Thermal management and control simulation method for formation workshop

Abstract

The invention discloses a formation workshop heat management and control simulation method, which comprises the following steps: acquiring temperature change data of formation cabinets in the first time to obtain an actual temperature curve, enabling a single formation cabinet to be equivalent to a heating unit to obtain a power density curve and a simulation temperature curve, and calculating a simulation temperature curve according to the power density curve, obtaining a simulation temperature result and generating a simulation temperature curve; adjusting the preset power to enable the difference value between the simulation temperature curve and the actual temperature curve to be smaller than or equal to a first threshold value, determining the heating power of the formation cabinet, and performing formation process simulation of the formation workshop to obtain a temperature distribution cloud picture; according to the temperature distribution cloud picture, the layout and the number of the refrigerants in the formation workshop are optimized and adjusted, the optimal layout is obtained, and accurate input parameters are provided for the formation process simulation process of the formation workshop, so that the simulation result precision is improved, and the formation process effect and the battery quality in the actual production process are improved.

Description

Technical Field

[0001] The present invention relates to the field of lithium battery manufacturing, and more specifically, to a thermal management and control simulation method for a formation workshop. Background Art

[0002] The main steps of the formation process are to repeatedly charge and discharge the battery to eventually stabilize the battery parameters. During multiple charge and discharge processes, the battery will release a large amount of heat. If the released heat is not controlled, it will have an adverse effect on the formation process effect and even the battery quality.

[0003] The existing method of heat control in the chemical forming workshop through simulation usually treats the chemical forming cabinet as a single constant-temperature heat source, uses simulation software to calculate the heat flow field of the chemical forming workshop, and then sets the corresponding refrigerant quantity and layout. However, since the temperature of the chemical forming cabinet is affected by its own heating power, heat transfer coefficient and ambient temperature, the temperature measured by the above method is not equivalent to the actual heat generation of the chemical forming cabinet, which leads to inaccurate heat load input during the simulation calculation, resulting in reduced accuracy of the simulation results.

[0004] Therefore, there is an urgent need to provide a thermal management and control simulation method for a forming workshop that can treat a single forming cabinet as a single heating unit, provide more accurate input parameters for the simulation process, and thus improve the accuracy of the simulation results. Summary of the Invention

[0005] In view of this, the present invention provides a thermal management and control simulation method for a chemical forming workshop, comprising the steps of:

[0006] Collect the temperature change data of the forming cabinet in the first time and obtain the actual temperature curve;

[0007] The forming cabinet is equivalent to a heating unit to obtain the power density curve;

[0008] According to the power density curve, simulation analysis is performed to obtain the simulation temperature curve;

[0009] Adjusting the preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold;

[0010] Establishing a three-dimensional simulation model of the forming workshop to obtain a first three-dimensional model;

[0011] Conduct chemical formation process simulation to obtain temperature distribution cloud map;

[0012] According to the temperature distribution cloud map, the structure of the first three-dimensional model is adjusted so that the temperature in the first three-dimensional model is less than a second threshold.

[0013] Optionally, the forming cabinet is equivalent to a heating unit to obtain a power density curve, including the following steps:

[0014] Establishing a second three-dimensional model; the second three-dimensional model includes a formation cabinet and a plurality of lithium batteries disposed in the formation cabinet;

[0015] In the second three-dimensional model, setting a preset power and a preset time;

[0016] Performing a formation process simulation to obtain a power density curve, which is an image of a function expression of a preset power and a preset time;

[0017] Optionally, a simulation analysis is performed based on the power density curve to obtain a simulated temperature curve, including the following steps:

[0018] Meshing the second three-dimensional model and writing the process parameters into the second three-dimensional model;

[0019] Select the transient thermal analysis type and enter the process time and time step;

[0020] Add the first boundary condition and initial condition;

[0021] Entering a preset time and a corresponding preset power into the second three-dimensional model;

[0022] The second three-dimensional model is solved to obtain a simulation temperature result and generate a simulation temperature curve.

[0023] Optionally, adding a first boundary condition and an initial condition includes the steps of: setting a heat exchange condition; and setting an initial temperature.

[0024] Optionally, simulation analysis can be performed using finite element calculation software.

[0025] Optionally, before establishing the second three-dimensional model, the method further includes: obtaining process parameters of the formation cabinet, wherein the process parameters include thermal conductivity, density, and specific heat capacity.

[0026] Optionally, the first time is 15000s-18000s.

[0027] Optionally, the first three-dimensional model includes: at least two forming lines arranged in a forming workshop, an air outlet located at the top of the forming workshop and a refrigerant air inlet located at the side of the forming workshop, and the forming line includes at least two forming cabinets arranged at equal distances.

[0028] Optionally, the first threshold is 1°C-2°C, and the second threshold is 41°C-45°C.

[0029] Optionally, before performing the step of simulating the formation process and obtaining the temperature distribution cloud map, the method further includes: inputting test parameters into the first three-dimensional model, wherein the test parameters include inlet and outlet air volumes, refrigerant temperature and the preset power.

[0030] Compared with the prior art, the thermal management simulation method for a chemical forming workshop provided by the present invention achieves at least the following beneficial effects:

[0031] The present invention provides a thermal management and control simulation method for a forming workshop, comprising the steps of: collecting temperature change data of a forming cabinet within a first time period to obtain an actual temperature curve; since the heat generated by the forming cabinet cannot be quantitatively observed, a single forming cabinet can be equivalent to a heat generating unit to obtain a power density curve and a simulated temperature curve, thereby quantifying heat release data and improving simulation calculation accuracy; performing simulation analysis based on the power density curve to obtain a simulated temperature result and generate a simulated temperature curve; adjusting a preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold, determining the heat generation power of the forming cabinet, performing a forming process simulation of the forming workshop, and obtaining a temperature distribution cloud map; and optimizing and adjusting the layout and quantity of refrigerants in the forming workshop based on the temperature distribution cloud map to obtain an optimal layout, thereby avoiding the situation in existing simulation methods where the input temperature is not equal to the actual heat generated by the forming cabinet, further improving the accuracy of the simulation, providing relatively accurate input parameters for the forming process simulation process of the forming workshop, thereby improving the accuracy of the simulation result, and facilitating improving the forming process effect and battery quality in the actual production process. The present invention utilizes an equivalent heat capacity method to simplify the difficulty of heat load calculation, closely adapts to the actual production environment, and efficiently controls the heat load of the forming workshop.

[0032] Of course, any product implementing the present invention does not necessarily need to achieve all of the technical effects described above at the same time.

[0033] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0035] Figure 1 It is a schematic diagram of the forming cabinet provided by the present invention;

[0036] Figure 2 This is a flow chart of a thermal management and control simulation method for a chemical forming workshop provided by the present invention;

[0037] Figure 3 A flow chart of another thermal management and control simulation method for a forming workshop provided by the present invention;

[0038] Figure 4 This is a schematic structural diagram of a chemical formation workshop in Example 1 of the present invention;

[0039] Figure 5 Schematic diagram of actual temperature curve, preset power and simulated temperature curve;

[0040] Figure 6 This is the simulation result of the formation workshop before optimization of Example 1 of the present invention;

[0041] Figure 7 This is the simulation result of the formation workshop after optimization of Example 1 of the present invention. DETAILED DESCRIPTION

[0042] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention.

[0043] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0044] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0045] In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0046] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0047] The present invention provides a thermal management simulation method for a chemical forming workshop, referring to Figure 2-Figure 3 , including the steps of:

[0048] S1: Collect the temperature change data of the forming cabinet within the first time to obtain the actual temperature curve;

[0049] S2: Equivalently treat the forming cabinet as a heating unit to obtain the power density curve;

[0050] S3: Perform simulation analysis based on the power density curve to obtain a simulated temperature curve;

[0051] S4: adjusting the preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold;

[0052] S5: Establish a three-dimensional simulation model of the chemical forming workshop to obtain a first three-dimensional model;

[0053] S6: Input test parameters into the first three-dimensional model, where the test parameters include inlet and outlet air volumes, refrigerant temperature, and preset power;

[0054] S7: Perform chemical formation process simulation to obtain a temperature distribution cloud map;

[0055] S8: According to the temperature distribution cloud map, adjust the structure of the first three-dimensional model so that the temperature in the first three-dimensional model is less than a second threshold.

[0056] Specifically, refer to Figure 2-Figure 3 The present invention provides a thermal management and control simulation method for a chemical forming workshop, comprising the steps of:

[0057] S1: Collect the temperature change data of the forming cabinet within the first time to obtain the actual temperature curve;

[0058] It should be noted that the first time is the time during which the forming cabinet is in the forming process. In this embodiment, the time taken for the forming process, that is, the first time, is 15,000 seconds.

[0059] It should be noted that the temperature curve is a curve showing the change of temperature over time, i.e., a functional expression showing the corresponding change of temperature and time. In step S1, the temperature change data of the lithium battery, the formation cabinet and the formation workshop are collected within the first time. When a single lithium battery is undergoing the formation process, the measured temperature data will be affected by the battery material, geometry, and environment. Therefore, when measuring the temperature of a single lithium battery, it should be monitored in an adiabatic environment. When a single formation cabinet is undergoing the formation process, the measured temperature data will be affected by the distribution of temperature measurement points, the model of the formation cabinet, and the environment. Therefore, when measuring the temperature of the formation cabinet, it should be monitored in an adiabatic environment, and the number of temperature measurement points should be no less than 10. Figure 1 , Figure 1 Be the schematic diagram of formation cabinet in the present embodiment, for the ease of checking, use colored filling, red dot mark temperature measuring point 10, the temperature measuring point 10 of formation cabinet comprises 10 points in the present embodiment, can be the inside 5 of formation cabinet, outside 5, evenly distributed, its specific location, the present invention does not do concrete restriction.When gathering the temperature curve of whole formation workshop, temperature data can be subject to temperature measuring point distribution, formation cabinet layout, cabinet quantity influence, and when therefore measuring whole formation workshop temperature, temperature measuring point should be not less than 10.

[0060] It should be noted that due to the large size of the forming cabinet, the temperature distribution is uneven, and its heat generation mainly comes from the Joule heat generated when the cooling fan is running. To simplify the calculation, based on experience, 5%-20% of the equivalent heating power of all lithium batteries in the forming cabinet can be taken as the heating power of the forming cabinet.

[0061] It should be noted that, for example, in this embodiment, the lithium battery parameters are: 50mm long, 20mm wide, and 110mm high. The parameters of the forming cabinet are: 2100mm long, 2900mm wide, and 6300mm high. The workshop parameters are: 50,000mm long, 20,000mm wide, and 8,000mm high. A single forming cabinet has three layers, with a total of 60 battery cells. The forming cabinets in the forming workshop are distributed in three rows, with a total of 66 forming cabinets.

[0062] S2: Equivalently treating the forming cabinet as a heating unit to obtain a power density curve, including the following steps:

[0063] It should be noted that the simulation software used in this embodiment includes ANSYS Fluent or Siemens STAR-CCM+, and the present invention does not specifically limit the specific simulation software used.

[0064] Before step S21: establishing the second three-dimensional model, the process also includes: S20: acquiring process parameters of the forming cabinet.

[0065] S21: Establishing a second three-dimensional model; the second three-dimensional model includes a formation cabinet and a plurality of lithium batteries disposed in the formation cabinet;

[0066] S22: In the second three-dimensional model, set a preset power P(t) and a preset time T;

[0067] S23: Performing a formation process simulation to obtain a power density curve, where the power density curve is an image of a function expression of a preset power and a preset time;

[0068] It should be noted that, in step S2, equivalent heat capacity method is utilized to be equivalent to formation cabinet and internal battery core and simulate as one, and equivalent heat capacity method is a method for the heat capacity of a calculation system or material. It is based on the law of conservation of energy, simplifies the calculation of heat capacity by considering system or material as equivalent container, thereby reduces complicated calculation steps. In the present embodiment, the formation cabinet equipped with multiple battery cores can be equivalent to a single heating unit, replaces the temperature parameter of prior art with power density, for simulation provides comparatively accurate input parameter, thereby improves simulation result credibility.

[0069] It should be noted that in step S2, the equivalent heat capacity method is used to equate the forming cabinets in the entire forming workshop to heating units, such as Figure 4 As shown in the figure, Power is a curve showing the change of a preset power over a preset time, derived using the equivalent heat capacity method. T2 is the simulated temperature curve obtained by inputting this power change curve into the ANSYS transient thermal simulation module. It can be seen that the simulated temperature curve T2 at this preset power closely matches the actual temperature curve T1, indicating that this preset power can be used as the heating power of the forming cabinet.

[0070] S3: Perform simulation analysis based on the power density curve to obtain a simulated temperature curve;

[0071] Step S3 includes: S31: meshing the second three-dimensional model and writing process parameters into the second three-dimensional model, the process parameters including thermal conductivity, density and specific heat capacity.

[0072] S32: Select transient thermal analysis type and enter process time and time step;

[0073] S33: Add the first boundary condition and initial condition;

[0074] S34: inputting a preset time and a corresponding preset power into the second three-dimensional model;

[0075] S35: Solve the second three-dimensional model to obtain a simulation temperature result and generate a simulation temperature curve.

[0076] It should be noted that step S31 includes: meshing the second three-dimensional model and setting the mesh quality to be greater than or equal to 0.9 to ensure the accuracy of the calculation. Step S32 includes: setting the transient thermal analysis type, that is, selecting the "Transient" analysis type in Analysis Settings. And define the total time and time step, write in the settings of thermal conductivity, density, specific heat capacity and other parameters; step S33: add the first boundary condition and initial condition, including the steps of: setting the heat transfer condition, heat transfer condition: applied to the surface of the second three-dimensional model, defining the convection coefficient (radiation coefficient); setting the power density value input by time point: heat generation load (power density): select setting the initial temperature: set the Initial Temperature (initial temperature), usually the ambient temperature; step S34, select the target geometry in the simulation software, right-click and insert "Internal Heat Generation (internal heating)", then select "Tabular (table)" in the Magnitude (magnitude) column to input, that is, input the power density value by time point, and you can directly import the csv format table in the simulation software; step S35 includes: adjusting the convergence criterion and output control in Analysis Settings (analysis settings), saving high-frequency results for post-processing; running the solution, and after completion entering the time relationship curve post-processing, extracting the simulation temperature curve T2 for comparison with the actual temperature curve T1.

[0077] Step S4: adjusting the preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold.

[0078] S5: Establish a three-dimensional simulation model of the chemical forming workshop to obtain a first three-dimensional model;

[0079] S6: Input test parameters into the first three-dimensional model, where the test parameters include inlet and outlet air volumes, refrigerant temperature, and preset power;

[0080] It should be noted that step S5 includes building a simulation model of the formation workshop to obtain a first three-dimensional model; step S6 includes inputting test parameters into the first three-dimensional model, the test parameters including inlet and outlet air volume, refrigerant temperature and preset power; Figure 4 As shown, the first three-dimensional model is the formation workshop model used in the present embodiment, 1, 2, 3 are different formation lines, including multiple formation cabinets, 4 is an air outlet, 5 is an air conditioning (refrigerant) air inlet, wherein the refrigerant air inlet 5 is on the side of the formation workshop, and the air outlet 4 is on the top of the formation workshop; the preset power in step S2 is written into the first three-dimensional model, boundary conditions and initial conditions are set, and meshing is performed to ensure that the mesh quality is greater than or less than 0.9, to ensure the accuracy of calculation.

[0081] S7: Perform chemical formation process simulation to obtain a temperature distribution cloud map;

[0082] S8: According to the temperature distribution cloud map, adjust the structure of the first three-dimensional model so that the temperature in the first three-dimensional model is less than a second threshold.

[0083] It should be noted that step S8 optimizes the number and layout of tuyere, refrigerant and forming cabinets in the forming workshop according to the simulation calculation results. For example, Figure 5 As shown, different colors represent the temperature range. Figure 5 The simulation calculation results before optimization are optimized into the structure in the workshop, and the simulation calculation results after optimization can be obtained, such as Figure 6 As shown, different colors represent temperature ranges. Air outlet layout: Adjust to a uniform distribution to ensure uniform air circulation. Refrigerant quantity: Based on heat load calculations, set the number of refrigerants to 3 to meet the heat dissipation requirements of the forming cabinets. Cabinet layout: Adjust the spacing between forming cabinets to 0.5 meters to reduce thermal interference and improve overall heat dissipation.

[0084] Referring to Table 1 below, the data outside the brackets are the temperature results after optimization, and the data inside the brackets are the temperature results before optimization. By comparing the simulation results before and after optimization, it can be seen that the temperature of the formation cabinet is reduced by about 5°C, and the overall heat load control accuracy is improved by 15%, which can effectively avoid battery quality problems caused by excessive temperature.

[0085] Table 1 Temperature statistics before and after optimization of the formation workshop in Example 1 of the present invention

[0086] Location Maximum temperature / ℃ Lowest temperature / ℃ Range / ℃ Chemical Line 1 44.125(54.71) 41.315(41.315) 2.795(13.397) Chemical 2 lines 44.226(49.434) 41.062(41.315) 3.164(8.372) 3-wire 43.795(50.026) 41(41) 2.795(9.026)

[0087] Note: The black font data in brackets are the simulation temperature results before optimization, and the data outside the brackets are the simulation temperature results after optimization.

[0088] It can be understood that the present invention provides a thermal management and control simulation method for a formation workshop, comprising the steps of: collecting temperature change data of a formation cabinet within a first time to obtain an actual temperature curve; treating a single formation cabinet as a heating unit to obtain a power density curve and a simulated temperature curve, performing simulation analysis based on the power density curve, obtaining a simulated temperature result and generating a simulated temperature curve; adjusting a preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold, determining the heating power of the formation cabinet, performing a formation process simulation of the formation workshop, and obtaining a temperature distribution cloud map; optimizing and adjusting the layout and quantity of the refrigerant in the formation workshop based on the temperature distribution cloud map to obtain an optimal layout, avoiding the situation in which the input temperature in the existing simulation means is not equal to the actual heat generated by the formation cabinet, further improving the accuracy of the simulation, and providing more accurate input parameters for the formation process simulation process of the formation workshop, thereby improving the accuracy of the simulation results, which is beneficial to improving the formation process effect and battery quality in the actual production process.

[0089] In some optional embodiments, digital temperature sensors are used to collect temperature change data of the lithium battery, formation cabinet, and formation workshop.

[0090] It should be noted that the digital temperature sensor can be one or more of the STS35-DIS (STS3x series), TMP112AIDRLR, ADT7410TRZ-REEL7 and DS18B20. The STS35-DIS (STS3x series) has enhanced signal processing, user-selectable I2C address and communication frequency up to 1MHz, and can usually achieve an accuracy range of ±0.1°C; the TMP112AIDRLR model temperature sensor has an accuracy of up to ±0.5°C; the ADT7410TRZ-REEL7 is a high-precision digital temperature sensor suitable for occasions with high requirements for temperature measurement accuracy; the DS18B20 has high-temperature and high-precision measurement capabilities and uses an MSOP-8 package.

[0091] In some optional embodiments, simulation analysis is performed using finite element calculation software.

[0092] It should be noted that ANSYS Workbench is a collaborative simulation environment developed by ANSYS, which aims to provide engineers with a full-process simulation solution from geometric modeling to analysis and solution. The following are its main functions and application areas:

[0093] ANSYS Workbench supports simulations of multiple physical fields, including structural mechanics, fluid dynamics, thermodynamics, and electromagnetic field analysis. Users can complete multidisciplinary simulation tasks on the same platform, improving work efficiency. The ANSYS Workbench provides a unified user interface that integrates geometric modeling, meshing, boundary condition setting, analysis and solution, and result post-processing. Through this intuitive interface, engineers can perform simulation analysis more conveniently. ANSYS Workbench supports static and transient structural simulation, modal analysis, harmonic response analysis, and random vibration analysis, capable of simulating the response of structures under different load conditions, such as stress, strain, and vibration. The ANSYS Workbench platform includes built-in parametric design and optimization tools, supporting simulation-driven design. Users can quickly optimize design solutions and improve product performance by adjusting parameters.

[0094] In some optional embodiments, the first time is 15000s-18000s.

[0095] Optionally, the first time can be 15100s, 15350s, 15600s, 15860s, 15950s, 16200s, 16350s, 16450s, 16550s, 16780s, 17200s, 17600s, 17650s, 17680s, 17950s and 18000s. When the first time is greater than 18000s, the formation process time is too long and the charge and discharge time is too long, which affects the battery quality. When the first time is less than 15000s, the formation process time is too short, the charge and discharge time is too short, and the battery parameters are unstable. Therefore, when the first time is 15000s-18000s, the charge and discharge time is appropriate, which effectively stabilizes the battery parameters and improves the battery quality.

[0096] In some optional embodiments, the first threshold is 1°C-2°C.

[0097] Optionally, the first threshold value can be 1°C, 1.1°C, 1.2°C, 1.3°C, 1.4°C, 1.5°C, 1.6°C, 1.7°C, 1.8°C, 1.9°C, or 2°C. When the first threshold value is less than 1°C, the difference between the simulated temperature and the actual temperature is too small, and the actual temperature may be affected by the actual operating environment and will not be exactly the same as the data collected under the adiabatic environment in step S1, which will affect the accuracy of the simulation; when the first threshold value is greater than 2°C, the difference between the simulated temperature and the actual temperature is too large, and the accuracy of the parameters actually written during the simulation process will be reduced, affecting the simulation effect; therefore, when the first threshold value is 1°C-2°C, the difference between the simulated temperature and the actual temperature is moderate, which will neither affect the accuracy of the parameters written during the simulation process nor deviate significantly from the actual temperature, thereby improving the accuracy of the simulation results.

[0098] In some optional embodiments, the second threshold is 41°C-45°C.

[0099] Optionally, the second threshold value can be 41°C, 41.3°C, 41.5°C, 41.7°C, 42°C, 42.4°C, 42.5°C, 43°C, 43.2°C, 43.5°C, 43.7°C, 43.8°C, 44°C, 44.3°C, 44.5°C, 44.7°C, 44.8°C and 45°C. When the second threshold value is less than 41°C, the formation workshop releases too little heat, and the formation process is incomplete, which affects the battery quality and stability. When the second threshold value is greater than 45°C, the formation workshop releases too much heat, which affects the effect of the formation process and causes unstable battery quality. Therefore, when the second threshold value is 41°C-45°C, the formation process releases appropriate heat, the battery parameters are stable, and the battery quality can be effectively improved.

[0100] It can be seen from the above embodiments that the thermal management and control simulation method for a chemical forming workshop provided by the present invention achieves at least the following beneficial effects:

[0101] The present invention provides a thermal management and control simulation method for a formation workshop, comprising the following steps: collecting temperature change data of a formation cabinet within a first time period to obtain an actual temperature curve; treating a single formation cabinet as a heating unit to obtain a power density curve and a simulated temperature curve, performing simulation analysis based on the power density curve to obtain a simulated temperature result and generate a simulated temperature curve; adjusting a preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold, determining the heating power of the formation cabinet, performing a formation process simulation of the formation workshop, and obtaining a temperature distribution cloud map; and optimizing and adjusting the layout and quantity of refrigerants in the formation workshop based on the temperature distribution cloud map to obtain an optimal layout, thereby avoiding the situation in existing simulation methods where the input temperature is not equal to the actual heat generated by the formation cabinet, further improving the accuracy of the simulation, providing relatively accurate input parameters for the formation process simulation process of the formation workshop, thereby improving the accuracy of the simulation result, and facilitating improving the formation process effect and battery quality in the actual production process.

[0102] Although some specific embodiments of the present invention have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should be understood by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A thermal management simulation method for a chemical forming workshop, characterized in that: Including steps: Collect the temperature change data of the forming cabinet in the first time and obtain the actual temperature curve; The forming cabinet is equivalent to a heating unit to obtain a power density curve; Performing simulation analysis based on the power density curve to obtain a simulated temperature curve; Adjusting the preset power so that the difference between the simulated temperature curve and the actual temperature curve is less than or equal to a first threshold; Establishing a three-dimensional simulation model of the forming workshop to obtain a first three-dimensional model; Conduct chemical formation process simulation to obtain temperature distribution cloud map; According to the temperature distribution cloud map, the structure of the first three-dimensional model is adjusted so that the temperature in the first three-dimensional model is less than a second threshold.

2. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: The process of converting the formation cabinet into a heating unit to obtain a power density curve comprises the following steps: Establishing a second three-dimensional model; the second three-dimensional model includes the formation cabinet and a plurality of lithium batteries disposed in the formation cabinet; In the second three-dimensional model, setting a preset power and a preset time; A formation process simulation is performed to obtain the power density curve, which is an image of a function expression of the preset power and the preset time.

3. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: The method of performing simulation analysis based on the power density curve to obtain a simulated temperature curve includes the following steps: Meshing the second three-dimensional model and writing process parameters into the second three-dimensional model; Select the transient thermal analysis type and enter the process time and time step; Add the first boundary condition and initial condition; Inputting the preset time and the corresponding preset power into the second three-dimensional model; The second three-dimensional model is solved to obtain a simulation temperature result and generate a simulation temperature curve.

4. The thermal management simulation method for a chemical formation workshop according to claim 3, characterized in that: The adding of the first boundary condition and the initial condition includes the steps of setting heat exchange conditions, setting power density values to be input at time points, and writing initial temperatures.

5. The thermal management simulation method for a chemical formation workshop according to claim 3, characterized in that: Simulation analysis is performed using finite element calculation software.

6. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: Before establishing the second three-dimensional model, the method further includes: obtaining process parameters of the formation cabinet, wherein the process parameters include thermal conductivity, density and specific heat capacity.

7. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: The first time is 15000s-18000s.

8. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: The first three-dimensional model includes: at least two forming lines arranged in the forming workshop, an air outlet located at the top of the forming workshop and a refrigerant air inlet located at the side of the forming workshop, and the forming line includes at least two forming cabinets arranged at equal distances.

9. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: The first threshold is 1°C-2°C, and the second threshold is 41°C-45°C.

10. The thermal management simulation method for a chemical formation workshop according to claim 1, characterized in that: Before the step of performing chemical process simulation to obtain a temperature distribution cloud map, the method further includes: inputting test parameters into the first three-dimensional model, wherein the test parameters include inlet and outlet air volumes, refrigerant temperature, and the preset power.

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