Method for oven performance optimization based on thermal fluid-structure coupling and rare substance transfer field simulation
By using simulation methods based on thermal-fluid-structure interaction and rare-mass transport field, the structure and process parameters of the lithium battery electrode oven were optimized, solving the problem of insufficient oven performance in the existing technology. This enabled uniform drying and moisture removal of the electrode sheets, reducing production risks and costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEFEI GUOXUAN HIGH TECH POWER ENERGY
- Filing Date
- 2026-03-09
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies lack simulation optimization methods for lithium battery electrode ovens, which makes it impossible for baking equipment to effectively ensure uniform drying and moisture removal of the electrode sheets. This poses a risk of equipment performance not meeting requirements and production defects, and it is also impossible to directly determine the moisture distribution.
Based on the method of heat-fluid-structure interaction and rare substance transfer field simulation, a three-dimensional model of the oven and a fluid flow region model are constructed. The oven structure and process parameters are optimized through simulation model, including unidirectional coupling simulation of flow field, solid and fluid heat transfer, surface radiation and rare substance transfer physical field. The three-dimensional structure and process parameters are adjusted to meet the preset temperature uniformity and moisture concentration requirements.
By using simulation optimization methods, the oven optimization cycle was shortened, production costs were reduced, uniform drying and moisture removal of the electrode sheets were ensured, production defects caused by insufficient equipment performance were avoided, and a comprehensive evaluation of the oven performance was achieved.
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Figure CN122174736A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method for optimizing oven performance based on thermal-fluid-structure interaction and rare-material transport field simulation, belonging to the field of baking and drying simulation design. Background Technology
[0002] Lithium-ion battery electrodes are granular coatings. During electrode fabrication, a uniform wet slurry is applied to a metal current collector; this step is called coating. Then, drying evaporates the water and other solvents from the wet slurry, solidifying the wet film; this step is the post-coating baking and drying process. Drying is divided into three stages: a transition stage, a constant-rate drying stage, and a decreasing-rate drying stage. Each stage has different requirements for process parameters such as temperature and airflow. The baking rate and uniformity at each stage affect the final coated electrode's thickness, areal density, and other properties that determine electrode quality. Furthermore, some production lines, such as pre-lithiation lines, involve other baking equipment like uncoated baking, all of which have strict requirements for electrode drying. Therefore, it is necessary to ensure that the oven's structural design and process parameters meet the coating's quality requirements. Simulation of oven temperature rise is used to prevent issues caused by unreasonable equipment structure leading to unsatisfactory oven performance, thus mitigating risks in advance and reducing experimental verification and production costs. Meanwhile, for the optimization and modification of existing drying ovens, simulation-based optimization can shorten the optimization cycle, promptly avoid electrode defects caused by oven drying problems, and prevent significant economic losses due to scrap, thus meeting production needs. Currently, there is a lack of simulation optimization methods specifically for lithium battery electrode drying ovens.
[0003] On the other hand, moisture in the electrodes is one of the key factors to control during lithium battery manufacturing. Moisture reacts with the electrolyte, consuming lithium ions and reducing battery capacity; it also generates gas during the reaction, leading to dangers such as battery swelling and leakage. Therefore, it is necessary to remove the moisture in the slurry during coating and before electrolyte injection using baking equipment. The baking equipment must ensure that moisture on both sides of the electrodes is evaporated and removed evenly and smoothly during baking, and the internal structure of the oven must be designed to prevent moisture accumulation and secondary contamination of the electrodes. This is related to the uniformity and flow of hot air in the oven, but the distribution of moisture can only be indirectly determined from the flow field or thermal field alone. The patent application with publication number CN108733945A, entitled "An Optimization Method for the Structure of a Suspended Drying Device Oven," belongs to the technical field of equipment in the printing and packaging industry. It discloses a method for determining the optimal structure of a suspended drying oven by measuring the velocity, temperature, and pressure values at different locations on the substrate under velocity, temperature, and pressure fields. However, it does not involve directly judging the distribution of moisture. Summary of the Invention
[0004] This invention provides a method for optimizing oven performance based on thermal-fluid-structure interaction and rare-material transport field simulation, which solves the problems disclosed in the background art.
[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: Oven performance optimization method based on heat-fluid-structure interaction and rare-mass transport field simulation: Construct a 3D model of the oven and a fluid flow region model, and build a simulation model based on the 3D model of the oven and the fluid flow region model; Obtain the oven process parameters; Using process parameters as boundary conditions, the flow field of the oven is simulated using a simulation model. If the wind speed on the surface of the electrode inside the oven does not meet the preset requirements in the flow field simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted until the wind speed on the surface of the electrode inside the oven meets the preset requirements. Using process parameters as boundary conditions, simulation models are used to simulate the physical fields of solid and fluid heat transfer, surface-to-surface radiation, and rare material transfer in the oven. The flow field is coupled with the physical fields of solid and fluid heat transfer and surface-to-surface radiation. If the temperature uniformity inside the oven does not meet the preset requirements in the simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted. The flow field and the physical field of rare substance transfer are coupled in one direction. If the moisture concentration in the oven does not meet the preset requirements in the simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted. The temperature uniformity and moisture concentration inside the oven simultaneously meet the preset requirements, and the adjusted three-dimensional structure and / or process parameters of the oven are output.
[0006] The technical effects achieved by the above method are: by establishing a simulation model of thermal-fluid-solid coupling and mass transfer of baking equipment, and optimizing the oven structure design and process parameters, the method is particularly suitable for the baking and drying of electrode sheets in the lithium battery industry.
[0007] Furthermore, the oven process parameters include: hot air temperature at the air inlet and outlet, temperature or heating power of the oil roller, pressure or flow rate at the air inlet and outlet, and moisture content of the workpiece and incoming electrode sheets; flow rate and temperature are used as input conditions for the air inlet, flow rate is used as input conditions for the air outlet, open boundary is used as input conditions for the inlet and outlet, and temperature is used as input conditions for the oil roller; concentration is used as input conditions for the moisture content of the incoming electrode sheets.
[0008] The technical effect achieved by the above method is that selecting process parameters as the optimization object makes it easier to make corresponding adjustments based on the simulation results.
[0009] Furthermore, the method for building a simulation model based on the 3D model of the oven and the fluid flow region model includes: selecting "conjugate heat transfer, turbulence, k-epsilon", "dilute mass transfer", and "surface-to-surface radiation" as the physics field, and selecting "steady state" as the research mode; when selecting "conjugate heat transfer, turbulence, k-epsilon", the default output physics field interfaces are "solid and fluid heat transfer" and "turbulence, k-epsilon"; and importing the 3D model of the oven in the general format into the simulation model. The fluid region model of the laser welding dust removal system is obtained using Boolean operations and deletion methods, while retaining the original 3D oven model. If the oven is a symmetrical model in terms of geometry, flow field, and thermal field, the model used is symmetrical along the x and y axes, and a preset scale oven model is used for simulation. In the geometry menu bar, select "Form Union". In the material selection, the material properties of the fluid domain and the oven are selected, with air used as the material property of the fluid domain, 304 stainless steel as the material property of the oven, 430 stainless steel as the material property of the conveyor roller, and the electrode slurry property as the electrode material property.
[0010] The technical effect achieved by the above method is to make the simulation effect closer to the actual production process.
[0011] Furthermore, the method of using process parameters as boundary conditions to simulate the flow field of the oven using a simulation model includes: inputting process parameters as boundary conditions into the turbulent physical field; selecting the geometric model of air, i.e., the fluid region, in the turbulent physical field; setting the air inlet and return air inlet as velocity inlets; setting the inlet and outlet as open boundaries with zero normal stress, where zero normal stress means the inlet is connected to the external environment and the relative pressure is zero; setting the symmetrical fluid surface as a symmetrical boundary; creating a boundary layer using a hexahedral mesh at the wall surface and dividing the remaining parts using a tetrahedral mesh; and using a direct solver or an iterative solver to solve the simulation results.
[0012] The technical effect achieved by the above method is that the simulation results of the flow field can reveal the airflow situation in the oven, and the rationality of the structure can be preliminarily judged based on the flow field results.
[0013] Furthermore, the method for simulating the solid and fluid heat transfer physical field of an oven using a simulation model with process parameters as boundary conditions includes: inputting process parameters as boundary conditions into the solid and fluid heat transfer physical field; selecting all domains in the solid and fluid heat transfer physical field, setting the oven geometry as solid, and the air geometry as fluid; setting the initial temperature as the workshop ambient temperature, and setting the oven air inlet and oil roller as temperature heat sources; setting the oven return air inlet as an outflow condition; setting the oven inlet and outlet as open boundaries, and setting their upstream temperature as the workshop temperature; setting the oven outer surface and the surfaces adjacent to the inlet and outlet as heat flux boundary conditions and setting corresponding heat transfer coefficients, the corresponding heat transfer coefficients being determined based on the oven's insulation effect, with smaller values indicating better insulation; inputting the external temperature within the heat flux boundary conditions on the oven surface; setting symmetrical fluid and solid surfaces as symmetrical boundaries; this physical field node is used for calculating heat conduction and heat convection.
[0014] The technical effect achieved by the above method is that it can measure the heat conduction and heat convection performance of the oven.
[0015] Furthermore, the method of using process parameters as boundary conditions and employing simulation models to calculate the surface-to-surface radiation physical field includes: inputting process parameters as boundary conditions into the surface-to-surface radiation physical field; selecting the surface where the solid and fluid intersect in the surface-to-surface radiation physical field, i.e., the surfaces of all structures within the oven; setting the refractive index of the transparent medium to 1; selecting "two perpendicular symmetry planes" in "Symmetry of surface-to-surface radiation"; and selecting the intersecting axis and symmetry point; this physical field node is for calculating thermal radiation.
[0016] The technical effect achieved by the above method is that it can measure the thermal radiation performance of the oven.
[0017] Furthermore, the method of simulating the physical field of rare substance transport using a simulation model with process parameters as boundary conditions includes: inputting process parameters as boundary conditions into the rare substance transport physical field; selecting the geometric model of air, i.e., the fluid region, within the rare substance transport physical field; setting the initial value as the moisture content in the workshop; setting the air inlet as the inflow boundary condition; setting the return air outlet as the outflow boundary condition; setting the inlet and outlet as open boundaries; setting the electrode as the concentration boundary condition and inputting the maximum value of the incoming material concentration; setting the symmetrical fluid surface as the symmetrical boundary; and using this physical field node to calculate the moisture distribution.
[0018] The technical effect achieved by the above method is that the physical field of dilute substances is used to calculate the case where the moisture content in the air is low, the solute only interacts with the solvent, and the density of the solvent is equal to the density of the solute. This method is suitable for scenarios in the lithium battery industry where the moisture content of the baked electrode sheets is high.
[0019] Furthermore, the method for unidirectionally coupling the flow field with the physical fields of solid and fluid heat transfer, surface-to-surface radiation, and rare matter transfer includes: establishing "non-isothermal flow," "surface-to-surface radiation heat transfer," and "reactive flow, rare matter" in the corresponding physical fields; selecting "turbulent flow, k-epsilon," and "solid and fluid heat transfer" in the coupling interface of non-isothermal flow; selecting "solid and fluid heat transfer" and "surface-to-surface radiation" in the coupling interface of surface-to-surface radiation heat transfer; and selecting "turbulent flow, k-epsilon," and "rare matter transfer" in the coupling interface of reactive flow, rare matter. In the solver, select steady state. In the physics interface, check "Solid and fluid heat transfer", "Surface to surface radiation" and "Reactive flow, dilute matter". In the corresponding physics coupling interface, check "Non-isothermal flow", "Surface to surface radiation heat transfer" and "Reactive flow, dilute matter". Select the flow field calculation results in the value of the unsolved variables and perform unidirectional coupling simulation calculations of the flow field with the solid and fluid heat transfer physics field, the surface to surface radiation physics field and the dilute matter transfer.
[0020] The technical effect achieved by the above method is that the performance of the oven can be comprehensively judged by simulating the flow field results, thermal field results, and moisture concentration field results.
[0021] The beneficial effects achieved by this invention are as follows: the flow field results determine whether the flow trend meets expectations and whether there are eddies and dead zones; the thermal field results determine whether the temperature of the incoming material is uniform during baking and whether the temperature value meets the process requirements; and the moisture concentration field results determine whether there is a risk of moisture accumulation in the oven structure design. This fills the gap in verifying the baking performance of the oven during the design stage, controls the uniformity of the oven temperature and the flow path of air and moisture inside the oven from a technical perspective, shortens the optimization cycle and reduces cost investment, and achieves cost reduction and efficiency improvement. Attached Figure Description
[0022] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 This is a schematic diagram of a 3D model of an oven. Figure 3 A schematic diagram of the grid used to divide the oven; Figure 4 This is a schematic diagram of the airflow cross-section inside the oven; Figure 5 This is a schematic diagram of the temperature cross-section inside the oven; Figure 6 This is a schematic diagram of the moisture distribution inside the drying oven. Figure 7 A schematic diagram of the air velocity cross-section inside the drying oven after optimizing the positions of the air outlet and the conveyor rollers; Figure 8This is a schematic diagram of the temperature cross-section inside the optimized oven; Figure 9 This is a schematic diagram of the moisture distribution cross-section inside the optimized oven.
[0023] Figure label: 1. Cavity; 2. Air inlet; 3. Air outlet; 4. Conveyor roller; 5. Feed inlet; 6. Discharge outlet; 7. Passing roller; 8. Oil roller; 9. Electrode. Detailed Implementation
[0024] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.
[0025] like Figure 1 As shown, this invention provides a method for optimizing oven performance based on thermal-fluid-structure interaction and rarefied mass transport field simulation, including: A 3D model of the oven is constructed. This model is created using modeling and Boolean operations to construct the fluid region model of the oven, while retaining the original 3D model. Actual or designed process parameters are obtained to build a simulation model. These parameters include: inlet / outlet wind speed / pressure values, inlet temperature, workshop moisture content, maximum moisture content of incoming materials, fluid material properties, oven material properties, conveyor roller material properties, and conveyor roller temperature / heating power (if the conveyor roller has a heating function). Based on the constructed simulation model, the flow field simulation results of the oven are obtained, and the oven structural design or process parameters are optimized until the flow field results meet the requirements. The thermal field and moisture concentration field results are calculated using the flow field simulation results. When the differences between the thermal field and moisture concentration field results and the expectations exceed a set threshold, the corresponding 3D model structural design or process parameters of the oven are optimized, and the above steps are repeated. When the optimized simulation model's thermal field and moisture concentration field results are within the expected range, this is output as the final result. This method can be used for both optimizing design schemes and modifying the structure of floor-standing ovens.
[0026] The specific steps of this method are as follows: The first step is to create a 3D model of the oven in any 3D modeling software, such as... Figure 2As shown, the oven includes a cavity 1, an air inlet 2, an air return outlet 3, a conveyor roller 4, a feed inlet 5, and a discharge outlet 6. The cavity 1 has a feed inlet 5 and a discharge outlet 6 at both ends. The cavity 1 wall has multiple air inlets 2 and air return outlets 3, typically located above and below the cavity 1. These multiple air inlets 2 and air return outlets 3 can be designed with different sizes and structures according to requirements. A conveyor roller 4 is installed inside the cavity. The conveyor roller 4 can be designed without heating (e.g., a passing roller 7 or an oil roller 8). In this invention, the incoming material is electrode sheets 9. The electrode sheets 9 can be conveyed horizontally along the same vertical direction within the cavity 1, or they can be conveyed horizontally in staggered vertical directions. This invention uses a conveyor belt path that staggers horizontally along vertical directions. The electrode sheet 9 enters the cavity 1 from the unwinding mechanism through the feed inlet 5, and is conveyed to the discharge outlet 6 by the conveyor roller 4. During this process, hot air from the air inlet 2 or the conveyor roller 4 with heating function heats the electrode sheet to achieve a drying effect. Finally, it is sent to the winding mechanism for winding. The model used in this invention can be simplified to an axisymmetric model in terms of geometry and physical field. Therefore, a 1 / 4 oven model is used for simulation to shorten the calculation time and improve efficiency. The three-dimensional model of the oven is converted into a common format of three-dimensional software, such as Parasolid format.
[0027] The second step is to open the COMSOL software, create a new 3D simulation model, select "Conjugate Heat Transfer, Turbulence, k-epsilon", "Dilute Mass Transfer", and "Surface-to-Surface Radiation" for the physics field, and select "Steady State" for the study. When "Conjugate Heat Transfer, Turbulence, k-epsilon" is selected, the software will output the "Solid and Fluid Heat Transfer" and "Turbulence, k-epsilon" physics field interfaces by default. Import the oven 3D model in the general format into the simulation model.
[0028] The third step is geometric model processing. A fluid region model of the oven is established in COMSOL, which is a three-dimensional model that covers the oven. The fluid region model of the laser welding dust removal system is obtained by Boolean operation-elimination method, while retaining the original three-dimensional model of the oven. If the oven is a symmetrical model in terms of geometry, flow field and thermal field, the simulation model can be simplified. The model used in this invention is symmetrical along the x and y axes, that is, 1 / 4 of the oven model is used for simulation. In the geometry menu bar, select "Form Union" to ensure that the mesh intersections of the subsequent solid domain and fluid domain are consistent.
[0029] The fourth step is to select material properties. In the material selection, the material properties of the fluid domain and the oven are selected. In this invention, air is used as the material property of the fluid domain, 304 stainless steel is used as the material property of the oven, 430 stainless steel is used as the material property of the conveyor roller, and the electrode slurry property is used as the electrode material property.
[0030] Step 5: Obtain the actual / designed process parameters. These parameters include the hot air temperature at the air inlet 2 and the return air outlet 3, the temperature or heating power (if any) of the oil roller 8, the pressure or flow rate at the air inlet 2 and the return air outlet 3, and the moisture content of the workshop and the incoming electrode sheets. The temperature is typically obtained by online temperature measuring devices such as thermocouples or by handheld measuring devices such as thermal imagers. The heating power is typically taken as the set value of the equipment. The flow rate or pressure is typically taken as the stable average value of the online monitoring flow rate, flow rate, or pressure measuring instrument on the equipment, or as the stable average value obtained at a designated measurement point in the pipeline using a handheld measuring instrument. The moisture content is obtained by sampling and testing with a Karl Fischer moisture meter, and the moisture content must be the maximum value within the process or monitoring range. This invention uses flow rate and temperature as input conditions for the air inlet, flow rate as input condition for the return air outlet, open boundary as input condition for the inlet and outlet, temperature as input condition for the oil roller, and concentration as input condition for the moisture content of the incoming electrode sheets.
[0031] Step 6: Input the process parameters as boundary conditions into the turbulent physical field, select the geometric model of air in the turbulent physical field, i.e. the fluid region, and set the air inlet and return air inlet as velocity inlets; set the inlet and outlet as open boundaries with zero normal stress, where the zero normal stress inlet means that the inlet is connected to the external environment and the relative pressure is zero; set the symmetrical fluid surface as a symmetrical boundary.
[0032] Step 7: Mesh generation. After the mesh is generated, check that there are no problems and proceed to the next step. If an error occurs, you need to modify the erroneous mesh and repair the mesh before proceeding to the next step. Figure 3 For the grid division of the oven, a hexahedral mesh is used to create the boundary layer on the wall, and a tetrahedral mesh is used for the rest. The inlet and outlet and the area near the electrode need to be appropriately refined.
[0033] Step 8: Flow field calculation and analysis. A new study is initiated. Since this invention focuses on the temperature and wind speed distribution inside the oven during steady-state operation, the flow and thermal fields within the oven can be considered as steady-state. Therefore, steady-state simulation calculations are performed during the solution period. When selecting a solver, either a direct solver or an iterative solver can be used. Direct solvers offer faster speed and higher accuracy, but have higher space complexity, placing higher demands on workstations or servers, and in some cases, the results are not easily converged. Iterative solvers take longer but consume fewer computational resources, and within a certain error tolerance range, the results are more likely to converge.
[0034] The ninth step is to post-process the flow field results, create a two-dimensional plotting group, select the cross section in the direction of the electrode belt or the width direction, and draw the wind speed cross section diagram of the protective gas. The wind speed on the electrode surface is judged based on the results of the two-dimensional plotting group. Figure 4This is a schematic diagram of the airflow cross-section inside the oven. If there are vortex dead zones around the electrode in the flow field, or if there is a significant difference between the simulated airflow and the design airflow, it is necessary to adjust the number and arrangement of the air inlets and outlets or the conveyor rollers, or adjust the airflow velocity at the air inlets and outlets. For example, adjust the position of the conveyor rollers to avoid areas where the airflow does not reach, i.e., reduce vortex dead zones; increase the number of air inlets or increase the airflow velocity at the air inlets in areas with low airflow. Recalculate the flow field results until the airflow uniformity on the electrode surface meets the requirements. Figure 7 A schematic diagram of the air velocity cross-section inside the oven after optimizing the position of the air outlet and the conveyor roller.
[0035] The flow field simulation results can reveal the airflow within the oven. These results can be used to initially assess the structural rationality. If numerous eddies or uneven wind speeds on the electrode surface are observed, the boundary conditions and three-dimensional structure must be verified for rationality. After fixing these issues, the simulation should be recalculated. The flow field simulation results only characterize the fluid velocity or mass flow rate. While they reflect the distribution trend of matter, they cannot directly reveal the temperature and moisture distribution. Therefore, it is necessary to calculate whether the protective gas covers the welding area using the thermal field and rarefied matter transfer physical field. The thermal field includes the three basic modes of heat transfer: conduction, convection, and radiation. The rarefied matter transfer physical field is used to calculate cases where the moisture content in the air is low. The solute interacts only with the solvent, and the solvent density is equal to the solute density. This is suitable for scenarios in the lithium battery industry where high moisture content in the baked electrodes is required.
[0036] Step 10: Begin the simulation setup for the thermal field and rarefied matter transfer physical field. After the flow field calculation is completed and confirmed to be problem-free, input the process parameters as boundary conditions into the solid and fluid heat transfer physical field. Select all domains in the solid and fluid heat transfer physical field, set the oven geometry as solid, and the air geometry as fluid; set the initial temperature to the workshop ambient temperature, and set the air inlet and oil roller as temperature heat sources; set the return air outlet as the outflow condition; set the inlet and outlet as open boundaries, and set their upstream temperature to the workshop temperature; set the outer surface of the oven and the surfaces adjacent to the inlet and outlet as heat flux boundary conditions and set the corresponding heat transfer coefficients. The corresponding heat transfer coefficients are determined based on the oven's insulation effect; the smaller the value, the better the insulation effect; input the external temperature within the heat flux boundary conditions of the oven surface, such as the corresponding workshop temperature, the temperature of the inlet and outlet air ducts, etc.; set the symmetrical fluid and solid surfaces as symmetrical boundaries; this physical field node is for calculating heat conduction and heat convection.
[0037] Step 11: Input the process parameters as boundary conditions into the surface-to-surface radiation physical field. Select the surface where the solid and fluid intersect in the surface-to-surface radiation physical field, i.e., the surface of all structures in the oven. Set the refractive index of the transparent medium to 1. Select "two perpendicular symmetry planes" in "symmetry of surface-to-surface radiation" and select the intersecting axis and symmetry point. This physical field node is for the calculation of thermal radiation.
[0038] Step 12: Input the process parameters as boundary conditions into the rare substance transfer physical field. Select the geometric model of air, i.e., the fluid region, in the rare substance transfer physical field. Set the initial value to the moisture content in the workshop. Set the air inlet as an inflow boundary condition. Set the return air outlet as an outflow boundary condition. Set the inlet and outlet as open boundaries. Set the electrode as a concentration boundary condition and input the maximum value of the incoming material concentration. Set the symmetrical fluid surface as a symmetrical boundary. This physical field node is for calculating the moisture distribution.
[0039] Step 13: Unidirectional coupling simulation calculation of the flow field with the thermal field and rare matter transfer field. The results of the thermal field and rare matter transfer field have almost no impact on the flow field results. Therefore, to save computational resources and improve efficiency, the flow field is unidirectionally coupled with the thermal field and rare matter transfer: "Non-isothermal flow," "Surface-to-surface radiation heat transfer," and "Reactive flow, rare matter" are established in the multiphysics field. In the coupling interface of the non-isothermal flow, "turbulent flow, k-epsilon," and "solid and fluid heat transfer" are selected; in the coupling interface of the surface-to-surface radiation heat transfer, "solid and fluid heat transfer" and "surface-to-surface radiation" are selected; and in the coupling interface of the reactive flow, rare matter, "turbulent flow, k-epsilon," and "rare matter transfer" are selected.
[0040] At this point, it is necessary to ensure that the mesh has not been modified after the above steps. If the mesh changes due to the update of the boundary condition settings, it will be impossible to correctly extract the data of the subsequent single-coupling flow field within the mesh. Therefore, steps seven and eight need to be recalculated. Only after the calculation is completed and no errors are reported can the next step be performed.
[0041] Step 14: Create a new study. In the solver, select steady state. In the physics interface, check "Solid and fluid heat transfer", "Surface to surface radiation", and "Reactive flow, dilute matter". In the multiphysics coupling interface, check "Non-isothermal flow", "Surface to surface radiation heat transfer", and "Reactive flow, dilute matter". In the values of unsolved variables, select the flow field calculation results from step 8 and perform a unidirectional coupling simulation calculation of the flow field, heat field, and dilute matter transfer physics field.
[0042] Step 15: After the unidirectional coupling simulation calculation of the flow field and thermal field is completed, post-processing is performed to create a two-dimensional plotting group, select the cross section in the direction of the electrode strip, and draw the temperature distribution map. The results of the two-dimensional plotting group are used to determine whether the temperature value and uniformity meet the requirements. Figure 5 This is a schematic diagram of the temperature cross-section. If the temperature uniformity does not meet the requirements, the three-dimensional structure or process parameters need to be adjusted, and the unidirectional coupling simulation of the flow field and thermal field needs to be recalculated until the temperature uniformity meets the requirements. Specifically: if the simulated temperature is lower than the design temperature, the temperature is increased by adding heat sources, that is, increasing the number or temperature of air inlets, or increasing the number or temperature of conveyor rollers with heating effect; conversely, if the simulated temperature is higher than the design temperature, the number and temperature of heat sources are reduced. Figure 8 This is a schematic diagram of the optimized temperature cross-section.
[0043] Step 16: After the unidirectional coupling simulation calculation of the flow field and the physical field of rare matter transfer is completed, post-processing is performed to create a two-dimensional plotting group, select the cross section in the direction of the electrode belt, and plot the mass fraction of moisture. The results of the two-dimensional plotting group are used to determine whether the moisture drying condition meets the requirements. Figure 6 This is a schematic diagram of the moisture distribution cross-section. Generally, if the moisture concentration difference exceeds 10%, i.e., the red area in the image extends beyond the electrode or exists in other areas of the oven, there is a risk of moisture accumulation in the excess area. Adjustments to the 3D structure or process parameters are necessary. For example, if the concentration in a certain area near the electrode is 10% higher than the design concentration, there is a risk of moisture accumulation in that area, meaning the baked electrode may have excessive moisture content. The airflow speed or temperature at that location needs to be increased, specifically involving the adjustment methods mentioned in steps nine and ten. The unidirectional coupling simulation of the flow field and the rarefied material transfer physical field should be recalculated until the moisture concentration reaches the required level. Figure 9 This is a schematic diagram of the optimized moisture distribution.
[0044] Step 17: Generate a simulation report.
[0045] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
[0046] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.
Claims
1. A method for optimizing oven performance based on thermal-fluid-structure interaction and rarefied mass transport field simulation, characterized in that: Construct a 3D model of the oven and a fluid flow region model, and build a simulation model based on the 3D model of the oven and the fluid flow region model; Obtain the oven process parameters; Using process parameters as boundary conditions, the flow field of the oven is simulated using a simulation model. If the wind speed on the surface of the electrode inside the oven does not meet the preset requirements in the flow field simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted until the wind speed on the surface of the electrode inside the oven meets the preset requirements. Using process parameters as boundary conditions, simulation models are used to simulate the physical fields of solid and fluid heat transfer, surface-to-surface radiation, and rare material transfer in the oven. The flow field is coupled with the physical fields of solid and fluid heat transfer and surface-to-surface radiation. If the temperature uniformity inside the oven does not meet the preset requirements in the simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted. The flow field and the physical field of rare substance transfer are coupled in one direction. If the moisture concentration in the oven does not meet the preset requirements in the simulation results, the three-dimensional structure and / or process parameters of the oven are adjusted. The temperature uniformity and moisture concentration inside the oven simultaneously meet the preset requirements, and the adjusted three-dimensional structure and / or process parameters of the oven are output.
2. The oven performance optimization method based on thermal-fluid-structure interaction and rare-mass transport field simulation according to claim 1, characterized in that, The oven process parameters include: hot air temperature at the air inlet and outlet, temperature or heating power of the oil roller, pressure or flow rate at the air inlet and outlet, and moisture content of the workpiece and incoming electrode sheets; flow rate and temperature are used as input conditions for the air inlet, flow rate is used as input conditions for the air outlet, open boundary is used as input conditions for the inlet and outlet, and temperature is used as input conditions for the oil roller; concentration is used as input conditions for the moisture content of the incoming electrode sheets.
3. The oven performance optimization method based on thermal-fluid-structure interaction and rarefaction mass transport field simulation according to claim 1, characterized in that, The method for building a simulation model based on a 3D model of an oven and a fluid flow region model includes: selecting "conjugate heat transfer, turbulence, k-epsilon", "dilute mass transfer", and "surface-to-surface radiation" as the physics field, and selecting "steady state" for the research; when selecting "conjugate heat transfer, turbulence, k-epsilon", the default output physics field interfaces are "solid and fluid heat transfer" and "turbulence, k-epsilon"; and importing the 3D model of the oven in the general format into the simulation model. The fluid region model of the laser welding dust removal system is obtained by using Boolean operations and deletion methods, while retaining the original 3D model of the oven. If the oven is a symmetrical model in terms of geometry, flow field, and thermal field, the model used is symmetrical along the x and y axes, and a preset scale oven model is used for simulation. In the geometry menu bar, select "Form Union". In the material selection, the material properties of the fluid domain and the oven are selected, with air used as the material property of the fluid domain, 304 stainless steel as the material property of the oven, 430 stainless steel as the material property of the conveyor roller, and the electrode slurry property as the electrode material property.
4. The oven performance optimization method based on thermal-fluid-structure interaction and rarefaction mass transport field simulation according to claim 1, characterized in that, The method of using process parameters as boundary conditions to simulate the flow field of an oven using a simulation model includes: inputting process parameters as boundary conditions into a turbulent physical field; selecting the geometric model of air, i.e., the fluid region, within the turbulent physical field; setting the air inlet and outlet as velocity inlets; setting the inlet and outlet as open boundaries with zero normal stress, where zero normal stress means the inlet is connected to the external environment and the relative pressure is zero; setting symmetrical fluid surfaces as symmetrical boundaries; creating a boundary layer using hexahedral meshes at the wall surface and dividing the remaining area using tetrahedral meshes; and using a direct solver or an iterative solver to solve the simulation results.
5. The oven performance optimization method based on thermal-fluid-structure interaction and rarefaction mass transport field simulation according to claim 1, characterized in that, The method for simulating the solid and fluid heat transfer physics field of an oven using process parameters as boundary conditions and a simulation model includes: inputting process parameters as boundary conditions into the solid and fluid heat transfer physics field; selecting all domains in the solid and fluid heat transfer physics field, setting the oven geometry as solid, and the air geometry as fluid; setting the initial temperature as the ambient temperature of the workshop, and setting the oven's air inlet and oil roller as temperature heat sources; setting the oven's return air inlet as an outflow condition; setting the oven's inlet and outlet as open boundaries, and setting their upstream temperature as the workshop temperature; setting the oven's outer surface and the surfaces adjacent to the inlet and outlet as heat flux boundary conditions and setting corresponding heat transfer coefficients, the corresponding heat transfer coefficients being determined based on the oven's insulation effect, with smaller values indicating better insulation; inputting the external temperature within the heat flux boundary conditions of the oven surface; setting symmetrical fluid and solid surfaces as symmetrical boundaries; this physics field node is used for calculating heat conduction and heat convection.
6. The oven performance optimization method based on thermal-fluid-structure interaction and rarefaction mass transport field simulation according to claim 1, characterized in that, The method of using process parameters as boundary conditions to simulate the surface-to-surface radiation physical field includes: inputting process parameters as boundary conditions into the surface-to-surface radiation physical field; selecting the surface where the solid and fluid intersect in the surface-to-surface radiation physical field, i.e., the surface of all structures in the oven; setting the refractive index of the transparent medium to 1; selecting "two perpendicular symmetry planes" in "symmetry of surface-to-surface radiation"; and selecting the intersection axis and symmetry point; this physical field node is for the calculation of thermal radiation.
7. The oven performance optimization method based on thermal-fluid-structure interaction and rarefied mass transport field simulation according to claim 1, characterized in that, The method of simulating the physical field of rare substance transport using a simulation model with process parameters as boundary conditions includes: inputting process parameters as boundary conditions into the rare substance transport physical field; selecting the geometric model of air, i.e., the fluid region, in the rare substance transport physical field; setting the initial value as the moisture content in the workshop; setting the air inlet as the inflow boundary condition; setting the return air outlet as the outflow boundary condition; setting the inlet and outlet as open boundaries; setting the electrode as the concentration boundary condition and inputting the maximum value of the incoming material concentration; setting the symmetrical fluid surface as the symmetrical boundary; and using this physical field node to calculate the moisture distribution.
8. The oven performance optimization method based on thermal-fluid-structure interaction and rarefaction mass transport field simulation according to claim 1, characterized in that, Methods for unidirectionally coupling the flow field with the physical fields of solid and fluid heat transfer, surface-to-surface radiation, and rare matter transfer include: establishing "non-isothermal flow," "surface-to-surface radiation heat transfer," and "reactive flow, rare matter" in the corresponding physical fields; selecting "turbulent flow, k-epsilon" and "solid and fluid heat transfer" in the coupling interface of non-isothermal flow; selecting "solid and fluid heat transfer" and "surface-to-surface radiation" in the coupling interface of surface-to-surface radiation heat transfer; and selecting "turbulent flow, k-epsilon" and "rare matter transfer" in the coupling interface of reactive flow, rare matter. In the solver, select steady state. In the physics interface, check "Solid and fluid heat transfer", "Surface to surface radiation" and "Reactive flow, dilute matter". In the corresponding physics coupling interface, check "Non-isothermal flow", "Surface to surface radiation heat transfer" and "Reactive flow, dilute matter". Select the flow field calculation results in the value of the unsolved variables and perform unidirectional coupling simulation calculations of the flow field with the solid and fluid heat transfer physics field, the surface to surface radiation physics field and the dilute matter transfer.