Digital wind tunnel model simulation method, device, equipment, storage medium and product

Abstract

The present invention discloses a digital wind tunnel model simulation method, device, equipment, storage medium and product, including obtaining a pre-built initial heavy-duty truck body model, and performing region division preprocessing on the initial heavy-duty truck body model to obtain a heavy-duty truck body simulation model; determining model simulation parameters of the heavy-duty truck body simulation model, and generating a heavy-duty truck body digital model based on the model simulation parameters; performing simulation analysis on at least one area of ​​interest in the heavy-duty truck body digital model to obtain simulation analysis results of each area of ​​interest; determining target boundary simulation parameters based on the simulation analysis results of at least one area of ​​interest, and updating the model simulation parameters of the heavy-duty truck body digital model based on the target boundary simulation parameters to obtain target heavy-duty truck body simulation model parameter adjustment results, thereby solving the problem that heavy trucks are difficult to conduct actual vehicle testing and improving the simulation accuracy of digital wind tunnel simulation experiments for heavy trucks and the consistency of simulation experiment results.

Description

Technical Field

[0001] The present invention relates to the field of digital processing technology, and in particular to a digital wind tunnel model simulation method, device, equipment, storage medium and product. Background Art

[0002] When heavy-duty trucks and other large commercial vehicles are in motion, they involve a variety of vehicle aerodynamic technologies, such as vehicle air resistance, vehicle wind noise, vehicle fan system air volume, air conditioning system, intake and exhaust fluid temperature, etc. The above-mentioned aerodynamic analysis mainly includes wind tunnel tests, road tests, computational fluid dynamics technology and other methods. Among them, wind tunnel tests can accurately simulate the aerodynamic characteristics of the whole vehicle, but currently, large-sized vehicles such as heavy-duty trucks in China cannot meet the wind tunnel blockage ratio requirements. Therefore, it is difficult to use real vehicle testing, and some aerodynamic characteristics cannot be analyzed using scaled model tests, which is not conducive to the analysis of fluid dynamics technology for heavy-duty trucks. At the same time, although road tests can more accurately reproduce user scenarios, relevant test results are difficult to obtain, there are many road interference factors, and the accuracy of test results is poor.

[0003] To shorten the heavy-duty truck development cycle, researchers have developed a computational fluid dynamics (CFD) application method that combines wind tunnel testing with simulated wind tunnel testing. However, this method can only assist with passenger car styling design and aerodynamic optimization, ultimately improving performance. It is less effective for large vehicles like heavy-duty trucks, which prioritize performance and problem-solving. Furthermore, the virtual wind tunnel dimensions differ significantly from those used for passenger car wind tunnel testing.

[0004] Therefore, how to set and adjust the body model simulation parameters of heavy trucks, the difficulty in conducting actual vehicle testing of heavy trucks, and improving the simulation accuracy and consistency of simulation experiment results of digital wind tunnel simulation experiments for heavy trucks have become topics that relevant technical personnel urgently need to study. Summary of the Invention

[0005] The present invention provides a digital wind tunnel model simulation method, device, equipment, storage medium and product to solve the problem of difficulty in conducting actual vehicle testing of heavy trucks by setting and adjusting the simulation parameters of the heavy truck body model, and to improve the simulation accuracy of the heavy truck digital wind tunnel simulation experiment and the consistency of the simulation experiment results.

[0006] According to one aspect of the present invention, a digital wind tunnel model simulation method is provided, comprising:

[0007] Obtaining a pre-built initial heavy truck body model, and performing region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes a plurality of body model sub-regions;

[0008] Determining model simulation parameters of the heavy truck body simulation model, and generating a heavy truck body digital model according to the model simulation parameters;

[0009] Performing simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas of the body model;

[0010] According to the simulation analysis result of the at least one area of ​​interest, target boundary simulation parameters are determined, and according to the target boundary simulation parameters, model simulation parameters of the heavy truck body digital model are updated to obtain target heavy truck body simulation model parameter adjustment results.

[0011] According to another aspect of the present invention, there is provided a digital wind tunnel model simulation device, comprising:

[0012] A heavy truck body simulation model acquisition module is used to obtain a pre-built initial heavy truck body model and perform region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes multiple body model sub-regions;

[0013] A heavy truck body digital model generation module is used to determine the model simulation parameters of the heavy truck body simulation model and generate the heavy truck body digital model according to the model simulation parameters;

[0014] a simulation analysis result acquisition module, configured to perform simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body, and obtain simulation analysis results for each area of ​​interest; the area of ​​interest is one or more of the plurality of sub-areas of the body model;

[0015] The model simulation parameter updating module is used to determine the target boundary simulation parameters according to the simulation analysis results of the at least one area of ​​interest, and to update the model simulation parameters of the heavy truck body digital model according to the target boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment results.

[0016] According to another aspect of the present invention, an electronic device is provided, comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can perform the digital wind tunnel model simulation method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the digital wind tunnel model simulation method according to any embodiment of the present invention when executed.

[0021] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the digital wind tunnel model simulation method according to any embodiment of the present invention is implemented.

[0022] The technical solution of the embodiment of the present invention is to obtain a pre-built initial heavy truck body model and perform region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes multiple body model sub-regions; determine the model simulation parameters of the heavy truck body simulation model, and generate a heavy truck body digital model based on the model simulation parameters; perform simulation analysis on at least one focus area in the heavy truck body digital model to obtain simulation analysis results of each focus area; the focus area is one or more of the multiple body model sub-regions; determine the target boundary simulation parameters based on the simulation analysis results of at least one focus area, and update the model simulation parameters of the heavy truck body digital model based on the target boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment results. This technical solution can obtain the analysis results of the simulation analysis of the simulation parameters set for the heavy truck body model by processing and analyzing the initial heavy truck body model, thereby realizing the setting and adjustment of the simulation parameters of the heavy truck body model, solving the problem that heavy trucks are difficult to conduct actual vehicle testing, and shortening the development cycle of the whole vehicle.

[0023] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 This is a flow chart of a digital wind tunnel model simulation method provided according to the first embodiment of the present invention;

[0026] Figure 2 This is a flow chart of a digital wind tunnel model simulation method provided according to the second embodiment of the present invention;

[0027] Figure 3 2 is a schematic structural diagram of a digital wind tunnel model simulation device provided according to a third embodiment of the present invention;

[0028] Figure 4 The figure is a schematic diagram of the structure of an electronic device for implementing the digital wind tunnel model simulation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged 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 variations thereof 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 clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Example 1

[0032] Figure 1 A flowchart of a digital wind tunnel model simulation method is provided for the first embodiment of the present invention. This embodiment is applicable to situations where large-sized heavy trucks cannot meet the wind tunnel blockage ratio requirements, it is difficult to use real vehicle testing, and some aerodynamic characteristics cannot be analyzed using scaled models. The method can be executed by a digital wind tunnel model simulation device, which can be implemented in the form of hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110 , obtaining a pre-built initial heavy truck body model, and performing region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes a plurality of body model sub-regions.

[0034] The initial heavy-duty truck body model can be a model constructed based on the three-dimensional data of the heavy-duty truck body. Specifically, it can be a display model generated by technicians based on the heavy-duty truck body information directly input, and does not support aerodynamic characteristics analysis. The heavy-duty truck body simulation model can be a body model generated based on the initial heavy-duty truck body model, with a model sub-region capable of performing aerodynamic characteristics analysis. The aerodynamic characteristics may include wind resistance, wind noise, and intake and exhaust of the heavy-duty truck body.

[0035] The pre-processing of the initial heavy-duty truck body model by region division can specifically involve identifying and dividing the obtained initial heavy-duty truck body model into sub-regions. Specifically, the corresponding heavy-duty truck body in the initial heavy-duty truck body model may include a front portion and a body portion. The front portion can be divided, for example, to obtain a front windshield region, left and right door glass regions, and an intake and exhaust grille region. The body portion can also be divided, for example, to obtain a trailer region and a cargo box region. Based on the resulting sub-regions of the body model, a body simulation model is generated for aerodynamic characteristics analysis.

[0036] S120: Determine model simulation parameters of the heavy truck body simulation model, and generate a heavy truck body digital model according to the model simulation parameters.

[0037] The model simulation parameters may be dimension parameters set for each sub-region of the heavy truck body simulation model, and may be specifically set by relevant technicians based on practical experience. For example, the dimensions of the front windshield region may be set to, for example, 195 cm in length and 100 cm in width.

[0038] The digital model of the heavy truck body may specifically be a simulation model of the heavy truck body generated according to size parameters set for each sub-region of the body model.

[0039] Optionally, model simulation parameters of the heavy-duty truck body simulation model are determined, and a digital model of the heavy-duty truck body is generated based on the model simulation parameters, including: obtaining the number of axles of the heavy-duty truck body simulation model, and determining the associated axles that are associated with the adjustment of the body posture; determining the type of cargo box corresponding to the heavy-duty truck body to which the heavy-duty truck body simulation model belongs; determining the cargo box position parameters of the heavy-duty truck body cargo box based on the associated axles according to the cargo box type; determining the relative position relationship between the cargo box and the body boundary of the heavy-duty truck body simulation model based on the cargo box position parameters; determining the model simulation parameters of the heavy-duty truck body simulation model based on the relative position relationship, and generating a digital model of the heavy-duty truck body based on the model simulation parameters.

[0040] Among them, the number of axles can refer to the number of rows of tires in the heavy truck body corresponding to the heavy truck body simulation model. For example, if there are three rows of tires in the heavy truck body, it can be determined that the number of axles of the heavy truck body simulation model corresponding to the heavy truck body is three.

[0041] The associated axles may specifically refer to the first axle and the last axle in the heavy truck body. For example, if the number of axles in the heavy truck body is four, the associated axles of the heavy truck body are the first axle and the fourth axle. The cargo box type may include trailers, cargo boxes, and flatbed trailers.

[0042] Specifically, the number of axles of the heavy truck body can be determined, and specific axles (i.e., the first axle and the last axle) can be selected as the associated axles for the heavy truck posture adjustment, so that the posture of the heavy truck body is more consistent with the state under the actual weight balance condition, that is, the heavy truck body can be guaranteed to be in the same straight line under the condition of the actual weight balance of the heavy truck body. For example, if the cargo is placed too close to the tail of the heavy truck body, the posture of the heavy truck body can be obtained with the tail facing down and the head facing up. At the same time, the cargo box position parameter information of the heavy truck body cargo box can also be adjusted according to the cargo box type and the associated axles. Specifically, the position parameter information of different cargo box types is different. For example, the cargo box can be a load-bearing matching cargo box, or it can be a trailer cargo box or other cargo box types that need to match a saddle. Then, the position parameters can be adjusted according to different cargo box types.

[0043] The body boundary may refer to the contour boundary of the heavy truck body corresponding to the heavy truck body simulation model. Specifically, heavy trucks are large vehicles, and the overall posture of the heavy truck body and the position parameter information of the entire vehicle position are relatively complex. When the heavy truck body is under different counterweight conditions, the overall posture of the heavy truck body varies greatly. Therefore, trucks, tractor trailers, etc. need to combine the relative position relationship between the body boundaries of the entire vehicle, cargo box, trailer, etc. to set the model simulation parameters of the heavy truck body simulation model, thereby generating a heavy truck body digital model.

[0044] S130 , performing simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas of the body model.

[0045] The region of interest can be a sub-region of the vehicle body model where aerodynamic data of the heavy-duty truck body can be directly collected and aerodynamic characteristics of the heavy-duty truck body can be calculated. For example, the front surface area and the front windshield area can be used to obtain the heavy-duty truck body's drag coefficient, and the left and right door glass areas can be used to obtain the heavy-duty truck body's wind noise data. In this case, the front surface area, the front windshield area, and the left and right door glass areas can be identified as the region of interest. Simulation analysis results can include the heavy-duty truck body's drag coefficient, wind noise, and the heavy-duty truck body's intake and exhaust system parameters.

[0046] The simulation analysis results of each area of ​​interest can be obtained by collecting and analyzing the aerodynamic data of the heavy truck body for each body model sub-area for which the aerodynamic characteristic data of the heavy truck body can be obtained, and obtaining the aerodynamic characteristic analysis results corresponding to each model sub-area. For example, if the drag coefficient of the heavy truck body is analyzed, the front surface area and the front windshield area can be focused on to obtain the body surface pressure and the flow field in the nearby space, and to obtain the relevant flow field, surface pressure, vortex and other data to analyze the drag coefficient of the heavy truck body; if the wind noise of the heavy truck body is analyzed, the left and right door glass areas can be focused on to obtain the pressure pulsation and gap airflow on the surface of the left and right door glass areas respectively, to obtain the wind noise related acoustic indicators, glass pressure pulsation, noise distribution diagram, noise slice diagram and other data to analyze the wind noise of the heavy truck body.

[0047] Optionally, a simulation analysis is performed on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest, including: obtaining aerodynamic simulation results of the digital model of the heavy truck body based on model simulation parameters of the digital model of the heavy truck body and based on preset simulation working conditions; and performing simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body based on the aerodynamic simulation results to obtain simulation analysis results for each area of ​​interest.

[0048] Among them, the simulation working condition scenario may refer to the simulation of the real scene of the heavy truck body corresponding to the digital model of the heavy truck body during the actual driving process, where the real scene may include climbing, high-speed driving and crosswind, etc. The specific simulation working condition scenario may be set by technical personnel based on actual experience.

[0049] Specifically, the aerodynamic results of the heavy truck body digital model can be obtained by simulating the real scenes encountered by the heavy truck body during actual driving, and collecting aerodynamic simulation data near the heavy truck body based on the real simulated scenes. Furthermore, based on the obtained aerodynamic results, any model sub-area in the heavy truck body digital model can be simulated and analyzed to obtain the corresponding simulation analysis results. Continuing with the above example, for example, the surface pressure of the vehicle body and the flow field in the surrounding space can be collected to obtain aerodynamic data such as the relevant flow field, surface pressure, vorticity, etc., and the drag coefficient of the front surface area and the front windshield area can be simulated and analyzed to obtain the simulation results of the heavy truck body drag coefficient; the pressure pulsation and gap airflow data of the left and right door glass areas can also be collected separately to obtain wind noise related acoustic indicators, glass pressure pulsation, noise distribution diagram, noise slice diagram and other aerodynamic data, so as to simulate and analyze the wind noise of the left and right door glass areas separately and obtain the simulation results of the heavy truck body wind noise.

[0050] S140. Determine target boundary simulation parameters based on the simulation analysis results of at least one area of ​​interest, and update model simulation parameters of the heavy truck body digital model based on the target boundary simulation parameters to obtain target heavy truck body simulation model parameter adjustment results.

[0051] The target boundary simulation parameters may refer to the model simulation parameters of the heavy-duty truck body digital model whose simulation analysis results meet the heavy-duty truck body design requirements. The design requirements may specifically refer to the simulation analysis results meeting pre-set aerodynamic characteristic values, which may include pre-set body drag coefficient, body wind noise value, and intake and exhaust system parameters.

[0052] Updating the model simulation parameters of the heavy-duty truck body digital model may specifically refer to iteratively updating the model simulation parameters stored in a historical database using model simulation parameters obtained that meet heavy-duty truck body design standards. The historical database may be a database used to store model simulation parameters obtained from historical heavy-duty truck body simulations. For example, if a pre-set aerodynamic characteristic value for the drag coefficient is 0.5Cd (Drag Coefficient), a simulation analysis of the drag coefficient of the front surface area and the front windshield area may be performed, and the simulation result for the heavy-duty truck body drag coefficient is 0.42Cd. This means that the simulation analysis result for the drag coefficient is lower than the pre-set aerodynamic characteristic value for the drag coefficient. The model simulation parameters for the front surface area and the front windshield area in the heavy-duty truck body digital model may then be determined as target boundary simulation parameters. Furthermore, the model simulation parameters in the historical database may be updated based on the target boundary simulation parameters, resulting in an adjustment result for the model parameters of the heavy-duty truck body simulation model.

[0053] It should be noted that the heavy truck body digital model can be specifically generated by setting the model parameters of the model sub-region in the heavy truck body simulation model. Therefore, the heavy truck body digital model and the heavy truck body simulation model can be exactly the same or different.

[0054] Optionally, based on the simulation analysis results of at least one area of ​​interest, target boundary simulation parameters are determined, and based on the target boundary simulation parameters, the model simulation parameters of the heavy-duty truck body digital model are updated to obtain the target heavy-duty truck body simulation model parameter adjustment results, including: based on the simulation analysis results of at least one area of ​​interest, judging whether the area boundary simulation parameters corresponding to each area of ​​interest meet the preset boundary simulation parameter storage conditions; if so, determining the target heavy-duty truck body boundary simulation parameters, and based on the target heavy-duty truck body boundary simulation parameters, adjusting the parameters of the heavy-duty truck body digital model to obtain the target heavy-duty truck body simulation model parameter adjustment results.

[0055] The boundary simulation parameter storage condition may be to determine whether the model simulation parameters of the heavy truck body digital model and the preset simulation working condition scenario meet the preset parameter range.

[0056] For example, continuing with the above example, the aerodynamic characteristic value of the drag coefficient can be 0.5Cd, and the parameter range of the side wind in the preset simulation working condition scenario can be 0 to 30 meters per second. In the simulation analysis of the heavy truck body, the side wind is 25 meters per second, and the analysis result of the simulation analysis of the drag coefficient of the heavy truck body is 0.45Cd, then it can be determined that the corresponding regional boundary simulation parameters meet the preset boundary simulation parameter storage conditions; if a side wind of more than 30 meters per second occurs in the simulation analysis of the heavy truck body, the corresponding regional boundary simulation parameters can be determined as not meeting the preset boundary simulation parameter storage conditions, and the simulation model analysis results can be directly output.

[0057] The technical solution of the embodiment of the present invention is to obtain a pre-built initial heavy truck body model and perform region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes multiple body model sub-regions; determine the model simulation parameters of the heavy truck body simulation model, and generate a heavy truck body digital model based on the model simulation parameters; perform simulation analysis on at least one focus area in the heavy truck body digital model to obtain simulation analysis results of each focus area; the focus area is one or more of the multiple body model sub-regions; determine the target boundary simulation parameters based on the simulation analysis results of at least one focus area, and update the model simulation parameters of the heavy truck body digital model based on the target boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment results. This technical solution can obtain the analysis results of the simulation analysis of the simulation parameters set for the heavy truck body model by processing and analyzing the initial heavy truck body model, realize the setting and adjustment of the simulation parameters of the heavy truck body model, solve the problem that heavy trucks are difficult to conduct actual vehicle testing, and improve the simulation accuracy of the heavy truck digital wind tunnel simulation experiment and the consistency of the simulation experiment results.

[0058] Example 2

[0059] Figure 2 This is a flow chart of a digital wind tunnel model simulation method provided in the second embodiment of the present invention. Figure 2 This is a flow chart of a digital wind tunnel model simulation method provided in the second embodiment of the present invention. Based on the above embodiments, this embodiment further optimizes the above digital wind tunnel model simulation method.

[0060] Furthermore, the step of "pre-processing the initial heavy truck body model by dividing the regions to obtain a heavy truck body simulation model" is refined into "performing regional segmentation on the initial heavy truck body model through a grid generator to obtain a plurality of body model sub-regions; determining the relative position of each body model sub-region relative to the initial heavy truck body model according to the regional position coordinates of each body model sub-region; for any body model sub-region, judging whether the body model sub-region meets the preset key region judgment condition according to the regional relative position of the body model sub-region; if so, adjusting the parameters of the grid generator, and based on the grid generator with the adjusted parameters, performing regional segmentation on the body model sub-region to obtain an updated body model sub-region; generating a heavy truck body simulation model according to each updated body model sub-region" to improve the generation method of the heavy truck body simulation model. Figure 2 As shown, the method includes:

[0061] S210 , obtaining a pre-built initial heavy truck body model, and performing region segmentation on the initial heavy truck body model using a mesh generator to obtain a plurality of body model sub-regions.

[0062] The pre-built initial heavy truck body model can be segmented using a mesh generator to obtain different model sub-regions within the initial heavy truck body model. The mesh generator can include structured and unstructured meshes, and specific algorithms can include partial differential equations and joint element methods to identify and segment the model sub-regions within the initial heavy truck body model. This embodiment does not impose any specific limitations on this.

[0063] Specifically, the initial heavy truck body model is segmented into regions through a grid generator to obtain multiple body model sub-regions. Different model sub-regions in the initial heavy truck body model can be identified and divided. Specifically, the initial heavy truck body model can be segmented through an unstructured network to obtain the front windshield, left and right door glass, and intake and exhaust grille regions divided into a grid.

[0064] S220 : Determine the relative position of each body model sub-region relative to the initial heavy truck body model according to the regional position coordinates of each body model sub-region.

[0065] The regional position coordinates may specifically refer to the coordinates of the center points of each vehicle body model sub-region. Specifically, there is a corresponding association relationship between each vehicle body model sub-region, and the regional position coordinates of each vehicle body model sub-region are relatively fixed relative to the regional position of the initial heavy truck body model. For example, if the position coordinates of the left door region in each vehicle body model sub-region are (1, 1, 2), the position coordinates of the right door region are (4, 4, 2), the regional position coordinates of the left door glass are (1, 1, 3), the regional position coordinates of the right door are (4, 4, 3), the regional position coordinates of the front windshield are (2, 0, 3), and the regional position coordinates of the intake and exhaust grille region are (2, 0, 1), then the position information of each vehicle body model sub-region relative to the initial heavy truck body model can be determined based on the regional position coordinates of each vehicle body model sub-region.

[0066] S230 : For any vehicle body model sub-region, determine whether the vehicle body model sub-region meets a preset key region determination condition according to the relative position of the vehicle body model sub-region.

[0067] The key area judgment condition may be used to determine whether the vehicle body model sub-area is an area for performing aerodynamic characteristic simulation analysis of a heavy truck body.

[0068] For example, continuing with the above example, according to the regional position coordinates of the front windshield area being (2, 0, 3), it can be determined that the front windshield area is located at the front end of the initial heavy truck body model relative to the initial heavy truck body model. It can be mainly the area used for simulation analysis of the heavy truck body drag coefficient, that is, the front windshield area can be determined as the key area.

[0069] S240: If yes, adjust the parameters of the grid generator, and segment the vehicle body model sub-region based on the grid generator with the adjusted parameters to obtain updated vehicle body model sub-regions.

[0070] Adjusting the parameters of the grid generator may be adjusting the size of the region segmented by the grid generator, and specifically, may be improving the quality of the grid generated by the grid generator. Specifically, if the front windshield area is a key area for simulation analysis of the drag coefficient of a heavy truck body, it is necessary to adjust the quality of the grid generated by the grid generator, and use the adjusted grid generator to perform a more detailed division of the front windshield area, such as by using a structured network to divide the front windshield area into 5×5 cm grids. This embodiment does not impose any specific restrictions on this.

[0071] S250: Generate a heavy truck body simulation model based on the updated body model sub-regions.

[0072] Among them, the model sub-region of the initial heavy truck body model processed by the grid generator can be obtained, specifically, the model sub-region after the coarse processing of the initial heavy truck body model divided by the unstructured network, and the model sub-region after the key area is updated by the structured network can be obtained, and thereby a heavy truck body simulation model that can perform heavy truck body aerodynamic characteristics analysis can be generated.

[0073] Optionally, a heavy truck body simulation model is generated based on the updated body model sub-regions, including: determining the regional boundary association relationship between each body model sub-region and its corresponding adjacent body model sub-region, and determining whether each body model sub-region meets the preset boundary continuity judgment condition based on the regional boundary association relationship; if not, filling the regional grid of the boundary area between the body model sub-region that does not meet the boundary continuity judgment condition and its adjacent body model sub-region until the boundary continuity judgment condition is met, thereby obtaining the heavy truck body simulation model.

[0074] The boundary continuity judgment condition can determine whether the coordinate difference between adjacent boundary positions of the associated vehicle body model sub-regions meets a preset threshold. The threshold can be preset by technicians based on actual experience.

[0075] For example, the threshold for the difference between the boundary position coordinates of the left door region and the boundary position coordinates of the left door glass region is 0.1. The boundary position coordinates of the left door region can be (1, 1, 2.5), and the boundary position coordinates of the left door glass region can be (1, 1, 2.55). Therefore, if the difference between the boundary position coordinates of the left door region and the boundary position coordinates of the left door glass region is 0.05, it can be determined that the preset boundary continuity judgment condition is met between the left door region and the left door glass region. Alternatively, the boundary position coordinates of the left door region can be (1, 1, 2.3), and the boundary position coordinates of the left door glass region can be (1, 1, 2.6). Therefore, if the difference between the boundary position coordinates of the left door region and the boundary position coordinates of the left door glass region is 0.3, it can be determined that the preset boundary continuity judgment condition is not met between the left door region and the left door glass region. Specifically, a grid of a certain size standard can be set, such as a 0.25×0.25 grid, to fill the boundary area between the left door area and the left door glass area with a regional grid to meet the boundary continuity judgment condition and obtain a heavy truck body simulation model.

[0076] Optionally, before generating a heavy-duty truck body simulation model based on the updated body model sub-regions, it also includes: identifying each body component in the initial heavy-duty truck body model, and for any body component in the initial heavy-duty truck body model, judging whether the body component meets a preset retention judgment standard; if not, deleting the body component from the initial heavy-duty truck body model, and obtaining an updated initial heavy-duty truck body model.

[0077] Among them, the body parts may include internal space parts of the body such as the cockpit, engine and heat shield, etc., and may also include external body parts such as the front windshield, left and right door glass, etc., and may also include external porous parts of the body such as intake and exhaust grilles, etc.

[0078] Among them, judging whether the body component meets the preset retention judgment standard can specifically be to determine whether the body component can have an effect on the aerodynamic characteristics analysis results of the heavy-duty truck body. Optionally, if the body component is an internal space component of the vehicle body, it can be determined that the body component does not meet the preset retention judgment standard, and the body component can be deleted from the initial heavy-duty truck body model, and an updated initial heavy-duty truck body model can be obtained. For example, if the internal component is a vehicle body engine, in the actual heavy-duty truck body design, the layout position of the engine is usually hidden inside the vehicle body, so the analysis results of the aerodynamic characteristics of the heavy-duty truck body can be completely unaffected by the vehicle body engine, that is, if it is determined that the vehicle body engine does not meet the preset retention judgment standard, the body component can be deleted from the initial heavy-duty truck body model.

[0079] Optionally, if the body part is a porous external part, it can be determined that the body part does not meet the preset retention judgment criteria and the body part can be separated from the initial heavy-duty truck body model; the separated body parts are individually set to obtain an updated initial heavy-duty truck body model. By identifying the body parts of the initial heavy-duty truck body model, the internal body parts and the external porous parts of the heavy-duty truck body can be automatically identified, removed, and separated, thereby improving the efficiency of generating heavy-duty truck body simulation models and reducing the loss of computing resources required for model simulation.

[0080] S260: Determine model simulation parameters of the heavy truck body simulation model, and generate a heavy truck body digital model according to the model simulation parameters.

[0081] S270 , performing simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas of the body model.

[0082] S280. Determine target boundary simulation parameters based on the simulation analysis results of at least one area of ​​interest, and update model simulation parameters of the heavy truck body digital model based on the target boundary simulation parameters to obtain target heavy truck body simulation model parameter adjustment results.

[0083] The technical solution of the embodiment of the present invention is to segment the initial heavy-duty truck body model using a grid generator to obtain multiple body model sub-regions; determine the relative position of each body model sub-region relative to the initial heavy-duty truck body model based on the regional position coordinates of each body model sub-region; determine whether the body model sub-region meets the preset key region judgment conditions based on the regional relative position of the body model sub-region; if so, adjust the parameters of the grid generator, and segment the body model sub-region based on the parameter-adjusted grid generator to obtain updated body model sub-regions; and generate a simulated heavy-duty truck body model based on each updated body model sub-region. This technical solution improves the processing efficiency before model simulation and ensures the accuracy and reliability of the initial heavy-duty truck body model by utilizing automated pre-processing technology to process and adjust the initial heavy-duty truck body model. The grid generator is also used to transform the initial heavy-duty truck body model, ensuring that simulation parameters can be set and adjusted for the heavy-duty truck body model, solving the problem of difficulty in conducting actual vehicle testing of heavy-duty trucks and improving the simulation accuracy and consistency of simulation results of digital wind tunnel simulation experiments of heavy-duty trucks.

[0084] Example 3

[0085] Figure 3This is a schematic diagram of the structure of a digital wind tunnel model simulation device provided in the third embodiment of the present invention. The digital wind tunnel model simulation device provided in the embodiment of the present invention is applicable to situations where large-sized heavy trucks cannot meet the wind tunnel blockage ratio requirements, it is difficult to use real vehicle testing, and some aerodynamic characteristics cannot be analyzed using scaled models. The digital wind tunnel model simulation device can be implemented in the form of hardware and / or software, such as Figure 3 As shown, it specifically includes: an initial model acquisition module 310, a digital model generation module 320, a simulation analysis module 330 and a simulation parameter update module 340.

[0086] The initial model acquisition module 310 is used to obtain a pre-built initial heavy truck body model and perform region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes multiple body model sub-regions;

[0087] The digital model generation module 320 is used to determine the model simulation parameters of the heavy truck body simulation model and generate the digital model of the heavy truck body according to the model simulation parameters;

[0088] A simulation analysis module 330 is configured to perform simulation analysis on at least one region of interest in the digital model of the heavy truck body, and obtain simulation analysis results for each region of interest; the region of interest is one or more of the plurality of sub-regions of the body model;

[0089] The simulation parameter updating module 340 is used to determine the target boundary simulation parameters according to the simulation analysis results of the at least one area of ​​interest, and to update the model simulation parameters of the heavy truck body digital model according to the target boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment results.

[0090] This technical solution can obtain the analysis results of the simulation parameters set for the heavy-duty truck body model by processing and analyzing the initial heavy-duty truck body model, realize the setting and adjustment of the simulation parameters of the heavy-duty truck body model, solve the problem that heavy-duty trucks are difficult to conduct actual vehicle testing, and improve the simulation accuracy of heavy-duty truck digital wind tunnel simulation experiments and the consistency of simulation experiment results.

[0091] Optionally, the initial model acquisition module 310 includes:

[0092] A region segmentation unit is used to perform region segmentation on the initial heavy truck body model through a mesh generator to obtain a plurality of body model sub-regions;

[0093] a relative position determining unit, configured to determine the relative position of each of the vehicle body model sub-regions relative to the initial heavy truck body model according to the regional position coordinates of each of the vehicle body model sub-regions;

[0094] A region condition judgment unit is used to judge, for any vehicle body model sub-region, whether the vehicle body model sub-region meets a preset key region judgment condition according to the region relative position of the vehicle body model sub-region;

[0095] a region segmentation unit, configured to adjust parameters of the mesh generator if the vehicle body model sub-region meets a preset key region judgment condition, and perform region segmentation on the vehicle body model sub-region based on the mesh generator with the adjusted parameters to obtain an updated vehicle body model sub-region;

[0096] The body model generating unit is used to generate a simulated heavy truck body model according to each updated body model sub-region.

[0097] Optionally, the initial model acquisition module 310 further includes:

[0098] a body component identification unit, configured to identify each body component in the initial heavy truck body model before generating a heavy truck body simulation model based on each updated body model sub-region, and determine, for any body component in the initial heavy truck body model, whether the body component meets a preset retention judgment criterion;

[0099] The initial model updating unit is configured to delete the body component from the initial heavy truck body model if it is determined that the body component does not meet a preset retention judgment standard, and obtain an updated initial heavy truck body model.

[0100] Optionally, the vehicle body model generation unit is specifically used to:

[0101] Determining a region boundary association relationship between each vehicle body model sub-region and its corresponding adjacent vehicle body model sub-region, and determining whether each vehicle body model sub-region satisfies a preset boundary coherence judgment condition based on the region boundary association relationship;

[0102] If the body model sub-region does not meet the preset boundary coherence judgment condition, the boundary area of ​​the body model sub-region that does not meet the boundary coherence judgment condition and its adjacent body model sub-region is filled with regional grids until the boundary coherence judgment condition is met, thereby obtaining a simulated heavy truck body model.

[0103] Optionally, the heavy truck body digital model generation module 320 is specifically used to obtain the number of axles of the heavy truck body simulation model, and determine the associated axles that are associated with the body posture adjustment; determine the cargo box type corresponding to the heavy truck body to which the heavy truck body simulation model belongs; determine the cargo box position parameters of the heavy truck body cargo box based on the associated axles according to the cargo box type; determine the relative position relationship between the cargo box and the body boundary of the heavy truck body simulation model based on the cargo box position parameters; determine the model simulation parameters of the heavy truck body simulation model based on the relative position relationship, and generate the heavy truck body digital model based on the model simulation parameters.

[0104] Optionally, the simulation analysis result acquisition module 330 is specifically used to obtain the aerodynamic simulation results of the heavy-duty truck body digital model based on the model simulation parameters of the heavy-duty truck body digital model and based on a preset simulation working condition scenario; based on the aerodynamic simulation results, perform simulation analysis on at least one area of ​​interest in the heavy-duty truck body digital model to obtain simulation analysis results for each area of ​​interest.

[0105] Optionally, the model simulation parameter update module 340 is specifically used to determine whether the regional boundary simulation parameters corresponding to each of the focus areas meet the preset boundary simulation parameter storage conditions based on the simulation analysis results of the at least one focus area; if so, determine the target heavy truck body boundary simulation parameters, and adjust the parameters of the heavy truck body digital model according to the target heavy truck body boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment results.

[0106] The digital wind tunnel model simulation device provided in the embodiment of the present invention can execute the digital wind tunnel model simulation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0107] Example 4

[0108] Figure 4 A schematic diagram of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0109] like Figure 4As shown, electronic device 40 includes at least one processor 41 and memory, such as read-only memory (ROM) 42 and random access memory (RAM) 43, communicatively connected to at least one processor 41. The memory stores computer programs executable by the at least one processor. Processor 41 can perform various appropriate actions and processes based on the computer programs stored in ROM 42 or loaded from storage unit 48 into RAM 43. RAM 43 can also store various programs and data required for the operation of electronic device 40. Processor 41, ROM 42, and RAM 43 are interconnected via bus 44. An input / output (I / O) interface 45 is also connected to bus 44.

[0110] Multiple components in the electronic device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a magnetic disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0111] Processor 41 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. Processor 41 executes the various methods and processes described above, such as the digital wind tunnel model simulation method.

[0112] In some embodiments, the digital wind tunnel model simulation method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the digital wind tunnel model simulation method described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to execute the digital wind tunnel model simulation method in any other suitable manner (e.g., via firmware).

[0113] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0114] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0115] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0116] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device that has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0117] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0118] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0119] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0120] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A digital wind tunnel model simulation method based on a heavy truck, characterized in that: include: Obtaining a pre-built initial heavy truck body model, and performing region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes a plurality of body model sub-regions; Determining model simulation parameters of the heavy truck body simulation model, and generating a heavy truck body digital model according to the model simulation parameters; Performing simulation analysis on at least one region of interest in the digital model of the heavy-duty truck body to obtain simulation analysis results for each region of interest; the region of interest is one or more of a plurality of vehicle body model sub-regions; the region of interest is a vehicle body model sub-region from which aerodynamic data of the heavy-duty truck body can be directly collected and aerodynamic characteristics of the heavy-duty truck body can be calculated; obtaining the simulation analysis results for each region of interest is specifically based on collecting and analyzing aerodynamic data of the heavy-duty truck body for each vehicle body model sub-region from which aerodynamic characteristics data of the heavy-duty truck body can be obtained, and obtaining aerodynamic characteristics analysis results corresponding to each model sub-region; Determining target boundary simulation parameters according to the simulation analysis results of the at least one area of ​​interest, and updating model simulation parameters of the heavy truck body digital model according to the target boundary simulation parameters to obtain target heavy truck body simulation model parameter adjustment results; The method of determining the model simulation parameters of the heavy truck body simulation model and generating the heavy truck body digital model according to the model simulation parameters includes: Obtaining the number of axles of the heavy truck body simulation model and determining associated axles associated with the body posture adjustment; wherein the associated axles specifically refer to the first axle and the last axle in the heavy truck body; Determine the cargo box type corresponding to the heavy truck body to which the heavy truck body simulation model belongs; Determining cargo box position parameters of the heavy truck body cargo box according to the cargo box type and based on the associated axles; Determining a relative positional relationship between the cargo box and a body boundary of the heavy truck body simulation model according to the cargo box position parameters; Determining model simulation parameters of a heavy truck body simulation model according to the relative position relationship, and generating a heavy truck body digital model based on the model simulation parameters; The initial heavy truck body model is preprocessed to obtain a heavy truck body simulation model, including: Performing region segmentation on the initial heavy truck body model by a mesh generator to obtain a plurality of body model sub-regions; Determining the relative position of each of the body model sub-regions relative to the initial heavy truck body model according to the regional position coordinates of each of the body model sub-regions; For any vehicle body model sub-region, judging whether the vehicle body model sub-region meets a preset key region judgment condition based on the relative position of the vehicle body model sub-region; wherein the key region judgment condition is used to determine whether the vehicle body model sub-region is a region for heavy truck body aerodynamic characteristics simulation analysis; If yes, adjusting the parameters of the grid generator, and segmenting the sub-region of the vehicle body model based on the grid generator after the parameter adjustment to obtain an updated sub-region of the vehicle body model; A heavy truck body simulation model is generated based on the updated sub-regions of the body model.

2. The method according to claim 1, characterized in that Before generating a heavy truck body simulation model based on the updated body model sub-regions, the following steps are also included: Identifying each body component in the initial heavy truck body model, and determining, for any body component in the initial heavy truck body model, whether the body component meets a preset retention judgment criterion; If not, the body component is deleted from the initial heavy truck body model, and an updated initial heavy truck body model is obtained.

3. The method according to claim 1, characterized in that Generate a heavy truck body simulation model based on the updated sub-areas of each body model, including: Determining a region boundary association relationship between each vehicle body model sub-region and its corresponding adjacent vehicle body model sub-region, and determining whether each vehicle body model sub-region satisfies a preset boundary coherence judgment condition based on the region boundary association relationship; If not, the vehicle body model sub-region that does not meet the boundary coherence judgment condition and the boundary region of its adjacent vehicle body model sub-region are filled with regional grids until the boundary coherence judgment condition is met, thereby obtaining a heavy truck body simulation model.

4. The method according to claim 1, wherein Performing simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest includes: Obtaining an aerodynamic simulation result of the heavy truck body digital model according to the model simulation parameters of the heavy truck body digital model and based on a preset simulation working condition scenario; According to the aerodynamic simulation results, a simulation analysis is performed on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results for each area of ​​interest.

5. The method according to claim 1, characterized in that Determining target boundary simulation parameters according to the simulation analysis results of the at least one area of ​​interest, and updating model simulation parameters of the heavy truck body digital model according to the target boundary simulation parameters to obtain target heavy truck body simulation model parameter adjustment results, including: According to the simulation analysis result of the at least one region of interest, determining whether the region boundary simulation parameters corresponding to each region of interest meet a preset boundary simulation parameter storage condition; If so, target heavy truck body boundary simulation parameters are determined, and parameters of the heavy truck body digital model are adjusted according to the target heavy truck body boundary simulation parameters to obtain target heavy truck body simulation model parameter adjustment results.

6. A digital wind tunnel model simulation device based on a heavy truck, characterized in that: include: An initial model acquisition module is used to obtain a pre-built initial heavy truck body model and perform region division preprocessing on the initial heavy truck body model to obtain a heavy truck body simulation model; the heavy truck body simulation model includes multiple body model sub-regions; A digital model generation module is used to determine the model simulation parameters of the heavy truck body simulation model and generate the digital model of the heavy truck body according to the model simulation parameters; a simulation analysis module, configured to perform simulation analysis on at least one region of interest in the digital model of the heavy-duty truck body, and obtain simulation analysis results for each region of interest; the region of interest being one or more of a plurality of vehicle body model subregions; the region of interest being a vehicle body model subregion from which aerodynamic data of the heavy-duty truck body can be directly collected and aerodynamic characteristics of the heavy-duty truck body can be calculated; obtaining the simulation analysis results for each region of interest is specifically based on collecting and analyzing aerodynamic data of the heavy-duty truck body for each vehicle body model subregion from which aerodynamic characteristics data of the heavy-duty truck body can be obtained, and obtaining aerodynamic characteristics analysis results corresponding to each model subregion; a simulation parameter updating module, configured to determine target boundary simulation parameters based on the simulation analysis results of the at least one area of ​​interest, and update the model simulation parameters of the heavy truck body digital model based on the target boundary simulation parameters to obtain a target heavy truck body simulation model parameter adjustment result; The digital model generation module is specifically used to obtain the number of axles of the heavy truck body simulation model and determine the associated axles that are associated with the body posture adjustment; wherein the associated axles specifically refer to the first axle and the last axle in the heavy truck body; Determine the cargo box type corresponding to the heavy truck body to which the heavy truck body simulation model belongs; Determining cargo box position parameters of the heavy truck body cargo box according to the cargo box type and based on the associated axles; Determining a relative positional relationship between the cargo box and a body boundary of the heavy truck body simulation model according to the cargo box position parameters; Determining model simulation parameters of a heavy truck body simulation model according to the relative position relationship, and generating a heavy truck body digital model based on the model simulation parameters; Wherein, the heavy truck body simulation model acquisition module includes: A region segmentation unit is used to perform region segmentation on the initial heavy truck body model through a mesh generator to obtain a plurality of body model sub-regions; a relative position determining unit, configured to determine the relative position of each of the vehicle body model sub-regions relative to the initial heavy truck body model according to the regional position coordinates of each of the vehicle body model sub-regions; A region condition judgment unit is configured to judge, for any vehicle body model sub-region, whether the vehicle body model sub-region satisfies a preset key region judgment condition based on the relative position of the vehicle body model sub-region; wherein the key region judgment condition is used to determine whether the vehicle body model sub-region is a region for performing aerodynamic characteristics simulation analysis of a heavy truck body; a region segmentation unit configured to adjust parameters of the mesh generator if the subregion of the vehicle body model satisfies a preset critical region judgment condition, and perform region segmentation on the subregion of the vehicle body model based on the mesh generator with the adjusted parameters, thereby obtaining updated subregions of the vehicle body model; wherein adjusting parameters of the mesh generator is adjusting the size of the region segmentation performed by the mesh generator, specifically, improving the quality of the mesh generated by the mesh generator; The body model generating unit is used to generate a simulated heavy truck body model according to each updated body model sub-region.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the digital wind tunnel model simulation method based on a heavy truck according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the digital wind tunnel model simulation method based on a heavy truck according to any one of claims 1 to 5 when executed.

9. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the digital wind tunnel model simulation method based on a heavy truck according to any one of claims 1 to 5.

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