A simulation optimization method for heat dissipation design of optical component packaging

Abstract

The present invention discloses a simulation optimization method for heat dissipation design of optical component packaging, including: establishing a three-dimensional simulation model based on the actual packaging structure of the optical component, and setting the model boundary conditions; running the simulation, outputting the model calculation results, and determining the heat dissipation effect evaluation parameters and the parameter group to be optimized according to the model calculation results; assigning values ​​to each parameter in the parameter group to be optimized one by one, determining the optimal solution of each parameter according to the numerical change of the heat dissipation effect evaluation parameter, and outputting the optimal parameter result. The present invention meets the heat dissipation requirements of the chip through local optimization, avoids making a large number of physical objects for verification tests, and also avoids the problems of blindly selecting glue with extremely high thermal conductivity, blindly increasing the external dimensions of the heat dissipation block, etc., which cause performance redundancy and bring unnecessary reliability risks. It not only shortens the design time of the packaging solution of the optical component, but also saves a lot of manpower and material costs, and greatly improves the research and development iteration speed of the optical component.

Description

Technical Field

[0001] The present invention relates to the technical field of heat dissipation simulation, and in particular to a simulation optimization method for heat dissipation design of optical component packaging. Background Art

[0002] An optical component is a multi-chip packaged optical component that has the characteristics of high packaging density, multiple IO ports, small size, and high power consumption. Moreover, as the requirements for the performance of optical components in the field of optical communications become increasingly higher, the long-term reliability of the product is increasingly affected by temperature.

[0003] At present, optical components generally adopt COB packaging. Although it has the advantages of low cost and high density, in terms of heat dissipation design, it is still necessary to consider many factors such as the material of the substrate, the layout of the chip, the selection of bonding and thermal conductive glue, the size and material of the thermal conductive structure, the material of the packaging shell, the extreme operating temperature of different chips, and the packaging cost. Therefore, in the product testing stage, while considering the above factors, it is also necessary to take into account performance and cost. It is necessary to repeatedly conduct sample packaging tests to verify the actual effect. Not only is the efficiency low and the cost high, but also due to the design redundancy of some factors, it is not only unhelpful for heat dissipation, but will introduce unnecessary reliability risks, and sometimes lead to nonlinear increases in packaging costs and packaging process difficulty. Summary of the invention

[0004] To solve the above technical problems, the present invention provides a simulation optimization method for heat dissipation design of optical component packaging. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0005] The present invention adopts the following technical solution:

[0006] The present invention provides a simulation optimization method for optical component packaging heat dissipation design, comprising:

[0007] Establish a three-dimensional simulation model based on the actual packaging structure of the optical component and set the model boundary conditions;

[0008] Run the simulation, output the model calculation results, and determine the heat dissipation effect evaluation parameters and the parameter group to be optimized according to the model calculation results;

[0009] The parameters in the parameter group to be optimized are assigned values ​​one by one in turn, the optimal solution of each parameter is determined according to the numerical change of the heat dissipation effect evaluation parameter, and the optimal parameter result is output.

[0010] Furthermore, the process of establishing a three-dimensional simulation model based on the actual packaging structure of the optical component includes: creating a three-dimensional model corresponding to each structure in the optical component; establishing a PCB model file, and the PCB model file contains data on PCB substrate copper layer parameters and wiring methods; converting the created three-dimensional model and the PCB model file into a format recognizable by an electronic product thermal analysis simulation environment and importing them into the simulation environment to form the three-dimensional simulation model; setting the material properties of each part of the structure of the three-dimensional simulation model.

[0011] Furthermore, the model boundary conditions include: power of each chip in the optical component, working environment temperature, package shell temperature, and cooling method.

[0012] Furthermore, the model calculation results include: a temperature distribution cloud diagram of the three-dimensional simulation model and temperature values ​​of each structure in the model.

[0013] Furthermore, the temperature of the device with the largest power consumption and / or the highest temperature in the three-dimensional simulation model is used as the heat dissipation effect evaluation parameter; the basic parameters of the structure at the position exceeding the thermal resistance set threshold are used as the parameter group to be optimized, wherein the basic parameters include: the thermal conductivity of the structure and the size of the structure.

[0014] Furthermore, the process of assigning values ​​to each parameter in the parameter group to be optimized one by one and determining the optimal solution of each parameter according to the numerical change of the heat dissipation effect evaluation parameter includes: selecting any parameter in the parameter group to be optimized as the first test parameter, and assigning values ​​to the first test parameter one by one, and recording the numerical value of the heat dissipation effect evaluation parameter during the assignment process, and determining the optimal solution of the first test parameter according to the numerical change of the heat dissipation effect evaluation parameter; maintaining the first test parameter to the optimal solution, selecting another parameter in the parameter group to be optimized as the second test parameter, and performing the assignment and recording process to obtain the optimal solution of the second test parameter, and repeating the above process until the optimal solution of each parameter in the parameter group to be optimized is obtained.

[0015] Furthermore, the numerical change of the heat dissipation effect evaluation parameter refers to the rate of change of the numerical value, or the rate of change and rate of change of the exponential value.

[0016] Furthermore, when the value change rate of the heat dissipation effect evaluation parameter is higher than a preset value, the value of the current parameter to be optimized is output as the optimal parameter result; when the value change rate of the heat dissipation effect evaluation parameter is lower than the preset value, and the value change rate is higher than the preset value, the value of the current parameter to be optimized is output as the optimal parameter result.

[0017] Furthermore, when the change rate of the value of the heat dissipation effect evaluation parameter is lower than a preset value, the corresponding parameter to be optimized is deleted from the parameter group to be optimized.

[0018] The beneficial effects brought by the present invention are as follows: a digital heat dissipation model of the optical component is established, and the temperature distribution under the working conditions of the chip is simulated, so as to determine the optimal parameters of the specific factors affecting the heat dissipation, and meet the heat dissipation requirements of the chip through local optimization, avoiding the production of a large number of physical objects for verification tests, and also avoiding the problems of blindly selecting glue with extremely high thermal conductivity, blindly increasing the external dimensions of the heat dissipation block, etc., which cause performance redundancy and bring unnecessary reliability risks. It not only shortens the packaging solution design time of the optical component, but also saves a lot of manpower and material costs, and greatly improves the R&D iteration speed of the optical component. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a chip distribution map based on a three-dimensional model of the actual packaging structure of the optical component;

[0021] Figure 2 It is a schematic diagram of the internal structure of a three-dimensional model based on the actual packaging structure of an optical component;

[0022] Figure 3 This is a picture of the temperature distribution cloud map output after running the simulation;

[0023] Figure 4 It is a curve diagram showing the influence of the thermal conductivity of the first thermal conductive adhesive on the junction temperature of the driver chip;

[0024] Figure 5 It is a curve diagram showing the influence of the thermal conductivity of the second thermal conductive adhesive on the junction temperature of the driver chip;

[0025] Figure 6 It is a curve diagram showing the influence of the thickness of the third heat conducting block on the junction temperature of the driver chip;

[0026] Figure 7 It is a curve diagram showing the influence of the width of the third heat conducting block on the junction temperature of the driver chip;

[0027] Figure 8 It is a curve diagram showing the influence of the length of the third heat conducting block on the junction temperature of the driver chip;

[0028] Fig. 9 This is a curve showing how the junction temperature of the driver chip is affected by the thermal conductivity of the conductive adhesive. DETAILED DESCRIPTION

[0029] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It should be clear that the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] In some illustrative embodiments, the present invention provides a simulation optimization method for optical component package heat dissipation design, comprising the following steps:

[0031] S1: Establish a three-dimensional simulation model based on the actual packaging structure of the optical component. The specific process is as follows:

[0032] First, use Solidworks software to build a 3D model based on the actual packaging structure of the optical component. Figure 1 , Figure 2 The optical component shown includes a PCB substrate 1, a conductive adhesive 2, a driver chip 3, a transimpedance amplifier 4, an optical chip 5, a first thermal conductive adhesive 6, a first thermal conductive block 7, a second thermal conductive block 8, a third thermal conductive block 9, a second thermal conductive adhesive 10 and a packaging shell 11.

[0033] At the same time, the dimensions of the first heat conducting block 7, the second heat conducting block 8 and the third heat conducting block 9 are extracted, and the dimension values ​​are shown in the following table;

[0034] name Thickness / mm Width / mm Length / mm The first heat conducting block 0.43 1.32 3.32 The second heat conducting block 0.38 1.28 3.32 The third heat conducting block 1.42 2.4 8.48

[0035] Then, use Cadence software to create a PCB model file, which contains the data of the copper layer parameters and wiring method of the PCB substrate 1, and output the ODB++ file for the Icepak software to import the copper layer and wiring of the PCB model.

[0036] Then, the PCB model file and the three-dimensional model created using the Solidworks software are converted into a format recognizable by the electronic product thermal analysis simulation environment and imported into the simulation environment to form a three-dimensional simulation model. Among them, the electronic product thermal analysis simulation environment of this embodiment is a simulation environment established using the Icepak software. The specific process is to use the Workbench software Geometry to import the three-dimensional model established by the Solidworks software, and simplify the various components of the three-dimensional model into a form recognizable by Icepak. Then use the Icepak software to import the three-dimensional model after the Geometry simplification process, and import the real copper layer and wiring files of the PCB substrate 1 into the PCB model in Icepak, so that the PCB board model has real thermal conductivity data.

[0037] Finally, set the material properties of each part of the 3D simulation model as shown in the following table:

[0038] name Material Thermal conductivity Chips (driver chips, transimpedance amplifiers, optical chips) silicon 148 Package copper 387 The first heat conducting block, the second heat conducting block, and the third heat conducting block ALN 180 The first thermal conductive glue \ 1.5 Second thermal conductive glue \ 3 Conductive adhesive \ 2.5

[0039] S2: Setting model boundary conditions, specifically setting the boundary conditions of the optical component 3D simulation model in Icepak software. The model boundary conditions include: power of each chip in the optical component, working environment temperature, package shell temperature, and cooling method.

[0040] In the actual simulation of this embodiment, the power of the driver chip is set to 3.6W, the power of the transimpedance amplifier is set to 1.4W, the working environment temperature is set to 25° C., the package shell temperature is set to 85° C., and the cooling method is set to air convection.

[0041] S3: Divide the grid, run the simulation, output the model calculation results, and determine the heat dissipation effect evaluation parameters and the parameter group to be optimized based on the model calculation results. The model calculation results include: the temperature distribution cloud map of the three-dimensional simulation model created in S1 and the temperature values ​​of each structure in the model, such as the temperature values ​​of the driver chip 3, the transimpedance amplifier 4, the first heat conduction block 7, the second heat conduction block 8, the third heat conduction block 9, and the packaging shell 11.

[0042] Based on the above settings and parameters of the optical component 3D simulation model, as the initial value, the temperature distribution cloud diagram output after running the simulation is as follows: Figure 3 As shown, according to the temperature gradient distribution of the cloud map, the temperature of the device with the largest power consumption and / or the highest temperature in the three-dimensional simulation model is used as the heat dissipation effect evaluation parameter, and the basic parameters of the structure at the position exceeding the thermal resistance set threshold are used as the parameter group to be optimized, where the basic parameters include: the thermal conductivity of the structure and the size of the structure.

[0043] In this embodiment, since the driver chip 3 has the largest power consumption and the highest temperature, its junction temperature Tj is used as the heat dissipation effect evaluation parameter of the three-dimensional simulation model of the optical component. According to the temperature distribution cloud map, it is identified that there is a relatively large thermal resistance between the first heat-conducting block 7 and the third heat-conducting block 9, and between the third heat-conducting block 9 and the packaging shell 11, and the thermal resistance value exceeds the set thermal resistance threshold. The most direct factor affecting the thermal resistance is the thermal conductivity of the thermal conductive glue. Therefore, in this embodiment, the thermal conductivity of the first thermal conductive glue 6 and the second thermal conductive glue 10 are used as parameters to be optimized. At the same time, indirect factors such as the thickness, length, width of the third heat-conducting block 9 and the thermal conductivity of the conductive glue 2 are also used as parameters to be optimized. Finally, the parameter group to be optimized in this embodiment includes the following parameters:

[0044] Thermal conductivity of the first thermally conductive adhesive 6;

[0045] Thermal conductivity of the second thermally conductive adhesive 10;

[0046] The thickness, length and width of the third heat conducting block 9;

[0047] Thermal conductivity of conductive adhesive 2.

[0048] S4: assign values ​​to each parameter in the parameter group to be optimized one by one, determine the optimal solution of each parameter according to the numerical change of the heat dissipation effect evaluation parameter, and output the optimal parameter result. The numerical change of the heat dissipation effect evaluation parameter refers to the rate of change of the numerical value, or the rate of change and rate of change of the index value. The specific process of S4 is as follows:

[0049] First, any parameter in the parameter group to be optimized is selected as the first test parameter, and the first test parameter is assigned values ​​one by one, and the value of the heat dissipation effect evaluation parameter is recorded during the assignment process, and the optimal solution of the first test parameter is determined according to the value change of the heat dissipation effect evaluation parameter;

[0050] Then, the first test parameter is maintained until the optimal solution is obtained, another parameter in the parameter group to be optimized is selected as the second test parameter, and values ​​are assigned one by one, the values ​​of the heat dissipation effect evaluation parameters are recorded, and the optimal solution of the second test parameter is obtained according to the value change of the heat dissipation effect evaluation parameters;

[0051] Repeat the above process, that is, assign values ​​to each parameter in the parameter group to be optimized one by one, find the optimal solution for each parameter, and then optimize the next parameter on this basis until the optimal solution for each parameter in the parameter group to be optimized is obtained.

[0052] The specific process of S4 is explained below with specific values:

[0053] S41: Using the initial value of the three-dimensional simulation model of the optical component as a reference, record the junction temperature Tj of the driver chip 3 under different thermal conductivity coefficients of the first thermal conductive adhesive 6, and the statistical results are as follows: Figure 4 shown.

[0054] from Figure 4 It can be seen that when the thermal conductivity of the first thermal conductive adhesive 6 increases from 1.5 W / (m·K) to 20 W / (m·K), the junction temperature Tj decreases from 137.22° C. to 112.30° C., and the numerical change rate is 18.16% of the temperature reduction.

[0055] It can be seen from the change trend of the junction temperature Tj of the driver chip 3 that when the thermal conductivity reaches 20 W / (m·K), if the thermal conductivity of the first thermal conductive adhesive 6 is increased, the junction temperature Tj tends to be flat and will not decrease significantly.

[0056] Therefore, in this embodiment, since the numerical change rate of the heat dissipation effect evaluation parameter of 18.16% is higher than the preset value, and at the same time, the numerical change rate of the heat dissipation effect evaluation parameter is lower than the preset value, the numerical value of the current parameter to be optimized, 20W / (m·K), can be output as the optimal parameter result.

[0057] S42: Taking the optimal parameter result obtained in step S41 as the initial value of this step, recording the junction temperature Tj of the driver chip 3 under different thermal conductivity coefficients of the second thermal conductive adhesive 10, and the statistical results are as follows: Figure 5 shown.

[0058] from Figure 5 It can be seen that when the thermal conductivity of the second thermal conductive adhesive 10 increases from 3W / (m·K) to 25W / (m·K), the junction temperature Tj decreases from 112.30°C to 100.68°C. By calculating: (112.30-100.68)÷137.22×100%=8.47%, it is obtained that the temperature is reduced by 8.47% compared with the initial value of the junction temperature Tj of 137.22°C, that is, the numerical change rate is a temperature reduction of 8.47%.

[0059] It can be seen from the change trend of the junction temperature Tj of the driver chip 3 that when the thermal conductivity reaches 25 W / (m·K), if the thermal conductivity of the second thermal conductive adhesive 10 is increased, the junction temperature Tj tends to be flat and will not decrease significantly.

[0060] Therefore, in this embodiment, since the numerical change rate of the heat dissipation effect evaluation parameter of 8.47% is higher than the preset value, and at the same time, the numerical change rate of the heat dissipation effect evaluation parameter is lower than the preset value, the numerical value of the current parameter to be optimized, 25W / (m·K), can be output as the optimal parameter result.

[0061] S43: Taking the optimal parameter result of step S42 as the initial value of this step, the junction temperature Tj of the driver chip 3 when the third heat conducting block 9 has different thicknesses is calculated. The statistical results are as follows: Figure 6 shown.

[0062] from Figure 6 It can be seen that when the thickness of the third heat-conducting block 9 increases from 1.42 mm to 1.65 mm, the junction temperature Tj decreases from 100.68°C to 100.23°C. By calculating: (100.68-100.23)÷137.22×100%=0.33%, it is obtained that the temperature is reduced by 0.33% compared with the initial value of the junction temperature Tj of 137.22°C, that is, the numerical change rate is a temperature reduction of 0.33%.

[0063] At this time, it can be seen that the thickness of the third heat-conducting block 9 has little effect on the junction temperature Tj of the driver chip 3, but because the numerical change rate of the heat dissipation effect evaluation parameter of 0.33% is higher than the preset value, the value of the current parameter to be optimized, 1.65 mm, can be output as the optimal parameter result.

[0064] S44: Taking the optimal parameter result of step S43 as the initial value of this step, the junction temperature Tj of the driver chip 3 when the third heat conducting block 9 has different widths is calculated. The statistical results are as follows: Figure 7 shown.

[0065] from Figure 7 It can be seen that when the width of the third heat-conducting block 9 increases from 2.4 mm to 4.5 mm, the junction temperature Tj decreases from 100.23°C to 98.81°C. By calculating: (100.23-98.81)÷137.22×100%=1.03%, it is obtained that the temperature is reduced by 1.03% compared with the initial value of the junction temperature Tj of 137.22°C, that is, the numerical change rate is a temperature reduction of 1.03%.

[0066] At this time, it can be seen that the width of the third heat conducting block 9 has little effect on the junction temperature Tj of the driver chip 3, but because the numerical change rate of the heat dissipation effect evaluation parameter of 1.03% is higher than the preset value, the current value of the parameter to be optimized, 4.5 mm, can be output as the optimal parameter result.

[0067] S45: Taking the optimal parameter result of step S44 as the initial value of this step, the junction temperature Tj of the driver chip 3 when the third heat conducting block 9 has different lengths is calculated. The statistical results are as follows: Figure 8 shown.

[0068] from Figure 8 It can be seen that when the length of the third heat-conducting block 9 increases from 8.48 mm to 9.08 mm, the junction temperature Tj drops from 98.81°C to 97.83°C. By calculating: (98.81-97.83)÷137.22×100%=0.71%, it is obtained that the temperature is reduced by 0.71% compared with the initial value of the junction temperature Tj of 137.22°C, that is, the numerical change rate is a temperature reduction of 0.71%.

[0069] At this time, it can be seen that the length of the third heat-conducting block 9 has little effect on the junction temperature Tj of the driver chip 3. However, since the numerical change rate of the heat dissipation effect evaluation parameter of 0.71% is higher than the preset value, the numerical value of the current parameter to be optimized corresponding to 97.83°C, 8.68mm, can be output as the optimal parameter result.

[0070] S46: Taking the optimal parameter result of step S45 as the initial value of this step, recording the junction temperature Tj of the driver chip 3 under different thermal conductivity of the conductive glue 2, the statistical results are as follows: Fig. 9 shown.

[0071] from Fig. 9 It can be seen that when the thermal conductivity of the conductive adhesive 2 increases from 2.5W / (m·K) to 20W / (m·K), the junction temperature Tj drops from 97.83°C to 97.73°C. By calculating: (97.83-97.73)÷137.22×100%=0.07%, it is obtained that the temperature is reduced by 0.07% compared with the initial value of the junction temperature Tj of 137.22°C, that is, the numerical change rate is a temperature reduction of 0.07%.

[0072] In S46, in the process of assigning values ​​to the conductive glue 2, the numerical change rate of the junction temperature Tj of the driver chip 3 is a temperature decrease of 0.07%. Since 0.07% is lower than the set threshold, that is, the numerical change rate of the current heat dissipation effect evaluation parameter is lower than the preset value, the corresponding parameter to be optimized is deleted from the parameter group to be optimized. That is, since the thermal conductivity of the conductive glue 2 has almost no effect on the junction temperature Tj of the driver chip 3, no optimization is required.

[0073] S5: Complete the entire optimization process based on the optimal parameter results.

[0074] In this embodiment, through the temperature distribution cloud map, it is identified that there is a relatively large thermal resistance between the first heat-conducting block 7 and the third heat-conducting block 9, and between the third heat-conducting block 9 and the packaging shell 11, and the most direct factor affecting the thermal resistance is the thermal conductivity of the thermal conductive adhesive. Therefore, by improving the thermal conductivity of the first thermal conductive adhesive 6 and the second thermal conductive adhesive 10, the junction temperature Tj of the driver chip 3 is reduced from 137.22°C to 100.68°C, with a reduction of up to 26.63%.

[0075] By optimizing the size of the third heat-conducting block 9 of the heat dissipation structure of the optical component, it is found that the size of the third heat-conducting block 9 has a relatively small effect on the junction temperature Tj of the driver chip 3. In this embodiment, it is shown that by optimizing the size of the heat-conducting structure of the optical component, that is, the thickness, width, and length parameters of the third heat-conducting block 9, when the corresponding size approaches the limit of the overall structure, the junction temperature Tj of the driver chip 3 is reduced from 100.68°C to 97.83°C, and the reduction is only 2.08%.

[0076] By optimizing the thermal conductivity of the conductive adhesive 2 of the optical component, it is found that the thermal conductivity of the conductive adhesive 2 has almost no effect on the junction temperature Tj of the driver chip 3, and no optimization is required.

[0077] The present invention obtains the temperature gradient in the optical component model through the temperature distribution cloud map of the three-dimensional simulation model of the optical component, identifies the factors that have a significant impact on the heat dissipation effect, and then formulates a targeted optimization plan. Specifically, after comprehensively optimizing the above parameters of the three-dimensional simulation model of the optical component, the junction temperature Tj of the driver chip 3 is reduced from 137.22°C to 97.73°C, a decrease of 28.78%, and the heat dissipation effect is optimal. The dimensions of each heat conduction block after optimization are as follows:

[0078]

[0079]

[0080] The optimized glue parameters are as follows:

[0081] name Material Thermal conductivity The first thermal conductive glue \ 20 Second thermal conductive glue \ 25 Conductive adhesive \ 2.5

[0082] The present invention provides a standard thermal simulation optimization method for packaging heat dissipation design for products such as optical components. According to the above-mentioned simulation optimization method, this embodiment finds the best heat dissipation solution, avoids making a large number of physical objects for verification tests, and also avoids blindly selecting glue with extremely high thermal conductivity, blindly increasing the external dimensions of the heat dissipation block, etc., which causes performance redundancy and brings unnecessary reliability risks. It not only shortens the packaging solution design time of the optical component, but also saves a lot of manpower and material costs, and greatly improves the R&D iteration speed of the optical component.

[0083] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A simulation optimization method for heat dissipation design of optical component packaging, characterized in that: The simulation optimization method comprises: Establish a three-dimensional simulation model based on the actual packaging structure of the optical component and set the model boundary conditions; Run the simulation, output the model calculation results, and determine the heat dissipation effect evaluation parameters and the parameter group to be optimized based on the model calculation results. The model calculation results include: the temperature distribution cloud diagram of the three-dimensional simulation model and the temperature values ​​of each structure in the model. According to the temperature gradient distribution of the cloud map, the temperature of the device with the largest power consumption and / or the highest temperature in the three-dimensional simulation model is used as the heat dissipation effect evaluation parameter; The basic parameters of the structure at the position exceeding the set threshold value of thermal resistance are used as the parameter group to be optimized; Assigning values ​​to each parameter in the parameter group to be optimized one by one, determining the optimal solution of each parameter according to the numerical change of the heat dissipation effect evaluation parameter, and outputting the optimal parameter result, The process of assigning values ​​to the parameters in the parameter group to be optimized one by one and determining the optimal solution of each parameter according to the numerical change of the heat dissipation effect evaluation parameter includes: Selecting any parameter in the parameter group to be optimized as the first test parameter, assigning values ​​to the first test parameters one by one, and recording the value of the heat dissipation effect evaluation parameter during the assignment process, and determining the optimal solution of the first test parameter according to the value change of the heat dissipation effect evaluation parameter; The first test parameter is maintained to the optimal solution, another parameter in the parameter group to be optimized is selected as the second test parameter, and the assignment and recording process is performed to obtain the optimal solution of the second test parameter, and the above process is repeated until the optimal solution of each parameter in the parameter group to be optimized is obtained.

2. The simulation optimization method for heat dissipation design of optical component packaging according to claim 1 is characterized in that: The process of establishing a three-dimensional simulation model based on the actual packaging structure of the optical component includes: Create a three-dimensional model corresponding to each structure in the optical component; Establishing a PCB model file, wherein the PCB model file includes data on the copper layer parameters and wiring method of the PCB substrate; Converting the created three-dimensional model and the PCB model file into a format recognizable by an electronic product thermal analysis simulation environment and importing them into the simulation environment to form the three-dimensional simulation model; The material properties of each part of the structure of the three-dimensional simulation model are set.

3. The simulation optimization method for heat dissipation design of optical component packaging according to claim 2, characterized in that: The model boundary conditions include: power of each chip in the optical component, working environment temperature, package shell temperature, and cooling method.

4. The simulation optimization method for heat dissipation design of optical component packaging according to claim 1, characterized in that: The basic parameters include: thermal conductivity of the structure and the size of the structure.

5. The simulation optimization method for heat dissipation design of optical component packaging according to claim 1, characterized in that: The numerical change of the heat dissipation effect evaluation parameter refers to the rate of change of the numerical value, or the rate of change and rate of change of the exponential value.

6. The simulation optimization method for heat dissipation design of optical component packaging according to claim 5, characterized in that: When the change rate of the value of the heat dissipation effect evaluation parameter is higher than a preset value, the value of the current parameter to be optimized is output as the optimal parameter result.

7. The simulation optimization method for heat dissipation design of optical component packaging according to claim 5, characterized in that: When the value change rate of the heat dissipation effect evaluation parameter is lower than the preset value, and the value change rate is higher than the preset value, the value of the current parameter to be optimized is output as the optimal parameter result.

8. The simulation optimization method for heat dissipation design of optical component packaging according to claim 5, characterized in that: When the change rate of the value of the heat dissipation effect evaluation parameter is lower than a preset value, the corresponding parameter to be optimized is deleted from the parameter group to be optimized.

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