanics simulation, computer equipment and storage medium

Abstract

The application provides a kind of based on fluid mechanics simulation lithium battery slurry mixing equipment optimization method, device, computer equipment and storage medium;The above-mentioned based on fluid mechanics simulation lithium battery slurry mixing equipment optimization method includes: establishing the geometric model of several lithium battery slurry mixing equipment;Respectively, each geometric model is subjected to model simplification processing, and the fluid region needing calculation is extracted;Each geometric model is divided into finite element grid, and the local area of the stirring paddle of each geometric model is subjected to encryption processing, to obtain the grid file of each geometric model;Determine the basic control equation of the calculation flow field of lithium battery slurry mixing, and the basic control equation is subjected to volume integral processing;Corresponding material properties of lithium battery slurry added in geometric model are obtained, and the medium flow model is determined according to the calculation equation of Reynolds coefficient;The above-mentioned optimization method can save a lot of research and development time and research and development cost, and can also improve test effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation design of lithium battery slurry mixing equipment, in particular to a lithium battery slurry mixing equipment optimization method and device based on fluid mechanics simulation, a computer device and a storage medium. BACKGROUND

[0002] With the rapid development of the global new energy electric vehicle market, lithium batteries, as one of the core power sources, have achieved great success and wide application in the new energy field. Among them, in the production and manufacturing process of lithium batteries, lithium battery slurry stirring is one of the key process links. Lithium battery slurry is usually a mixture composed of active materials (such as positive electrode materials, negative electrode materials), conductive agents, binders and solvents, etc. These raw materials are fully mixed and uniformed by stirring to ensure the performance and stability of the battery, therefore, the research and development of lithium battery slurry mixing equipment is particularly important.

[0003] Past research largely depends on test results, and has many drawbacks. The technical personnel cannot fully understand the specific conditions of the flow field flow characteristics in the stirring system, and it is difficult to provide reliable reference for engineering practice, making the design process of lithium battery slurry mixing equipment more complicated and repeated testing, resulting in the need for a large amount of research and development costs and a long research and development time for lithium battery slurry mixing equipment, and poor test results for the material mixing equipment.

[0004] Therefore, the present application provides a lithium battery slurry mixing equipment simulation optimization method based on computational fluid dynamics. SUMMARY

[0005] The purpose of the present application is to overcome the deficiencies in the prior art, and to provide a lithium battery slurry mixing equipment optimization method, device, computer device and storage medium based on fluid mechanics simulation, which has lower research and development cost, shorter research and development time and better test results.

[0006] The purpose of the present application is achieved by the following technical solutions:

[0007] A lithium battery slurry mixing equipment optimization method based on fluid mechanics simulation, comprising:

[0008] Establishing a plurality of geometric models of lithium battery slurry mixing equipment;

[0009] Respectively performing model simplification processing on each geometric model, and extracting fluid regions that need to be calculated;

[0010] Dividing a finite element mesh for each geometric model, and performing encryption processing on a local region of the stirring paddle of each geometric model to obtain a mesh file of each geometric model;

[0011] determining basic control equations of a computational flow field of lithium battery slurry mixing, and volume-integrating the basic control equations;

[0012] acquiring material properties corresponding to the lithium battery slurry added in the geometric model, and determining a medium flow model according to a Reynolds number calculation equation; wherein the material properties include density and viscosity;

[0013] acquiring physical parameters of initial conditions and boundary conditions, and performing steady-state flow field solving on the computational fluid model of the stirred tank of each geometric model by a solver to obtain corresponding solving results; wherein the physical parameters include a preset rotating speed of the stirring paddle in the stirred tank of the geometric model;

[0014] respectively performing residual error judgment on the solving results corresponding to each geometric model; if the residual error converges, the solving results are saved;

[0015] establishing a component transport equation, adding a tracer, and respectively performing transient solving on the computational fluid model in the stirred tank of each geometric model to obtain fluid parameters of the stirred tanks of the multiple geometric models, and taking the steady-state solving results of each geometric model as initial values of the component transport equation;

[0016] post-processing the fluid parameters of the stirred tank of each geometric model to obtain stirring and mixing data of the concentration of the tracer in the stirred tank of the corresponding geometric model changing over time and flow field velocity cloud map data in the stirred tank;

[0017] comparing the stirring and mixing data of the stirred tanks of the multiple geometric models, and taking the geometric model corresponding to the optimal stirring and mixing data as a design model of the lithium battery slurry mixing device.

[0018] In one embodiment, the basic control equations include a mass conservation equation and a momentum conservation equation; the step of determining basic control equations of a computational flow field of lithium battery slurry mixing, and volume-integrating the basic control equations includes:

[0019] determining basic control equations of a computational flow field of lithium battery slurry mixing;

[0020] respectively volume-integrating the mass conservation equation and the momentum conservation equation.

[0021] In one embodiment, the mass conservation equation is: ; and the momentum conservation equation is: ;

[0022] wherein, is the fluid density, tis the local velocity component of the fluid at the point in the time t V u , v , w ; x , y , z is the spatial direction position; p is the pressure in the fluid micro-element; is the viscous stress acting on the surface of the micro-element; is the gravity volume force in the direction is the external volume force in the direction

[0023] In one embodiment, the step of extracting the fluid region requiring calculation comprises:

[0024] The fluid region requiring calculation is extracted by volume extraction and Boolean operation.

[0025] In one embodiment, the step of dividing the finite element grid for each geometric model comprises: adopting a non-structural tetrahedral grid method to divide the finite element grid for each geometric model, and performing encryption processing in the region of the corresponding stirring paddle of each geometric model.

[0026] In one embodiment, the viscosity change of the lithium battery slurry conforms to the pseudoplastic fluid.

[0027] The non-Newtonian fluid is simulated by adopting a power-law fluid model, and the power-law fluid satisfies wherein is the shear stress, K is the consistency coefficient, is the shear strain rate, n is the power-law index, and n <1.

[0028] In one embodiment, the calculation equation of the Reynolds coefficient of the non-Newtonian fluid is:

[0029] wherein: Re is a dimensionless number; V is the average flow rate, m / s; D is the stirring paddle diameter, mm; is the fluid density, kg / m 3 ，n is the power-law index.

[0030] In one embodiment, the component transport equation is: wherein is the density of the fluid, is the velocity of the fluid, ​​​mass fraction of the tracer, diffusion coefficient of the tracer in the fluid, wherein diffusivity of the tracer, source term, no chemical reaction involved in the numerical simulation of lithium battery slurry mixing, the value of 0, t time.

[0031] An optimization device of a lithium battery slurry mixing equipment based on fluid mechanics simulation, comprising:

[0032] a geometric model establishing module for establishing geometric models of a plurality of lithium battery slurry mixing equipments;

[0033] a model simplification and extraction module for performing model simplification processing on each of the geometric models and extracting fluid regions to be calculated;

[0034] a division module for dividing each of the geometric models into finite element meshes and performing encryption processing on a local region of an agitator of each of the geometric models to obtain a mesh file of each of the geometric models;

[0035] an integral processing module for determining a basic control equation of a calculation flow field of lithium battery slurry mixing and performing volume integral processing on the basic control equation;

[0036] a flow pattern determining module for obtaining material properties corresponding to lithium battery slurry added into the geometric models and determining a medium flow model according to a calculation equation of a Reynolds coefficient;

[0037] a flow field solving module for obtaining physical parameters of initial conditions and boundary conditions, performing steady-state flow field solving on a calculation fluid model of an agitator tank of each of the geometric models through a solver, and obtaining corresponding solving results; wherein the physical parameters include a preset rotating speed of the agitator in the agitator tank of the geometric model;

[0038] a residual error judging module for performing residual error judgment on the solving results corresponding to each of the geometric models; if the residual error converges, the solving results are saved;

[0039] an equation establishing module for establishing a component transport equation, adding a tracer, and performing transient solving on the calculation fluid model in the agitator tank of each of the geometric models to obtain fluid parameters of the agitator tanks of the plurality of geometric models, and taking the steady-state solving results of each geometric model as initial values of the component transport equation;

[0040] A parameter processing module is configured to post-process fluid parameters of the stirring tank of each geometric model to obtain stirring and mixing data of the tracer concentration of the stirring tank of the corresponding geometric model changing over time and flow field velocity cloud map data in the stirring tank.

[0041] A comparison output module is configured to compare the stirring and mixing data of the stirring tanks of the plurality of geometric models, and take the geometric model corresponding to the optimal stirring and mixing data as the design model of the lithium battery slurry mixing device.

[0042] A computer device comprises a memory and a processor, and the memory stores a computer program.

[0043] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the method in any of the above embodiments.

[0044] Compared with the prior art, the present application has at least the following advantages:

[0045] 1. The optimization method of the lithium battery slurry mixing equipment based on the fluid mechanics simulation, first, a plurality of geometric models of the lithium battery slurry mixing equipment are established; then, each geometric model is subjected to model simplification processing, and a fluid region to be calculated is extracted, i.e. a slurry region of a stirring tank of the geometric model is extracted; then, a finite element mesh is divided for each geometric model to obtain a mesh file of each geometric model; then, a basic control equation of a calculation flow field of the lithium battery slurry mixing is determined, and the basic control equation is subjected to volume integral processing; then, a material property corresponding to the lithium battery slurry added into the geometric model is obtained, and a medium flow model is determined according to a calculation equation of the Reynolds coefficient; then, physical parameters of initial conditions and boundary conditions are obtained, and a solver is used to perform steady-state flow field solving on a calculation fluid model of the stirring tank of each geometric model to obtain a corresponding solving result; then, the solving result corresponding to each geometric model is subjected to residual error judgment; if the residual error converges, the solving result is saved; then, a component transport equation is established, a tracer is added, and transient solving is performed on the calculation fluid model in the stirring tank of each geometric model to obtain fluid parameters of the stirring tank of a plurality of geometric models, and the steady-state solving result of each geometric model is used as an initial value of the component transport equation; then, the fluid parameters of the stirring tank of each geometric model are subjected to post-processing to obtain stirring and mixing data of the concentration of the tracer of the stirring tank of the corresponding geometric model with time and flow field velocity cloud map data in the stirring tank; finally, the stirring and mixing data of the stirring tank of a plurality of geometric models are compared, and the geometric model corresponding to the optimal stirring and mixing data is used as a design model of the lithium battery slurry mixing equipment, so that the engineering problem of structural optimization of the lithium battery mixing equipment is realized through the computational fluid mechanics analysis, and the design method of the lithium battery mixing equipment is simple and convenient.

[0046] 2. The optimization method, solves the problem that the traditional optimization design needs to judge the stirring effect of the lithium battery mixing equipment through experiments, and a large amount of time and money is spent, so that the research and development cost of the optimization method is low, the flow field simulation analysis is performed in the stirring tank, not only the time required for the structural optimization of the lithium battery mixing equipment is greatly shortened, i.e. the research and development time of the lithium battery mixing equipment is shortened, but also the problem of poor experimental effect of the traditional lithium battery mixing equipment is solved, so that the lithium battery mixing equipment after optimization better meets the actual production needs of the battery mixing equipment. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as limiting the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0048] Figure 1 Figure of the original paddle type lithium battery slurry mixing device;

[0049] Figure 2 Flow chart of the optimization method of the lithium battery slurry mixing device based on fluid mechanics simulation in an embodiment;

[0050] Figure 3 Schematic diagram of the grid of the fluid calculation area in the original paddle type geometric model;

[0051] Figure 4 Flow field velocity nephogram and trace diagram of the original paddle type;

[0052] Figure 5 Flow field velocity nephogram and trace diagram of the optimized paddle type;

[0053] Figure 6 Flow chart of the optimization method of the lithium battery slurry mixing device based on fluid mechanics simulation in another embodiment;

[0054] Figure 7 Schematic diagram of the tracer feeding position and monitoring point;

[0055] Figure 8a Monitoring point concentration-time curve diagram of the original paddle type;

[0056] Figure 8b Monitoring point concentration-time curve diagram of the optimized paddle type;

[0057] Figure 9 Figure of the optimized paddle type lithium battery slurry mixing device;

[0058] Figure 10 Internal structure diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0059] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the related drawings. The preferred embodiments of the present application are shown in the drawings. However, the present application can be implemented in many different forms, and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0060] It should be noted that when an element is referred to as being "on" another element, it can be directly on the other element or intervening elements can also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements can also be present. As used herein the terms "vertical", "horizontal", "left", "right", and the like are merely used for the purpose of illustration and are not intended to be limiting.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0062] The application provides a kind of based on fluid mechanics simulation lithium battery slurry mixing equipment optimization method, including the following steps or part of all: establish the geometric model of several lithium battery slurry mixing equipment;Respectively on each described geometric model is model simplified processing, and extract the fluid region needing calculation;Each described geometric model is divided into finite element grid, and the local area of each described geometric model of stirring paddle is encrypted processing, obtains the grid file of each described geometric model;Determine the basic control equation of the calculation flow field of lithium battery slurry mixing, and the basic control equation is volume integral processing;Corresponding material attribute of lithium battery slurry added in the described geometric model is obtained, and medium flow model is determined according to the calculation equation of Reynolds coefficient;Wherein the material attribute includes density and viscosity;The physical parameters of initial condition and boundary condition are obtained, and the calculation fluid model of each described geometric model of stirring tank is solved by solver steady flow field, and corresponding solution result is obtained;Wherein the physical parameters include the preset rotating speed of the stirring paddle in the stirring tank of the geometric model;Respectively on each described geometric model corresponding solution result is residual error judgment;If the residual error converges, the solution result is saved;Establish component transport equation, and add tracer, and then respectively on each described geometric model of stirring tank in the calculation fluid model is transiently solved, to obtain the fluid parameter of the stirring tank of multiple described geometric models, and the result of each geometric model steady-state solution is used as the initial value of component transport equation;The fluid parameter of the stirring tank of each described geometric model is post-processed, and the concentration of tracer of the corresponding stirring tank of the geometric model with time-varying stirring mixing data and stirring tank flow field velocity nephogram data is obtained;The stirring mixing data of the stirring tank of multiple described geometric models is compared, and the geometric model corresponding to the optimal stirring mixing data is used as the design model of the lithium battery slurry mixing equipment.

[0063] The optimization method of the lithium battery slurry mixing equipment based on the fluid mechanics simulation, firstly, establishes a plurality of geometric models of lithium battery slurry mixing equipment; then, respectively, carries out model simplification processing on each geometric model, and extracts the fluid region to be calculated, that is, extracts the slurry region of the stirring tank of the geometric model; then, divides the finite element grid for each geometric model to obtain the grid file of each geometric model; then, determines the basic control equation of the calculation flow field of the lithium battery slurry mixing, and carries out volume integral processing on the basic control equation; then, obtains the material properties corresponding to the lithium battery slurry added in the geometric model, and determines the medium flow model according to the calculation equation of the Reynolds coefficient; then, obtains the physical parameters of the initial condition and the boundary condition, and carries out steady-state flow field solving on the calculation fluid model of the stirring tank of each geometric model through the solver to obtain the corresponding solving result; then, respectively, carries out residual judgment on the solving result corresponding to each geometric model; if the residual converges, the solving result is saved; then, establishes the component transport equation, adds the tracer, and respectively carries out transient solving on the calculation fluid model in the stirring tank of each geometric model to obtain the fluid parameters of the stirring tank of a plurality of geometric models, and takes the steady-state solving result of each geometric model as the initial value of the component transport equation; then, carries out post-processing on the fluid parameters of the stirring tank of each geometric model to obtain the stirring and mixing data of the concentration of the tracer of the stirring tank of the corresponding geometric model with time and the flow field velocity cloud map data in the stirring tank; finally, compares the stirring and mixing data of the stirring tank of a plurality of geometric models, and takes the geometric model corresponding to the optimal stirring and mixing data as the design model of the lithium battery slurry mixing equipment, so that the engineering problem of structural optimization of the lithium battery mixing equipment is realized through the computational fluid mechanics analysis, and the design method of the lithium battery mixing equipment is simple and convenient; the optimization method solves the problem that the traditional optimization design needs to judge the stirring effect of the lithium battery mixing equipment through experiments, which consumes a lot of time and money, so that the research and development cost of the optimization method is low, the flow field simulation analysis is carried out in the stirring tank, which not only greatly shortens the time required for the structural optimization of the lithium battery mixing equipment, that is, shortens the research and development time of the lithium battery mixing equipment, but also solves the problem that the traditional lithium battery mixing equipment has poor test effect, so that the lithium battery mixing equipment after optimization better meets the actual production needs of the battery mixing equipment.

[0064] In one embodiment, the basic control equation includes a mass conservation equation and a momentum conservation equation; the step of determining the basic control equation of the calculation flow field of the lithium battery slurry mixing, and carrying out volume integral processing on the basic control equation includes:

[0065] determining the basic control equation of the calculation flow field of the lithium battery slurry mixing;

[0066] respectively, carrying out volume integral processing on the mass conservation equation and the momentum conservation equation.

[0067] In one embodiment, the mass conservation equation is: ; the momentum conservation equation is: ;

[0068] wherein, is the fluid density, t is time, the flow velocity of any point in the fluid field V is the local velocity component of the flow in the direction of u , v , w ; x , y , z is the spatial direction position; p is the pressure in the fluid micro-element; is the viscous stress acting on the surface of the micro-element; is the gravity volume force in the direction of is the external volume force in the direction of is the external volume force in the direction of In one embodiment, the step of extracting the fluid region requiring calculation is specifically:

[0069] The fluid region requiring calculation is extracted by volume extraction and Boolean operation.

[0070] In one embodiment, the step of dividing the finite element grid for each geometric model is specifically: the finite element grid is divided by using the method of unstructured tetrahedral mesh for each geometric model, and the region of the corresponding stirring paddle of each geometric model is subjected to encryption processing.

[0071] In one embodiment, the viscosity change of the lithium battery slurry conforms to the pseudoplastic fluid;

[0072] The power-law fluid model is used to simulate the non-Newtonian fluid, and the power-law fluid satisfies wherein, is the shear stress, K is the consistency coefficient, is the shear strain rate, n is the power-law index, and n <1.

[0073] In one embodiment, the calculation equation of the Reynolds coefficient of the non-Newtonian fluid is:

[0074] ; wherein: Re is a dimensionless number; V is the average flow velocity, m / s; D is the stirring paddle diameter, mm; is the fluid density, kg / m 3 , n is the power-law index.

[0075] In one embodiment, the component transport equation is: wherein is the density of the fluid, is the velocity of the fluid, is the mass fraction of the tracer, is the diffusion coefficient of the tracer in the fluid, wherein is the diffusivity of the tracer, is the source term, no chemical reaction is involved in the numerical simulation process of lithium battery slurry mixing, the value of t is 0, and t is time.

[0076] The application also provides an optimization device for a lithium battery slurry mixing equipment based on fluid mechanics simulation, comprising:

[0077] a geometric model establishing module, configured to establish geometric models of a plurality of lithium battery slurry mixing equipments;

[0078] a model simplification and extraction module, configured to perform model simplification processing on each of the geometric models respectively, and extract fluid regions that need to be calculated;

[0079] a division module, configured to divide each of the geometric models into finite element meshes, and perform encryption processing on a local region of an agitator of each of the geometric models, to obtain a mesh file of each of the geometric models;

[0080] an integral processing module, configured to determine a basic control equation of a calculation flow field of lithium battery slurry mixing, and perform volume integral processing on the basic control equation;

[0081] a flow field solving module, configured to obtain physical parameters of initial conditions and boundary conditions, perform steady-state flow field solving on a calculation fluid model of an agitator tank of each of the geometric models through a solver, and obtain corresponding solving results; wherein the physical parameters include a preset rotating speed of the agitator in the agitator tank of the geometric model;

[0082] a residual error judging module, configured to perform residual error judging on the solving results corresponding to each of the geometric models respectively; if the residual error converges, the solving results are saved;

[0083] an equation establishing module, configured to establish a component transport equation, add a tracer, and perform transient-state solving on a calculation fluid model in an agitator tank of each of the geometric models, to obtain fluid parameters of the agitator tanks of the plurality of geometric models, and take the results of the steady-state solving of each geometric model as initial values of the component transport equation;

[0084] The parameter processing module is used to post-process the fluid parameters of the stirring tank of each geometric model to obtain the stirring and mixing data of the concentration of the tracer in the stirring tank of the corresponding geometric model as a function of time, as well as the velocity cloud map data of the flow field in the stirring tank.

[0085] The comparison output module is used to compare the mixing data of the stirring tanks of multiple geometric models, and to take the geometric model corresponding to the optimal mixing data as the design model of the lithium battery slurry mixing equipment.

[0086] This application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the above embodiments.

[0087] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0088] Taking the structural optimization of a type of lithium battery slurry mixing equipment as an example, the original slurry-type lithium battery slurry mixing equipment is shown in the figure below. Figure 1 As shown. To better understand the technical solution and beneficial effects of this application, the following detailed description is provided in conjunction with specific embodiments:

[0089] like Figure 2 As shown, an optimization method for a lithium battery slurry mixing device based on fluid dynamics simulation in one embodiment includes some or all of the following steps:

[0090] S101, Establish geometric models of several lithium battery slurry mixing devices.

[0091] In this embodiment, geometric models of several lithium battery slurry mixing devices are established, that is, geometric models of at least two lithium battery slurry mixing devices are established. It should be noted that the limitation of "at least" mentioned in this disclosure includes the number itself, and so on below. For example, "at least two" includes the case where the quantity is two.

[0092] S103, each of the geometric models is simplified and the fluid region to be calculated is extracted.

[0093] In this embodiment, each geometric model is simplified, and the fluid region to be calculated is extracted. Specifically, each geometric model is imported into the SpaceClaim module of ANSYS (computer-aided engineering software, also known as CAE software) for model simplification, and the fluid region to be calculated is extracted. For example, if there are two geometric models, then there are two fluid regions that need to be calculated sequentially.

[0094] S105, dividing a finite element mesh for each of the geometric models, and performing encryption processing on a local area of the stirring paddle of each of the geometric models to obtain a mesh file of each of the geometric models.

[0095] In one embodiment, the step of dividing a finite element mesh for each of the geometric models is specifically: using a non-structured tetrahedral mesh method to divide a finite element mesh for each geometric model, and using a non-structured tetrahedral mesh method to perform encryption processing on the area of the corresponding stirring paddle of each of the geometric models. One geometric model corresponds to a geometric model of the original slurry type. In this embodiment, a non-structured tetrahedral method of the Mesh module of ANSYS is used to divide a finite element mesh for each of the geometric models, and encryption processing is performed on the local area of the stirring paddle of each of the geometric models to obtain a corresponding mesh file of each of the geometric models, while ensuring mesh quality and calculation accuracy.

[0096] Further, the local area of the stirring paddle of each of the geometric models is encrypted to obtain n different grid quantities of the calculation domain mesh, and grid independence verification is performed to select the optimal grid quantity of the calculation domain mesh to better ensure mesh quality and calculation time cost. Wherein n is an integer. For example, n is 4, and the grid quantity is 762536, that is, the calculation domain mesh with a grid quantity of 762536 is selected. The fluid calculation area mesh in the geometric model of the original paddle type is as shown in Figure 3 .

[0097] S107, determining the basic control equation of the calculation flow field of the lithium battery slurry mixing, and performing volume integral processing on the basic control equation.

[0098] In this embodiment, the basic control equation of the calculation flow field of the lithium battery slurry mixing is determined, and the basic control equation is volume integral processed. In one embodiment, the basic control equation includes a mass conservation equation and a momentum conservation equation; the step of determining the basic control equation of the calculation flow field of the lithium battery slurry mixing and performing volume integral processing on the basic control equation includes: first, determining the basic control equation of the calculation flow field of the lithium battery slurry mixing; second, performing volume integral processing on the mass conservation equation and the momentum conservation equation, respectively.

[0099] In one embodiment, the mass conservation equation is: ; and the momentum conservation equation is: ;

[0100] wherein, is the fluid density, t is the time, and the flow rate of any point in the fluid field VThe local velocity components of the fluid element are respectively u , v , w ; x , y , z The direction is the spatial direction position; p is the pressure in the fluid element; is the viscous stress acting on the surface of the element; is the gravity volume force in the direction of , is the external volume force in the direction of .

[0101] S109, the material properties corresponding to the lithium battery slurry added in the geometric model are obtained, and the medium flow model is determined according to the calculation equation of the Reynolds coefficient.

[0102] In this embodiment, the material properties corresponding to the lithium battery slurry added in the geometric model are obtained, and the medium flow model is determined according to the calculation equation of the Reynolds coefficient, wherein the material properties include density and viscosity; specifically, the material properties corresponding to the lithium battery slurry can be manually pre-set according to the actual situation to obtain the material properties corresponding to the lithium battery slurry added in the geometric model. For example, the density of the lithium battery slurry is set to 1600 kg / m 3 , the viscosity is set to a non-Newtonian fluid, and further, when setting the data, the minimum viscosity is set to 10000 cP, and the maximum viscosity is set to 100000 cP, and the viscosity of the lithium battery changes between the maximum viscosity and the minimum viscosity.

[0103] Further, the formula is used for calculation, wherein τ is the shear stress, K is the consistency coefficient, γ is the shear strain rate, and n is the power-law index; wherein two groups of τ and γ data are obtained by measurement, that is, two groups of data (τ1, γ1) and (τ2, γ2) are obtained by measurement, and then the data K and n are calculated by the formula. In this embodiment, for the lithium battery slurry, the consistency coefficient K is calculated to be 5, and the power-law index n is calculated to be 0.5.

[0104] In this embodiment, the consistency coefficient K is 5, and the power-law index n is 0.5. When n < 1, it represents a pseudoplastic fluid, shear thinning; when n = 1, it represents a Newtonian fluid; when n > 1, it represents an extensional fluid, shear thickening.

[0105] In one embodiment, the viscosity of the lithium battery slurry changes in accordance with a pseudoplastic fluid; a power-law fluid model is used to simulate a non-Newtonian fluid, and the power-law fluid satisfies , wherein is the shear stress, K is the consistency coefficient, Shear rate, n Power law index, and n <1.

[0106] In one embodiment, the Reynolds number of the non-Newtonian fluid is calculated by the following equation:

[0107] ; wherein: Re is a dimensionless number; if Re≤2000, it is in a laminar state; if Re>2000, it is in a turbulent state; V is the average flow rate, m / s; D is the diameter of the stirring paddle, mm; is the fluid density, kg / m 3 In this embodiment, D=0.69m; p=1600kg / m 3 ; V=0.73m / s; K is 5; n is 0.5; Re is calculated by substituting the formula to be 419.42, i.e. Re is less than 2000. Since Re is less than 2000, the viscosity model is set to the laminar flow model.

[0108] S111, obtaining the physical parameters of the initial conditions and the boundary conditions, and solving the steady flow field of the computational fluid model of the stirring tank of each geometric model by the solver to obtain the corresponding solution results.

[0109] In this embodiment, the physical parameters of the initial conditions and the boundary conditions are obtained, and the steady flow field of the computational fluid model of the stirring tank of each geometric model is solved by the solver to obtain the corresponding solution results; wherein the physical parameters include the preset rotating speed of the stirring paddle in the stirring tank of the geometric model. In one embodiment, the preset rotating speed of the stirring paddle is 35rpm~50rpm. In this embodiment, the preset rotating speed of the stirring paddle is 40rpm. The stirring paddle rotating area is set as multiple reference systems, i.e. the stirring paddle rotating area is processed by the multiple reference system method. It should be noted that the boundary conditions include setting the blade area as a dynamic area, setting other areas as static areas, and data exchange between the dynamic and static areas is completed through the exchange surface interface. The stirring tank wall is set as a stationary boundary, the blade wall is in a dynamic area, the fluid relative to the dynamic area is stationary, the boundary is set as a rotating wall, and the speed is set to 0. The stirring shaft wall is in a static area, relative to the surrounding stationary liquid, and is in motion, the boundary is set as a rotating wall, and the speed is consistent with the rotating speed of the stirring paddle.

[0110] S113, respectively judging the residual error of the solution results corresponding to each geometric model; if the residual error converges, the solution results are saved.

[0111] In the embodiment, the residual error of each geometric model is judged respectively. If the residual error converges, the solving result is saved as the initial condition for the concentration field calculation. The flow field velocity nephogram and the trace diagram of the original propeller type are shown in FIG. 8, and the flow field velocity nephogram and the trace diagram of the optimal propeller type are shown in FIG. 9. On the contrary, if the residual error does not converge, the boundary condition is reset, as shown in FIG. 10. Figure 4 Figure 5 Figure 6

[0112] S115, the component transport equation is established, the tracer is added, and the transient solution of the computational fluid model in each stirring tank of the geometric model is performed to obtain the fluid parameters of the stirring tank of the geometric model.

[0113] Figure 7 FIG. 11 shows the schematic diagram of the tracer feeding position and the monitoring point. In the embodiment, the component transport equation is established, the tracer is added, and the transient solution of the computational fluid model in each stirring tank of the geometric model is performed to obtain the fluid parameters of the stirring tank of the geometric model, and the concentration field calculation is realized. The result of the steady-state solution of each geometric model is taken as the initial value of the component transport equation.

[0114] In one embodiment, the material parameters of the tracer are the same as the material parameters of the lithium battery slurry. In the embodiment, the material parameter characteristics of the tracer are set to be the same as the material parameter characteristics of the lithium battery slurry. In the Patch module of ANSYS FLUENT, the concentration of the feeding area is set to 1, and the concentration of other areas is set to 0, and the concentration monitoring point is established, as shown in FIG. 12, to confirm the addition area of the tracer. Further, the transient solution of the computational fluid model in the stirring tank is performed again, and only the component transport equation is solved, and the flow equation is closed. Figure 7

[0115] In one embodiment, the component transport equation is as follows: wherein is the density of the fluid, is the velocity of the fluid, is the mass fraction of the tracer, is the diffusion coefficient of the tracer in the fluid, wherein is the diffusion rate of the tracer, is the source term, and the numerical simulation process of the lithium battery slurry mixing does not involve chemical reaction, the value of is 0, and t is time.

[0116] ​​​​S117, post-processing the fluid parameters of the stirred tank of each of the geometric models to obtain the stirring mixing data of the tracer concentration of the stirred tank of the corresponding geometric model changing with time and the flow field velocity cloud atlas data in the stirred tank.

[0117] In this embodiment, the fluid parameters of the stirred tank of each of the geometric models are post-processed to obtain the stirring mixing data of the tracer concentration of the stirred tank of the corresponding geometric model changing with time.

[0118] Further, the step of post-processing the fluid parameters of the stirred tank of each of the geometric models comprises: first, establishing the data plotting of the plurality of monitoring points of each geometric model to obtain the tracer concentration changing with time curve, thereby obtaining a plurality of tracer concentration changing with time curves; wherein the monitoring point concentration changing with time curve of the original slurry type is as shown in Figure 8a , and the monitoring point concentration changing with time curve of the optimal slurry type is as shown in Figure 8b .

[0119] S119, comparing the stirring mixing data of the stirred tanks of the plurality of geometric models, and taking the geometric model corresponding to the optimal stirring mixing data as the design model of the lithium battery slurry mixing device.

[0120] In this embodiment, the stirring mixing data of the stirred tanks of the plurality of geometric models are compared, and the geometric model corresponding to the optimal stirring mixing data is taken as the design model of the lithium battery slurry mixing device (i.e. the optimal slurry type lithium battery slurry mixing device), that is, the geometric model corresponding to the shortest stirring uniform mixing time required under the same stirring effect condition is taken as the design model of the lithium battery slurry mixing device. In combination with Figure 8a and Figure 8b , it can be known that the monitoring point concentration changing with time curve of the optimal slurry type stirring paddle is superior to that of the original slurry type stirring paddle.

[0121] Specifically, the optimal (i.e. the optimal slurry type) stirring mixing data is 100s, that is, the shortest stirring uniform mixing time is 100s, which is shorter than the traditional (i.e. the original slurry type) stirring uniform mixing time (350s), so that the structure with the shortest time is determined to achieve the optimal mixing effect of the lithium battery slurry, and the optimal structure of the lithium battery slurry mixing device is realized. The optimal slurry type lithium battery slurry mixing device is as shown in Figure 9 .

[0122] The optimization method of the lithium battery slurry mixing equipment based on the fluid mechanics simulation, first, establishes a plurality of geometric models of lithium battery slurry mixing equipment; then, respectively, carries out model simplification processing on each geometric model, and extracts the fluid region to be calculated, that is, extracts the slurry region of the stirring tank of the geometric model; then, divides the finite element grid for each geometric model to obtain the grid file of each geometric model; then, determines the basic control equation of the calculation flow field of the lithium battery slurry mixing, and carries out volume integral processing on the basic control equation; then, obtains the material properties corresponding to the lithium battery slurry added in the geometric model, and determines the medium flow model according to the calculation equation of the Reynolds coefficient; then, obtains the physical parameters of the initial condition and the boundary condition, and carries out steady-state flow field solving on the calculation fluid model of the stirring tank of each geometric model through the solver to obtain the corresponding solving result; then, respectively, carries out residual judgment on the solving result corresponding to each geometric model; if the residual converges, the solving result is saved; then, establishes the component transport equation, adds the tracer, and respectively carries out transient solving on the calculation fluid model in the stirring tank of each geometric model to obtain the fluid parameters of the stirring tank of a plurality of geometric models, and takes the steady-state solving result of each geometric model as the initial value of the component transport equation; then, carries out post-processing on the fluid parameters of the stirring tank of each geometric model to obtain the stirring and mixing data of the concentration of the tracer of the stirring tank of the corresponding geometric model with time and the flow field velocity cloud map data in the stirring tank; finally, compares the stirring and mixing data of the stirring tank of a plurality of geometric models, and takes the geometric model corresponding to the optimal stirring and mixing data as the design model of the lithium battery slurry mixing equipment, so that the engineering problem of structural optimization of the lithium battery mixing equipment is realized through the computational fluid mechanics analysis, the design method of the lithium battery mixing equipment is simple and convenient; the optimization method solves the problem that the traditional optimization design needs to judge the stirring effect of the lithium battery mixing equipment through experiments, which consumes a lot of time and money, so that the research and development cost of the optimization method is lower, the flow field simulation analysis is carried out in the stirring tank, not only the time required for the structural optimization of the lithium battery mixing equipment is greatly shortened, that is, the research and development time of the lithium battery mixing equipment is shortened, but also the problem of poor test effect of the traditional lithium battery mixing equipment is solved, so that the lithium battery mixing equipment after optimization better meets the actual production needs of the battery mixing equipment.

[0123] In one embodiment, the step of extracting the fluid region to be calculated is specifically: extracting the fluid region to be calculated through volume extraction and Boolean operation to improve the extraction reliability of the fluid region.

[0124] Further, the step of transiently solving the computational fluid model in each of the mixing tanks of the geometric model is specifically: on the basis of the steady flow field calculation result, the mixing transient of the tracer is solved, the result after the steady calculation converges is taken as the initial value, and then the transient calculation is performed, and only the component transport equation needs to be calculated.

[0125] Compared with the traditional optimization design method through experimental structure, the optimization method has the following advantages:

[0126] (1) The computational fluid dynamics software can provide data and flow field information which are difficult to obtain by experimental method; the mixing effect of lithium battery slurry in the mixing tank can be described by using the tracer method.

[0127] (2) In the actual test process of the lithium battery mixing equipment, the lithium battery slurry as the material to be stirred has huge cost, and good effect is not necessarily obtained, the computational fluid dynamics software only needs to be simulated on the computer equipment, and a large amount of cost is saved.

[0128] (3) The researchers can directly evaluate the data to verify the new design by using the computational fluid dynamics software, which is helpful for technological innovation, and greatly shortens the research and development process of the lithium battery slurry mixing equipment.

[0129] The application also provides an optimization device for lithium battery slurry mixing equipment based on fluid mechanics simulation, comprising a geometric model establishing module, a model simplification extraction module, a division module, an integral processing module, a flow pattern determining module, a flow field solving module, a residual error judging module, an equation establishing module, a parameter processing module and a comparison output module; the geometric model establishing module is used for establishing geometric models of several lithium battery slurry mixing equipment; the model simplification extraction module is used for respectively performing model simplification processing on each geometric model and extracting fluid regions that need to be calculated; the division module is used for dividing finite element grids for each geometric model and performing encryption processing on local regions of stirring paddles of each geometric model to obtain grid files of each geometric model; the integral processing module is used for determining basic control equations of calculation flow fields of lithium battery slurry mixing and performing volume integral processing on the basic control equations; the flow pattern determining module is used for obtaining material properties corresponding to lithium battery slurry added in the geometric model and determining a medium flow model according to a Reynolds coefficient calculation equation; the flow field solving module is used for obtaining physical parameters of initial conditions and boundary conditions, performing steady-state flow field solving on calculation fluid models of stirring tanks of each geometric model through a solver to obtain corresponding solving results; wherein the physical parameters include preset rotating speeds of stirring paddles in the stirring tanks of the geometric models; the residual error judging module is used for respectively performing residual error judgment on solving results corresponding to each geometric model; if the residual error converges, the solving results are saved; the equation establishing module is used for establishing a component transport equation, adding a tracer and respectively performing transient solving on calculation fluid models in stirring tanks of each geometric model to obtain fluid parameters of stirring tanks of the plurality of geometric models, taking results of steady-state solving of each geometric model as initial values of the component transport equation; the parameter processing module is used for post-processing fluid parameters of stirring tanks of each geometric model to obtain stirring and mixing data of the tracers of the corresponding geometric models changing with time and flow field velocity nephogram data in the stirring tanks; and the comparison output module is used for comparing stirring and mixing data of stirring tanks of the plurality of geometric models and taking the geometric model corresponding to optimal stirring and mixing data as a design model of the lithium battery slurry mixing equipment.

[0130] In the embodiment, after the geometric model establishing module establishes the geometric models of a plurality of lithium battery slurry mixing devices, the model simplification extraction module performs model simplification processing on each geometric model respectively, and extracts the fluid region to be calculated, that is, extracts the slurry region of the stirring tank of the geometric model; then the division module divides each geometric model into finite element grids to obtain a grid file of each geometric model; then the integral processing module determines the basic control equation of the calculation flow field of the lithium battery slurry mixing, and performs volume integral processing on the basic control equation; then the flow pattern module obtains the material properties corresponding to the lithium battery slurry added into the geometric model, and determines the medium flow model according to the calculation equation of the Reynolds coefficient; then the flow field solving module obtains the physical parameters of the initial conditions and the boundary conditions, and performs steady-state flow field solving on the calculation fluid model of the stirring tank of each geometric model through a solver to obtain the corresponding solving result; then the residual error judgment module performs residual error judgment on the solving result corresponding to each geometric model respectively; if the residual error converges, the solving result is saved; then the equation establishing module establishes the component transport equation, adds a tracer, and performs transient solving on the calculation fluid model in the stirring tank of each geometric model to obtain the fluid parameters of the stirring tank of a plurality of geometric models, and takes the steady-state solving result of each geometric model as the initial value of the component transport equation; then the parameter processing module performs post-processing on the fluid parameters of the stirring tank of each geometric model to obtain the stirring and mixing data of the concentration of the tracer of the stirring tank of the corresponding geometric model with time and the flow field velocity cloud map data in the stirring tank; finally, the comparison and output module compares the stirring and mixing data of the stirring tank of a plurality of geometric models, and takes the geometric model corresponding to the optimal stirring and mixing data as the design model of the lithium battery slurry mixing device, so that the engineering problem of structure optimization of the lithium battery mixing device is realized through computational fluid dynamics analysis, and the design method of the lithium battery mixing device is simple and convenient; the above-mentioned optimization method solves the problem that the traditional optimization design needs to judge the stirring effect of the lithium battery mixing device through experiments, which consumes a large amount of time and money, so that the research and development cost of the optimization method is relatively low, the flow field simulation analysis is performed in the stirring tank, the time required for the structure optimization of the lithium battery mixing device is greatly shortened, that is, the research and development time of the lithium battery mixing device is shortened, and the problem of poor experimental effect of the traditional lithium battery mixing device is solved, so that the lithium battery mixing device after optimization better meets the actual production needs of the battery mixing device.

[0131] The application also provides a computer device, which can be a server, and an internal structure diagram of the computer device can be as shown in Figure 10As shown in the figure. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for data storage of geometric models, material properties, Reynolds number calculation equations, etc. The network interface of the computer device is used for communication connection with external terminals through the network. The computer program is executed by the processor to implement the steps of the method described in any of the above embodiments.

[0132] Those skilled in the art can understand that, Figure 10 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0133] In one of the embodiments, the present application also provides a computer device including a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0134] In one of the embodiments, the present application also provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0135] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiments. Any reference to memory, storage, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0136] Compared with the prior art, the present application has at least the following advantages:

[0137] 1. The optimization method of the lithium battery slurry mixing equipment based on the fluid mechanics simulation, first, a plurality of geometric models of the lithium battery slurry mixing equipment are established; then, each geometric model is subjected to model simplification processing, and a fluid region to be calculated is extracted, that is, a slurry region of a stirring tank of the geometric model is extracted; then, each geometric model is divided into a finite element grid to obtain a grid file of each geometric model; then, basic control equations of a calculation flow field of the lithium battery slurry mixing are determined, and the basic control equations are subjected to volume integral processing; then, material properties corresponding to the lithium battery slurry added into the geometric model are obtained, and a medium flow model is determined according to a calculation equation of a Reynolds coefficient; then, physical parameters of initial conditions and boundary conditions are obtained, and a solver is used to perform steady-state flow field solving on a calculation fluid model of the stirring tank of each geometric model to obtain a corresponding solving result; then, the solving result corresponding to each geometric model is subjected to residual error judgment; if the residual error converges, the solving result is saved; then, a component transport equation is established, a tracer is added, and transient solving is performed on the calculation fluid model in the stirring tank of each geometric model to obtain fluid parameters of the stirring tank of a plurality of geometric models, and the steady-state solving result of each geometric model is used as an initial value of the component transport equation; then, the fluid parameters of the stirring tank of each geometric model are subjected to post-processing to obtain stirring and mixing data of the concentration of the tracer of the stirring tank of the corresponding geometric model with time and flow field velocity cloud map data in the stirring tank; and finally, the stirring and mixing data of the stirring tank of a plurality of geometric models are compared, and the geometric model corresponding to the optimal stirring and mixing data is used as a design model of the lithium battery slurry mixing equipment, so that the engineering problem of structural optimization of the lithium battery mixing equipment is realized through computational fluid mechanics analysis, and the design method of the lithium battery mixing equipment is simple and convenient.

[0138] 2. The optimization method, solves the problem that a large amount of time and money is spent in judging the stirring effect of the lithium battery mixing equipment through experiments in the traditional optimization design, so that the research and development cost of the optimization method is low, and the flow field simulation analysis is performed in the stirring tank, so that the time required for the structural optimization of the lithium battery mixing equipment is greatly shortened, that is, the research and development time of the lithium battery mixing equipment is shortened, and the problem of poor experimental effect of the traditional lithium battery mixing equipment is solved, so that the lithium battery mixing equipment after optimization better meets the actual production needs of the battery mixing equipment.

[0139] The above-described embodiments only express several embodiments of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. An optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation, characterized in that, include: Establish geometric models of several lithium battery slurry mixing devices; Each of the geometric models is simplified, and the fluid region to be calculated is extracted. Each geometric model is meshed with a finite element mesh, and the local area of ​​the stirring impeller of each geometric model is refined to obtain the mesh file of each geometric model. The basic governing equations for the computational flow field of lithium battery slurry mixing are determined, and the basic governing equations are then subjected to volume integration. Obtain the material properties corresponding to the lithium battery slurry added to the geometric model, and determine the medium flow model according to the calculation equation of the Reynolds coefficient; wherein the material properties include density and viscosity; The physical parameters and boundary conditions of the initial conditions are obtained, and the steady-state flow field of the computational fluid model of the stirring tank of each geometric model is solved by the solver to obtain the corresponding solution results; wherein the physical parameters include the preset rotation speed of the stirring blade in the stirring tank of the geometric model. Perform residual judgment on the solution results corresponding to each of the geometric models; If the residual converges, the solution result is saved. Component transport equations are established, tracers are added, and then the computational fluid dynamics model in the stirred tank of each geometric model is solved transiently to obtain the fluid parameters of the stirred tank of multiple geometric models. The steady-state solution of each geometric model is used as the initial value of the component transport equation. The fluid parameters of the stirred tank of each geometric model are post-processed to obtain the stirring and mixing data of the tracer concentration changing with time and the velocity cloud map data of the flow field in the stirred tank of the corresponding geometric model. The mixing data of the stirring tanks of multiple geometric models are compared, and the geometric model corresponding to the optimal mixing data is used as the design model of the lithium battery slurry mixing equipment.

2. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The fundamental governing equations include the mass conservation equation and the momentum conservation equation; The steps of determining the fundamental governing equations for the computational flow field of lithium battery slurry mixing and performing volume integration on these fundamental governing equations include: Determine the fundamental governing equations for the computational flow field of lithium battery slurry mixing; The mass conservation equation and the momentum conservation equation are respectively processed by volume integration.

3. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 2, characterized in that, The mass conservation equation is: The momentum conservation equation is: ; in, For fluid density, t Let time be the velocity at any point within the fluid field. V The local velocity components are respectively u , v , w ; x , y , z The directions are spatial positions; p is the pressure in the fluid element. It is the viscous stress acting on the surface of the micro-element; for Gravitational volume force in the direction of gravity for External volume force in the direction.

4. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The specific steps for extracting the fluid region to be calculated are as follows: The fluid region to be calculated is extracted through volume extraction and Boolean operations.

5. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The specific steps for dividing each geometric model into finite element meshes are as follows: finite element meshes are divided for each geometric model using an unstructured tetrahedral mesh method, and the mesh is refined in the region corresponding to the stirring impeller of each geometric model.

6. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The viscosity change of the lithium battery slurry conforms to that of a pseudoplastic fluid; A power-law fluid model is used to simulate non-Newtonian fluids, wherein the power-law fluid satisfies ,in For shear stress, K This is the consistency coefficient. Shear strain rate n It is the power-law exponent, and n <1.

7. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The equation for calculating the Reynolds coefficient of a non-Newtonian fluid is: ;in: Re It is a dimensionless number; V The average flow velocity is m / s; D is the diameter of the impeller, mm. Fluid density, kg / m³ 3 ，n This is the power-law exponent.

8. The optimization method for lithium battery slurry mixing equipment based on fluid dynamics simulation according to claim 1, characterized in that, The component transport equation is as follows: ,in For the density of the fluid, For the velocity of the fluid, The mass fraction of the tracer. The diffusion coefficient of the tracer in the fluid is denoted as . ,in The diffusivity of the tracer, As a source term, the numerical simulation of lithium battery slurry mixing does not involve chemical reactions. The value is 0. t For time.

9. An optimization device for lithium battery slurry mixing equipment based on fluid dynamics simulation, characterized in that, include: The geometric model building module is used to build geometric models of several lithium battery slurry mixing devices. The model simplification and extraction module is used to simplify each of the geometric models and extract the fluid regions that need to be calculated. The meshing module is used to divide each geometric model into finite element meshes and to refine the local area of ​​the stirring impeller of each geometric model to obtain the mesh file of each geometric model. An integral processing module is used to determine the basic control equations of the computational flow field for mixing lithium battery slurry, and to perform volume integral processing on the basic control equations. The flow pattern determination module is used to obtain the material properties corresponding to the lithium battery slurry added to the geometric model, and to determine the medium flow model based on the calculation equation of the Reynolds coefficient. The flow field solution module is used to obtain the physical parameters and boundary conditions of the initial conditions, and to perform steady-state flow field solution on the computational fluid model of the stirred tank of each geometric model through the solver to obtain the corresponding solution results; wherein the physical parameters include the preset rotational speed of the stirring blade in the stirred tank of the geometric model. The residual judgment module is used to perform residual judgment on the solution results corresponding to each of the geometric models. If the residual converges, the solution result is saved. The equation building module is used to build component transport equations and add tracers. Then, the computational fluid model in the stirred tank of each geometric model is solved transiently to obtain the fluid parameters of the stirred tank of multiple geometric models. The steady-state solution of each geometric model is used as the initial value of the component transport equation. The parameter processing module is used to post-process the fluid parameters of the stirring tank of each geometric model to obtain the stirring and mixing data of the concentration of the tracer in the stirring tank of the corresponding geometric model as a function of time, as well as the velocity cloud map data of the flow field in the stirring tank. The comparison output module is used to compare the mixing data of the stirring tanks of multiple geometric models, and to take the geometric model corresponding to the optimal mixing data as the design model of the lithium battery slurry mixing equipment.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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