Optical performance simulation method and device of optical component and storage medium

Abstract

The invention provides an optical performance simulation method and device of an optical assembly and a storage medium, and the simulation method comprises the steps: obtaining initial values of a plurality of component parameters of the optical assembly, and building an initial model of the optical assembly according to the initial values of the plurality of component parameters; determining a plurality of key parameters from the plurality of component parameters according to the initial model; determining a plurality of candidate values of each key parameter according to the initial values of the plurality of key parameters; combining the candidate values of the plurality of key parameters through a robustness design algorithm to obtain a plurality of candidate parameter value groups; a plurality of candidate parameter value groups are configured for the initial model for simulation, and simulation results of the optical performance indexes corresponding to the candidate parameter value groups are obtained; and based on a simulation result, determining an optimal parameter value from the plurality of candidate values of each key parameter through a robustness design algorithm so as to obtain an optimal parameter value group. The simulation method can improve the efficiency and precision of optical simulation.

Description

Technical Field

[0001] The present application relates to the technical field of optical components, and in particular to a method, device and storage medium for simulating the optical performance of an optical component. Background Art

[0002] In the design of optical components, there are relatively strict requirements for the two optical performance indicators of brightness value and brightness uniformity. Optical simulation plays a vital role in the design and optimization of optical systems. However, due to the complexity of optical systems, the simulation process often requires a lot of computing resources and time, especially when considering multiple uncertain factors, the efficiency of the simulation and the stability of the results may be seriously affected. Therefore, how to improve the efficiency of optical simulation and ensure the reliability of the results has become an important topic in the current field of optical design. Summary of the invention

[0003] In order to solve the above technical problems, the present disclosure provides a method, device and storage medium for simulating the optical performance of an optical component.

[0004] To achieve the above objectives, in a first aspect, the present application provides a method for simulating optical performance of an optical component, the simulation method comprising:

[0005] Acquiring initial values ​​of multiple component parameters of the optical component, and establishing an initial model of the optical component according to the initial values ​​of the multiple component parameters;

[0006] determining a plurality of key parameters from the plurality of component parameters according to the initial model;

[0007] Determining a plurality of candidate values ​​for each key parameter based on the initial values ​​of the plurality of key parameters;

[0008] Combining the candidate values ​​of the plurality of key parameters by a robust design algorithm to obtain a plurality of candidate parameter value groups; wherein each candidate parameter value group includes the values ​​of the plurality of key parameters, and the value of each key parameter is one of the corresponding plurality of candidate values;

[0009] The initial model is configured with the plurality of candidate parameter value groups for simulation, and simulation results of optical performance indicators corresponding to the plurality of candidate parameter value groups are obtained;

[0010] Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups, the optimal parameter value is determined from the multiple candidate values ​​of each key parameter through a robust design algorithm, thereby obtaining an optimal parameter value group; wherein the optimal parameter value group includes the values ​​of the multiple key parameters, and the value of each key parameter is the corresponding optimal parameter value.

[0011] The optical performance simulation method of the optical component provided by the present application obtains the initial values ​​of multiple component parameters of the optical component, establishes the initial model of the optical component according to the initial values ​​of the multiple component parameters, determines multiple key parameters according to the initial model, determines multiple candidate values ​​of each key parameter according to the initial values ​​of the multiple key parameters, combines the candidate values ​​of the multiple key parameters through a robust design algorithm to obtain multiple candidate parameter value groups, configures the initial model with multiple candidate parameter value groups for simulation, obtains the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups, and based on the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups, determines the optimal parameter value from the multiple candidate values ​​of each key parameter through a robust design algorithm, thereby obtaining the optimal parameter value group. The simulation method introduces a robust design technology algorithm for the complexity and multivariate influencing factors of the optical system, reduces the influence of uncertainty factors in the simulation process, can quickly determine the optimal parameter value group, and thus can improve the efficiency and accuracy of optical simulation.

[0012] In a second aspect, the present application also provides an optical performance simulation device for an optical component, the optical performance simulation device comprising a processor and a memory; the memory is coupled to the processor, the memory is used to store computer program code, the computer program code comprises computer instructions, and when the processor executes the computer instructions, the optical performance simulation device for the optical component performs the optical performance simulation method for the optical component as described in the first aspect.

[0013] In a third aspect, the present application also provides a computer-readable storage medium, in which a computer program or instruction is stored. When the computer program or instruction is executed by an optical performance simulation device for an optical component, the optical performance simulation device for the optical component performs the optical performance simulation method for the optical component as described in the first aspect.

[0014] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of a method for simulating optical performance of an optical component provided in an embodiment of the present application;

[0016] Figure 2 This is a schematic diagram of the first structure of an optical component provided in an embodiment of the present application;

[0017] Figure 3 yes Figure 2 A cross-sectional structural diagram of the optical component shown along the cutting line kk;

[0018] Figure 4 is a second structural schematic diagram of an optical component provided in an embodiment of the present application;

[0019] Figure 5 This is a third structural schematic diagram of the optical component provided in the embodiment of the present application.

[0020] The following are the descriptions of the reference numerals:

[0021] Optical components 100

[0022] First glass layer 11

[0023] Second glass layer 12

[0024] Shielding layer 13

[0025] Reflective element 14

[0026] Light emitting element 15

[0027] Light guide bar 16

[0028] Adhesive layer 17

[0029] Light incident surface 161

[0030] Light emitting surface 162

[0031] The following specific implementation methods will illustrate the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] In addition, the terms "first", "second", etc. in the specification of the present invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] It should be noted that, in the absence of conflict, the features in the embodiments of the present application may be combined with each other.

[0035] See also Figure 1 The present application provides a method for simulating the optical performance of an optical component, the simulation method comprising steps S1 to S6, which are specifically as follows:

[0036] Step S1, acquiring initial values ​​of multiple component parameters of the optical component, and establishing an initial model of the optical component according to the initial values ​​of the multiple component parameters;

[0037] Step S2, determining a plurality of key parameters from the plurality of component parameters according to the initial model;

[0038] Step S3, determining multiple candidate values ​​for each key parameter according to the initial values ​​of the multiple key parameters;

[0039] Step S4, combining the candidate values ​​of the multiple key parameters by a robust design algorithm to obtain multiple candidate parameter value groups; wherein each candidate parameter value group includes the values ​​of the multiple key parameters, and the value of each key parameter is one of the corresponding multiple candidate values;

[0040] Step S5, configuring the initial model with the plurality of candidate parameter value groups for simulation, and obtaining simulation results of optical performance indicators corresponding to the plurality of candidate parameter value groups;

[0041] Step S6, based on the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups, determine the optimal parameter value from the multiple candidate values ​​of each key parameter through a robust design algorithm, so as to obtain an optimal parameter value group; wherein the optimal parameter value group includes the values ​​of the multiple key parameters, and the value of each key parameter is the corresponding optimal parameter value.

[0042] The optical performance simulation method of the optical component provided by the present application obtains the initial values ​​of multiple component parameters of the optical component, establishes the initial model of the optical component according to the initial values ​​of the multiple component parameters, determines multiple key parameters according to the initial model, determines multiple candidate values ​​of each key parameter according to the initial values ​​of the multiple key parameters, combines the candidate values ​​of the multiple key parameters through a robust design algorithm to obtain multiple candidate parameter value groups, configures the initial model with multiple candidate parameter value groups for simulation, obtains the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups, and based on the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups, determines the optimal parameter value from the multiple candidate values ​​of each key parameter through a robust design algorithm, thereby obtaining the optimal parameter value group. The simulation method introduces a robust design technology algorithm for the complexity and multivariate influencing factors of the optical system, reduces the influence of uncertainty factors in the simulation process, can quickly determine the optimal parameter value group, and thus can improve the efficiency and accuracy of optical simulation.

[0043] See also Figure 2 to Figure 5 , Figure 2 This is a schematic diagram of the first structure of an optical component provided in an embodiment of the present application; Figure 3 yes Figure 2 A cross-sectional structural diagram of the optical component shown along the cutting line kk; Figure 4 is a second structural schematic diagram of an optical component provided in an embodiment of the present application; Figure 5 This is a third structural schematic diagram of the optical component provided in the embodiment of the present application.

[0044] This application takes the optical component as an atmosphere lamp as an example to introduce the optical performance simulation method of the optical component in detail. Figure 3 As shown, the optical component 100 includes a plurality of first glass layers 11 , a second glass layer 12 , a shielding layer 13 , a reflector 14 , a plurality of light emitting elements 15 , a light guide bar 16 and an adhesive layer 17 .

[0045] The first glass layer 11 and the second glass layer 12 are stacked along a first direction, and the shielding layer 13 and the reflective element 14 are located between the first glass layer 11 and the second glass layer 12 .

[0046] The light guide bar 16 is bonded to the side of the second glass layer 12 facing away from the first glass layer 11 through the bonding layer 17 . The light guide bar 16 has a light incident surface 161 and a light emitting surface 162 .

[0047] The plurality of light emitting elements 15 are spaced apart from the light incident surface 161 of the light guide bar 16 and are evenly arranged along the extension direction of the light guide bar 16. The light emitted by the plurality of light emitting elements 15 can enter the light guide bar 16 through the light incident surface 161, and the light emitted through the light exit surface 162 can enter the second glass layer 12 from the side of the second glass layer 12 away from the first glass layer 11. The reflector 14 is used to reflect the light transmitted in the second glass layer 12 so that the reflected light is emitted from the side of the second glass layer 12 away from the first glass layer 11.

[0048] For example, Figure 2-Figure 3 As shown, the first glass layer 11 and the second glass layer 12 are stacked along the X-axis direction, and the light guide bar 16 is bonded to the second glass layer 12 through the bonding layer 17. The light guide bar 16 extends along the Z-axis direction, and the plurality of light emitting elements 15 are arranged along the Z-axis direction, and the light incident surface 161 of the light guide bar 16 is a surface facing the light emitting elements 15. The X-axis direction is perpendicular to the Z-axis direction.

[0049] In the embodiment of the present application, the optical component 100 includes multiple first glass layers 11, a second glass layer 12, a shielding layer 13, a reflector 14, multiple light-emitting elements 15, a light guide strip 16 and an adhesive layer 17. In other embodiments, the optical component 100 may also include other components, which are not limited here.

[0050] The initial values ​​of the parameters of the multiple components of the optical assembly 100 are obtained by obtaining at least one parameter of each component. For example, the parameters of any component of the first glass layer 11, the second glass layer 12, the shielding layer 13, the reflector 14, the multiple light-emitting elements 15, the light guide strip 16, and the adhesive layer 17 may include parameters such as geometric size parameters of the component (for example, length, width, thickness, surface shape, and distance between other components, etc.), material property parameters (for example, material type, transmittance, reflectivity, refractive index, diffusivity, etc.), etc.

[0051] The parameters of the plurality of light emitting elements 15 may further include an arrangement spacing L3 (ie, a spacing between adjacent light emitting elements 15 ), and light source characteristic parameters (eg, including light color, wavelength, luminous flux, etc.).

[0052] There may be more than one reflector 14 , and the parameters of the reflector 14 may further include the arrangement of the reflector 14 . For example, Figure 4 The reflective elements 14 are arranged randomly, that is, the size of each reflective element 14 is random, and the spacing between adjacent reflective elements 14 is also random; Figure 3The reflective elements 14 are arranged in a manner of gradually decreasing in size, that is, the size of each reflective element 14 gradually decreases in a direction away from the light emitting element 15; Figure 5 The reflective elements 14 are arranged in a manner of gradually increasing in size, that is, the size of each reflective element 14 gradually increases in the direction away from the light emitting element 15. Of course, in other embodiments, the reflective elements 14 can also be arranged in other manners, which are not limited here.

[0053] In some embodiments, determining a plurality of key parameters from the plurality of component parameters according to the initial model comprises:

[0054] A plurality of key parameters are determined from the plurality of component parameters according to the initial model and a preset key parameter mapping table.

[0055] The preset key parameter mapping table records the correspondence between different initial models and different key parameter groups, wherein each key parameter group includes multiple key parameters. The preset key parameter mapping table can be pre-configured by an engineer.

[0056] by Figure 2 to Figure 5 Taking the optical component 100 as an example, in some embodiments, the multiple key parameters include at least one of the following parameters:

[0057] The surface shape of the first glass layer 11;

[0058] The arrangement pitch L3 of the plurality of light emitting elements 15;

[0059] The luminous flux of the light emitting element 15;

[0060] A distance L1 between the light incident surface 161 of the light guide bar 16 and the light emitting element 15;

[0061] The distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light emitting element 15 in the first direction;

[0062] the arrangement of the reflective element 14; and,

[0063] The light guide strip 16 has a width L2.

[0064] In some embodiments, determining a plurality of candidate values ​​for each key parameter according to the initial values ​​of the plurality of key parameters comprises:

[0065] A plurality of candidate values ​​for each key parameter are determined according to a preset candidate value mapping table for each key parameter and the initial values ​​of the plurality of key parameters.

[0066] The preset candidate value mapping table of each key parameter records the correspondence between different initial values ​​of the key parameter and different candidate value groups, wherein each candidate value group includes multiple candidate values. The preset key parameter mapping table can be pre-configured by an engineer.

[0067] Exemplarily, in one embodiment, the multiple key parameters include the surface shape of the first glass layer 11 (A), the arrangement spacing L3 of the multiple light-emitting elements 15 (B), the luminous flux of the light-emitting element 15 (C), the distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light-emitting element 15 in the first direction (D), the distance L1 between the light incident surface 161 of the light guide bar 16 and the light-emitting element 15 (E), the arrangement of the reflector 14 (F), and the width L2 of the light guide bar 16 (G). For the convenience of description, different symbols are used to represent different key parameters in the embodiments of the present application, wherein A represents the surface shape of the first glass layer 11, B represents the arrangement spacing L3 of the multiple light-emitting elements 15, C represents the luminous flux of the light-emitting element 15, D represents the distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light-emitting element 15 in the first direction, E represents the distance L1 between the light incident surface 161 of the light guide bar 16 and the light-emitting element 15, F represents the arrangement of the reflector 14, and G represents the width L2 of the light guide bar 16.

[0068] For example, please refer to Table 1, which shows the correspondence between the seven key parameters A to G and the candidate values, wherein the level 1 of each key parameter represents the initial value of the key parameter, and the level 1 to level 3 are multiple candidate values ​​of the key parameter, wherein the difference between the multiple candidate values ​​of each key parameter and the initial value of the key parameter is within the tolerance range corresponding to the key parameter. Taking the luminous flux (C) of the light-emitting element 15 as an example, its initial value is 0.48mm, and its candidate values ​​are 0.48mm, 0.53mm and 0.6mm. Taking the distance (D) between the center of the light incident surface 161 of the light guide bar 16 and the center of the light emitting element 15 in the first direction as an example, its initial value is centered (i.e., the distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light emitting element 15 in the first direction is zero), and its candidate values ​​are centered, offset by 0.5mm (i.e., the distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light emitting element 15 in the first direction is 0.5mm) and offset by 1.25mm (i.e., the distance between the center of the light incident surface 161 of the light guide bar 16 and the center of the light emitting element 15 in the first direction is 1.25mm). It should be noted that this application does not limit the number of candidate values ​​for each key parameter, and the number of candidate values ​​for each key parameter can be 2, 3, 4, etc.

[0069] Table 1 Schematic diagram of the correspondence between key parameters and candidate values

[0070]

[0071] Among them, the robust design algorithm, also known as the Taguchi design algorithm, is a method widely used in product design and experimental design. Its core goal is to find a parameter combination that makes the product or process run more stably in the operating environment. The specific steps of determining multiple candidate parameter value groups through the robust design algorithm belong to the existing technology and will not be repeated here.

[0072] Please refer to Table 2, which shows a plurality of candidate parameter value groups obtained by combining the candidate values ​​of the plurality of key parameters shown in Table 1 by the robust design algorithm, wherein Table 2 is also referred to as an orthogonal matrix, and in Table 2, each key parameter is also referred to as a factor, and the candidate value of each key parameter is also referred to as the level value of the factor. Wherein, since the standard orthogonal matrix includes L8, L9 and L18, wherein L8 is applicable to an experimental design with 3 factors, each factor having 2 level values, L9 is applicable to an experimental design with 4 factors, each factor having 3 level values, and L18 is applicable to an experimental design with 1 factor having 2 level values ​​and 7 factors having 3 level values. Since the embodiment of the present application includes 7 factors, in order to generate the standard orthogonal matrix L18, the error factor H is added in the present embodiment, and H does not represent any key parameter of the optical component, but is a virtual parameter. As shown in Table 1, A has 2 candidate values, and B~G each has 3 candidate values. The full arrangement simulation requires 2*3^7=4374 simulations. However, if the robust design algorithm is used to design the simulation, only 18 simulations are required. After a simple statistical processing of the output results of the 18 simulations, the optimal parameter value of each key parameter can be determined. Although the number of simulations is greatly reduced, the optimal result obtained from the robust design algorithm is close to the optimal result obtained from the complete arrangement method. Therefore, the use of the robust design algorithm for simulation can improve the efficiency of the simulation.

[0073] Table 2 Schematic diagram of candidate parameter value groups

[0074]

[0075] In some embodiments, the simulation method further includes:

[0076] Determine a plurality of error parameter value groups according to the plurality of candidate parameter value groups; wherein each error parameter value group includes values ​​of the plurality of key parameters, and there is at least one error parameter among the plurality of key parameters, and there is a preset error between the value of each error parameter and a candidate value of the error parameter;

[0077] The initial model is configured with the multiple error parameter groups for simulation to obtain simulation results of optical performance indicators corresponding to the multiple error parameter groups.

[0078] Furthermore, the simulation results of the optical performance indicators respectively corresponding to the plurality of candidate parameter value groups are based on, and the optimal parameter value is determined from the plurality of candidate values ​​of each key parameter by a robust design algorithm, including:

[0079] Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups and the multiple error parameter groups, an optimal parameter value is determined from the multiple candidate values ​​of each key parameter through a robust design algorithm.

[0080] It should be noted that in actual products, some of the multiple key parameters of the optical component may have certain errors due to limitations of the production process. Therefore, the errors of these parameters are taken into account and the initial model of the optical component is simulated. The simulation results obtained are closer to the actual product, and thus the simulation results are more accurate.

[0081] Of course, in other embodiments, the error of each key parameter may not be considered, and the optimal parameter value may be determined from multiple candidate values ​​of each key parameter through a robust design algorithm based only on the simulation results of the optical performance indicators corresponding to the multiple candidate parameter value groups.

[0082] Exemplarily, please refer to Table 3, which shows the multiple candidate parameter value groups and the multiple error parameter value groups. In the embodiment shown in Table 3, C and G of the seven key parameters A to G are error parameters. Specifically, the error value corresponding to the candidate value of C of 0.48mm is 0.53mm, that is, the error is 0.05mm; the error value corresponding to the candidate value of C of 0.53mm is 0.48mm, that is, the error is 0.05mm; the error value corresponding to the candidate value of C of 0.60mm is 0.54mm, that is, the error is 0.06mm. The error value corresponding to the candidate value of G of 10mm is 9.8mm, that is, the error is 0.2mm; the error value corresponding to the candidate value of G of 18mm is 17.8mm, that is, the error is 0.2mm; the error value corresponding to the candidate value of G of 25mm is 24.8mm, that is, the error is 0.2mm.

[0083] Table 3 Schematic diagram of candidate parameter value groups and error parameter value groups

[0084]

[0085]

[0086] In some embodiments, the optical performance index includes at least a first optical performance index, and the robustness design algorithm includes a signal-to-noise ratio calculation formula, wherein the first optical performance index is one of a brightness value and a brightness uniformity.

[0087] For example, see Figure 4Table 4 shows the simulation results of the brightness values ​​and brightness uniformity corresponding to the multiple candidate parameter value groups and the multiple error parameter groups. The simulation results of the brightness values ​​and brightness uniformity corresponding to each candidate parameter value group and each error parameter group may be statistical values ​​of the sampling results of the brightness values ​​of multiple preset sampling points on the second glass layer 12 of the optical component 100.

[0088] Table 4 Simulation results

[0089]

[0090]

[0091] In some embodiments, the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups are used to determine the optimal parameter value from the multiple candidate values ​​of each key parameter through a robust design algorithm, including:

[0092] Based on the simulation results of the first optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, and according to the signal-to-noise ratio calculation formula corresponding to the first optical performance indicator, the first optical performance indicator signal-to-noise ratios respectively corresponding to the candidate values ​​of each key parameter are calculated;

[0093] Determine the candidate value with the largest signal-to-noise ratio of the first optical performance indicator among the candidate values ​​of each key parameter as the first preferred parameter value of the key parameter;

[0094] Based at least on the first preferred parameter value of each key parameter, an optimal parameter value for each key parameter is determined.

[0095] Among them, in the robust design algorithm, the signal-to-noise ratio (S / N) is a key indicator to measure the stability of product quality, which reflects the system's sensitivity to noise.

[0096] The present application utilizes the first optical performance indicator signal-to-noise ratio corresponding to each candidate value of each key parameter to judge the pros and cons of each candidate value of each key parameter, which can quickly realize multi-parameter optimization and improve the efficiency of optical simulation.

[0097] In some embodiments, the simulation results of the first optical performance indicators respectively corresponding to the plurality of candidate parameter value groups are based on, according to the signal-to-noise ratio calculation formula corresponding to the first optical performance indicator, to calculate the first optical performance indicator signal-to-noise ratios respectively corresponding to the candidate values ​​of each key parameter, including:

[0098] Based on the simulation results of the first optical performance indicators respectively corresponding to the multiple candidate parameter value groups and the multiple error parameter groups, and according to the signal-to-noise ratio calculation formula corresponding to the first optical performance indicator, the first optical performance indicator signal-to-noise ratio corresponding to each candidate value of each key parameter is calculated.

[0099] In some embodiments, the simulation method further includes:

[0100] Based on the first optical performance indicator signal-to-noise ratios corresponding to each candidate value of each key parameter, the first optical performance indicator signal-to-noise ratio range of each key parameter is calculated; wherein the first optical performance indicator signal-to-noise ratio range of each key parameter is the difference between the maximum value and the minimum value of the first optical performance indicator signal-to-noise ratios corresponding to each candidate value of the key parameter;

[0101] Sorting the first optical performance indicator signal-to-noise ratio extreme differences of the multiple key parameters to obtain a first sorting result;

[0102] At least according to the first sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator.

[0103] It should be noted that in the robust design algorithm, stable factors (Noise Factors), adjustment factors (Control Factors) and minor factors (Less Significant Factors) are three key concepts, which play different roles in experimental design and quality control. Specifically, stable factors are factors that cannot be controlled or difficult to control in the experiment, which may lead to increased variability in the experimental results. In the robust design algorithm, these noise factors are manipulated to force variations, and then the optimal control factor settings that make the process or product resistant to these variations are determined. Adjustment factors are factors that can be controlled and adjusted in the experiment, and engineers can optimize the experimental results by changing the levels of these factors. Minor factors have relatively little effect on the experimental results and may not be given priority in the experimental design. In the robust design algorithm, the main focus is on those major factors that have a significant impact on the response variable, while minor factors may be ignored after preliminary analysis or considered as subsequent optimization.

[0104] The present application divides the multiple key parameters into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator based at least on the first sorting result, and is capable of determining the degree of influence of each key parameter on the first optical performance indicator, thereby facilitating engineers to change the value of the adjustment factor to optimize the first optical performance indicator.

[0105] For example, please refer to Table 5, which takes the first optical performance index as brightness value as an example, and shows the first sorting result obtained from the simulation results shown in Table 4. In this embodiment, the key parameters in the first sorting result are sorted according to the sorting rule from large to small according to the extreme difference value, and specifically, the first sorting result is DAEBHCGF.

[0106] Among them, in the robustness design algorithm, the signal-to-noise ratio is divided into three types: large, small and eye-to-eye. Among them, for a large signal-to-noise ratio, the larger the signal-to-noise ratio is, the better, and ideally it tends to infinity; for a small signal-to-noise ratio, the smaller the signal-to-noise ratio is, the better, and ideally it tends to zero; for an eye-to-eye signal-to-noise ratio, the signal-to-noise ratio is expected to fluctuate around a fixed target value, and the smaller the fluctuation, the better. When designing the optical component 100, it is usually hoped that the brightness value of the optical component 100 can reach the target brightness value (for example, 4nit). Therefore, the present application adopts the eye-to-eye signal-to-noise ratio calculation formula to calculate the brightness value signal-to-noise ratio. Specifically, the signal-to-noise ratio calculation formula is SN=10*Log10(Ybar^2 / s^2), wherein Ybar is the mean brightness value, s is the standard deviation, and taking A taking a level value of 1 (i.e., the surface shape of the first glass layer 11 is a plane) as an example, Ybar is the average value of the simulation results of the brightness values ​​corresponding to the 18 groups of numerical values ​​in Table 4 where A takes a level value of 1, and s is the standard deviation of the simulation results of the brightness values ​​corresponding to the 18 groups of numerical values.

[0107] Among them, according to the principle of maximum signal-to-noise ratio, the first preferred parameter values ​​of the eight key parameters A~H are A2B1C1D1E2F2G2H1, that is, the first preferred parameter value of A is curved surface, the first preferred parameter value of B is 20mm, the first preferred parameter value of C is 0.48mm, the first preferred parameter value of D is in the middle, the first preferred parameter value of E is 1.2mm, the first preferred parameter value of F is from small to large, the first preferred parameter value of G is 18mm, and the first preferred parameter value of H is 1.

[0108] Table 5 Schematic diagram of the first sorting results

[0109]

[0110] In some embodiments, the simulation method further includes:

[0111] Based on the simulation results of the first optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, the mean values ​​of the first optical performance indicators respectively corresponding to the candidate values ​​of each key parameter are calculated;

[0112] Based on the first optical performance index means corresponding to each candidate value of each key parameter, the first optical performance index mean range of each key parameter is calculated; wherein the first optical performance index mean range of each key parameter is the difference between the maximum value and the minimum value of the first optical performance index means corresponding to each candidate value of the key parameter;

[0113] The first optical performance index mean values ​​and ranges of the multiple key parameters are sorted to obtain a second sorting result.

[0114] For example, please refer to Table 6, which takes the first optical performance index as brightness value as an example, and shows the second sorting result obtained from the simulation results shown in Table 4. In this embodiment, the key parameters in the second sorting result are sorted according to the sorting rule from large to small according to the extreme difference value, and specifically, the second sorting result is BDFEHGCA.

[0115] Table 6 Schematic diagram of the second sorting results

[0116]

[0117] In some embodiments, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator at least according to the first sorting result, including:

[0118] According to the first sorting result and the second sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator.

[0119] It should be noted that, the classification result of the multiple key parameters obtained by combining the first sorting result and the second sorting result has higher classification accuracy than the classification result obtained only according to the first sorting result.

[0120] In some embodiments, the multiple key parameters are divided into stable factors, adjustment factors, and secondary factors that affect the robustness of the first optical performance indicator according to the first sorting result and the second sorting result, including:

[0121] Determine the key parameter that ranks first by a preset number of digits in both the first sorting result and the second sorting result as a stabilizing factor that affects the robustness of the first optical performance indicator;

[0122] Determine a key parameter that ranks only in the first sorting result or only in the second sorting result and is ranked in the front by a preset number of places as an adjustment factor that affects the robustness of the first optical performance indicator;

[0123] A key parameter that is not ranked in the front by a preset number of places in both the first sorting result and the second sorting result is determined as a secondary factor affecting the robustness of the first optical performance indicator.

[0124] Exemplarily, please refer to Table 7. Table 7 takes the brightness value as an example of the first optical performance indicator, and shows the first classification result of the multiple key parameters obtained by the first sorting result in Table 4 and the second sorting result in Table 5. In this embodiment, the front preset number of digits is the first 4 digits. In other embodiments, the front preset number of digits may also be other values, which are not limited here.

[0125] Table 7 Schematic table of the first classification results of key parameters

[0126] Key Parameters First sort result Second sort result First category results A 2 - Adjustment Factors B 4 1 Stabilizing factors C - - Secondary factors D 1 2 Stabilizing factors E 3 4 Stabilizing factors F - 3 Adjustment Factors G - - Secondary factors H - - Secondary factors

[0127] In some embodiments, the optical performance index further includes a second optical performance index, wherein the second optical performance index is the other of brightness value and brightness uniformity.

[0128] The method further comprises: determining an optimal parameter value from a plurality of candidate values ​​of each key parameter based on the simulation results of the optical performance indicators respectively corresponding to the plurality of candidate parameter value groups by a robust design algorithm;

[0129] Based on the simulation results of the second optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, and according to the signal-to-noise ratio calculation formula corresponding to the second optical performance indicator, the signal-to-noise ratio of the second optical performance indicator respectively corresponding to each candidate value of each key parameter is calculated;

[0130] The candidate value with the largest signal-to-noise ratio of the second optical performance indicator corresponding to each candidate value of each key parameter is determined as the second preferred parameter value of the key parameter.

[0131] The step of determining the optimal parameter value of each key parameter based at least on the first preferred parameter value of each key parameter comprises:

[0132] Based on the first preferred parameter value and the second preferred parameter value of each key parameter, an optimal parameter value of each key parameter is determined.

[0133] It should be noted that, based on the simulation results of the brightness values ​​corresponding to the multiple candidate parameter value groups, the first preferred parameter value of each key parameter is determined, and based on the simulation results of the brightness uniformity corresponding to the multiple candidate parameter value groups, the second preferred parameter value of each key parameter is determined, and based on the first preferred parameter value and the second preferred parameter value of each key parameter, the optimal parameter value of each key parameter is determined. Therefore, when designing the optical component 100, the two optical performance indicators of brightness value and brightness uniformity can be taken into account to ensure that the two optical performance indicators reach the corresponding target values, which can improve the efficiency of the design.

[0134] In some embodiments, the simulation results of the second optical performance indicators respectively corresponding to the plurality of candidate parameter value groups are based on, according to the signal-to-noise ratio calculation formula corresponding to the second optical performance indicator, to calculate the second optical performance indicator signal-to-noise ratios respectively corresponding to the respective candidate values ​​of each key parameter, including:

[0135] Based on the simulation results of the second optical performance indicators corresponding to the multiple candidate parameter value groups and the multiple error parameter groups, the signal-to-noise ratio of the second optical performance indicator corresponding to each candidate value of each key parameter is calculated according to the signal-to-noise ratio calculation formula corresponding to the second optical performance indicator.

[0136] In some embodiments, the simulation method further includes:

[0137] Based on the second optical performance indicator signal-to-noise ratio corresponding to each candidate value of each key parameter, the second optical performance indicator signal-to-noise ratio range of each key parameter is calculated; wherein the second optical performance indicator signal-to-noise ratio range of each key parameter is the difference between the maximum value and the minimum value of the second optical performance indicator signal-to-noise ratio corresponding to each candidate value of the key parameter;

[0138] Sorting the second optical performance indicator signal-to-noise ratio extreme differences of the multiple key parameters to obtain a third sorting result;

[0139] At least according to the third sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the second optical performance indicator.

[0140] The present application divides the multiple key parameters into stable factors, adjustment factors and secondary factors that affect the robustness of the second optical performance indicator based at least on the third sorting result, and is capable of determining the degree of influence of each key parameter on the second optical performance indicator, thereby facilitating engineers to change the value of the adjustment factor to optimize the second optical performance indicator.

[0141] For example, please refer to Table 8, which takes the second optical performance indicator as brightness uniformity as an example, and shows the third sorting result obtained from the simulation results shown in Table 4. In this embodiment, the key parameters in the third sorting result are sorted according to the sorting rule from large to small extreme values, and specifically, the third sorting result is FGEBADHC.

[0142] When designing the optical component 100 , it is usually hoped that the brightness uniformity of the optical component 100 can be as small as possible. Therefore, the present application adopts a formula for calculating a small signal-to-noise ratio to calculate the brightness uniformity signal-to-noise ratio.

[0143] Among them, according to the principle of maximum signal-to-noise ratio, the second preferred parameter values ​​of the eight key parameters A~H are A1B1C2D1E2F2G3H3, that is, the second preferred parameter value of A is plane, the second preferred parameter value of B is 20mm, the second preferred parameter value of C is 0.53mm, the second preferred parameter value of D is centered, the second preferred parameter value of E is 1.2mm, the second preferred parameter value of F is from small to large, the second preferred parameter value of G is 25mm, and the second preferred parameter value of H is 3.

[0144] Table 8 Schematic diagram of the third sorting results

[0145]

[0146] In some embodiments, the simulation method further includes:

[0147] Based on the simulation results of the second optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, the average values ​​of the second optical performance indicators respectively corresponding to the candidate values ​​of each key parameter are calculated;

[0148] Based on the mean values ​​of the second optical performance indicators corresponding to the candidate values ​​of each key parameter, the mean range of the second optical performance indicators of each key parameter is calculated; wherein the mean range of the second optical performance indicators of each key parameter is the difference between the maximum value and the minimum value of the mean values ​​of the second optical performance indicators corresponding to the candidate values ​​of the key parameter;

[0149] The second optical performance index mean values ​​and ranges of the multiple key parameters are sorted to obtain a fourth sorting result.

[0150] For example, please refer to Table 9, which takes the brightness value as an example of the second optical performance index, and shows the fourth sorting result obtained from the simulation results shown in Table 4. In this embodiment, the key parameters in the fourth sorting result are sorted according to the sorting rule from large to small according to the extreme difference value, and specifically, the fourth sorting result is FGEBADCH.

[0151] Table 9 Schematic diagram of the fourth sorting results

[0152] level A B C D E F G H 1 0.59 0.5887 0.6563 0.5879 0.5961 0.8972 0.725 0.6276 2 0.6685 0.6264 0.6118 0.6663 0.5855 0.3847 0.6059 0.6378 3 0.6727 0.6198 0.6335 0.7062 0.6058 0.5568 0.6224 Very bad 0.0785 0.084 0.0445 0.0784 0.1207 0.5124 0.1682 0.0153 Ranking 5 4 7 6 3 1 2 8

[0153] In some embodiments, the optical performance simulation method further includes:

[0154] According to the third sorting result and the fourth sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the second optical performance indicator.

[0155] In some embodiments, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the second optical performance indicator according to the third sorting result and the fourth sorting result, including:

[0156] Determine the key parameter that ranks first by a preset number of digits in both the third sorting result and the fourth sorting result as a stabilizing factor that affects the robustness of the second optical performance indicator;

[0157] Determine the key parameter that ranks only in the third sorting result or only in the fourth sorting result by a preset number of places as an adjustment factor that affects the robustness of the second optical performance indicator;

[0158] A key parameter that is not ranked in the front by a preset number of places in both the third sorting result and the fourth sorting result is determined as a secondary factor affecting the robustness of the second optical performance indicator.

[0159] For example, please refer to Table 10. Table 10 takes the brightness uniformity as an example of the second optical performance indicator. Table 10 shows the second classification results of the multiple key parameters obtained by the third sorting result in Table 8 and the fourth sorting result in Table 9. In this embodiment, the number of pre-set digits is the first 4 digits. In other embodiments, the number of pre-set digits may also be other values, which are not limited here.

[0160] Table 10 Schematic diagram of the second classification results of key parameters

[0161] Key Parameters The third sorting result Fourth sorting result Second category results A - - Secondary factors B 4 4 Stabilizing factors C - - Secondary factors D - - Secondary factors E 3 3 Stabilizing factors F 1 1 Stabilizing factors G 2 2 Stabilizing factors H - - Secondary factors

[0162] In some embodiments, determining the optimal parameter value of each key parameter based on the first preferred parameter value and the second preferred parameter value of each key parameter includes:

[0163] When a first preferred parameter value and a second preferred parameter value of a key parameter are equal, determining the first preferred parameter value as the optimal parameter value of the key parameter;

[0164] When the first preferred parameter value and the second preferred parameter value of a key parameter are not equal, the brightness uniformity preferred parameter value of the key parameter is determined as the optimal parameter value of the key parameter; wherein the brightness uniformity preferred parameter value of the key parameter is the preferred parameter value determined according to the brightness uniformity signal-to-noise ratio between the first preferred parameter value and the second preferred parameter value.

[0165] It is not difficult to understand that the brightness value of the optical component 100 is most affected by the luminous flux of the light-emitting element 15. Therefore, the brightness value of the optical component 100 can be adjusted to reach the target brightness value by adjusting the luminous flux of the light-emitting element 15. However, the brightness uniformity of the optical component 100 will be affected by the comprehensive influence of many component parameters. Therefore, it is much more difficult to adjust the brightness uniformity than to adjust the brightness value. Therefore, when the first preferred parameter value and the second preferred parameter value of a key parameter are not equal, the preferred parameter value of the brightness uniformity of the key parameter is determined as the optimal parameter value of the key parameter, which can give priority to ensuring that the optical uniformity of the optical component 100 meets the requirements.

[0166] For example, taking the first optical performance index as brightness value and the second optical performance index as brightness uniformity as an example, as mentioned above, the first preferred parameter values ​​of the eight key parameters A to H are A2B1C1D1E2F2G2H1, and the second preferred parameter values ​​of the eight key parameters A to H are A1B1C2D1E2F2G3H3. Among them, the first preferred parameter values ​​and the second preferred parameter values ​​of B, D, E, and F are equal, then the optimal parameter value of B is horizontal value 1, i.e. 20mm, the optimal parameter value of D is horizontal value 1, i.e. centered, the optimal parameter value of E is horizontal value 2, i.e. 1.2mm, and the optimal parameter value of F is horizontal value 2, i.e. small to large. If the first preferred parameter values ​​and the second preferred parameter values ​​of A, C, and G are not equal, the optimal parameter value of A is horizontal value 1, i.e., plane; the optimal parameter value of C is horizontal value 2, i.e., 0.53 mm; and the optimal parameter value of G is horizontal value 3, i.e., 25 mm. Therefore, the optimal parameter values ​​of the seven key parameters A to G are A1B1C2D1E2F2G3.

[0167] In some embodiments, the simulation method further includes:

[0168] The initial model is configured with an initial parameter value group for simulation, and a simulation result of an optical performance index corresponding to the initial parameter value group is obtained; wherein the initial parameter value group includes values ​​of the multiple key parameters, and the value of each key parameter is a corresponding initial value;

[0169] The initial model is configured with the optimal parameter value group for simulation to obtain simulation results of optical performance indicators corresponding to the optimal parameter value group.

[0170] In this way, by comparing the simulation results of the optical performance indicators corresponding to the initial parameter value group with the simulation results of the optical performance indicators corresponding to the optimal parameter value group, it can be verified whether the optimal parameter value group meets the design requirements.

[0171] Exemplarily, it is assumed that when designing the optical component 100, the design requirements to be met are a brightness value of 4nit and a brightness uniformity of ≤25%. Please refer to Table 11, which shows the simulation results of the optical performance indicators corresponding to the initial parameter value group in Table 1 and the simulation results of the optical performance indicators corresponding to the optimal parameter value group obtained by the optical performance simulation method of the optical component provided in this application. It can be seen from Table 11 that there is a large gap between the simulation results of the brightness value and brightness uniformity corresponding to the initial parameter value group and the target brightness value and target brightness uniformity. The simulation result of the brightness value corresponding to the optimal parameter value group is 3.83nit, which is closer to the target brightness value of 4nit than the simulation result of the brightness value corresponding to the initial parameter value group, which is 4.54nit. In addition, the simulation result of the brightness uniformity corresponding to the optimal parameter value group is 18.9%, which is significantly lower than the simulation result of the brightness uniformity corresponding to the initial parameter value group, which is 83.7%, and is also lower than the target brightness uniformity of 25%. Therefore, the optimal parameter value group can ensure that the brightness value and brightness uniformity of the optical component 100 meet the design requirements.

[0172] Table 11 Comparison of simulation results of optical performance indicators corresponding to the initial parameter value group and the optimal parameter value group

[0173]

[0174] In some embodiments, the simulation method further includes:

[0175] Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups, the prediction results of the optical performance indicators corresponding to the optimal parameter value group are calculated through a statistical analysis module.

[0176] Exemplarily, the statistical analysis module can be a predictive analysis module in Minitab software, wherein Minitab software can provide a series of statistical analysis tools, including descriptive statistics, hypothesis testing, regression analysis, quality control, etc., which can be used to discover trends, solve problems and gain valuable insights from data. The predictive analysis module in Minitab software can process large amounts of data, quickly develop models, and generate accurate predictive models.

[0177] In this way, by comparing the simulation results of the optical performance indicators corresponding to the optimal parameter value group and the predicted results of the optical performance indicators corresponding to the optimal parameter value group, the accuracy of the initial model can be verified and further verification can be made as to whether the optimal parameter value group meets the design requirements.

[0178] Exemplarily, please refer to Table 12, which shows the predicted results of the optical performance indicators corresponding to the optimal parameter value group. By comparing Table 11 and Table 12, it can be seen that the predicted result of the brightness value corresponding to the optimal parameter value group is 3.98167, which is close to the simulation value 3.83, and the predicted result of the brightness uniformity corresponding to the optimal parameter value group is 13.84%, which is also close to the simulation result 18.9%. Therefore, it can be further determined that the initial model is accurate and the optimal parameter value group obtained by the optical performance simulation method of the optical component provided in the present application can ensure that the optical performance indicators of the optical component meet the design requirements.

[0179] Table 12 Prediction results of optical performance indicators corresponding to the optimal parameter value group

[0180] Combination Solution Brightness value Brightness uniformity A1B1C2D1E2F2G3 3.98167 13.84％ A2B1C2D1E2F2G3 4.22167 20.68％

[0181] Based on the same inventive concept, the present application also provides an optical performance simulation device for an optical component, the optical performance simulation device comprising a processor and a memory; the memory is coupled to the processor, the memory is used to store computer program code, the computer program code comprises computer instructions, and when the processor executes the computer instructions, the optical performance simulation device for the optical component performs the optical performance simulation method for the optical component as described in any of the above embodiments.

[0182] Based on the same inventive concept, the present application also provides a computer-readable storage medium, in which a computer program or instruction is stored. When the computer program or instruction is executed by an optical performance simulation device of an optical component, the optical performance simulation device of the optical component executes the optical performance simulation method of the optical component as described in any of the above embodiments.

[0183] The computer storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0184] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0185] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0186] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer or may be connected to an external computer (e.g., via the Internet using an Internet service provider) through any type of network, including a local area network (LAN) or a wide area network (WAN).

[0187] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0188] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for simulating the optical performance of an optical component, characterized in that: The simulation method comprises: Acquiring initial values ​​of multiple component parameters of the optical component, and establishing an initial model of the optical component according to the initial values ​​of the multiple component parameters; determining a plurality of key parameters from the plurality of component parameters according to the initial model; Determining a plurality of candidate values ​​for each key parameter based on the initial values ​​of the plurality of key parameters; Combining the candidate values ​​of the plurality of key parameters by a robust design algorithm to obtain a plurality of candidate parameter value groups; wherein each candidate parameter value group includes the values ​​of the plurality of key parameters, and the value of each key parameter is one of the corresponding plurality of candidate values; The initial model is configured with the plurality of candidate parameter value groups for simulation, and simulation results of optical performance indicators corresponding to the plurality of candidate parameter value groups are obtained; Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups, the optimal parameter value is determined from the multiple candidate values ​​of each key parameter through a robust design algorithm, thereby obtaining an optimal parameter value group; wherein the optimal parameter value group includes the values ​​of the multiple key parameters, and the value of each key parameter is the corresponding optimal parameter value.

2. The optical performance simulation method of an optical component according to claim 1, characterized in that: The optical performance index includes at least a first optical performance index, and the robustness design algorithm includes a signal-to-noise ratio calculation formula; The method of determining the optimal parameter value from the multiple candidate values ​​of each key parameter based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups by a robust design algorithm comprises: Based on the simulation results of the first optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, and according to the signal-to-noise ratio calculation formula corresponding to the first optical performance indicator, the first optical performance indicator signal-to-noise ratios respectively corresponding to the candidate values ​​of each key parameter are calculated; Determine the candidate value with the largest signal-to-noise ratio of the first optical performance indicator among the candidate values ​​of each key parameter as the first preferred parameter value of the key parameter; Based at least on the first preferred parameter value of each key parameter, an optimal parameter value for each key parameter is determined.

3. The optical performance simulation method of an optical component according to claim 2, characterized in that: The simulation method further comprises: Based on the first optical performance indicator signal-to-noise ratios corresponding to each candidate value of each key parameter, the first optical performance indicator signal-to-noise ratio range of each key parameter is calculated; wherein the first optical performance indicator signal-to-noise ratio range of each key parameter is the difference between the maximum value and the minimum value of the first optical performance indicator signal-to-noise ratios corresponding to each candidate value of the key parameter; Sorting the first optical performance indicator signal-to-noise ratio extreme differences of the multiple key parameters to obtain a first sorting result; At least according to the first sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator.

4. The optical performance simulation method of an optical component according to claim 3, characterized in that: The simulation method further comprises: Based on the simulation results of the first optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, the mean values ​​of the first optical performance indicators respectively corresponding to the candidate values ​​of each key parameter are calculated; Based on the first optical performance index means corresponding to each candidate value of each key parameter, the first optical performance index mean range of each key parameter is calculated; wherein the first optical performance index mean range of each key parameter is the difference between the maximum value and the minimum value of the first optical performance index means corresponding to each candidate value of the key parameter; Sorting the first optical performance index mean values ​​and ranges of the plurality of key parameters to obtain a second sorting result; The step of dividing the plurality of key parameters into stable factors, adjustment factors and secondary factors affecting the robustness of the first optical performance indicator at least according to the first sorting result comprises: According to the first sorting result and the second sorting result, the multiple key parameters are divided into stable factors, adjustment factors and secondary factors that affect the robustness of the first optical performance indicator.

5. The optical performance simulation method of an optical component according to claim 4, characterized in that: Each key parameter in the first sorting result and the second sorting result is sorted according to the sorting rule of range value from large to small; The method of dividing the plurality of key parameters into stable factors, adjustment factors and secondary factors affecting the robustness of the first optical performance indicator according to the first sorting result and the second sorting result includes: Determine the key parameter that ranks first by a preset number of digits in both the first sorting result and the second sorting result as a stabilizing factor that affects the robustness of the first optical performance indicator; Determine a key parameter that ranks only in the first sorting result or only in the second sorting result and is ranked in the front by a preset number of places as an adjustment factor that affects the robustness of the first optical performance indicator; A key parameter that is not ranked at the top by a preset number of places in both the first sorting result and the second sorting result is determined as a secondary factor affecting the robustness of the first optical performance indicator.

6. The optical performance simulation method of an optical component according to claim 2, characterized in that: The first optical performance index is one of brightness value and brightness uniformity.

7. The optical performance simulation method of an optical component according to claim 6, characterized in that: The optical performance index further includes a second optical performance index; wherein the second optical performance index is the other of a brightness value and a brightness uniformity; The method further comprises: determining an optimal parameter value from a plurality of candidate values ​​of each key parameter based on the simulation results of the optical performance indicators respectively corresponding to the plurality of candidate parameter value groups by a robust design algorithm; Based on the simulation results of the second optical performance indicators respectively corresponding to the plurality of candidate parameter value groups, and according to the signal-to-noise ratio calculation formula corresponding to the second optical performance indicator, the signal-to-noise ratio of the second optical performance indicator respectively corresponding to each candidate value of each key parameter is calculated; Determine the candidate value with the largest signal-to-noise ratio of the second optical performance indicator among the candidate values ​​of each key parameter as the second preferred parameter value of the key parameter; The step of determining the optimal parameter value of each key parameter based at least on the first preferred parameter value of each key parameter comprises: Based on the first preferred parameter value and the second preferred parameter value of each key parameter, an optimal parameter value of each key parameter is determined.

8. The optical performance simulation method of an optical component according to claim 1, characterized in that: The simulation method further comprises: Determine a plurality of error parameter value groups according to the plurality of candidate parameter value groups; wherein each error parameter value group includes values ​​of the plurality of key parameters, and there is at least one error parameter among the plurality of key parameters, and there is a preset error between the value of each error parameter and a candidate value of the error parameter; The initial model is configured with the multiple error parameter groups for simulation, to obtain simulation results of optical performance indicators corresponding to the multiple error parameter groups; The method of determining the optimal parameter value from the multiple candidate values ​​of each key parameter based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups by a robust design algorithm comprises: Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups and the multiple error parameter groups, an optimal parameter value is determined from the multiple candidate values ​​of each key parameter through a robust design algorithm.

9. The optical performance simulation method of an optical component according to claim 1, characterized in that: The simulation method further comprises: The initial model is configured with an initial parameter value group for simulation, and a simulation result of an optical performance index corresponding to the initial parameter value group is obtained; wherein the initial parameter value group includes values ​​of the multiple key parameters, and the value of each key parameter is a corresponding initial value; The initial model is configured with the optimal parameter value group for simulation to obtain simulation results of optical performance indicators corresponding to the optimal parameter value group.

10. The optical performance simulation method of an optical component according to claim 9, characterized in that: The simulation method further comprises: Based on the simulation results of the optical performance indicators respectively corresponding to the multiple candidate parameter value groups, the prediction results of the optical performance indicators corresponding to the optimal parameter value group are calculated through a statistical analysis module.

11. The optical performance simulation method of an optical component according to claim 1, characterized in that: The optical assembly includes a plurality of first glass layers, a second glass layer, a shielding layer, a reflector, a plurality of light-emitting elements, a light guide strip and an adhesive layer; The first glass layer and the second glass layer are stacked along a first direction, and the shielding layer and the reflective element are located between the first glass layer and the second glass layer; The light guide bar is bonded to the side of the second glass layer away from the first glass layer through the bonding layer, the light guide bar has a light incident surface and a light emitting surface, the plurality of light emitting elements are spaced apart from the light incident surface of the light guide bar and are evenly arranged along the extension direction of the light guide bar, the light emitted by the plurality of light emitting elements can enter the light guide bar through the light incident surface, and the light emitted through the light emitting surface can enter the second glass layer from the side of the second glass layer away from the first glass layer; The reflector is used to reflect the light transmitted in the second glass layer, so that the reflected light is emitted from a side of the second glass layer facing away from the first glass layer.

12. The optical performance simulation method of an optical component according to claim 11, characterized in that: The plurality of key parameters include at least one of the following parameters: the surface shape of the first glass layer; The arrangement spacing of the plurality of light emitting elements; The luminous flux of the light emitting element; The distance between the light incident surface of the light guide bar and the light emitting element; The distance between the center of the light incident surface of the light guide strip and the center of the light emitting element in the first direction; the arrangement of the reflective elements; The width of the light guide strip.

13. An optical performance simulation device for an optical component, characterized in that: It comprises a processor and a memory; the memory is coupled to the processor, the memory is used to store computer program code, the computer program code comprises computer instructions, when the processor executes the computer instructions, the optical performance simulation device of the optical component executes the optical performance simulation method of the optical component as described in any one of claims 1-12.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program or instruction. When the computer program or instruction is executed by the optical performance simulation device of the optical component, the optical performance simulation device of the optical component executes the optical performance simulation method of the optical component as described in any one of claims 1-12.

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