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

Abstract

The invention discloses a digital wind tunnel model simulation method, device and equipment, a storage medium and a product, and the method comprises the steps: obtaining a pre-constructed initial heavy truck body model, and carrying out the region division preprocessing of the initial heavy truck body model, and obtaining a heavy truck body simulation model; 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 heavy truck body digital model to obtain a simulation analysis result of each region of interest; and according to the simulation analysis result of the at least one region of interest, determining a target boundary simulation parameter, and according to the target boundary simulation parameter, updating the model simulation parameter of the heavy truck body digital model to obtain a target heavy truck body simulation model parameter adjustment result, thereby solving the problem that the heavy truck is difficult to carry out real vehicle test, and improving the test efficiency. And the simulation precision of the heavy truck digital wind tunnel simulation experiment and the consistency of simulation experiment results are improved.

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 trucks and other large commercial vehicles are driving, they involve a variety of technologies in the field of vehicle aerodynamics, such as vehicle air resistance, vehicle wind noise, vehicle fan system air volume, air conditioning system, intake and exhaust fluid temperature, etc. The above 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 at present, large-sized vehicles such as heavy trucks in China cannot meet the wind tunnel blockage ratio requirements. Therefore, it is difficult to use real vehicle tests, and some aerodynamic characteristics analysis cannot be tested with scaled models, which is not conducive to the analysis of fluid dynamics technology for heavy trucks. At the same time, although road tests can more accurately reproduce user scenarios, it is difficult to obtain relevant test results, there are many road interference factors, and the accuracy of the test results is poor.

[0003] In order to shorten the development cycle of heavy trucks, researchers have developed an application method of computational fluid dynamics technology, combining wind tunnel tests and simulated wind tunnel tests, but this application method can only help with the styling design and aerodynamic optimization of passenger cars to achieve performance improvement. It has little effect on the size, performance, and problem solving of large vehicles such as heavy trucks, and the size of the virtual wind tunnel is quite different from that of the passenger car wind tunnel test.

[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 of digital wind tunnel simulation experiments for heavy trucks and the consistency of simulation experiment results 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, so as to solve the problem that heavy trucks are difficult to conduct actual vehicle testing 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] Acquire 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 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 focus area, the target boundary simulation parameters are determined, and according to the target boundary simulation parameters, the model simulation parameters of the heavy truck body digital model are updated to obtain the target heavy truck body simulation model parameter adjustment result.

[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 acquire 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 a plurality of 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, used 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 of each area of ​​interest; the area of ​​interest is one or more of the multiple 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 focus area, 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, the electronic device 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, 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 described in 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 described in 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 obtains a heavy truck body simulation model by obtaining a pre-built initial heavy truck body model and performing region division preprocessing on the initial heavy truck body model; the heavy truck body simulation model includes multiple body model sub-regions; the model simulation parameters of the heavy truck body simulation model are determined, and a heavy truck body digital model is generated according to the model simulation parameters; at least one focus area in the heavy truck body digital model is simulated and analyzed to obtain simulation analysis results of each focus area; the focus area is one or more of the multiple body model sub-regions; according to the simulation analysis results of at least one focus area, the target boundary simulation parameters are determined, and according to the target boundary simulation parameters, the model simulation parameters of the heavy truck body digital model are updated 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 it is difficult to conduct real vehicle testing of heavy trucks, and shorten the development cycle of the whole vehicle.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily 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 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 is a flow chart of a digital wind tunnel model simulation method provided according to Embodiment 2 of the present invention;

[0027] Figure 3 is a structural schematic diagram of a digital wind tunnel model simulation device provided according to Embodiment 3 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 scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification 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 data 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 that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 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 the case where a large-sized heavy truck cannot meet the wind tunnel blockage ratio requirement, and it is difficult to use a real vehicle for testing, and some aerodynamic characteristics cannot be analyzed using a scaled model. 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 truck body model may be a model constructed based on the three-dimensional data of the heavy truck body, and may be a display model generated by a technician based on the heavy truck body information directly input, and may not support aerodynamic characteristics analysis; the heavy truck body simulation model may be a body model generated based on the initial heavy truck body model, and may have a model sub-region capable of performing aerodynamic characteristics analysis. The aerodynamic characteristics may include the wind resistance, wind noise, and intake and exhaust of the heavy truck body.

[0035] The region division preprocessing of the initial heavy truck body model may specifically be the identification and division of the model sub-regions of the acquired initial heavy truck body model. Specifically, the corresponding heavy truck body in the initial heavy truck body model may include a front part and a body part, wherein the front part may be divided, such as the front windshield area, the left and right door glass areas, and the intake and exhaust grille areas, etc.; the body part may also be divided, such as the trailer area and the cargo box area, etc., and a body simulation model for aerodynamic characteristic analysis is generated according to each body model sub-region obtained by division.

[0036] S120, 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.

[0037] The model simulation parameters may be size parameters set for each sub-area of ​​the vehicle body model in the heavy truck body simulation model, and may be set by relevant technicians based on actual experience. For example, the size of the front windshield area may be set, such as 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 the 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 body posture adjustment; determining the type of cargo box corresponding to the heavy-duty truck body to which the heavy-duty truck body simulation model belongs; determining 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 a trailer, a cargo box, and a flatbed trailer.

[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 posture adjustment of the heavy truck, so that the posture of the heavy truck body is more consistent with the state under the actual counterweight condition, that is, the heavy truck body can be guaranteed to be in the same straight line under the condition of the actual counterweight of the heavy truck body. Exemplarily, if the placement position of the cargo is too close to the tail of the heavy truck body, the posture of the whole vehicle with the tail of the heavy truck body downward and the head upward can be obtained. 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, and it can also be a trailer cargo box and other cargo box types that need to match the saddle, and 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, the heavy truck belongs to a large vehicle, that is, the overall posture of the heavy truck body and the position parameter information of the whole vehicle position are relatively complex. When the heavy truck body is under different counterweight conditions, the whole vehicle posture of the heavy truck body is quite different. Therefore, trucks, tractor trailers, etc. need to combine the relative position relationship between the whole vehicle, cargo box, trailer, etc., and the body boundary to set the model simulation parameters of the heavy truck body simulation model, so as to generate 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 of each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas of the body model.

[0045] Among them, the area of ​​interest can be a sub-area of ​​the body model that can directly collect the aerodynamic data of the heavy truck body and calculate the aerodynamic characteristics of the heavy truck body. For example, the drag coefficient of the heavy truck body can be obtained through the front surface area and the front windshield area, and the wind noise data of the heavy truck body can be obtained through the left and right door glass areas. Then the front surface area, the front windshield area, and the left and right door glass areas can be determined as the area of ​​interest. The simulation analysis results can include the drag coefficient of the heavy truck body, the wind noise of the heavy truck body, and the parameters of the intake and exhaust system of the heavy truck body.

[0046] Among them, 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 that can obtain the aerodynamic characteristics data of the heavy truck body, and obtaining the aerodynamic characteristics 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 nearby space flow field, and 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, and 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 an aerodynamic simulation result 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 a preset simulation working condition scenario; and based on the aerodynamic simulation result, 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.

[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 real scene encountered by the heavy truck body in the actual driving process can be simulated, and the aerodynamic simulation data near the heavy truck body can be collected according to the real simulated scene, so as to obtain the aerodynamic results of the heavy truck body digital model. Furthermore, any model sub-area in the heavy truck body digital model can be simulated and analyzed according to the obtained aerodynamic results, and the corresponding simulation analysis results can be obtained. Continuing with the above example, the surface pressure of the vehicle body and the flow field in the nearby space can be collected to obtain the relevant flow field, surface pressure, vortex and other aerodynamic data, 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 drag coefficient of the heavy truck body; the pressure pulsation and gap airflow data of the left and right door glass areas can also be collected respectively to obtain the wind noise related acoustic indicators, glass pressure pulsation, noise distribution diagram, noise slice diagram and other aerodynamic data, so as to realize the simulation analysis of the wind noise of the left and right door glass areas respectively, and obtain the simulation results of the wind noise of the heavy truck body.

[0050] S140, determining target boundary simulation parameters according to the simulation analysis results of 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.

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

[0052] Among them, updating the model simulation parameters of the heavy truck body digital model specifically refers to iteratively updating the model simulation parameters stored in the historical database by obtaining the model simulation parameters that meet the heavy truck body design requirements. The historical database can be a database for storing the model simulation parameters obtained in the historical heavy truck body simulation. Exemplarily, if the pre-set aerodynamic characteristic value of the drag coefficient is 0.5Cd (Drag Coefficient, unit of drag coefficient), the drag coefficient of the front surface area and the front windshield area can be simulated and analyzed, and the simulation result of the heavy truck body drag coefficient is 0.42Cd, that is, the drag coefficient simulation analysis is performed, and the simulation analysis result obtained is lower than the pre-set aerodynamic characteristic value of the drag coefficient. Then, the model simulation parameters of the front surface area and the front windshield area in the heavy truck body digital model can be determined as the target boundary simulation parameters. Furthermore, the model simulation parameters in the historical database can be updated according to the target boundary simulation parameters to obtain the adjustment result of the model parameters of the heavy 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 completely 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, model simulation parameters of the heavy-duty truck body digital model are updated to obtain 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 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 target heavy-duty truck body simulation model parameter adjustment results.

[0055] Among them, the boundary simulation parameter storage condition can 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, the parameter range of the side wind in the preset simulation working condition scenario can be 0 to 30 meters per second, and the side wind in the simulation analysis of the heavy truck body 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 appears 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 obtains a heavy truck body simulation model by obtaining a pre-built initial heavy truck body model and performing region division preprocessing on the initial heavy truck body model; the heavy truck body simulation model includes multiple body model sub-regions; the model simulation parameters of the heavy truck body simulation model are determined, and a heavy truck body digital model is generated according to the model simulation parameters; at least one focus area in the heavy truck body digital model is simulated and analyzed to obtain simulation analysis results of each focus area; the focus area is one or more of the multiple body model sub-regions; according to the simulation analysis results of at least one focus area, the target boundary simulation parameters are determined, and according to the target boundary simulation parameters, the model simulation parameters of the heavy truck body digital model are updated 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 it is difficult to conduct real vehicle testing on heavy trucks, and improve the simulation accuracy of the heavy truck digital wind tunnel simulation experiment and the consistency of the simulation experiment results.

[0058] Embodiment 2

[0059] Figure 2 A flowchart of a digital wind tunnel model simulation method provided in Embodiment 2 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 through a mesh generator to obtain a plurality of body model sub-regions.

[0062] The pre-built initial heavy truck body model can be segmented by a grid generator to obtain different model sub-regions in the initial heavy truck body model. The grid generator can include structured grids and unstructured grids, and specific algorithms can include partial differential equations and joint element methods, etc., to identify and divide the model sub-regions of the initial heavy truck body model, which is not specifically limited in this embodiment.

[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 divided through an unstructured network to obtain the front windshield, left and right door glass, intake and exhaust grille and other 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] Among them, the regional position coordinates may specifically refer to the coordinates of the center point of each body model sub-region. Specifically, there is a corresponding association relationship between each body model sub-region, and the regional position coordinates of each body model sub-region are relatively fixed relative to the regional position of the initial heavy truck body model. Exemplarily, if the position coordinates of the left door region in each 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 body model sub-region relative to the initial heavy truck body model can be determined based on the regional position coordinates of each body model sub-region.

[0066] S230: for any vehicle body model sub-region, determine whether the vehicle body model sub-region satisfies a preset key region determination condition according to the region 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 as (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] Among them, adjusting the parameters of the grid generator may be adjusting the size of the area segmentation performed by the grid generator, and specifically, it 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 grid division of the front windshield area through a structured network, and specifically, the front windshield area may be divided into 5×5 cm grids, and this embodiment does not impose specific restrictions on this.

[0071] S250: Generate a heavy truck body simulation model according to each updated body model sub-region.

[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 rough processing of dividing the initial heavy truck body model by the unstructured network, and the model sub-region after updating the key area by using the structured network can be obtained, and thereby a heavy truck body simulation model that can perform aerodynamic characteristics analysis of the heavy truck body 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 satisfies a preset boundary continuity judgment condition based on the regional boundary association relationship; if not, performing regional grid filling on the boundary area between the body model sub-region that does not satisfy the boundary continuity judgment condition and its adjacent body model sub-region until the boundary continuity judgment condition is satisfied, thereby obtaining a heavy truck body simulation model.

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

[0075] For example, the threshold of the difference between the boundary position coordinates of the left door area and the boundary position coordinates of the left door glass area is 0.1. The boundary position coordinates of the left door area can be (1, 1, 2.5), and the boundary position coordinates of the left door glass can be (1, 1, 2.55), that is, it can be calculated that the difference between the boundary position coordinates of the left door area and the boundary position coordinates of the left door glass area is 0.05, and it can be determined that the left door area and the left door glass area meet the preset boundary continuity judgment condition; the boundary position coordinates of the left door area can also be (1, 1, 2.3), and the boundary position coordinates of the left door glass can also be (1, 1, 2.6), that is, the difference between the boundary position coordinates of the left door area and the boundary position coordinates of the left door glass area is 0.3, and it can be determined that the left door area and the left door glass area do not meet the preset boundary continuity judgment condition. 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 truck body simulation model based on the updated body model sub-regions, it also includes: identifying each body component in the initial heavy truck body model, and for any body component in the initial heavy truck body model, determining whether the body component meets a preset retention judgment standard; if not, deleting the body component from the initial heavy truck body model, and obtaining an updated initial heavy 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.

[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 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 truck body model to obtain an updated initial heavy truck body model. Exemplarily, if the internal component is a vehicle body engine, in the actual heavy truck body design, the layout position of the engine is usually hidden inside the vehicle body. Therefore, the analysis results of the aerodynamic characteristics of the heavy 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 truck body model.

[0079] Optionally, if the body part is a porous part on the outside of the body, it can be determined that the body part does not meet the preset retention judgment standard, and the body part is split from the initial heavy truck body model; the split body parts are set separately, and the updated initial heavy truck body model is obtained. By identifying the body parts of the initial heavy truck body model, the internal body parts and the porous parts on the outside of the heavy truck body can be automatically identified, removed and split, which improves the generation efficiency of the heavy truck body simulation model and reduces the loss of computing resources for model simulation.

[0080] S260, 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.

[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 of 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 according to the simulation analysis results of at least one area of ​​interest, and update 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.

[0083] The technical solution of the embodiment of the present invention is to segment the initial heavy truck body model through 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 truck body model according to the regional position coordinates of each body model sub-region; judge whether the body model sub-region meets the preset key area judgment condition according to 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 grid generator after parameter adjustment to obtain the updated body model sub-region; generate a simulated heavy truck body model according to each updated body model sub-region. This technical solution improves the processing efficiency before model simulation by using automated pre-processing technology to process and adjust the initial heavy truck body model, and ensures the accuracy and reliability of the initial heavy truck body model. The initial heavy truck body model is transformed by using a grid generator to ensure that the simulation parameters of the heavy truck body model can be set and adjusted, which solves the problem that it is difficult to conduct real vehicle testing on heavy trucks, and improves the simulation accuracy of the digital wind tunnel simulation experiment of heavy trucks and the consistency of the simulation experiment results.

[0084] Embodiment 3

[0085] Figure 3The digital wind tunnel model simulation device provided in the third embodiment of the present invention is a structural schematic diagram. The digital wind tunnel model simulation device provided in the embodiment of the present invention can be applied to the situation where a large-sized heavy truck cannot meet the wind tunnel blockage ratio requirement, it is difficult to use a real vehicle test, and some aerodynamic characteristics cannot be analyzed using a scaled model. 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. Among them,

[0086] The initial model acquisition module 310 is used to acquire 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 a plurality of 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 heavy truck body digital model according to the model simulation parameters;

[0088] The simulation analysis module 330 is used to perform simulation analysis on at least one area of ​​interest in the digital model of the heavy truck body to obtain simulation analysis results of each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas 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 focus area, 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 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 it is difficult to conduct actual vehicle testing on heavy trucks, and improving the simulation accuracy of the heavy truck digital wind tunnel simulation experiment and the consistency of the simulation experiment results.

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

[0092] A region segmentation unit, used for performing 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 determination unit, used for determining the regional 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, for judging, for any vehicle body model sub-region, whether the vehicle body model sub-region satisfies 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 the parameters of the grid generator if the vehicle body model sub-region meets the preset key region judgment condition, and perform region segmentation on the vehicle body model sub-region based on the grid 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 is used to identify each body component in the initial heavy truck body model before generating a heavy truck body simulation model according to each updated body model sub-region, and for any body component in the initial heavy truck body model, determine whether the body component meets a preset retention judgment standard;

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

[0100] Optionally, the vehicle body model generating unit is specifically used for:

[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 according to the region boundary association relationship;

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

[0103] Optionally, the heavy-duty truck body digital model generation module 320 is specifically used to obtain the number of axles of the heavy-duty 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-duty truck body to which the heavy-duty truck body simulation model belongs; determine the cargo box position parameters of the heavy-duty 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-duty truck body simulation model based on the cargo box position parameters; determine the model simulation parameters of the heavy-duty truck body simulation model based on the relative position relationship, and generate the heavy-duty truck body digital model based on the model simulation parameters.

[0104] Optionally, the simulation analysis result acquisition module 330 is specifically used to obtain 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; based on the aerodynamic simulation result, a simulation analysis is performed on at least one focus area in the heavy truck body digital model to obtain simulation analysis results for each of the focus areas.

[0105] Optionally, the model simulation parameter updating 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 based on 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] Embodiment 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 processing, cellular phones, smart phones, 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 required herein.

[0109] like Figure 4As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0110] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.

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

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

[0113] Various implementations of the systems and techniques described above herein 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), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, 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 equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 may be implemented on an electronic device having: 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0117] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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 a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0119] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0120] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A digital wind tunnel model simulation method, characterized in that: include: Acquire 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 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 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; According to the simulation analysis result of the at least one focus area, the target boundary simulation parameters are determined, and according to the target boundary simulation parameters, the model simulation parameters of the heavy truck body digital model are updated to obtain the target heavy truck body simulation model parameter adjustment result.

2. The method according to claim 1, characterized in that The initial heavy truck body model is preprocessed to obtain a heavy truck body simulation model, including: By using a mesh generator, the initial heavy truck body model is segmented into regions to obtain a plurality of body model sub-regions; Determining the relative position of each of the sub-regions of the vehicle body model relative to the initial heavy truck body model according to the regional position coordinates of each of the sub-regions of the vehicle body model; For any vehicle body model sub-region, judging whether the vehicle body model sub-region meets a preset key region judgment condition according to the relative position of the vehicle body model sub-region; 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 each body model.

3. The method according to claim 2, characterized in that Before generating a heavy truck body simulation model according to each updated body model sub-region, it also includes: Identify each body part in the initial heavy truck body model, and for any body part in the initial heavy truck body model, determine whether the body part meets a preset retention determination 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.

4. The method according to claim 2, characterized in that: Generate a heavy truck body simulation model based on the updated body model sub-areas, 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 according to 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.

5. The method according to claim 1, characterized in that 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, including: Obtaining the number of axles of the heavy truck body simulation model, and determining associated axles 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; Determining the cargo box position parameters of the heavy truck body cargo box according to the cargo box type and based on the associated axle; Determining the relative position relationship between the cargo box and the body boundary of the heavy truck body simulation model according to the cargo box position parameters; According to the relative position relationship, model simulation parameters of the heavy truck body simulation model are determined, and based on the model simulation parameters, a heavy truck body digital model is generated.

6. The method according to claim 1, characterized in that 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: According to the model simulation parameters of the heavy truck body digital model and based on the preset simulation working condition scenario, an aerodynamic simulation result of the heavy truck body digital model is obtained; According to the aerodynamic simulation result, 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.

7. 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, the target heavy truck body boundary simulation parameters are determined, and the parameters of the heavy truck body digital model are adjusted according to the target heavy truck body boundary simulation parameters to obtain the target heavy truck body simulation model parameter adjustment result.

8. A digital wind tunnel model simulation device, characterized in that: include: An initial model acquisition module is used to acquire 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 a plurality of body model sub-regions; A digital model generation module, 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, used 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 of each area of ​​interest; the area of ​​interest is one or more of the multiple sub-areas of the body model; The simulation parameter updating module is used to determine the target boundary simulation parameters according to the simulation analysis results of the at least one focus area, 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.

9. The device according to claim 8, characterized in that The heavy truck body simulation model acquisition module includes: A region segmentation unit, used for performing 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 determination unit, used for determining the regional 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, for judging, for any vehicle body model sub-region, whether the vehicle body model sub-region satisfies a preset key region judgment condition according to the region relative position of the vehicle body model sub-region; A region segmentation unit, configured to adjust the parameters of the grid generator if the vehicle body model sub-region meets the preset key region judgment condition, and perform region segmentation on the vehicle body model sub-region based on the grid generator with the adjusted parameters to obtain an updated vehicle body model sub-region; The body model generating unit is used to generate a simulated heavy truck body model according to each updated body model sub-region.

10. 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 according to any one of claims 1 to 7.

11. 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 according to any one of claims 1 to 7 when executed.

12. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the digital wind tunnel model simulation method according to any one of claims 1 to 7 is implemented.

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