Vehicle body NTF simulation and test benchmarking result post-processing method and device and medium

Abstract

The invention discloses a vehicle body NTF simulation and test benchmarking result post-processing method and device and a storage medium, and the method comprises the steps: formulating an NTF target value according to vehicle type positioning, benchmarking vehicle types or response point target differentiation; building finite element models of an interior vehicle body and a sound cavity; generating an NTF solving file according to the excitation point and response point information; solving and calculating a finite element model; nTF test and data export are carried out; preprocessing test data; nTF simulation or test result automatic post-processing is carried out; and exporting and evaluating a result, if a problem frequency point which does not meet a target value or is poor in benchmarking precision exists, carrying out structure optimization or model precision improvement, and if the problem frequency point does not exist, outputting an analysis report.

Description

Technical Field

[0001] The present application relates to the field of NTF simulation technology, and in particular to a method, device and storage medium for post-processing vehicle body NTF simulation and test benchmarking results. Background Art

[0002] The body NTF (Noise Transfer Function) refers to the ratio of the linear system response (sound pressure near the ears of the driver and passengers) to the excitation (unit excitation load applied at the body excitation point). It is mainly used to evaluate the body NVH performance in the early stage of vehicle development. The weak points of the body design are determined through the NTF analysis results, and the structure is optimized to improve the body NVH performance.

[0003] The commercial vehicle body adopts two-stage vibration isolation, and the main noise excitation paths in the vehicle are the body suspension installation points and the upper air intake installation points. The number of cab suspension and air intake installation points of different models is different, and the number of response points is different due to the different number of drivers and passengers in commercial vehicles. The number of NTF curves is not fixed and the number of curves is large (number of excitation points * 3 * number of human ear response points in the vehicle, for example: 6 body side suspension installation points, 7 air intake installation points, 2 ear response points in the vehicle, a total of 78 NTF result curves), manual processing of curves is time-consuming, inefficient and prone to errors, and according to the preset target value, manual identification of problem frequency points that do not meet the target value is inefficient and prone to missing some problem points.

[0004] The experimental NTF is mainly tested and data processed by Lms Test.Lab or HEAD software, and the simulation NTF data is mainly read by Altair's Hypergraph software. Since the test software and simulation software data are incompatible, Hypergraph cannot directly read the original NTF data of the test. In addition, due to the difference in the format of simulation and test data, the test data must be preprocessed before it can be read by the Hypergraph software. Manual processing of reading test data and identifying problem points where the benchmarking accuracy does not meet the standards is time-consuming and prone to errors.

[0005] The current solution has the following main disadvantages: Disadvantage 1: When NTF is manually or automatically post-processed, it can only post-process and draw for a fixed number of excitation points and response points. It cannot automatically identify and process NTF results of different numbers of excitation points and response points. It is time-consuming to identify problem frequency points according to target values ​​and it is easy to miss some problem points. When comparing multiple groups of curves, the curve visualization operation is cumbersome and it is necessary to manually set the visualization of each curve in each window on each page. Disadvantage 2: The existing NTF automated post-processing can only post-process simulation data, and cannot process test data, which makes it inconvenient to perform simulation and test benchmarking analysis. Summary of the invention

[0006] The present application provides a vehicle body NTF simulation and test benchmarking result post-processing method, device and storage medium to solve the above-mentioned problems.

[0007] On the one hand, the present application provides a method for post-processing vehicle body NTF simulation and test benchmarking results, the method comprising the following steps:

[0008] Step S1: Formulate NTF target values ​​according to vehicle model positioning, benchmark vehicle models or response point target differentiation;

[0009] Step S2: constructing interior body and acoustic cavity finite element models;

[0010] Step S3: Generate NTF solution file according to the information of excitation point and response point;

[0011] Step S4: finite element model solution calculation;

[0012] Step S5: NTF test and data export;

[0013] Step S6: test data preprocessing;

[0014] Step S7: automatic post-processing of NTF simulation or test results;

[0015] Step S8: Result export and evaluation. If there are problem frequency points that do not meet the target value or have poor benchmarking accuracy, perform structural optimization or improve model accuracy. If not, output an analysis report.

[0016] In one implementation of the present application, in step S2, the interior body finite element model needs to include a white body with glass, opening and closing parts, interior and exterior decoration, and the acoustic cavity finite element model needs to include the main acoustic cavity, seats, instrument panel, sundries box, and berth.

[0017] In one implementation of the present application, step S3 specifically includes: running a header file generation script to generate a SET set of excitation points and response points, working condition information, excitation loads and loading information, solution parameter settings, and calling a solution header file of the interior body and acoustic cavity finite element model based on the excitation point and response point node information.

[0018] In one implementation of the present application, step S4 is specifically: solving and calculating the model through the header file to obtain the NTF simulation calculation result .pch file.

[0019] In one implementation of the present application, step S5 is specifically: conducting an actual vehicle NTF test according to the set excitation points and response points, and exporting the raw data to a .csv file.

[0020] In one implementation of the present application, step S6 is specifically:

[0021] Step S61: Run the test data preprocessing script;

[0022] Step S62: pre-process the test data according to the data reading format of the Hypergraph software, retain the excitation point and direction, response point information, delete other test information, retain the frequency axis information of curve 1, delete redundant frequency axis information, and adjust the data type and format.

[0023] In one implementation of the present application, step S7 is specifically:

[0024] Step S71: running the NTF automated post-processing script;

[0025] Step S72: define the NTF result file address, automatically pick up the file extension name through file extension $filePath and call different response file reading scripts according to the file extension name;

[0026] Step S73: automatically obtain the working condition information through file GetSubcaseList, set the response data type, automatically obtain the number of response points, automatically set the window level of each page in Hypergraph according to the number of response points, read the response data of each excitation point in X, Y, and Z directions to the response point in X direction in sequence, draw a curve chart, and set a specific display range for each window on each page through the Scale information table;

[0027] Step S74: performing a single round or multiple rounds of simulation data reading, or simulation and test data reading according to the analysis purpose;

[0028] Step S75: according to the preset target value information table, draw the target value curve through dat SetValue$target;

[0029] Step S76: If multiple sets of data are imported at the same time and it is not convenient for comparative analysis, the display and hiding of specific curves in specific windows of specific pages can be batch controlled through cur SetVisibilityTrue / False;

[0030] Step S77: Because the NTF range of concern for different car models or ear response positions may be different or the focus of result viewing may be different, the axis SetMin$min and axis SetMax$max integrated in the script can be used to flexibly adjust the coordinate axis range as needed, and the prefix and suffix names of different curves can be set through cur SetName$name to distinguish them. The display position of the curve legend can be adjusted through legendSetPosition$x,$y, etc., and the visualization of the curve can be controlled as needed.

[0031] In one implementation of the present application, step S8 specifically includes:

[0032] Step S81: If simulation result analysis is performed, according to the target value setting, for the problematic frequency points that do not meet the target value requirements, the problematic frequency point information where the sound pressure of the ear response point under the excitation direction of each excitation point exceeds the target value can be exported according to {Point Exciting Name / ID Direction Point Response Name / ID F / Hz SPL / dB(A)}, or the maximum response amplitude can be exported to a .csv file in the format of {Point Exciting Name / ID Point Direction ResponseName / ID F / Hz Max SPL / dB(A)} through tcl::mathfunc::max{*}$yValue. If there are frequency points that do not meet the target value requirements, their structure can be optimized. If not, all or specific page numbers and window graphs can be batch exported as needed, and an analysis report can be output according to the report template.

[0033] Step S82: If simulation and test benchmarking is performed, according to the benchmarking accuracy requirements, if there are problems with poor benchmarking accuracy, the model accuracy can be improved. If not, the curve charts of all or specific pages and windows can be batch exported as needed, and the analysis report can be output according to the report template.

[0034] The present application also provides a vehicle body NTF simulation and test benchmarking result post-processing device, the device comprising:

[0035] at least one processor; and,

[0036] a memory communicatively connected to the at least one processor; wherein,

[0037] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can complete the aforementioned vehicle body NTF simulation and test benchmarking result post-processing method.

[0038] The present application also provides a non-volatile computer storage medium for post-processing of vehicle body NTF simulation and test benchmarking results, which stores computer executable instructions, and is characterized in that the computer executable instructions are executed by a processor to implement the aforementioned vehicle body NTF simulation and test benchmarking result post-processing method.

[0039] The present application provides a method, device and storage medium for post-processing the results of NTF simulation and test benchmarking of a vehicle body. The NTF post-processing has a wide range of applications and can automatically post-process different numbers of excitation points and response points set under different vehicle models or working conditions and different types of response data formats. To improve the flexibility and convenience of operations such as visualization of curves and drawing areas, on the basis of the original operations of Hypergraph, the post-processing script integrates more flexible and convenient operations such as target value setting, drawing area coordinate range adjustment, curve color linearity and visualization, legend adjustment, and curve prefix and suffix name adjustment and labeling. The curve can be flexibly operated according to the analysis purpose and focus, which is convenient for curve image display and result viewing. Through the pre-processing of the original test data, the redundant information of the test NTF original data is deleted, the data format is adjusted, and other operations are performed to facilitate the test data to be read into the finite element Hypergraph software and subsequent NTF post-processing. Import simulation and test NTF data, perform simulation and test NTF benchmarking, improve the accuracy of problem points with poor benchmarking accuracy, and improve the accuracy of simulation NTF. After using NTF automated post-processing, the time is reduced from 4-5 days to 0.5 days or shorter, and the problem frequency points that do not meet the target values ​​can be exported according to the preset target values, which is convenient for identifying problem frequency points and determining the subsequent optimization direction, greatly improving the efficiency of NTF post-processing, simulation optimization iteration and benchmarking analysis, saving time costs and shortening the development cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0041] Figure 1 A flow chart of a method for post-processing vehicle body NTF simulation and test benchmarking results provided in an embodiment of the present application;

[0042] Figure 2 A flow chart of the iterative automated post-processing method for vehicle body NTF simulation optimization provided in an embodiment of the present application;

[0043] Figure 3 An example diagram of a vehicle body NTF simulation solution header file provided in an embodiment of the present application;

[0044] Figure 4An example diagram of part of the NTF simulation calculation results of the vehicle body provided in the embodiment of the present application;

[0045] Figure 5 The NTF simulation and test benchmarking results of the vehicle body provided in the embodiment of the present application;

[0046] Figure 6 A schematic diagram of a vehicle body NTF simulation and test benchmarking result post-processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0048] The embodiment of the present application provides a method, device and storage medium for post-processing the results of vehicle body NTF simulation and test benchmarking. The technical solution proposed in the embodiment of the present application is described in detail below with the help of the accompanying drawings.

[0049] Figure 1 A flow chart of a method for post-processing vehicle body NTF simulation and test benchmarking results provided in an embodiment of the present application. Figure 1 As shown, the method mainly includes the following steps:

[0050] Step S1: Formulate NTF target values ​​according to vehicle model positioning, benchmark vehicle models or response point target differentiation;

[0051] Step S2: constructing interior body and acoustic cavity finite element models;

[0052] Step S3: Generate NTF solution file according to the information of excitation point and response point;

[0053] Step S4: finite element model solution calculation;

[0054] Step S5: NTF test and data export;

[0055] Step S6: test data preprocessing;

[0056] Step S7: automatic post-processing of NTF simulation or test results;

[0057] Step S8: Result export and evaluation. If there are problem frequency points that do not meet the target value or have poor benchmarking accuracy, perform structural optimization or improve model accuracy. If not, output an analysis report.

[0058] In the embodiments of the present application, Figure 2 Flowchart of the automated post-processing method for vehicle body NTF simulation and test benchmarking provided in an embodiment of the present application.

[0059] In the embodiment of the present application, in the step S2, the interior body finite element model needs to include the white body with glass, opening and closing parts, interior and exterior decoration, the model information number range is 10000000-49999999, the excitation point number range is 1000001-1000050, the sound cavity finite element model needs to include the main sound cavity, seats (driver, co-driver and other seats), dashboard, sundries box, berth, etc., the information number range is 50000000-79999999, and the response point number range is 1000100-1000110. The following Table 1 is an NTF excitation point and response point information table for automatic post-processing of the NTF simulation optimization and test benchmarking results of the vehicle body shown in the present invention, including the excitation points, response point IDs and names preset in step 2.

[0060] Table 1 Car body NTF excitation point and response point information table

[0061]

[0062] In an embodiment of the present application, step S3 specifically includes: running a header file generation script, generating a SET set including excitation points and response points, working condition information, excitation loads and loading information, solution parameter settings, and calling a solution header file of the interior body and acoustic cavity finite element model according to the excitation point and response point node information.

[0063] In the embodiment of the present application, the step S4 is specifically: solving and calculating the model through the header file to obtain the NTF simulation calculation result .pch file.

[0064] In the embodiment of the present application, the step S5 is specifically: carrying out the actual vehicle NTF test according to the set excitation points and response points, and exporting the raw data to a .csv file.

[0065] In the embodiment of the present application, the step S6 is specifically as follows:

[0066] Step S61: Run the test data preprocessing script;

[0067] Step S62: pre-process the test data according to the data reading format of the Hypergraph software, retain the excitation point and direction, response point information, delete other test information, retain the frequency axis information of curve 1, delete redundant frequency axis information, and adjust the data type and format.

[0068] In the embodiment of the present application, the step S7 is specifically as follows:

[0069] Step S71: running the NTF automated post-processing script;

[0070] Step S72: define the NTF result file address (.pch or .csv file), automatically pick up the file extension (.pch or .csv) through file extension$filePath and call different response file reading scripts according to the file extension;

[0071] Step S73: automatically obtain the working condition information through file GetSubcaseList, set the response data type (acceleration, velocity, displacement), automatically obtain the number of response points, automatically set the window level of each page in Hypergraph according to the number of response points, read the X-direction response data of each excitation point to the response point in turn, draw a curve chart, and set a specific display range for each window on each page through the Scale information table;

[0072] Step S74: performing a single round or multiple rounds of simulation data reading, or simulation and test data reading according to the analysis purpose;

[0073] Step S75: according to the preset target value information table, draw the target value curve through dat SetValue$target;

[0074] Step S76: If multiple sets of data are imported at the same time and it is not convenient for comparative analysis, the display and hiding of specific curves in specific windows of specific pages can be batch controlled through cur SetVisibilityTrue / False;

[0075] Step S77: Because the NTF range of concern for different car models or ear response positions may be different or the focus of result viewing may be different, the axis SetMin$min and axis SetMax$max integrated in the script can be used to flexibly adjust the coordinate axis range as needed, and the prefix and suffix names of different curves can be set through cur SetName$name to distinguish them. The display position of the curve legend can be adjusted through legendSetPosition$x,$y, etc., and the visualization of the curve can be controlled as needed.

[0076] In the embodiment of the present application, the step S8 specifically includes:

[0077] Step S81: If simulation result analysis is performed, according to the target value setting, for the problematic frequency points that do not meet the target value requirements, the problematic frequency point information where the sound pressure of the ear response point under the excitation direction of each excitation point exceeds the target value can be exported according to {Point Exciting Name / ID Direction Point Response Name / ID F / Hz SPL / dB(A)}, or the maximum response amplitude can be exported to a .csv file in the format of {Point Exciting Name / ID Point Direction ResponseName / ID F / Hz Max SPL / dB(A)} through tcl::mathfunc::max{*}$yValue. If there are frequency points that do not meet the target value requirements, their structure can be optimized. If not, all or specific page numbers and window graphs can be batch exported as needed, and an analysis report can be output according to the report template.

[0078] Step S82: If simulation and test benchmarking is performed, according to the benchmarking accuracy requirements, if there are problems with poor benchmarking accuracy, the model accuracy can be improved. If not, the curve charts of all or specific pages and windows can be batch exported as needed, and the analysis report can be output according to the report template.

[0079] In the present application, refer to Figure 3 , Figure 3 The present invention shows an example of a solution header file for automated post-processing of vehicle body NTF simulation optimization and test benchmarking results. The obtained excitation point and response point IDs and names are used to generate corresponding excitation point and response point SET sets, working condition settings (working condition label setting format: excitation point name_excitation point ID: excitation force direction, number of working conditions: number of excitation points*3), excitation settings (excitation load and loading information: unit excitation force in the three directions of X / Y / Z for each excitation point in the frequency range of 0 to 600 Hz), and the solution type, solution parameters, and model file calling statements in the NTF solution header file are synchronously set.

[0080] Reference Figure 4 , Figure 4This is an example of the content of the NTF simulation calculation result .pch file for the automatic post-processing of the vehicle body NTF simulation optimization and test benchmarking results shown in the present invention. The working condition information is identified according to the SUBCASE ID, the excitation point ID and excitation direction are identified according to the LABEL, and the response point information is identified according to the POINT ID. The data between adjacent working conditions is the NTF result corresponding to one working condition, separated by a space, and the field before the "S" character is the frequency (i.e., the X-axis of the result curve). The first field after the "S" character is the response (the response in the NTF result file is the sound pressure, which needs to be converted into the A-weighted sound pressure level, i.e., the Y-axis of the result curve), and so on, to complete the reading of a result file. If a simulation optimization scheme comparison or simulation test benchmarking is performed, repeat this step to complete the reading of multiple result files.

[0081] Reference Figure 5 , Figure 5 An example of a simulation and test benchmarking result diagram for automatic post-processing of a vehicle body NTF simulation optimization and test benchmarking results shown in the present invention, the curve diagram includes an NTF response curve (as shown in the figure, under simulation and test analysis, the NTF response of the response point under a unit excitation force in the three directions of the excitation point X, Y, and Z) and a target value curve (as shown in the target curve, the target value curve can be a straight line or a segmented curve according to the setting).

[0082] The above is a method for post-processing vehicle body NTF simulation and test benchmarking results provided by an embodiment of the present application. Based on the same inventive concept, an embodiment of the present application also provides a device for post-processing vehicle body NTF simulation and test benchmarking results. Figure 6 A schematic diagram of a post-processing device for vehicle body NTF simulation and test benchmarking results provided in an embodiment of the present application, such as Figure 6 As shown, the device mainly includes: at least one processor 601; and a memory 602 that is communicatively connected to the at least one processor; wherein the memory 602 stores instructions that can be executed by the at least one processor 601, and the instructions are executed by the at least one processor 601 so that the at least one processor 601 can complete the aforementioned vehicle body NTF simulation and test benchmarking result post-processing method.

[0083] In addition, an embodiment of the present application also provides a non-volatile computer storage medium for post-processing of vehicle body NTF simulation and test benchmarking results, which stores computer executable instructions. The computer executable instructions are executed by a processor to implement the aforementioned vehicle body NTF simulation and test benchmarking result post-processing method.

[0084] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0085] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0087] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0088] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0089] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0090] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for post-processing vehicle body NTF simulation and test benchmarking results, characterized in that: The method comprises the following steps: Step S1: Formulate NTF target values ​​according to vehicle model positioning, benchmark vehicle models or response point target differentiation; Step S2: constructing interior body and acoustic cavity finite element models; Step S3: Generate NTF solution file according to the information of excitation point and response point; Step S4: finite element model solution calculation; Step S5: NTF test and data export; Step S6: test data preprocessing; Step S7: automatic post-processing of NTF simulation or test results; Step S8: Result export and evaluation. If there are problem frequency points that do not meet the target value or have poor benchmarking accuracy, perform structural optimization or improve model accuracy. If not, output an analysis report.

2. A vehicle body NTF simulation and test benchmarking result post-processing method according to claim 1, characterized in that: In step S2, the interior body finite element model must include the white body with glass, opening and closing parts, interior and exterior decoration, and the acoustic cavity finite element model must include the main acoustic cavity, seats, instrument panel, sundries box, and berth.

3. The method for post-processing vehicle body NTF simulation and test benchmarking results according to claim 1, characterized in that: The step S3 specifically includes: running the header file generation script, generating a SET set including the excitation point and response point, working condition information, excitation load and loading information, solution parameter settings, and calling the solution header file of the interior body and acoustic cavity finite element model according to the excitation point and response point node information.

4. The method for post-processing vehicle body NTF simulation and test benchmarking results according to claim 1, characterized in that: The step S4 is specifically: solving and calculating the model through the header file to obtain the NTF simulation calculation result .pch file.

5. The method for post-processing vehicle body NTF simulation and test benchmarking results according to claim 1, characterized in that: The step S5 specifically includes: carrying out the actual vehicle NTF test according to the set excitation points and response points, and exporting the raw data to a .csv file.

6. A vehicle body NTF simulation and test benchmarking result post-processing method according to claim 1, characterized in that: The step S6 is specifically: Step S61: Run the test data preprocessing script; Step S62: pre-process the test data according to the data reading format of the Hypergraph software, retain the excitation point and direction, response point information, delete other test information, retain the frequency axis information of curve 1, delete redundant frequency axis information, and adjust the data type and format.

7. The method for post-processing vehicle body NTF simulation and test benchmarking results according to claim 1, characterized in that: The step S7 is specifically: Step S71: running the NTF automated post-processing script; Step S72: define the NTF result file address, automatically pick up the file extension name through file extension $filePath and call different response file reading scripts according to the file extension name; Step S73: automatically obtain the working condition information through file GetSubcaseList, set the response data type, automatically obtain the number of response points, automatically set the window level of each page in Hypergraph according to the number of response points, read the response data of each excitation point in X, Y, and Z directions to the response point in X direction in sequence, draw a curve chart, and set a specific display range for each window on each page through the Scale information table; Step S74: performing a single round or multiple rounds of simulation data reading, or simulation and test data reading according to the analysis purpose; Step S75: according to the preset target value information table, draw the target value curve through dat SetValue$target; Step S76: If multiple sets of data are imported at the same time and it is not convenient for comparative analysis, the display and hiding of specific curves in specific windows of specific pages can be controlled in batches through cur SetVisibility True / False; Step S77: Because the NTF range of concern for different car models or ear response positions may be different or the focus of result viewing may be different, the axis SetMin$min and axis SetMax$max integrated in the script can be used to flexibly adjust the coordinate axis range as needed, and the prefix and suffix names of different curves can be set through cur SetName$name to distinguish them. The display position of the curve legend can be adjusted through legend SetPosition$x,$y, etc., and the visualization of the curve can be controlled as needed.

8. The method for post-processing vehicle body NTF simulation and test benchmarking results according to claim 1, characterized in that: The step S8 specifically includes: Step S81: If simulation result analysis is performed, according to the target value setting, for the problematic frequency points that do not meet the target value requirements, the problematic frequency point information where the sound pressure of the ear response point under the excitation direction of each excitation point exceeds the target value can be exported according to {Point Exciting Name / ID Direction Point Response Name / ID F / Hz SPL / dB(A)}, or the maximum response amplitude can be exported to a .csv file in the format of {Point Exciting Name / ID Point Direction ResponseName / ID F / Hz Max SPL / dB(A)} through tcl::mathfunc::max{*}$yValue. If there are frequency points that do not meet the target value requirements, their structure can be optimized. If not, all or specific page numbers and window graphs can be batch exported as needed, and an analysis report can be output according to the report template. Step S82: If simulation and test benchmarking is performed, according to the benchmarking accuracy requirements, if there are problems with poor benchmarking accuracy, the model accuracy can be improved. If not, the curve charts of all or specific pages and windows can be batch exported as needed, and the analysis report can be output according to the report template.

9. A post-processing device for vehicle body NTF simulation and test benchmarking results, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can complete the vehicle body NTF simulation and test benchmarking result post-processing method described in any one of claims 1-8.

10. A non-volatile computer storage medium for post-processing of vehicle body NTF simulation and test benchmarking results, storing computer executable instructions, characterized in that: The computer executable instructions are executed by a processor to implement a vehicle body NTF simulation and test benchmarking result post-processing method as described in any one of claims 1-8.

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