Automobile appearance parameter optimization method based on CFD simulation

Abstract

The invention discloses an automobile appearance parameter optimization method based on CFD simulation, and relates to the technical field of CFD simulation, and the method comprises the steps: constructing a virtual CFD space, and obtaining a virtual automobile element; setting a dynamic segmentation frame to carry out simulation division and standard adjustment on the virtual automobile elements to obtain a uniform element sequence, and carrying out edge collaborative capture on the uniform element sequence according to the judgment grid frame to obtain an edge feature element set; sending a virtual adjustment instruction to the virtual CFD space and carrying out expected adjustment to obtain an automobile transfer element, and carrying out same-block verification on the automobile transfer element to obtain a verification transfer difference; performing cyclic change on the virtual adjustment instruction according to the verification adjustment difference to obtain a change adjustment instruction, performing expected adjustment on the virtual automobile element through the change adjustment instruction, and performing adjustment judgment through the change verification difference map to obtain an excess adjustment parameter and a steady state adjustment parameter; and the shape parameter optimization speed is increased, the aerodynamic characteristics of the automobile are greatly improved, and the safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of CFD simulation, and specifically to an optimization method for automobile shape parameters based on CFD simulation. Background Technique

[0002] Computational fluid dynamics, abbreviated as CFD, is a technology that uses numerical analysis and data structures to analyze and solve fluid flow problems. By discretizing the physical model of fluid flow and using a computer for solution and analysis, a series of numerical solutions to problems such as fluid flow and heat transfer can be obtained. As a powerful numerical analysis tool, CFD simulation provides a method to predict and optimize performance at the product design stage, avoiding expensive physical prototype testing and possible failure risks.

[0003] Automobile shape parameters refer to the variables of various shapes and sizes of the automobile shell. These parameters determine the aerodynamic performance, appearance, internal space layout of the automobile, and the difficulty level during the manufacturing process. If the automobile shape parameters are not properly designed, it may lead to poor aerodynamic performance, such as high air resistance, large roll and lift, which will reduce fuel efficiency, acceleration performance, and handling stability. Therefore, it is necessary to optimize the automobile shape parameters through CFD simulation to improve the performance and competitiveness of the automobile. For this purpose, an optimization method for automobile shape parameters based on CFD simulation is provided. Summary of the Invention

[0004] The purpose of the present invention can be achieved through the following technical solutions: An optimization method for automobile shape parameters based on CFD simulation, comprising the following steps: Step S1: Collect comprehensive automobile data, construct a virtual CFD space, and obtain virtual automobile components; Step S2: Set a dynamic segmentation box to perform simulation segmentation on the automobile component area, obtain a virtual component sequence, perform standard adjustment on the virtual component sequence through an equilibrium standard to obtain a uniform component sequence, set a comprehensive determination coefficient for section division to obtain a segmented determination coefficient, upload the segmented determination coefficient to a grid extraction box to obtain a determination grid box, and perform edge collaborative capture on the uniform component sequence according to the determination grid box to obtain an edge feature component set; Step S3: Send a virtual adjustment instruction to the virtual CFD space and perform expected adjustment to obtain an automobile adjustment component, perform homomorphic transformation on the automobile adjustment component and perform same-block verification with the edge feature component set to obtain a verification adjustment difference; Step S4: Cyclically vary the virtual adjustment instruction according to the calibration transfer difference to obtain a variable adjustment instruction. Use the variable adjustment instruction to perform an expected adjustment on the virtual vehicle components and perform a same-block verification with the edge feature component set to obtain a variable verification difference map. Set a judgment demarcation axis to perform a critical comparison on the variable verification difference map to obtain a variable adjustment map block and a steady-state adjustment map block, and perform an adjustment judgment on the variable vehicle transfer components to obtain an over-adjustment parameter and a steady-state adjustment parameter.

[0005] The process of obtaining the virtual vehicle components includes: Set a simulation acquisition terminal, and use the simulation acquisition terminal to collect data from the vehicle to obtain comprehensive vehicle data; Construct a virtual CFD space based on the comprehensive vehicle data; Perform a homomorphic transformation on the vehicle to obtain virtual vehicle components, and upload the obtained virtual vehicle components to the virtual CFD space.

[0006] The process of obtaining the uniform component sequence includes: Set a dynamic segmentation frame according to the virtual vehicle components; Set a vehicle component area for the virtual vehicle components, and perform a simulation division on the vehicle component area according to the set dynamic segmentation frame to obtain a virtual component sequence; Set an equilibrium standard, and perform a standardized adjustment on the virtual component sequence according to the equilibrium standard to obtain a uniform component sequence, and the uniform component sequence includes a number of standardized component units.

[0007] The process of obtaining the edge feature component set includes: Set a comprehensive determination coefficient, perform a morphological regulation on the comprehensive determination coefficient to obtain a regulation parameter; Perform a section division on the comprehensive determination coefficient according to the obtained regulation parameter to obtain a segmented determination coefficient; Set a grid extraction frame, and upload the obtained segmented determination coefficient to the grid extraction frame to obtain a determination grid frame; Upload the determination grid frame to the uniform component sequence, and perform an edge collaborative capture on the uniform component sequence through the determination grid frame to obtain an edge feature component set.

[0008] The process of performing an edge collaborative capture on the uniform component sequence through the determination grid frame includes: Upload the determination grid frame to the first standardized component unit of the uniform component sequence, and mark the corresponding area of the determination grid frame in the standardized component unit as the grid cell area; Perform a feature capture on the grid cell area through the determination grid frame to obtain an edge component block; Translate and slide the obtained judgment grid box based on the standard component unit to reach the next grid cell area, and perform capture convolution on the grid cell area until all areas of the standard component unit are covered. Sort the edge component tiles according to the standard component unit to obtain a sub-unit tile sequence; According to the homogeneous component sequence, upload the judgment grid box to the next standard component unit, repeat the process of obtaining the sub-unit tile sequence until the homogeneous component sequence is covered, and sort the sub-unit tile sequence according to the homogeneous component sequence to obtain an edge feature component set.

[0009] The process of obtaining the calibration adjustment difference includes: Send a virtual adjustment instruction to the virtual CFD space, receive the virtual adjustment instruction through the virtual vehicle component, and perform expected adjustment according to the received virtual adjustment instruction to obtain a vehicle adjustment component; Perform homomorphic transformation on the vehicle adjustment component to obtain an edge adjustment set, and match the edge adjustment set according to the obtained edge feature component set to obtain a matching adjustment sequence and a matching sub-unit sequence; Perform same-block verification on the matching adjustment sequence and the matching sub-unit sequence to obtain the calibration adjustment difference.

[0010] The process of obtaining the variable verification difference graph includes: Perform cyclic variation on the virtual adjustment instruction according to the calibration adjustment difference to obtain a variable adjustment instruction; Perform expected adjustment on the virtual vehicle component according to the variable adjustment instruction to obtain a variable vehicle adjustment component, and perform homomorphic transformation on the obtained variable vehicle adjustment component to obtain a variable edge adjustment set; Perform same-block verification on the variable edge adjustment set according to the edge feature component set to obtain a variable calibration adjustment difference, and generate a variable verification difference graph according to the variable calibration adjustment difference.

[0011] The process of obtaining the over-adjustment parameter and the steady-state adjustment parameter includes: Set a judgment demarcation axis and upload the set judgment demarcation axis to the variable verification difference graph; Perform critical comparison on the variable verification difference graph according to the judgment demarcation axis to obtain a variable adjustment tile and a steady-state adjustment tile; Based on the variable verification difference graph, perform adjustment judgment on the variable vehicle adjustment component according to the obtained variable adjustment tile and steady-state adjustment tile to obtain the over-adjustment parameter and the steady-state adjustment parameter.

[0012] Compared with the prior art, the beneficial effects of the present invention are: In the virtual simulation space, the virtual components of the vehicle are simulated and divided, and the three-dimensional vehicle model is sliced into pictures, which is beneficial to extracting the vehicle parameter features. The parameter data in different forms of expression are converted into a unified standard picture set form, greatly improving the simulation speed; Send an adjustment instruction to the virtual vehicle and monitor the parameter features of the adjusted virtual vehicle. It can be quickly iterated, improving time efficiency and reducing market risks. It can adjust to the extreme conditions of the vehicle's external shape parameters in the virtual space, increasing the design flexibility, greatly improving the vehicle's aerodynamic characteristics, and contributing to improving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0014] Figure 1 It is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0016] As Figure 1 shown, a method for optimizing the external shape parameters of a vehicle based on CFD simulation includes the following steps: Step S1: Collect comprehensive vehicle data, construct a virtual CFD space, and obtain virtual vehicle components; Step S2: Set a dynamic slicing frame to perform simulation division on the vehicle component area, obtain a virtual component sequence, perform specification adjustment on the virtual component sequence through an equilibrium standard, obtain a uniform component sequence, set a comprehensive determination coefficient for section division, obtain a sectional determination coefficient, upload the sectional determination coefficient to the grid extraction frame, obtain a determination grid frame, and perform edge collaborative capture on the uniform component sequence according to the determination grid frame to obtain an edge feature component set; Step S3: Send a virtual adjustment instruction to the virtual CFD space and perform expected adjustment to obtain a vehicle mobilization component, perform homomorphic transformation on the vehicle mobilization component and perform homomorphic block verification with the edge feature component set to obtain a verification mobilization difference; Step S4: Cyclically vary the virtual adjustment instruction according to the calibration transfer difference to obtain a variable adjustment instruction. Use the variable adjustment instruction to perform an expected adjustment on the virtual vehicle components and perform a same-block verification with the edge feature component set to obtain a variable verification difference map. Set a judgment demarcation axis to perform a critical comparison on the variable verification difference map to obtain a variable adjustment map block and a steady-state adjustment map block, and perform an adjustment judgment on the variable vehicle transfer components to obtain an over-adjustment parameter and a steady-state adjustment parameter.

[0017] It should be further noted that in the specific implementation process, the process of constructing the virtual CFD space and obtaining the virtual vehicle components includes: Set a simulation acquisition terminal, and collect data on the vehicle through the simulation acquisition terminal to obtain comprehensive vehicle data; The comprehensive vehicle data includes shape geometry data, dynamics data, and fluid boundary conditions. Among them, the shape geometry data includes the overall dimensions of the vehicle, body contour data, and body detail data. The dynamics data includes mass distribution and kinematic parameters. The fluid boundary conditions include the physical properties of the vehicle and the surrounding environment of the vehicle.

[0018] Construct a virtual CFD space based on the obtained comprehensive vehicle data. The virtual CFD space is synchronously constructed according to CFD simulation. Usually, computer-aided design software (such as CAD) is used to construct the geometric model of the CFD simulation. Then, the internal structure of the obtained virtual CFD space is exactly the same as the model constructed for the vehicle's CFD simulation; Perform a homomorphic transformation on the vehicle to obtain virtual vehicle components, and upload the obtained virtual vehicle components to the virtual CFD space; Furthermore, the homomorphic transformation means converting the vehicle into a three-dimensional solid model diagram according to computer-aided design software, which is the virtual vehicle component, and the virtual vehicle component is uploaded at the central position of the virtual CFD space.

[0019] Set a dynamic segmentation frame according to the obtained virtual vehicle components. The size of the dynamic segmentation frame is related to the shape geometry data and dynamics data. Set the corresponding size according to the obtained shape geometry data and dynamics data, and at different parts of the virtual vehicle components, the size of the set dynamic segmentation frame is different; Set a vehicle component area according to the obtained virtual vehicle components. The vehicle component area represents a certain area containing the virtual vehicle components, and is set in the virtual CFD space according to the surrounding environment of the vehicle in the fluid boundary conditions. Then, the set vehicle component area includes the virtual vehicle and the surrounding environment in the virtual space; Perform a simulation division on the vehicle component area according to the set dynamic segmentation frame to obtain a virtual component sequence; It should be further noted that, in the specific implementation process, the simulation division means setting a starting origin in the automotive component area, where the starting origin represents the starting point of segmentation. According to the set starting origin, the direction of segmenting the automotive component area can be determined. For example, the segmentation direction can be starting from the boundary of the rear area of the vehicle and translating horizontally, or the segmentation direction can be starting from the boundary of the bottom area of the vehicle tire and translating vertically. Upload the obtained dynamic segmentation frame to the starting origin of the automotive component area. At the starting origin, segment the automotive component area through the dynamic segmentation frame to obtain virtual component sub-units, and set a dynamic distance according to the shape geometry data. The dynamic distance represents the distance that the dynamic segmentation frame translates to the next position and is set according to the shape geometry data. To make the extraction of automotive details more comprehensive, a sufficiently small dynamic distance needs to be set so that the number of virtual component sub-units obtained by segmentation is sufficient. Then, the obtained virtual component sub-units are in the form of pictures. In particular, in this embodiment, the dynamic distance is set so that the virtual component sub-units obtained by segmentation are in the form of pictures, and the set dynamic distance is the minimum value within the range that can be translated. Translate the dynamic segmentation frame according to the dynamic distance. At the next translation position, segment the automotive component area through the dynamic segmentation frame to obtain virtual component sub-units, and translate according to the dynamic distance until reaching the edge position of the automotive component area. Then, the segmentation is completed, and the obtained virtual component sub-units are counted according to the segmentation order to obtain a virtual component sequence. The virtual component sequence is sorted from the virtual component sub-units obtained according to the segmentation order of the automotive component area. Set an equilibrium standard, which includes a saturation standard and a size standard. The size standard includes the number of pixels in the horizontal dimension and the number of pixels in the vertical dimension. The saturation standard means adjusting the saturation of the color channels of the virtual component sub-units. According to the three color channels included in the color image, the saturation is adjusted to the set saturation standard in each channel. Regulate and adjust the virtual component sequence according to the obtained equilibrium standard to obtain a uniform component sequence. Furthermore, the regulation and adjustment means adjusting each virtual component sub-unit in the virtual component sequence according to the equilibrium standard to obtain a regulated component unit, that is, uniformly adjusting the saturation of the virtual component sub-units and at the same time regulating and cropping the picture size to obtain regulated component units with exactly the same saturation and size, and combining the regulated component units according to the virtual component sequence to obtain a uniform component sequence. Set a comprehensive determination coefficient, and the comprehensive determination coefficient is in the form of a function. Perform morphological regulation on the obtained comprehensive determination coefficient to obtain a regulation parameter. The morphological regulation refers to controlling the stretching and translation transformations of the comprehensive determination coefficient in the time dimension and frequency dimension, recording the parameters of the stretching and translation transformations, and obtaining the regulation parameters; According to the obtained regulation parameters, the comprehensive determination coefficient is divided into sections to obtain the segmented determination coefficient; Further, the process of the section division includes: Based on the comprehensive determination coefficient, the distance between two adjacent regulation parameters is statistically obtained to obtain the regulation interval. According to the obtained regulation interval and regulation parameters, the determination series is obtained, and the obtained determination series is marked as G, where, Z represents the coefficient length of the comprehensive determination coefficient, j represents the regulation interval, m represents the number of regulation intervals in the comprehensive determination coefficient, c represents the regulation parameter, " " means rounding down after calculating the result of " "; According to the obtained determination series, the comprehensive determination coefficient is equally divided to obtain the segmented determination coefficient, where the equal division means equally dividing the comprehensive determination coefficient according to the number of determination series to obtain the segmented determination coefficients of equal length; A grid extraction frame is set. The grid extraction frame is a matrix composed of several elements, and the number of elements is determined by the determination series, that is, the number of elements is the same as the determination series; The obtained segmented determination coefficients are uploaded to the grid extraction frame to obtain the determination grid frame. Here, "uploading the obtained segmented determination coefficients to the grid extraction frame" means uploading the segmented determination coefficients to the corresponding element positions of the grid extraction frame in sequence according to the order of equal division, that is, each element in the grid extraction frame has a segmented determination coefficient; The determination grid frame is uploaded to the homogeneous component sequence, and the homogeneous component sequence is edge - collaboratively captured through the determination grid frame to obtain the edge feature component set; It should be further noted that in the specific implementation process, the process of the edge - collaborative capture includes: According to the arrangement order of the homogeneous component sequence, the obtained determination grid frame is uploaded to the first standard component unit of the homogeneous component sequence, and the corresponding area of the determination grid frame in the standard component unit is marked as the grid cell area; The grid cell area is feature - captured through the determination grid frame to obtain the edge component tile. Here, the feature capture means performing capture convolution on the elements in the determination grid frame and the corresponding positions in the grid cell area. The capture convolution means convolving the segmented determination coefficient at each element position with the pixels at the corresponding position in the grid cell area to obtain the edge component tile; Translate and slide the obtained judgment grid box based on the standard component unit to reach the next grid cell area, and perform capture convolution on the grid cell area until all areas of the standard component unit are covered. Sort the edge component tiles according to the standard component unit to obtain a sub-unit tile sequence; Upload the obtained judgment grid box to the next standard component unit according to the obtained uniform component sequence, repeat the process of obtaining the sub-unit tile sequence until the uniform component sequence is covered, and sort the sub-unit tile sequence according to the uniform component sequence to obtain an edge feature component set; Mark the obtained edge component tiles as ,"i−j" represents the j-th edge component tile in the i-th sub-unit tile sequence. i represents the number of the sub-unit tile sequence in the edge feature component set, and j represents the number of the edge component tile. i = 1, 2, 3, ……, v1, where v1 is a positive integer, and j = 1, 2, 3, ……, v2, where v2 is a positive integer.

[0020] Send a virtual adjustment instruction to the virtual CFD space. The virtual vehicle component receives the virtual adjustment instruction and performs an expected adjustment according to the received virtual adjustment instruction to obtain a vehicle mobilization component; Further, the virtual adjustment instruction represents an instruction for adjusting the vehicle in the virtual CFD space, including adjusting the geometric data, dynamic data, and external environment of the vehicle. Each adjustment is recorded as a virtual adjustment instruction. Adjust the virtual vehicle component according to the obtained virtual adjustment instruction and perform virtual capture on the virtual vehicle component after the expected adjustment to obtain a vehicle mobilization component. Here, virtual capture means that after the virtual vehicle component executes the virtual adjustment instruction, the three-dimensional solid model of the virtual vehicle component is collected again to obtain the vehicle mobilization component, that is, the vehicle mobilization component is the virtual vehicle component after the expected adjustment; Perform a homomorphism transformation on the obtained vehicle mobilization component to obtain an edge mobilization set; Further, the process of the homomorphism transformation includes: Perform a simulation division on the vehicle mobilization component according to the dynamic segmentation box and the vehicle component area to obtain a mobilization area sequence, and the mobilization area sequence includes mobilization component units; Perform a standard adjustment on the mobilization area sequence according to the obtained equilibrium standard to obtain a uniform mobilization sequence, and the uniform mobilization sequence includes standard mobilization units, and the standard mobilization units are obtained according to the mobilization component units; Upload the judgment grid box to the uniform transfer sequence, and through the judgment grid box, cooperatively capture the edges of the uniform transfer sequence to obtain an edge transfer set. The edge transfer set includes a transfer tile sequence, which is obtained based on transfer component tiles, and the transfer component tiles are obtained by performing capture convolution on each grid cell area of the standard transfer unit with the judgment grid box. Among them, the transfer tile sequence represents all the transfer component tiles corresponding to a standard transfer unit; Obtain the subunit tile sequence within the edge feature component set, match the obtained subunit tile sequence with the corresponding transfer tile sequence, and obtain a matching transfer sequence and a matching subunit sequence; Furthermore, the matching means that in the virtual CFD space, obtain the standard component units at the corresponding same positions of the virtual vehicle component and the vehicle transfer component, and record them as the matching transfer sequence and the matching subunit sequence respectively; Perform same-block verification on the obtained matching transfer sequence and matching subunit sequence to obtain a verification transfer difference; Furthermore, the process of the same-block verification includes: Obtain the edge component tile and the transfer component tile at the corresponding positions in the matching transfer sequence and the matching subunit sequence; Perform pixel verification on the obtained edge component tile and transfer component tile to obtain a verification transfer difference, and mark the obtained verification transfer difference as ∆XF, where, , θ represents a weight factor, then " " calculates the difference at the same pixel position, "i−j−k" represents the kth pixel of the jth edge component tile of the ith subunit tile sequence, k represents the pixel position number of the edge component tile, " " represents the mth pixel of the jth transfer component tile of the ith transfer tile sequence, m represents the pixel position number of the transfer component tile, m = 1, 2, 3,..., v3, and v3 is a positive integer; In particular, according to "the subunit tile sequence is matched with the corresponding transfer tile sequence", the numbers of the obtained transfer component tiles are the same as the numbers of the edge component tiles, and the numbers of the transfer tile sequences are the same as the numbers of the subunit tile sequences.

[0021] Cyclically vary the virtual adjustment instruction according to the obtained verification transfer difference to obtain a variable adjustment instruction; Furthermore, the cyclic variation means that according to the vehicle shape geometry data, dynamics data, and external environment, perform variable adjustment to obtain adjustment instructions with different parameters until the variable adjustment reaches the maximum range that the vehicle shape geometry data, dynamics data, and external environment can withstand, and record the adjusted instructions to obtain a variable adjustment instruction; For example, adjust the vehicle kinematic parameter from h1 to h2; Perform the expected adjustment on the virtual vehicle components according to the obtained change adjustment instruction to obtain the changed vehicle mobilization components, and perform a homomorphism transformation on the obtained changed vehicle mobilization components to obtain the changed edge mobilization set; Perform a same-block check on the changed edge mobilization set according to the obtained edge feature component set to obtain the changed check mobilization difference; Statistically analyze the obtained changed check mobilization difference and generate a changed check difference graph based on the statistically analyzed changed check mobilization difference; Furthermore, the obtained changed check difference graph is a two-dimensional rectangular coordinate system composed of mobilization curves generated by the changed check mobilization difference, and one changed check difference graph corresponds to the mobilization curves corresponding to the changed check mobilization differences of all mobilization component blocks obtained by one change adjustment instruction. Each point on the curve represents the changed check mobilization difference corresponding to a mobilization component block; Set a judgment boundary axis for the obtained changed check difference and upload the set judgment boundary axis to the changed check difference graph; Furthermore, the set judgment boundary axis is a horizontal line parallel to the horizontal axis and is a pre-set threshold line; Perform a critical comparison on the changed check difference graph according to the obtained judgment boundary axis to obtain variable adjustment blocks and steady-state adjustment blocks; Furthermore, within the changed check difference graph, when the changed check mobilization difference is greater than or equal to the judgment boundary axis, obtain the mobilization component block corresponding to the changed check mobilization difference, denoted as the variable adjustment block; When the changed check mobilization difference is less than the judgment boundary axis, obtain the mobilization component block corresponding to the changed check mobilization difference, denoted as the steady-state adjustment block; Based on the changed check difference graph, perform an adjustment judgment on the changed vehicle mobilization components according to the obtained variable adjustment blocks and steady-state adjustment blocks to obtain over-adjustment parameters and steady-state adjustment parameters; It should be further noted that in the specific implementation process, the process of the adjustment judgment includes: Statistically analyze the number of variable adjustment blocks and steady-state adjustment blocks in the changed check difference graph to obtain the number of variable blocks and the number of steady-state blocks; When the number of variable blocks ≥ β0 * the number of steady-state blocks, where β0 represents the multiple weight and β0 ≥ 2, obtain the change adjustment instruction corresponding to the changed vehicle mobilization component, and perform a transformation on the obtained change adjustment instruction to obtain over-adjustment parameters. The transformation means recording the parameters that need to be adjusted in the change adjustment instruction as over-adjustment parameters, indicating that the set parameters are not conducive to the normal operation of the vehicle and are unqualified vehicle parameters; When the number of variable blocks < β1 * the number of steady-state blocks, where β0 represents the proportion weight, 0 < β0 < 1, obtain the variable adjustment instruction corresponding to the variable vehicle adjustment component, transform the obtained variable adjustment instruction, and obtain the steady-state adjustment parameter, indicating that the set parameter will not affect the normal operation of the vehicle and is a qualified vehicle parameter.

[0022] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific embodiments. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An optimization method for automobile exterior parameters based on CFD simulation, characterized in that, It includes the following steps: Step S1: Collect comprehensive vehicle data, construct a virtual CFD space, and obtain virtual vehicle components; Step S2: Set a dynamic segmentation box to simulate the segmentation of the vehicle component area, obtain a virtual component sequence, perform a standardized adjustment on the virtual component sequence according to an equilibrium criterion to obtain a uniform component sequence, set a comprehensive determination coefficient for section division to obtain a sectional determination coefficient, upload the sectional determination coefficient to a grid extraction box to obtain a determination grid box, and perform edge collaborative capture on the uniform component sequence according to the determination grid box to obtain an edge feature component set; Step S3: Send a virtual adjustment instruction to the virtual CFD space and perform an expected adjustment to obtain a vehicle adjustment component, perform a homomorphic transformation on the vehicle adjustment component and perform a same-block verification with the edge feature component set to obtain a verification adjustment difference; Step S4: Cyclically vary the virtual adjustment instruction according to the verification adjustment difference to obtain a variable adjustment instruction, perform an expected adjustment on the virtual vehicle components through the variable adjustment instruction and perform a same-block verification with the edge feature component set to obtain a variable verification difference graph, set a judgment demarcation axis to perform a critical comparison on the variable verification difference graph to obtain a variable adjustment graph block and a steady-state adjustment graph block, and perform an adjustment judgment on the variable vehicle adjustment component to obtain an over-adjustment parameter and a steady-state adjustment parameter.

2. The method for optimizing the external shape parameters of an automobile based on CFD simulation according to claim 1, characterized in that, The process of obtaining virtual vehicle components includes: Set a simulation acquisition terminal, collect vehicle data through the simulation acquisition terminal to obtain comprehensive vehicle data; Construct a virtual CFD space according to the comprehensive vehicle data; Perform a homomorphic transformation on the vehicle to obtain virtual vehicle components, and upload the obtained virtual vehicle components to the virtual CFD space.

3. The optimization method for automobile shape parameters based on CFD simulation according to claim 2, characterized in that The process of obtaining a uniform component sequence includes: Set a dynamic segmentation box according to the virtual vehicle components; Set a vehicle component area for the virtual vehicle components, and perform a simulation segmentation on the vehicle component area according to the set dynamic segmentation box to obtain a virtual component sequence; Set an equilibrium criterion, and perform a standardized adjustment on the virtual component sequence according to the equilibrium criterion to obtain a uniform component sequence, and the uniform component sequence includes a number of standardized component units.

4. The method for optimizing the external shape parameters of an automobile based on CFD simulation according to claim 3, characterized in that, The process of obtaining an edge feature component set includes: Set a comprehensive determination coefficient, perform a morphological regulation on the comprehensive determination coefficient to obtain a regulation parameter; Perform section division on the comprehensive determination coefficient according to the obtained regulation parameter to obtain a sectional determination coefficient; Set a grid extraction box, upload the obtained sectional determination coefficient to the grid extraction box to obtain a determination grid box; Upload the determination grid box to the uniform component sequence, and perform edge collaborative capture on the uniform component sequence through the determination grid box to obtain an edge feature component set.

5. A method for optimizing the external shape parameters of an automobile based on CFD simulation according to claim 4, characterized in that, The process of performing edge collaborative capture on the uniform component sequence through the determination grid box includes: Upload the determination grid box to the first standardized component unit of the uniform component sequence, and mark the corresponding area of the determination grid box in the standardized component unit as a grid unit area; Perform feature capture on the grid unit area through the determination grid box to obtain an edge component block; Translate and slide the obtained judgment grid box based on the standard component unit to reach the next grid cell area, and perform capture convolution on the grid cell area until all areas of the standard component unit are covered. Sort the edge component tiles according to the standard component unit to obtain a sub-unit tile sequence; According to the homogeneous component sequence, upload the judgment grid box to the next standard component unit, repeat the process of obtaining the sub-unit tile sequence until the homogeneous component sequence is covered, and sort the sub-unit tile sequence according to the homogeneous component sequence to obtain an edge feature component set.

6. The method for optimizing the external shape parameters of an automobile based on CFD simulation according to claim 5, wherein, The process of obtaining the calibration adjustment difference includes: Send a virtual adjustment instruction to the virtual CFD space, receive the virtual adjustment instruction through the virtual vehicle component, and perform expected adjustment according to the received virtual adjustment instruction to obtain a vehicle adjustment component; Perform homomorphic transformation on the vehicle adjustment component to obtain an edge adjustment set, and match the edge adjustment set according to the obtained edge feature component set to obtain a matching adjustment sequence and a matching sub-unit sequence; Perform same-block verification on the matching adjustment sequence and the matching sub-unit sequence to obtain the calibration adjustment difference.

7. A method for optimizing automotive exterior parameters based on CFD simulation according to claim 6, characterized in that, The process of obtaining the variation verification difference graph includes: Cyclically vary the virtual adjustment instruction according to the calibration adjustment difference to obtain a variation adjustment instruction; Perform expected adjustment on the virtual vehicle component according to the variation adjustment instruction to obtain a variation vehicle adjustment component, and perform homomorphic transformation on the obtained variation vehicle adjustment component to obtain a variation edge adjustment set; Perform same-block verification on the variation edge adjustment set according to the edge feature component set to obtain a variation calibration adjustment difference, and generate a variation verification difference graph according to the variation calibration adjustment difference.

8. A method for optimizing the external shape parameters of an automobile based on CFD simulation according to claim 7, characterized in that, The process of obtaining the over-adjustment parameter and the steady-state adjustment parameter includes: Set a judgment demarcation axis and upload the set judgment demarcation axis to the variation verification difference graph; Perform a critical comparison on the variation verification difference graph according to the judgment demarcation axis to obtain a variable adjustment tile and a steady-state adjustment tile; Based on the variation verification difference graph, perform adjustment evaluation on the variation vehicle adjustment component according to the obtained variable adjustment tile and steady-state adjustment tile to obtain the over-adjustment parameter and the steady-state adjustment parameter.

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