A multi-light type precise thermal simulation method, device and medium

Abstract

The application discloses a multi-light-type precise thermal simulation method and device and a medium, relates to the technical field of multi-light-type precise thermal simulation, and comprises the following steps: establishing a whole vehicle global three-dimensional coordinate system, obtaining the whole vehicle three-dimensional coordinates of all pixels in the array based on the preset interval of the pixel array and the three-dimensional feature coordinates of the reference pixel, importing the corresponding gray light pattern picture of the target lighting scene, and calculating the optical duty cycle of each pixel based on the gray value normalization; based on the optical duty cycle, obtaining the chip power parameter and the thermal energy parameter corresponding to each pixel in the array through the preset full-load power parameter of each component; based on the chip power parameter and the thermal energy parameter, binding the whole vehicle three-dimensional coordinates of each pixel with the corresponding thermal energy parameter, generating a whole-array pixel three-dimensional power dataset, and converting the whole-array pixel three-dimensional power dataset into a standardized heat source file that can be recognized by simulation software.

Description

Technical Field

[0001] This invention relates to the field of multi-beam precise thermal simulation technology, and more specifically, to a multi-beam precise thermal simulation method, apparatus, and medium. Background Technology

[0002] Existing thermal simulation methods for HD modules mostly employ two-dimensional planar grayscale value definitions or roughly simplify the modeling of heat sources for LED packaged chips with tens of thousands of pixels. These methods lack precise pixel-level three-dimensional heat source mapping and adaptive multi-beam control based on the vehicle's global coordinate system. Furthermore, the differentiated power distribution of each pixel is difficult to accurately match with the vehicle's assembly reference coordinate system, and the spatial mapping relationship between pixel-level heat sources and the vehicle's three-dimensional geometric model is inefficient. It typically requires manual Excel processing to match coordinates and power parameters, and the heat source distribution needs to be reset when switching lighting scenes. Given the need for HD modules to output lighting for multiple scenarios such as low beam, high beam, pedestrian alert, adaptive light carpet, obstacle recognition, and welcome / farewell modes, the aforementioned methods still fall short in terms of heat source modeling accuracy, coordinate matching efficiency, and adaptability to multi-scenario simulation. Single-scenario data processing is time-consuming, making it difficult to fully meet the thermal reliability verification requirements during the rapid iterative design process of multi-beam HD automotive lights. Summary of the Invention

[0003] This invention provides a multi-light-type precise thermal simulation method, device, and medium to at least solve the technical problems in existing HD module thermal simulation methods, such as the lack of a unified spatial mapping relationship between pixel-level heat sources and the vehicle reference coordinate system, and the difficulty in quickly updating heat source data under different lighting scenarios.

[0004] According to one aspect of the present invention, in order to achieve the above-mentioned objective, a multi-mode precise thermal simulation method is provided, comprising:

[0005] Establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, obtain the three-dimensional coordinates of the whole vehicle for all pixels in the pixel array. Import the grayscale light pattern image corresponding to the target lighting scene and calculate the optical duty cycle of each pixel based on grayscale value normalization.

[0006] Based on the optical duty cycle, the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array are obtained by using the preset full-load power parameters of each component.

[0007] Based on the chip power parameters and thermal energy parameters, the three-dimensional coordinates of each pixel of the whole vehicle are bound to the corresponding thermal energy parameters to generate a full array pixel three-dimensional power dataset. The full array pixel three-dimensional power dataset is converted into a standardized heat source file that can be recognized by the simulation software. The standardized heat source file is imported into the thermal simulation software. Based on the physical stacking structure of the HD module, heat sources are loaded at the corresponding geometric positions of each layer, and boundary conditions are added to complete the thermal simulation.

[0008] Furthermore, the three-dimensional coordinates of the entire vehicle for all pixels within the pixel array are obtained, including:

[0009] Obtain the three-dimensional feature coordinates of the reference pixel and the preset spacing of the pixel array, wherein the preset spacing includes at least: horizontal row spacing and vertical column spacing;

[0010] Based on the three-dimensional feature coordinates of the reference pixel and the preset spacing, the three-dimensional coordinates of the entire vehicle for all pixels in the pixel array are determined.

[0011] Furthermore, the optical duty cycle of each pixel is calculated based on grayscale value normalization, including:

[0012] Obtain the grayscale value of each pixel in the grayscale image, where the grayscale value ranges from 0 to 255;

[0013] The optical duty cycle of each pixel is determined based on the maximum grayscale value of 255.

[0014] Iterate through all pixels of the grayscale image to generate optical duty cycle distribution data for the current lighting scene.

[0015] Furthermore, the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array are obtained, including:

[0016] Based on the optical duty cycle distribution data, determine the actual power parameters of the current pixel;

[0017] Based on the actual power parameters, the chip power parameters and thermal energy parameters corresponding to each pixel are determined. The chip power parameters and thermal energy parameters include: total input electrical power, LED light radiation energy, LED heat generation volume energy, driver chip Joule heat generation volume heat, inverter power loss, and packaging layer light absorption heat generation volume energy.

[0018] Furthermore, the three-dimensional coordinates of each pixel of the vehicle are bound to the corresponding thermal energy parameters to generate a full-array pixel three-dimensional power dataset. This full-array pixel three-dimensional power dataset is then converted into a standardized heat source file that can be recognized by simulation software, including:

[0019] Establish a lookup table with pixel index as key value to structurally bind the three-dimensional coordinates of the whole vehicle of each pixel with the corresponding power parameters of each layer;

[0020] Run the preset data processing script, read the lookup table, and based on the input interface protocol of the thermal simulation software, convert each set of bound data into standardized data containing spatial coordinate attributes and heat source intensity attributes, and write them in batches into standardized heat source files;

[0021] The generated standardized heat source file is imported into the thermal simulation software. Based on the three-dimensional coordinates in the standardized heat source file, the corresponding mesh node of the vehicle's three-dimensional geometric model is automatically located to complete the heat source loading.

[0022] Furthermore, based on the physical stacking structure of the HD modules, heat sources are applied at the corresponding geometric locations of each layer, including:

[0023] The LED heat-generating volume energy from the chip power parameters and thermal energy parameters is applied to the LED light-emitting layer;

[0024] The Joule thermal volumetric heat of the driver chip is applied to the driver chip layer;

[0025] Apply the power loss of the frequency converter to the frequency converter layer;

[0026] The volumetric energy of light absorption and heat generation in the encapsulation layer is transferred to the encapsulation layer.

[0027] Furthermore, after importing the standardized heat source file into the thermal simulation software, and loading heat sources at the corresponding geometric locations of each layer based on the physical stacking structure of the HD module, and supplementing boundary conditions to complete the thermal simulation, the process also includes:

[0028] When switching lighting scenes, obtain the target grayscale image corresponding to the target lighting scene after the switch;

[0029] Based on the target grayscale image, the optical duty cycle is determined and a new three-dimensional power dataset is generated.

[0030] Based on the new 3D power dataset, the standardized heat source file is updated, and a thermal simulation of the lighting scene after the switch is performed.

[0031] Furthermore, when switching between different lighting scenarios for simulation, only the corresponding grayscale light pattern image is replaced and a new three-dimensional power dataset is regenerated, without the need to re-divide the heat source blocks of the vehicle's three-dimensional geometric model.

[0032] According to one embodiment of the present invention, a multi-mode precision thermal simulation device is also provided, comprising:

[0033] The module is used to establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, the three-dimensional coordinates of the whole vehicle of all pixels in the pixel array are obtained. The grayscale light pattern image corresponding to the target lighting scene is imported, and the optical duty cycle of each pixel is calculated based on the grayscale value normalization.

[0034] The parameter module is used to obtain the chip power parameters and thermal energy parameters of each pixel in the pixel array based on the optical duty cycle and the preset full-load power parameters of each component.

[0035] The generation module is used to bind the three-dimensional coordinates of each pixel of the vehicle to the corresponding thermal energy parameters based on the chip power parameters and thermal energy parameters, generate a three-dimensional power dataset of the entire array of pixels, convert the three-dimensional power dataset of the entire array of pixels into a standardized heat source file that can be recognized by the simulation software, import the standardized heat source file into the thermal simulation software, load heat sources at the corresponding geometric positions of each layer based on the physical stacking structure of the HD module, and supplement boundary conditions to complete the thermal simulation.

[0036] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0037] In this embodiment of the invention, by establishing a global three-dimensional coordinate system for the entire vehicle and batch calculating the three-dimensional coordinates of all pixels based on the pixel array pattern, and by normalizing grayscale light pattern images to calculate the optical duty cycle and solving the power parameters of each pixel chip, the coordinates of each pixel can be bound with thermal energy parameters to generate a three-dimensional power dataset, which is then automatically converted into a standardized heat source file and loaded into thermal simulation software. This achieves pixel-level adaptive and accurate modeling of heat sources and unified mapping with the vehicle's reference coordinate system. This thermal simulation method completely overcomes the shortcomings of traditional methods, such as distorted heat source modeling, difficulty in coordinate matching, and low scene switching efficiency. It can accurately restore the differentiated power distribution of various light patterns to accurately identify the risk of local overheating of high-brightness pixels, and supports coupled thermal analysis of the headlight and the entire vehicle. At the same time, switching light patterns only requires replacing the grayscale image to quickly complete multi-condition simulation, which greatly improves the thermal reliability verification cycle of HD headlights in all scenarios and effectively ensures the thermal design safety and development efficiency of HD modules in multiple lighting scenarios. This solves the technical problem that existing HD module thermal simulation methods cannot achieve accurate mapping of heat sources based on vehicle coordinates for tens of thousands of pixels and rapid automatic simulation in multiple scenarios. Attached Figure Description

[0038] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0039] Figure 1 This is a flowchart of a multi-mode precise thermal simulation method according to one embodiment of the present invention;

[0040] Figure 2 This is a flowchart of a multi-mode precise thermal simulation method according to one embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the calibration of the light-emitting surface of an HD ten-thousand-pixel unit in a multi-light type precise thermal simulation method according to one embodiment of the present invention;

[0042] Figure 4 This is a multi-layer structure diagram of an HD packaged chip in a multi-optical precision thermal simulation method according to one embodiment of the present invention;

[0043] Figure 5 This is a structural block diagram of a multi-beam precision thermal simulation device according to one embodiment of the present invention. Detailed Implementation

[0044] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0046] According to an embodiment of the present invention, a method for accurate thermal simulation of multiple light types is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0047] This method embodiment can be executed in an electronic device or similar computing device that includes a memory and a processor. Taking operation on a vehicle terminal as an example, the vehicle terminal may include one or more processors (processors may include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), digital signal processing (DSP) chips, microcontroller units (MCUs), field-programmable gate arrays (FPGAs), neural network processors (NPUs), tensor processors (TPUs), artificial intelligence (AI) type processors, etc.) and a memory for storing data. Optionally, the vehicle terminal may also include transmission devices, input / output devices, and display devices for communication functions. Those skilled in the art will understand that the above structural description is merely illustrative and does not limit the structure of the vehicle terminal. For example, the vehicle terminal may include more or fewer components than described above, or have a different configuration than described above.

[0048] The memory can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the multi-light precise thermal simulation method in this embodiment of the invention. The processor executes various functional applications and data processing by running the computer program stored in the memory, thereby realizing the aforementioned multi-light precise thermal simulation method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0049] The transmission device is used to receive or send data via a network. Specific examples of the network mentioned above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0050] Display devices can be, for example, touchscreen liquid crystal displays (LCDs) and touch displays (also referred to as "touchscreens" or "touch displays"). The LCD allows users to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), which allows users to interact with the GUI through finger contact and / or gestures on a touch-sensitive surface. Optional human-computer interaction functions include: creating web pages, drawing, word processing, creating electronic documents, playing games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital video, playing digital music, and / or web browsing, etc. Executable instructions for performing the above human-computer interaction functions are configured / stored in one or more processor-executable computer program products or readable storage media.

[0051] Figure 1 This is a flowchart of a multi-mode precise thermal simulation method according to one embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0052] Step S110: Establish a global three-dimensional coordinate system for the entire vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, obtain the three-dimensional coordinates of all pixels within the pixel array. Import the grayscale light pattern image corresponding to the target lighting scene, and calculate the optical duty cycle of each pixel based on grayscale value normalization. The specific content is as follows:

[0053] In step S110, after the thermal simulation method is started, a global three-dimensional coordinate system for the entire vehicle must first be established. In actual vehicle applications, the spatial position of the pixel array of the HD module must precisely correspond to the vehicle assembly reference to ensure the accuracy of subsequent heat source loading positions. Specifically, a global three-dimensional coordinate system is established using the global reference point of the vehicle design model as the origin. This coordinate system encompasses a spatial measurement system with three dimensions: X-axis, Y-axis, and Z-axis. The X-axis corresponds to the length direction of the vehicle, the Y-axis to the width direction, and the Z-axis to the height direction. After the global three-dimensional coordinate system is established, all subsequent pixel coordinate calculations and heat source position calibrations are carried out based on this coordinate system.

[0054] Based on the establishment of the global 3D coordinate system of the entire vehicle, coordinate calculation is performed on the pixel array of the HD module. Due to the regular arrangement characteristics of the HD module pixel array, taking a 16,000-pixel (256×64) or 25,600-pixel (320×80) specification as examples, the positions of each pixel in space are not randomly distributed, but arranged in an array according to fixed horizontal row spacing and vertical column spacing. Based on this inherent pattern, a batch calculation method can be used to replace manual measurement, significantly improving the efficiency of coordinate extraction. In specific implementation, the pixel at the starting position is first selected from the pixel array as the reference pixel, typically the first pixel in the upper left corner of the array (i.e., the pixel corresponding to the first row and first column). This reference pixel has definite 3D feature coordinates in the global 3D coordinate system of the entire vehicle and can be directly extracted from the vehicle digital model using 3D measurement equipment.

[0055] After obtaining the 3D feature coordinates of the reference pixel, the preset spacing parameters of the pixel array are further obtained. These preset spacing parameters are inherent structural parameters determined at the factory of the HD module, including at least the horizontal row spacing and the vertical column spacing. The horizontal row spacing refers to the fixed distance between the centers of two adjacent pixels along the row direction, and the vertical column spacing refers to the fixed distance between the centers of two adjacent pixels along the column direction. These preset spacing parameters can be directly read from the HD module's design specifications or extracted from the module's digital model through 3D measurement. Based on the 3D feature coordinates of the reference pixel and the preset spacing of the pixel array, the 3D coordinates of all pixels in the array within the vehicle's global 3D coordinate system can be determined. Specifically, for any pixel in the i-th row and j-th column of the array, its X-axis coordinate is determined by the sum of the X-axis coordinate of the reference pixel and the horizontal row spacing multiplied by the row offset; its Y-axis coordinate is determined by the sum of the Y-axis coordinate of the reference pixel and the vertical column spacing multiplied by the column offset; and its Z-axis coordinate is consistent with the Z-axis coordinate of the reference pixel when the plane in which the pixel array is located is planar.

[0056] After calculating the 3D coordinates of the entire vehicle for all pixels, the grayscale light pattern images corresponding to the target lighting scene are imported in parallel or sequentially. In practical lighting applications, the HD module needs to support the output of multiple lighting scenes, including but not limited to conventional low beam and high beam lighting scenes, as well as customized lighting scenes such as pedestrian alerts, adaptive light carpets, obstacle recognition, and welcome / farewell modes. Each lighting scene corresponds to an independent grayscale light pattern image. The pixel size of this grayscale light pattern image perfectly matches the pixel array specifications of the HD module, and the grayscale value of each pixel in the image directly corresponds to the target driving brightness of the corresponding LED pixel in the HD module array. After the grayscale light pattern image is imported into the system, the grayscale value of each pixel needs to be extracted and parsed.

[0057] In a grayscale image, each pixel has a clearly defined grayscale value, ranging from 0 to 255. A grayscale value of 0 indicates that the corresponding LED is completely off, a grayscale value of 255 indicates that the corresponding LED is on at full brightness, and grayscale values ​​between 0 and 255 indicate that the corresponding LED is in a moderate brightness state with proportional dimming. To convert the grayscale values ​​into quantized parameters for subsequent power calculations, the optical duty cycle of each pixel is determined based on the maximum grayscale value of 255. The optical duty cycle essentially characterizes the driving ratio of the pixel's LED at full brightness, serving as a crucial intermediate quantity connecting the grayscale image definition and the electrical power parameter. For a single pixel, the optical duty cycle is obtained by dividing its grayscale value by the maximum grayscale value of 255. By iterating through all pixels in the grayscale image and performing the above calculations for each pixel, the optical duty cycle distribution data of the entire array of pixels in the current lighting scene can be generated. The optical duty cycle distribution data is stored in the form of a distribution matrix, in which the position of each element corresponds one-to-one with the row and column indices of the pixel array, providing a data foundation for the subsequent calculation of power parameters.

[0058] Step S120: Based on the optical duty cycle, and using the preset full-load power parameters of each component, the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array are obtained. The specific details are as follows:

[0059] In step S120, after generating the optical duty cycle distribution data, the calculation of power and thermal energy parameters begins. Each pixel in the HD module is not an isolated light source unit, but rather integrated into a multi-layered physical stack structure including an LED light-emitting layer, a driver chip layer, a frequency converter layer, and a packaging layer. The power loss generated by each pixel when lit will manifest as heat in different layers. Therefore, it is necessary to calculate the corresponding power and thermal energy parameters for each pixel in each layer to ensure the accuracy and completeness of subsequent heat source loading.

[0060] First, based on the optical duty cycle distribution data, the actual power parameters of the current pixel are determined. Each LED pixel in the HD module has a preset rated power at full brightness. This rated power is a known full-load power parameter of the component, which can be obtained from the HD module's product specifications or through actual measurement and calibration. In actual operation, the pixel does not always operate at full brightness, but is driven with a certain duty cycle according to the grayscale requirements of the target lighting scene. Therefore, the actual power parameters of the current pixel are determined by the full-load power parameter corresponding to the pixel and the optical duty cycle. The optical duty cycle characterizes the driving ratio of the pixel at full brightness. Multiplying the full-load power parameter by the optical duty cycle yields the actual input electrical power of the pixel in the current lighting scene.

[0061] After determining the actual power parameters of each pixel, the chip power parameters and thermal energy parameters corresponding to each pixel are further determined. In the HD module, electrical energy undergoes multiple physical energy conversion stages from input to final output as light energy. Each stage is accompanied by varying degrees of power loss and generates corresponding heat. The aforementioned chip power parameters and thermal energy parameters include several types: firstly, total input electrical power, which is the total electrical power obtained by each pixel from the driving circuit; secondly, LED light radiation energy, which is the energy that the LED chip converts a portion of the input electrical power into light energy and radiates outwards; thirdly, LED heat dissipation volumetric energy, which is the energy in the LED chip that is not converted into light energy and is directly dissipated as heat; fourthly, driver chip Joule heat volumetric heat, which is the Joule heat generated by the switching transistor in the driver chip due to its on-resistance when it is in the conducting state; fifthly, inverter power loss, which is the power loss of the inverter during operation due to switching actions and on-resistance; and sixthly, encapsulation layer light absorption heat volumetric energy, which is the heat generated when the light radiation emitted by the LED is absorbed by the encapsulation material as it passes through the encapsulation layer. The values ​​of all the above-mentioned power parameters and thermal energy parameters are directly related to the optical duty cycle and change synchronously with the change of the duty cycle.

[0062] Taking the volumetric energy of LED heating as an example, after deducting the portion of the actual input electrical power that is converted into light energy and radiated outwards, almost all of the remaining electrical power is converted into heat and accumulates inside the LED chip; this portion is the volumetric energy of LED heating. Taking the Joule heating volumetric energy of a driver chip as an example, the product of the on-resistance of the MOSFET in the driver chip and the square of the effective current, multiplied by the number of channels, yields the Joule heating volumetric energy generated by the driver chip under the current duty cycle. The effective current increases with the increase of the optical duty cycle, resulting in a corresponding increase in the heat generated by the driver chip. Taking the power loss of a frequency converter as an example, frequency converters experience both switching losses and conduction losses during operation. Both types of losses are closely related to the load current, which is directly determined by the optical duty cycle. Taking the volumetric energy of light absorption in the encapsulation layer as an example, when the light radiation emitted by the LED passes through the encapsulation layer material, the encapsulation material has a certain absorption rate for light of different wavelengths. The absorbed light energy is converted into heat and accumulates in the encapsulation layer. This portion of heat is determined by both the LED light radiation energy and the light absorptivity coefficient of the encapsulation material. In practical applications, the amount of heat generated by light absorption in the encapsulation layer is usually much smaller than the heat generated by the LED chip itself. However, in high power density HD modules, this heat is still significant. Accurately calculating and loading the heat generated by light absorption in the encapsulation layer helps improve the overall accuracy of the simulation.

[0063] It should be noted that the aforementioned chip power and thermal energy parameters are not optional choices, but rather a complete set of parameters that need to be calculated synchronously for each pixel under each lighting scenario. Each parameter corresponds to a different layer in the physical stacking structure of the HD module, providing the data foundation for subsequent layered application of heat sources. After the power and thermal energy parameters of all pixels are calculated, the calculation results need to be structured and stored for subsequent binding with the vehicle's 3D coordinates of each pixel. Typically, the distribution data of the power parameters of each layer is stored in matrix form, with the matrix dimensions consistent with the pixel array specifications. The value of each element in the matrix corresponds to the power or heat value of the pixel at that location in the current layer. This completes the process of calculating the chip power and thermal energy parameters for each pixel.

[0064] Step S140: Based on the chip power parameters and thermal energy parameters, bind the three-dimensional coordinates of each pixel to the corresponding thermal energy parameters to generate a full-array pixel three-dimensional power dataset. Convert the full-array pixel three-dimensional power dataset into a standardized heat source file that can be recognized by the simulation software. Import the standardized heat source file into the thermal simulation software. Based on the physical stacking structure of the HD module, load heat sources at the corresponding geometric positions of each layer and supplement boundary conditions to complete the thermal simulation. The specific content is as follows:

[0065] In step S140, after solving for the power parameters and thermal energy parameters of each pixel chip, the generation and standardization of the three-dimensional power dataset begins. Due to the large number of pixels in the HD module, taking a 16,000-pixel or 25,600-pixel specification as an example, each pixel contains the vehicle's three-dimensional coordinates and multiple thermal energy parameters corresponding to four different physical layer structures: the LED light-emitting layer, the driver chip layer, the inverter layer, and the packaging layer. This information needs to be structurally bound to form a complete dataset for subsequent simulation software use. Therefore, a lookup table is first established using pixel indices as keys. The pixel indices use row and column numbering, with the row number corresponding to the pixel's row position in the array and the column number corresponding to the pixel's column position. Each set of row and column numbers uniquely identifies a pixel. In the lookup table, the vehicle's three-dimensional coordinates of the pixel are structurally bound to the corresponding power parameters of each layer. That is, the X-axis coordinates, Y-axis coordinates, Z-axis coordinates, and parameters such as LED heat generation volumetric energy, driver chip Joule heat generation volumetric heat, inverter power loss, and packaging layer light absorption heat generation volumetric energy are associated with the same index entry. After performing the above binding operation on all pixels, a full array of pixel 3D power dataset is generated.

[0066] After generating the full-array pixel 3D power dataset, because mainstream thermal simulation software has specific data input format requirements, it cannot directly read the original lookup table format data. Therefore, the 3D power dataset needs to be converted into a standardized heat source file that the simulation software can recognize. To this end, a pre-built data processing script is run to perform the format conversion. This script is pre-written into the equipment control system or simulation pre-processing system and integrates format definition rules that match the input interface protocol of the target thermal simulation software. After the script runs, it first reads all the bound data stored in the aforementioned lookup table, and then, according to the input interface protocol requirements of the thermal simulation software, converts each set of bound data into standardized data containing spatial coordinate attributes and heat source intensity attributes. The spatial coordinate attributes include the X-axis, Y-axis, and Z-axis coordinates of the pixel in the vehicle's global 3D coordinate system, and the heat source intensity attributes include the power or heat values ​​corresponding to the pixel in the LED light-emitting layer, driver chip layer, inverter layer, and encapsulation layer, respectively. After the conversion is complete, all standardized data is batch-written into the standardized heat source file. Depending on the different interface requirements of the target thermal simulation software, this standardized heat source file can be output in a common data format such as comma-separated value format or Extensible Markup Language format.

[0067] Once the standardized heat source file is generated, it can be imported into the thermal simulation software for subsequent simulation operations. During the import process, the thermal simulation software reads each set of data from the standardized heat source file and automatically locates the corresponding mesh node of the vehicle's 3D geometric model based on the 3D coordinates carried in the data, completing the automatic loading and spatial mapping of the heat source. This eliminates the need for manual specification of the position of each pixel heat source in the model, enabling rapid and accurate loading of tens of thousands of pixel heat sources. After the heat sources are loaded, different types of heat sources are loaded at the corresponding geometric positions of each layer according to the physical stacking structure of the HD module. The multi-layered physical stacking structure of the HD module, from bottom to top or top to bottom, includes an LED light-emitting layer, a driver chip layer, an inverter layer, and a packaging layer. The LED light-emitting layer is the functional layer where the pixel LED chips reside and is also the area with the most concentrated heat generation. The specific heat source allocation method is as follows: The LED heat generation volumetric energy from the aforementioned chip power parameters and thermal energy parameters is loaded onto the LED light-emitting layer. This part of the heat is the main heat source generated by the pixel LED chip during operation due to the limitation of electro-optical conversion efficiency. The Joule heat generation volumetric energy of the driver chip is loaded onto the driver chip layer. The driver chip layer is located below the LED light-emitting layer and contains the switching transistor array and related control circuits required to drive each pixel LED. The switching transistors generate Joule heat when they are in the conducting state, and the heat generation is directly related to the duty cycle. The inverter loss power is loaded onto the inverter layer. The inverter is used to convert the vehicle DC power supply into the voltage and current required to drive the LED. During the frequency conversion process, the switching devices will generate switching losses and conduction losses. The light absorption heat generation volumetric energy of the encapsulation layer is loaded onto the encapsulation layer. The encapsulation layer covers the LED light-emitting layer and plays a dual role of optical emission and physical protection. The light radiation emitted by the LED is partially absorbed and converted into heat when passing through the encapsulation material. Although this part of the heat is less than the heat generated by the LED itself, it will still affect the temperature distribution in high power density scenarios.

[0068] After the heat sources for each layer are loaded according to the above correspondence, the boundary conditions required for the simulation need to be added. The boundary conditions include at least the ambient temperature, the convective heat transfer coefficient, and the thermal conductivity of each layer material. The ambient temperature reflects the background temperature of the space where the HD module is located under actual vehicle operating conditions; for example, the ambient temperature can be set to a preset value. The convective heat transfer coefficient is used to characterize the ability of heat to be transferred from the module surface to the surrounding air, and can be set according to the airflow state and surface characteristics of the module location. The thermal conductivity of each layer material corresponds to the inherent thermal conductivity parameters of the materials used in the LED light-emitting layer, driver chip layer, inverter layer, and encapsulation layer, and is the basic input for heat conduction calculation. Based on the completion of heat source loading and boundary condition addition, a solid mesh is generated, and multi-physics field coupling calculations such as heat conduction and heat convection are performed on each layer structure to finally complete steady-state thermal simulation or transient thermal simulation. The simulation results can directly output the temperature distribution data of each pixel location and the overall temperature field cloud map of the module, which can be used to locate whether there is a risk of local overheating in the high-brightness pixel area, providing a quantitative basis for the multi-beam thermal reliability design of the HD module.

[0069] When switching between different lighting scenarios for simulation, there is no need to re-divide the heat source blocks of the vehicle's 3D geometric model or repeat the vehicle coordinate calculation process. Only the corresponding grayscale light pattern image needs to be replaced, the optical duty cycle redefined, a new 3D power dataset generated, and the standardized heat source file updated accordingly. This allows for rapid completion of the thermal simulation for the new scenario. This scenario switching process significantly reduces the data preparation time for multi-condition thermal simulation, effectively supporting the rapid iteration requirements for full-scenario thermal reliability verification of HD automotive lights.

[0070] Based on steps S110 to S140 above, in this embodiment of the invention, by establishing a global three-dimensional coordinate system for the whole vehicle and batch calculating the three-dimensional coordinates of all pixels of the whole vehicle based on the pixel array pattern, and by calculating the optical duty cycle and solving the power parameters of each pixel chip in conjunction with the normalization of grayscale light pattern images, the coordinates of each pixel can be bound with the thermal energy parameters to generate a three-dimensional power dataset and automatically converted into a standardized heat source file to be loaded into the thermal simulation software, thereby realizing the pixel-level heat source adaptive and accurate modeling and the unified mapping of the whole vehicle reference coordinate system. This thermal simulation method completely overcomes the shortcomings of traditional methods, such as distorted heat source modeling, difficulty in coordinate matching, and low scene switching efficiency. It can accurately reproduce the differentiated power distribution of various light patterns to accurately identify the risk of local overheating of high-brightness pixels, and supports coupled thermal analysis of the headlight and the whole vehicle. At the same time, switching light patterns only requires replacing the grayscale image to quickly complete multi-condition simulation, which greatly improves the thermal reliability verification cycle of HD headlights in all scenarios. It effectively ensures the thermal design safety and development efficiency of HD modules in multiple lighting scenarios, and solves the technical problem that existing HD module thermal simulation methods cannot achieve accurate mapping of heat sources based on vehicle coordinates for tens of thousands of pixels and rapid automatic simulation in multiple scenarios.

[0071] The multi-beam precise thermal simulation method of the present invention obtains the three-dimensional coordinates of the whole vehicle of all pixels in the array, including: obtaining the three-dimensional feature coordinates of the reference pixel and the preset spacing of the pixel array, wherein the preset spacing includes at least: horizontal row spacing and vertical column spacing; and determining the three-dimensional coordinates of the whole vehicle of all pixels in the array based on the three-dimensional feature coordinates of the reference pixel and the preset spacing.

[0072] Furthermore, the optical duty cycle of each pixel is calculated based on grayscale value normalization, including: obtaining the grayscale value of each pixel in the grayscale light pattern image, wherein the grayscale value ranges from 0 to 255; determining the optical duty cycle of each pixel based on the maximum grayscale value of 255; and traversing all pixels of the grayscale light pattern image to generate optical duty cycle distribution data of the current lighting scene.

[0073] Furthermore, the chip power parameters and thermal energy parameters corresponding to each pixel in the array are obtained, including: determining the actual power parameters of the current pixel based on the optical duty cycle distribution data; and determining the chip power parameters and thermal energy parameters corresponding to each pixel based on the actual power parameters. The chip power parameters and thermal energy parameters include: total input electrical power, LED light radiation energy, LED heat generation volumetric energy, driver chip Joule heat generation volumetric heat, inverter power loss, and packaging layer light absorption heat generation volumetric energy.

[0074] Furthermore, the three-dimensional coordinates of each pixel of the vehicle are bound to the corresponding thermal energy parameters to generate a full-array pixel three-dimensional power dataset. The full-array pixel three-dimensional power dataset is then converted into a standardized heat source file that can be recognized by the simulation software. This includes: establishing a lookup table with pixel indices as keys to structurally bind the three-dimensional coordinates of each pixel of the vehicle to the corresponding power parameters of each layer; running a pre-set data processing script to read the lookup table and, based on the input interface protocol of the thermal simulation software, converting each set of bound data into standardized data containing spatial coordinate attributes and heat source intensity attributes, and writing it in batches into the standardized heat source file; importing the generated standardized heat source file into the thermal simulation software, and automatically locating the corresponding mesh node of the three-dimensional geometric model of the vehicle according to the three-dimensional coordinates in the standardized heat source file to complete the heat source loading.

[0075] Furthermore, based on the physical stacking structure of the HD module, heat sources are applied at the corresponding geometric positions of each layer, including: applying the LED heat generation volume energy from the chip power parameters and thermal energy parameters to the LED light-emitting layer; applying the Joule heat generation volume heat of the driver chip to the driver chip layer; applying the inverter loss power to the inverter layer; and applying the light absorption heat generation volume energy of the encapsulation layer to the encapsulation layer.

[0076] Furthermore, after importing the standardized heat source file into the thermal simulation software, and loading heat sources at the corresponding geometric positions of each layer based on the physical stacking structure of the HD module, and supplementing boundary conditions to complete the thermal simulation, the process also includes: when switching lighting scenes, obtaining the target grayscale light pattern image corresponding to the target lighting scene after the switch; determining the optical duty cycle and generating a new three-dimensional power dataset based on the target grayscale light pattern image; updating the standardized heat source file based on the new three-dimensional power dataset, and performing thermal simulation of the lighting scene after the switch.

[0077] Furthermore, when switching between different lighting scenarios for simulation, only the corresponding grayscale light pattern image is replaced and a new three-dimensional power dataset is regenerated, without the need to re-divide the heat source blocks of the vehicle's three-dimensional geometric model.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0079] A multi-mode precise thermal simulation method according to another embodiment of the present invention, such as Figures 2-4 As shown, the method includes the following steps:

[0080] Suitable for 16,000-pixel and 25,600-pixel HD packaged chips of various specifications. The HD packaged chip integrates driver chip, frequency converter, pixel LED, and packaging structure; the HD module can output conventional low beam and high beam lighting scenarios, as well as customized lighting scenarios such as pedestrian alerts, adaptive light carpets, obstacle recognition, and welcome / farewell modes. Each scenario corresponds to an independent grayscale light pattern image, with a grayscale value range of 0~255, and a grayscale value of 255 is the standard for full pixel brightness; for example... Figure 4 The multi-layer structure diagram of the HD packaged chip shown includes: LED light-emitting layer 1, driver chip layer 2, inverter layer 3, and package layer 4. The thermal simulation method includes the following steps:

[0081] S10. Establish a coordinate mapping model;

[0082] First, establish a global 3D coordinate system for the entire vehicle. For the HD module pixel array (e.g., a 16,000-pixel array is arranged in 256×64, and a 25,600-pixel array is arranged in 320×80), select the pixel located at the starting position (e.g., row 1, column 1) within the array as the reference pixel, and obtain the 3D feature coordinates. Because the pixel arrangement of the HD module is regular, this embodiment uses a batch calculation method to obtain the coordinates of the entire array. The known horizontal row spacing of the pixels is... The vertical column spacing is For any nth element in the array line, number The pixels in the column, and the three-dimensional coordinates of the whole vehicle. The calculation is as follows:

[0083] (1)

[0084] (2)

[0085] (3)

[0086] (Note: If the pixel surface is not planar, the Z value needs to be corrected according to the surface equation.)

[0087] S20, Calculation of optical duty cycle;

[0088] Import the grayscale image of the target lighting scene. Define the optical duty cycle. The calculation formula is:

[0089] (4)

[0090] in This represents the grayscale value of the current pixel (range 0-255). Iterate through all pixels in the image to generate a complete optical duty cycle distribution matrix.

[0091] S30, Solving for multidimensional power parameters;

[0092] Based on optical duty cycle Based on the electro-optical conversion characteristics of the components, a hierarchical energy decoupling model is used to calculate various physical quantities. The specific calculation formulas are as follows:

[0093] (1) Total input power: ,in This is the forward conduction voltage of the LED. This is the peak drive current;

[0094] (2) LED light radiation surface energy ,in The electro-optical conversion efficiency of the LED chip;

[0095] (3) LED heating volume energy: That is, the portion of electrical energy that is not converted into light energy is converted into heat energy;

[0096] (4) Joule volumetric heat of the driving chip ,in RMS current (and duty cycle) (related) To drive the MOSFET's on-resistance, Number of channels;

[0097] (5) Inverter power loss: Estimate based on switching frequency and load current;

[0098] (6) Light absorption and heat generation in the encapsulation layer: ,in It is the absorption coefficient of the encapsulation material for a specific wavelength of light.

[0099] S40, Automated data processing and format conversion;

[0100] The calculated "pixel-level vehicle 3D coordinates" are then bound to the "power parameters" to generate a 3D power dataset containing tens of thousands of data points. This step utilizes a pre-built automated data processing program. The program's internal processing logic is as follows:

[0101] (1) Input interface: Read the CSV format power dataset (containing fields: Pixel_ID, X, Y, Z, Power_LED, Power_Chip...) and the geometric mesh file of the whole vehicle 3D model generated in step S30.

[0102] (2) Coordinate matching algorithm: The program traverses each coordinate point in the power dataset. Using a spatial search algorithm, the nearest mesh node or unit center is found in the 3D model mesh of the whole vehicle, and a mapping relationship between data points and simulation mesh is established.

[0103] (3) Format reconstruction: The mapped power data is reconstructed according to the specific format (such as .xml or .cmd script language) required by the thermal simulation software (such as Starccm+) to generate a standardized heat source file.

[0104] (4) Output interface: Outputs heat source files that can be directly read by simulation software.

[0105] S50: Layered loading and simulation execution; importing standardized heat source files into the thermal simulation software. Based on the physical stacking structure of the HD modules, a hierarchical model is established in the simulation software, allocating different heat sources to:

[0106] Will Apply to the surface of the LED light-emitting layer;

[0107] Will Loaded into the driver chip layer entity;

[0108] Will Loaded to the inverter layer;

[0109] Will The light absorbs heat and transfers it to the encapsulation layer.

[0110] When switching between different lighting scenarios for simulation, simply replace the corresponding grayscale image and re-execute steps S20~S50 to generate an independent three-dimensional power dataset to complete the comparison of simulation results for multiple scenarios.

[0111] The present invention will be further described below with reference to the embodiments.

[0112] Example 1: Thermal simulation of adaptive high beam scene with 25,600 pixels; In this example, the HD module pixel specification is 320 rows × 80 columns, totaling 25,600 pixels, and the horizontal and vertical spacing of the single pixel is fixed.

[0113] The specific steps are as follows:

[0114] 1. Establish a global 3D coordinate system for the entire vehicle: Select the first point at the top left corner of the array as the reference pixel, and collect the 3D feature coordinates of the four corners of the LED light-emitting surface, the midpoint of the driver chip, the midpoint of the inverter, and the midpoints of each layer of the encapsulation layer; traverse the system cyclically along the fixed offset of the rows and columns to generate all 25,600 pixels of the vehicle's 3D coordinates in batches.

[0115] 2. Import grayscale light pattern map: Import the adaptive high beam grayscale light pattern map, in which the grayscale of the road highlight area is 255 (duty cycle 100%), the grayscale of the light-dark transition area is 178 (69.80%), the grayscale of the road dark area is 20 (7.84%), and the grayscale of the area without light occlusion is 0 (0%). Calculate the two-dimensional distribution matrix of optical duty cycle pixel by pixel;

[0116] 3. Calculate power parameters: Based on the duty cycle matrix obtained in step 2, and combined with the physical characteristics of the HD module, calculate the energy distribution of each layer according to the following logic:

[0117] (1) Determine the total power consumption: Assume that the rated power of a single-pixel LED at grayscale 255 (duty cycle 100%) is (For example, 0.2W). This indicates the actual input electrical power of the current pixel. .

[0118] (2) Calculation of LED light source layer:

[0119] Effective luminous flux: based on the electro-optical conversion efficiency provided in the LED datasheet. (For example, 40%), calculate the emitted light energy. This portion of energy is loaded onto the LED light-emitting layer as a "volume heat source" or "surface light source".

[0120] (3) Calculation of the driving and control layer:

[0121] Driver IC heat generation: Driver chips mainly generate switching losses and conduction losses. Since the current is proportional to the duty cycle, its average heat generation power is approximately... (Linear simplified model) or more precise Model.

[0122] (4) Inverter / Power Supply Layer: Similarly, calculate the power loss under this operating condition based on the power conversion efficiency curve. .

[0123] (5) Photothermal coupling calculation of the encapsulation layer: Considering that some light will be absorbed by the lens or phosphor layer and converted into heat energy, the light absorption rate of the encapsulation material is set to be 100%. (For example, 5%). Then the additional heat source of the encapsulation layer... .

[0124] 4. 3D Data Construction and Automated Export: This step is achieved by executing a preset data processing script. The specific logic is as follows:

[0125] (1) Data index construction: The script first creates a two-dimensional array index, with the horizontal axis corresponding to the pixel column number. (1~80), the vertical axis corresponds to the pixel row number $i$(1~320).

[0126] (2) Coordinate-power mapping: The script iterates through the array, and for each index The coordinate formula generated in step 1 is used to calculate its absolute position in the vehicle coordinate system. At the same time, the power calculation results from step 3 are called to obtain the four power values ​​of LED, driver, inverter, and encapsulation layer at that location.

[0127] (3) Formatted output: The script writes the above data into a CSV file line by line according to the field order of ID, X_Coord, Y_Coord, Z_Coord, Power_LED, Power_Driver, Power_Inverter, and Power_Package.

[0128] 5. Simulation Execution: Import the CSV heat source file into the thermal simulation software, automatically match the 3D model of the whole vehicle based on the vehicle coordinates, and load the heat sources of LED, driver chip, inverter, and packaging structure in layers; set the ambient temperature to 25℃, the convective heat transfer coefficient of the engine compartment shell, and the thermal conductivity of each layer of material, and complete the steady-state thermal simulation after dividing the solid mesh; the simulation results can intuitively locate the local high temperature in the 255 grayscale high-brightness pixel area and identify the risk of overheating failure under high brightness conditions of high beam.

[0129] Example 2: Thermal simulation of a 16,000-pixel pedestrian alert light carpet scene;

[0130] The HD module has a resolution of 256×64 pixels, totaling 16384 pixels. A grayscale light pattern image for pedestrian alerts is imported, with the pedestrian sign pattern having a grayscale value of 233 (91.37% duty cycle) and the road background having a grayscale value of 100 (39.22% duty cycle). The system then sequentially performs vehicle coordinate extraction, grayscale duty cycle conversion, multi-layer chip power parameter calculation, and data processing to automatically generate a 3D power dataset for the entire vehicle. When switching scenes, only the grayscale image is replaced; there is no need to modify the heat source partitioning of the 3D vehicle model. This allows for rapid completion of the thermal simulation of the pedestrian alert operation, and direct comparison and analysis with the temperature field of the high beam operation in Example 1.

[0131] Example 3: Batch simulation verification in multiple scenarios;

[0132] Five types of grayscale light pattern images—low beam, high beam, adaptive light carpet, obstacle recognition, and welcome / farewell—are imported in batches. A multi-scene grayscale duty cycle conversion module sequentially generates five independent duty cycle matrices; a 3D power dataset automatic generation module outputs five standardized heat source files. These are then imported into simulation software to complete parallel simulations under multiple operating conditions. No manual modification of the model's heat source partitions is required throughout the process, significantly shortening the full-scenario thermal reliability verification cycle for HD automotive lights.

[0133] This invention also provides a multi-beam precision thermal simulation device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0134] Figure 5 According to one embodiment of the present invention, a multi-beam precision thermal simulation device includes:

[0135] Module 201 is used to establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, the three-dimensional coordinates of all pixels in the array are obtained. The grayscale light pattern image corresponding to the target lighting scene is imported, and the optical duty cycle of each pixel is calculated based on the grayscale value normalization.

[0136] The parameter module 202 is used to obtain the chip power parameters and thermal energy parameters corresponding to each pixel in the array based on the optical duty cycle and the preset full-load power parameters of each component.

[0137] The generation module 203 is used to bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding thermal energy parameters based on the chip power parameters and thermal energy parameters, generate a three-dimensional power dataset of the whole array pixels, convert the three-dimensional power dataset of the whole array pixels into a standardized heat source file that can be recognized by the simulation software, import the standardized heat source file into the thermal simulation software, load heat sources at the corresponding geometric positions of each layer based on the physical stacking structure of the HD module, and supplement boundary conditions to complete the thermal simulation.

[0138] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0139] According to one embodiment of the present invention, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described multi-mode precise thermal simulation method during runtime.

[0140] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0141] Step S1: Establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, obtain the three-dimensional coordinates of the whole vehicle for all pixels in the array. Import the grayscale light pattern image corresponding to the target lighting scene and calculate the optical duty cycle of each pixel based on grayscale value normalization.

[0142] Step S2: Based on the optical duty cycle, the chip power parameters and thermal energy parameters corresponding to each pixel in the array are obtained through the preset full-load power parameters of each component.

[0143] Step S3: Based on the chip power parameters and thermal energy parameters, bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding thermal energy parameters to generate a three-dimensional power dataset of the whole array pixels. Convert the three-dimensional power dataset of the whole array pixels into a standardized heat source file that can be recognized by the simulation software. Import the standardized heat source file into the thermal simulation software. Based on the physical stacking structure of the HD module, load heat sources at the corresponding geometric positions of each layer and supplement boundary conditions to complete the thermal simulation.

[0144] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the storage medium is located to execute the above-described multi-mode precise thermal simulation method.

[0145] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0146] Step S1: Establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, obtain the three-dimensional coordinates of the whole vehicle for all pixels in the array. Import the grayscale light pattern image corresponding to the target lighting scene and calculate the optical duty cycle of each pixel based on grayscale value normalization.

[0147] Step S2: Based on the optical duty cycle, the chip power parameters and thermal energy parameters corresponding to each pixel in the array are obtained through the preset full-load power parameters of each component.

[0148] Step S3: Based on the chip power parameters and thermal energy parameters, bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding thermal energy parameters to generate a three-dimensional power dataset of the whole array pixels. Convert the three-dimensional power dataset of the whole array pixels into a standardized heat source file that can be recognized by the simulation software. Import the standardized heat source file into the thermal simulation software. Based on the physical stacking structure of the HD module, load heat sources at the corresponding geometric positions of each layer and supplement boundary conditions to complete the thermal simulation.

[0149] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0150] According to one embodiment of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described multi-mode precise thermal simulation method.

[0151] Optionally, in this embodiment, the above-mentioned computer program product can be configured as a computer program that performs the following steps:

[0152] Step S1: Establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, obtain the three-dimensional coordinates of the whole vehicle for all pixels in the array. Import the grayscale light pattern image corresponding to the target lighting scene and calculate the optical duty cycle of each pixel based on grayscale value normalization.

[0153] Step S2: Based on the optical duty cycle, the chip power parameters and thermal energy parameters corresponding to each pixel in the array are obtained through the preset full-load power parameters of each component.

[0154] Step S3: Based on the chip power parameters and thermal energy parameters, bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding thermal energy parameters to generate a three-dimensional power dataset of the whole array pixels. Convert the three-dimensional power dataset of the whole array pixels into a standardized heat source file that can be recognized by the simulation software. Import the standardized heat source file into the thermal simulation software. Based on the physical stacking structure of the HD module, load heat sources at the corresponding geometric positions of each layer and supplement boundary conditions to complete the thermal simulation.

[0155] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0156] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components can be integrated into another system, or some features can be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections can be through some interfaces; indirect couplings or communication connections between units or modules can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0159] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0160] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0161] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-mode accurate thermal simulation method, characterized in that, include: A global three-dimensional coordinate system for the entire vehicle is established. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, the three-dimensional coordinates of all pixels in the pixel array are obtained. The grayscale light pattern image corresponding to the target lighting scene is imported, and the optical duty cycle of each pixel is calculated based on the grayscale value normalization. Based on the optical duty cycle, the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array are obtained by using the preset full-load power parameters of each component. Based on the chip power parameters and the thermal energy parameters, the three-dimensional coordinates of each pixel of the whole vehicle are bound to the corresponding thermal energy parameters to generate a full array pixel three-dimensional power dataset. The full array pixel three-dimensional power dataset is converted into a standardized heat source file that can be recognized by the simulation software. The standardized heat source file is imported into the thermal simulation software. Based on the physical stacking structure of the HD module, heat sources are loaded at the corresponding geometric positions of each layer, and boundary conditions are added to complete the thermal simulation.

2. The multi-mode precise thermal simulation method according to claim 1, characterized in that, Obtaining the three-dimensional coordinates of the entire vehicle for all pixels within the pixel array includes: Obtain the three-dimensional feature coordinates of the reference pixel and the preset spacing of the pixel array, wherein the preset spacing includes at least: horizontal row spacing and vertical column spacing; Based on the three-dimensional feature coordinates of the reference pixel and the preset spacing, the three-dimensional coordinates of the entire vehicle for all pixels in the pixel array are determined.

3. The multi-mode precise thermal simulation method according to claim 2, characterized in that, The optical duty cycle of each pixel is calculated based on grayscale value normalization, including: Obtain the grayscale value of each pixel in the grayscale image, wherein the grayscale value ranges from 0 to 255; The optical duty cycle of each pixel is determined based on the maximum grayscale value of 255. Traverse all pixels of the grayscale image to generate optical duty cycle distribution data for the current lighting scene.

4. The multi-mode precise thermal simulation method according to claim 3, characterized in that, Obtaining the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array includes: Based on the optical duty cycle distribution data, the actual power parameters of the current pixel are determined; Based on the actual power parameters, the chip power parameters and thermal energy parameters corresponding to each pixel are determined. The chip power parameters and thermal energy parameters include: total input electrical power, LED light radiation energy, LED heat generation volume energy, driver chip Joule heat generation volume heat, inverter power loss, and packaging layer light absorption heat generation volume energy.

5. The multi-mode precise thermal simulation method according to claim 4, characterized in that, The three-dimensional coordinates of each pixel in the vehicle are bound to the corresponding thermal energy parameters to generate a full-array pixel three-dimensional power dataset. This full-array pixel three-dimensional power dataset is then converted into a standardized heat source file recognizable by simulation software, including: Establish a lookup table with pixel index as key value, and structurally bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding power parameters of each layer; Run the preset data processing script, read the lookup table, and based on the input interface protocol of the thermal simulation software, convert each set of bound data into standardized data containing spatial coordinate attributes and heat source intensity attributes, and write them in batches into the standardized heat source file; The generated standardized heat source file is imported into the thermal simulation software, and the corresponding mesh node of the vehicle's three-dimensional geometric model is automatically located according to the three-dimensional coordinates in the standardized heat source file to complete the heat source loading.

6. The multi-mode precise thermal simulation method according to claim 5, characterized in that, Based on the physical stacking structure of the HD module, heat sources are applied at the corresponding geometric locations of each layer, including: The LED heat-generating volume energy from the chip power parameters and the thermal energy parameters is applied to the LED light-emitting layer; The Joule thermal volumetric heat of the driving chip is applied to the driving chip layer; The power loss of the frequency converter is applied to the frequency converter layer; The volumetric energy of light absorption and heating in the encapsulation layer is loaded onto the encapsulation layer.

7. The multi-mode precise thermal simulation method according to claim 6, characterized in that, After importing the standardized heat source file into the thermal simulation software, and loading heat sources at the corresponding geometric positions of each layer based on the physical stacking structure of the HD module, and supplementing boundary conditions to complete the thermal simulation, the software further includes: When switching lighting scenes, obtain the target grayscale image corresponding to the target lighting scene after the switch; Based on the target grayscale image, the optical duty cycle is determined and a new three-dimensional power dataset is generated. The standardized heat source file is updated based on the new three-dimensional power dataset, and a thermal simulation of the lighting scene after the switch is performed.

8. The multi-mode precise thermal simulation method according to claim 7, characterized in that, When switching between different lighting scenes for simulation, only the corresponding grayscale light pattern image is replaced and the new three-dimensional power dataset is regenerated, without the need to redivide the heat source blocks of the whole vehicle three-dimensional geometric model.

9. A multi-beam precision thermal simulation device, characterized in that, include: The module is used to establish a global three-dimensional coordinate system for the whole vehicle. Based on the preset spacing of the pixel array and the three-dimensional feature coordinates of the reference pixel, the three-dimensional coordinates of the whole vehicle of all pixels in the pixel array are obtained. The grayscale light pattern image corresponding to the target lighting scene is imported, and the optical duty cycle of each pixel is calculated based on the grayscale value normalization. The parameter module is used to obtain the chip power parameters and thermal energy parameters corresponding to each pixel in the pixel array based on the optical duty cycle and through preset full-load power parameters of each component. The generation module is used to bind the three-dimensional coordinates of each pixel of the whole vehicle with the corresponding thermal energy parameters based on the chip power parameters and the thermal energy parameters, generate a three-dimensional power dataset of the whole array pixels, convert the three-dimensional power dataset of the whole array pixels into a standardized heat source file that can be recognized by the simulation software, import the standardized heat source file into the thermal simulation software, load heat sources at the corresponding geometric positions of each layer based on the physical stacking structure of the HD module, and supplement boundary conditions to complete the thermal simulation.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium resides to perform the multi-optical precision thermal simulation method of any one of claims 1 to 8.

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