A method and system for optimizing key parameters of wind resistance performance of a cab of a light truck

Abstract

The application relates to the field of data processing and discloses a light truck cab wind resistance performance key parameter optimization method and system, which parameterizes engineering data of a light truck into vehicle engineering parameters, applies constraints to each part parameter of the vehicle cab, avoids the situation that an optimal solution is difficult to form in measurement and calculation, constructs a wind resistance performance test model to measure and calculate the wind resistance performance, continuously receives the adjusted vehicle engineering parameters, automatically and cyclically acquire wind resistance performance measurement samples, improves the optimization efficiency of the wind resistance performance, continuously optimizes through the wind resistance performance measurement samples, continuously adjusts and optimizes independent variables under the constraint condition, and reversely acquires optimized engineering parameters, and the application greatly improves the feasibility and accuracy of the wind resistance performance optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a light truck cab wind resistance performance key parameter optimization method and system. BACKGROUND

[0002] With the rapid development of the automobile industry, the market and users gradually increase the performance requirements of the vehicle, and the wind resistance coefficient as a key indicator of vehicle performance is naturally gradually valued, and the wind resistance coefficient is inevitably used as an important design target in the vehicle design stage.

[0003] In the prior art, the wind resistance performance of the cab of the light truck is usually not specifically optimized, and the design of the cab of the light truck is only completed by referring to the safety requirements of the structural parts. Due to the influence of the unique large windward surface of the light truck and the demand of the driver's field of view, the wind resistance performance of the cab of the light truck will not be optimized.

[0004] Therefore, how to design a parameter optimization method to improve the wind resistance performance of the cab of the light truck is a problem to be solved. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a light truck cab wind resistance performance key parameter optimization method and system, which parameterizes the engineering data of the light truck into vehicle engineering parameters to constrain each part of the vehicle cab parameters, avoids the difficulty of forming an optimal solution in measurement, and then constructs a wind resistance performance test model to measure the wind resistance performance, continuously receives the adjusted vehicle engineering parameters, and automatically cyclically obtains the wind resistance performance measurement sample, improves the optimization efficiency of the wind resistance performance, and continuously optimizes the wind resistance performance measurement sample under the constraint condition, continuously adjusts the optimization independent variable to obtain the optimization engineering parameter in reverse, and greatly improves the feasibility and accuracy of the wind resistance performance optimization.

[0006] The light truck cab wind resistance performance key parameter optimization method provided by the present application comprises:

[0007] After obtaining the engineering data of the light truck and preprocessing, the engineering data is parameterized to obtain vehicle engineering parameters;

[0008] A wind resistance performance test model is constructed according to the vehicle engineering parameters to measure the wind resistance performance;

[0009] Obtain the wind resistance performance optimization sample to obtain the optimization engineering parameter in reverse.

[0010] In summary, according to the key parameter optimization method of the wind resistance performance of the cab of the light truck, the engineering data of the light truck is parameterized into vehicle engineering parameters, constraints are applied to the parameters of each part of the cab of the vehicle, and the situation that it is difficult to form an optimal solution in measurement and calculation is avoided, then the wind resistance performance test model is constructed to measure and calculate the wind resistance performance, the adjusted vehicle engineering parameters are continuously received, and the wind resistance performance measurement samples are automatically and circularly obtained, the optimization efficiency of the wind resistance performance is improved, the optimization engineering parameters are reversely obtained by continuously optimizing the wind resistance performance measurement samples and continuously adjusting the optimization independent variables under the constraint condition, and the feasibility and accuracy of the wind resistance performance optimization are greatly improved. Specifically, the engineering data of the light truck is obtained and preprocessed, the engineering data is parameterized to obtain vehicle engineering parameters, constraints are applied to the parameters of each part of the cab of the vehicle, and the situation that it is difficult to form an optimal solution in measurement and calculation is avoided, the wind resistance performance test model is constructed according to the vehicle engineering parameters to measure and calculate the wind resistance performance, the optimization efficiency of the wind resistance performance is improved, the wind resistance performance optimization is performed on the wind resistance performance measurement samples to reversely obtain the optimization engineering parameters, and the feasibility and accuracy of the wind resistance performance optimization are greatly improved.

[0011] Further, the step of obtaining the engineering data of the light truck and pre-processing the engineering data to obtain vehicle engineering parameters specifically includes:

[0012] Obtaining the engineering data of the light truck, the engineering including cab outer sheet metal structure data, cab main body frame structure data, cab front windshield data, cab height limit line data and driver upper field of view interval arrangement data;

[0013] Pre-processing the engineering data, data cleaning is performed according to the vehicle design blueprint to remove incomplete data in the engineering data, and data filling is performed according to the standard data in the vehicle design blueprint;

[0014] Then, the pre-processed engineering data is parameterized according to a deformation analysis algorithm to obtain vehicle engineering parameters.

[0015] Further, the step of parameterizing the pre-processed engineering data according to the deformation analysis algorithm to obtain vehicle engineering parameters specifically includes:

[0016] Constructing a main constraint coordinate system according to the cab outer sheet metal structure data and the cab main body frame structure data, and determining cab skeleton structure node coordinate values and node connection vector values;

[0017] Setting a constraint variable according to the cab front windshield data, the constraint variable including a cab front windshield inclination angle;

[0018] According to the cab height limit line data and the driver upper field of view interval arrangement data, constraint conditions are set, including that the cab roof does not exceed the height limit line and the cab front windshield top is not lower than the driver's field of view line;

[0019] According to the main body constraint coordinate system, the constraint variable and the constraint condition, vehicle engineering parameters are obtained.

[0020] Further, the step of constructing the wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance calculation specifically includes:

[0021] According to the vehicle engineering parameters, a wind resistance performance test model is constructed to perform whole vehicle external flow field analysis;

[0022] According to the computer program file, wind resistance simulation data obtained by the wind resistance performance test model are imported into whole vehicle external flow field analysis calculation, and the deformation parameters of the previous cycle are updated;

[0023] The monitoring module in the wind resistance performance test model continuously captures deformation parameters superior to the current cycle wind resistance performance in the whole vehicle external flow field analysis.

[0024] Further, the step of constructing the wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance calculation further includes:

[0025] A deformation parameter control model is constructed to obtain the deformation parameters obtained by the wind resistance performance calculation;

[0026] The deformation parameters are reversely extracted to obtain vehicle engineering parameters containing constraint variables, and the constraint variables are used as optimization independent variables;

[0027] The optimization independent variables are used as sample labels, and according to the sample labels, a to-be-optimized parameter sample containing all the vehicle engineering parameters is obtained to produce a wind resistance performance calculation sample according to the to-be-optimized parameter sample.

[0028] Further, the step of obtaining the wind resistance performance calculation sample to perform wind resistance performance optimization to reversely obtain optimization engineering parameters specifically includes:

[0029] A wind resistance performance optimization model is constructed, and the wind resistance performance calculation sample is input into the wind resistance performance optimization model;

[0030] The whole vehicle wind resistance coefficient response of the wind resistance performance optimization model during optimization is set as a minimum value, and the wind resistance performance calculation sample amount and wind resistance performance calculation sample change space during optimization are determined;

[0031] The vehicle front windshield inclination angle is set as an optimization independent variable to control the wind resistance performance test model to perform wind resistance test adjustment.

[0032] Further, the step of setting the vehicle front windshield inclination angle as an optimization independent variable to control the wind resistance performance test model to adjust the wind resistance test specifically comprises:

[0033] The maximum height of the cab upper part is adjusted to 2 meters, and the driver's upper field of view angle is limited to 11 degrees;

[0034] The vehicle front windshield inclination angle is set as an optimization independent variable, and the vehicle front windshield inclination angle is continuously increased;

[0035] The cab height is adjusted and the wind resistance coefficient is calculated to obtain the wind resistance coefficient change amount by comparison;

[0036] Determine whether the wind resistance coefficient change amount is less than the preset wind resistance coefficient response threshold, if the wind resistance coefficient change amount is less than the preset wind resistance coefficient response threshold, the parameters in all wind resistance performance calculation samples in the current cycle are generated to obtain the optimization engineering parameters of the current vehicle.

[0037] The present application provides a light truck cab wind resistance performance key parameter optimization system, comprising:

[0038] The preprocessing module is used to obtain the engineering data of the light truck and perform preprocessing, and then the engineering data is parameterized to obtain the vehicle engineering parameters;

[0039] The test module is used to construct a wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance calculation;

[0040] The optimization module is used to obtain wind resistance performance calculation samples to optimize wind resistance performance, and to obtain optimization engineering parameters in reverse.

[0041] The present application also provides a storage medium, which stores one or more programs, and the programs are executed by a processor to realize the light truck cab wind resistance performance key parameter optimization method as described above.

[0042] The present application also provides a computer device, which comprises a memory and a processor, wherein:

[0043] The memory is used to store computer programs;

[0044] The processor is used to execute the computer programs stored in the memory to realize the light truck cab wind resistance performance key parameter optimization method as described above. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 The flow chart of the light truck cab wind resistance performance key parameter optimization method for the first embodiment of the present application;

[0046] Figure 2 This is a flow chart of a method for optimizing key parameters of wind resistance performance of a light truck cab, according to a second embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the structure of a light truck cab wind resistance performance key parameter optimization system proposed in the third embodiment of the present invention.

[0048] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0049] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0050] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0052] See also Figure 1 , which is a flow chart of a method for optimizing key parameters of wind resistance performance of a light truck cab, according to a first embodiment of the present invention. The method comprises steps S01 to S03, wherein:

[0053] Step S01: After obtaining and pre-processing engineering data of a light truck, the engineering data is parameterized to obtain vehicle engineering parameters;

[0054] It should be noted that in this embodiment, engineering data of a light truck is obtained, and the engineering data includes cab exterior sheet metal structure data, cab main frame structure data, cab front windshield data, cab height limit line data, and driver's upper field of view layout data;

[0055] The engineering data is preprocessed, data cleaning is performed according to a vehicle design blueprint, incomplete data in the engineering data is removed, and data filling is performed according to standard data in the vehicle design blueprint;

[0056] The preprocessed engineering data is parameterized according to a deformation analysis algorithm to obtain vehicle engineering parameters;

[0057] In this embodiment, a main constraint coordinate system is constructed according to cab outer panel structure data and cab main body frame structure data, and cab skeleton structure node coordinate values and node connection vector values are determined;

[0058] A constraint variable is set according to cab front windshield data, and the constraint variable includes a cab front windshield inclination angle;

[0059] A constraint condition is set according to cab height limit line data and driver upper field of view interval arrangement data, and the constraint condition includes that the cab roof does not exceed the height limit line and the cab front windshield top end is not lower than the driver field of view line;

[0060] The vehicle engineering parameters are obtained according to the main constraint coordinate system, the constraint variable, and the constraint condition.

[0061] Step S02: A wind resistance performance test model is constructed according to the vehicle engineering parameters to perform wind resistance performance calculation;

[0062] It should be noted that in this embodiment, the wind resistance performance test model is constructed according to the vehicle engineering parameters to perform whole vehicle outer flow field analysis;

[0063] According to the computer program file, wind resistance simulation data obtained by the wind resistance performance test model is imported into whole vehicle outer flow field analysis calculation, and the deformation parameters of the previous cycle are updated;

[0064] The monitoring module in the wind resistance performance test model continuously captures deformation parameters superior to the current cycle wind resistance performance in the whole vehicle outer flow field analysis;

[0065] In this embodiment, a deformation parameter control model is constructed to obtain deformation parameters obtained by wind resistance performance calculation;

[0066] The deformation parameters are reversely extracted to obtain vehicle engineering parameters containing constraint variables, and the constraint variables are used as optimization independent variables;

[0067] The optimization independent variables are used as sample labels, and a to-be-optimized parameter sample containing all the vehicle engineering parameters is obtained according to the sample labels, so as to produce a wind resistance performance calculation sample according to the to-be-optimized parameter sample.

[0068] Step S03: Obtain the wind resistance performance calculation sample to optimize the wind resistance performance, and inversely obtain the optimized engineering parameters;

[0069] It should be noted that in the embodiment, the wind resistance performance optimization model is constructed, and the wind resistance performance calculation sample is input into the wind resistance performance optimization model;

[0070] The vehicle wind resistance coefficient response of the wind resistance performance optimization model during optimization is set to a minimum value, and the wind resistance performance calculation sample quantity and wind resistance performance calculation sample change space during optimization are determined;

[0071] The vehicle front windshield angle is set as an optimization independent variable to control the wind resistance test model to adjust the wind resistance test;

[0072] In the embodiment, the maximum height of the cab upper part is adjusted to 2 meters, and the driver's upper field of view angle is limited to 11 degrees;

[0073] The vehicle front windshield angle is set as an optimization independent variable, and the vehicle front windshield angle is continuously increased;

[0074] The cab height is adjusted and the wind resistance coefficient is calculated to obtain the wind resistance coefficient change amount by comparison;

[0075] It is judged whether the wind resistance coefficient change amount is less than a preset wind resistance coefficient response threshold value, and if it is determined that the wind resistance coefficient change amount is less than the preset wind resistance coefficient response threshold value, the parameters in all wind resistance performance calculation samples in the current cycle are inversely generated as the optimized engineering parameters of the current vehicle.

[0076] In summary, according to the above light truck cab wind resistance performance key parameter optimization method, the engineering data of the light truck is parameterized into vehicle engineering parameters, the parameters of each part of the vehicle cab are constrained, the situation that it is difficult to form an optimal solution in calculation is avoided, the wind resistance performance test model is constructed to calculate the wind resistance performance, the adjusted vehicle engineering parameters are continuously received, and the wind resistance performance calculation sample is automatically obtained in a loop, the optimization efficiency of the wind resistance performance is improved, the wind resistance performance calculation sample is continuously optimized, and the optimization independent variable is continuously adjusted under the constraint condition to inversely obtain the optimized engineering parameters. The present application greatly improves the feasibility and accuracy of wind resistance performance optimization. Specifically, the engineering data of the light truck is obtained and preprocessed, the engineering data is parameterized to obtain vehicle engineering parameters, the parameters of each part of the vehicle cab are constrained, the situation that it is difficult to form an optimal solution in calculation is avoided, the wind resistance performance test model is constructed according to the vehicle engineering parameters to calculate the wind resistance performance, the optimization efficiency of the wind resistance performance is improved, the wind resistance performance calculation sample is obtained to optimize the wind resistance performance, and the optimized engineering parameters are inversely obtained. The present application greatly improves the feasibility and accuracy of wind resistance performance optimization.

[0077] Referring to Figure 2 , a flow chart of a light truck cab wind resistance performance key parameter optimization method according to a second embodiment of the present application is shown, and the light truck cab wind resistance performance key parameter optimization method comprises steps S11 to S16, wherein:

[0078] Step S11: Obtain engineering data of a light truck, including cab outer panel structure data, cab main frame structure data, cab front windshield data, cab height limit line data, and driver upper field of view interval arrangement data, preprocess the engineering data, clean the data according to the vehicle design blueprint to remove incomplete data in the engineering data, and fill the data according to the standard data in the vehicle design blueprint, and then parameterize the preprocessed engineering data according to a deformation analysis algorithm to obtain vehicle engineering parameters;

[0079] Step S12: Construct a main constraint coordinate system according to the cab outer panel structure data and the cab main frame structure data, and determine cab skeleton structure node coordinate values and node connection vector values, set constraint variables according to the cab front windshield data, including cab front windshield inclination angle, set constraint conditions according to the cab height limit line data and the driver upper field of view interval arrangement data, including that the cab roof does not exceed the height limit line and the top end of the cab front windshield is not lower than the driver's field of view line, and obtain vehicle engineering parameters according to the main constraint coordinate system, the constraint variables, and the constraint conditions;

[0080] Step S13: Construct a wind resistance performance test model according to the vehicle engineering parameters to analyze the overall vehicle external flow field, import wind resistance simulation data obtained by the wind resistance performance test model into the overall vehicle external flow field analysis calculation according to a computer program file, and update the deformation parameters of the previous cycle, and the monitoring module in the wind resistance performance test model continuously captures deformation parameters that are superior to the current cycle wind resistance performance in the overall vehicle external flow field analysis;

[0081] Step S14: Construct a deformation parameter control model to obtain deformation parameters obtained by the wind resistance performance calculation, and obtain vehicle engineering parameters containing constraint variables by reverse extraction of the deformation parameters, take the constraint variables as optimization independent variables, take the optimization independent variables as sample labels, and obtain a to-be-optimized parameter sample containing all vehicle engineering parameters according to the sample labels to make a wind resistance performance calculation sample according to the to-be-optimized parameter sample;

[0082] Step S15: constructing a wind resistance performance optimization model, inputting the wind resistance performance calculation sample into the wind resistance performance optimization model, setting the whole vehicle wind resistance coefficient response of the wind resistance performance optimization model as the minimum value during optimization, and determining the wind resistance performance calculation sample quantity and wind resistance performance calculation sample change space during optimization, setting the vehicle front windshield angle as the optimization independent variable, and adjusting the wind resistance test model to control the wind resistance test;

[0083] Step S16: adjusting the maximum height of the cab upper part to 2 meters, adjusting the driver's upper field of view angle limit to 11 degrees, setting the vehicle front windshield angle as the optimization independent variable, and continuously increasing the vehicle front windshield angle, adjusting the cab height and calculating the wind resistance coefficient, comparing the wind resistance coefficient change amount, and determining whether the wind resistance coefficient change amount is less than the preset wind resistance coefficient response threshold value, if the wind resistance coefficient change amount is less than the preset wind resistance coefficient response threshold value, the parameters in all wind resistance performance calculation samples in the current cycle are reversely generated as the optimization engineering parameters of the current vehicle.

[0084] It should be noted that the preset wind resistance coefficient response threshold value in the application is the standard wind resistance coefficient value in the vehicle design blueprint.

[0085] In summary, according to the above-mentioned light truck cab wind resistance performance key parameter optimization method, the engineering data of the light truck is parameterized into vehicle engineering parameters, the parameters of each part of the vehicle cab are constrained, the situation that it is difficult to form an optimal solution in calculation is avoided, the wind resistance performance test model is constructed to calculate the wind resistance performance, the adjusted vehicle engineering parameters are continuously received, and the wind resistance performance calculation sample is automatically obtained, the optimization efficiency of the wind resistance performance is improved, the wind resistance performance calculation sample is continuously optimized, and the optimization independent variable is continuously adjusted under the constraint condition, so as to reversely obtain the optimization engineering parameters, the application greatly improves the feasibility and accuracy of the wind resistance performance optimization. Specifically, the engineering data of the light truck is obtained and preprocessed, the engineering data is parameterized to obtain vehicle engineering parameters, the parameters of each part of the vehicle cab are constrained, the situation that it is difficult to form an optimal solution in calculation is avoided, the wind resistance performance test model is constructed according to the vehicle engineering parameters to calculate the wind resistance performance, the optimization efficiency of the wind resistance performance is improved, the wind resistance performance calculation sample is obtained to optimize the wind resistance performance, and the optimization engineering parameters are reversely obtained, the application greatly improves the feasibility and accuracy of the wind resistance performance optimization.

[0086] Please refer to Figure 3 , which is a structure schematic diagram of the light truck cab wind resistance performance key parameter optimization system according to the third embodiment of the application, and the system comprises:

[0087] The pretreatment module 10 is used for obtaining engineering data of the light truck, and the engineering data is parameterized to obtain vehicle engineering parameters after pretreatment.

[0088] The test module 20 is used for constructing a wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance calculation.

[0089] The optimization module 30 is used for obtaining wind resistance performance calculation samples to perform wind resistance performance optimization to reversely obtain optimized engineering parameters.

[0090] The application further provides a computer storage medium, which stores one or more programs, and the programs are executed by a processor to implement the light truck cab wind resistance performance key parameter optimization method.

[0091] The application further provides a computer device, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor is used for executing the computer program stored in the memory to implement the light truck cab wind resistance performance key parameter optimization method.

[0092] Those skilled in the art can understand that the logic and / or steps represented in the flowchart or described herein, for example, can be considered as a sequence list of executable instructions for implementing the logic function, and can be specifically implemented in any computer readable medium for use by or in combination with an instruction execution system, device or equipment (such as a computer-based system, a system including a processor or other system that can fetch and execute instructions from the instruction execution system, device or equipment). For the purpose of the present description, the "computer readable medium" can be any device that can contain a storage, communication, propagation or transmission of a program for use by or in combination with an instruction execution system, device or equipment.

[0093] More specific examples (non-exhaustive list) of the computer readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CD ROM). In addition, the computer readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by editing, interpreting or processing, if necessary, in other suitable ways, and then stored in the computer memory.

[0094] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the embodiments described above, various steps or methods can be implemented, for example, in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following techniques can be used to implement the hardware used to implement the described functions: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having logic gates for implementing the logic functions on data signals, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0095] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples.

[0096] The above-described embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but cannot be understood as a limitation on the scope of the patent of the present application. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for optimizing key parameters of wind resistance performance of a light truck cab, characterized in that: include: After obtaining and preprocessing engineering data of a light truck, the engineering data is parameterized to obtain vehicle engineering parameters; After obtaining and pre-processing the engineering data of the light truck, the step of parameterizing the engineering data to obtain vehicle engineering parameters specifically includes: Acquire engineering data of a light truck, the engineering data including cab exterior sheet metal structure data, cab main frame structure data, cab front windshield data, cab height limit data, and driver upper field of view layout data; Preprocessing the engineering data, performing data cleaning according to the vehicle design blueprint to remove incomplete data in the engineering data, and filling the data according to standard data in the vehicle design blueprint; Then, the pre-processed engineering data is parameterized according to the deformation analysis algorithm to obtain vehicle engineering parameters; The step of parameterizing the pre-processed engineering data according to the deformation analysis algorithm to obtain vehicle engineering parameters specifically includes: Construct the main constraint coordinate system based on the sheet metal structure data outside the cab and the main frame structure data of the cab, and determine the coordinate values ​​of the cab skeleton structure nodes and the node connection vector values; Setting constraint variables according to cab front windshield data, wherein the constraint variables include the inclination angle of the cab front windshield; Setting constraints based on cab height limit data and driver upper field of view interval layout data, wherein the constraints include the cab roof not exceeding the height limit and the top of the cab front windshield not being lower than the driver's field of view; Obtaining vehicle engineering parameters according to the subject constraint coordinate system, constraint variables, and constraint conditions; Constructing a wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance measurement; Obtain wind resistance performance measurement samples to optimize wind resistance performance and reversely obtain optimized engineering parameters.

2. The method for optimizing key parameters of wind resistance performance of a light truck cab according to claim 1, characterized in that: The step of constructing a wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance measurement specifically includes: Construct a wind resistance performance test model based on vehicle engineering parameters to analyze the vehicle's external flow field; According to the computer program file, the wind resistance simulation data obtained by the wind resistance performance test model is imported into the vehicle external flow field analysis and calculation, and the deformation parameters of the previous cycle are updated; The monitoring module in the drag performance test model continuously captures deformation parameters that are better than the current cycle drag performance during the vehicle external flow field analysis.

3. The method for optimizing key parameters of wind resistance performance of a light truck cab according to claim 1, characterized in that: The step of constructing a wind resistance performance test model according to the vehicle engineering parameters to perform wind resistance performance measurement further includes: Construct a deformation parameter control model to obtain the deformation parameters obtained from wind resistance performance measurement; Reversely extracting the deformation parameters to obtain vehicle engineering parameters including constraint variables, and using the constraint variables as optimization independent variables; The optimized independent variable is then used as a sample label, and a parameter sample to be optimized including all the vehicle engineering parameters is obtained according to the sample label, so as to produce a wind resistance performance measurement sample according to the parameter sample to be optimized.

4. The method for optimizing key parameters of wind resistance performance of a light truck cab according to claim 1, characterized in that: The step of obtaining wind resistance performance measurement samples to optimize wind resistance performance and reversely obtain optimization engineering parameters specifically includes: Constructing a wind resistance performance optimization model, and inputting wind resistance performance measurement samples into the wind resistance performance optimization model; Setting the whole vehicle drag coefficient response of the drag performance optimization model during optimization to a minimum value, and determining the drag performance measurement sample size and the drag performance measurement sample variation space during optimization; The vehicle's front windshield inclination angle is set as the optimization independent variable to control the wind resistance performance test model for wind resistance test adjustment.

5. The method for optimizing key parameters of wind resistance performance of a light truck cab according to claim 4, characterized in that: The step of setting the vehicle front windshield inclination angle as the optimization independent variable to control the wind resistance performance test model to perform wind resistance test adjustment specifically includes: Adjust the maximum height limit of the cab upper part to 2 meters, and adjust the driver's upper field of view angle limit to 11 degrees; Setting the vehicle's front windshield inclination angle as an optimization independent variable, and continuously increasing the vehicle's front windshield inclination angle; Adjust the cab height accordingly and calculate the drag coefficient to compare and obtain the change in the drag coefficient; Determine whether the change in the drag coefficient is less than a preset drag coefficient response threshold. If it is determined that the change in the drag coefficient is less than the preset drag coefficient response threshold, reversely generate the optimized engineering parameters of the current vehicle from the parameters in all drag performance measurement samples in the current cycle.

6. A light truck cab wind resistance performance key parameter optimization system, characterized by: include: A preprocessing module, configured to obtain engineering data of a light truck, perform preprocessing on the engineering data, and then perform parameterization processing on the engineering data to obtain vehicle engineering parameters; After obtaining and pre-processing the engineering data of the light truck, the step of parameterizing the engineering data to obtain vehicle engineering parameters specifically includes: Acquire engineering data of a light truck, the engineering data including cab exterior sheet metal structure data, cab main frame structure data, cab front windshield data, cab height limit data, and driver upper field of view layout data; Preprocessing the engineering data, performing data cleaning according to the vehicle design blueprint to remove incomplete data in the engineering data, and filling the data according to standard data in the vehicle design blueprint; Then, the pre-processed engineering data is parameterized according to the deformation analysis algorithm to obtain vehicle engineering parameters; The step of parameterizing the pre-processed engineering data according to the deformation analysis algorithm to obtain vehicle engineering parameters specifically includes: Construct the main constraint coordinate system based on the sheet metal structure data outside the cab and the main frame structure data of the cab, and determine the coordinate values ​​of the cab skeleton structure nodes and the node connection vector values; Setting constraint variables according to cab front windshield data, wherein the constraint variables include the inclination angle of the cab front windshield; Setting constraints based on cab height limit data and driver upper field of view interval layout data, wherein the constraints include the cab roof not exceeding the height limit and the top of the cab front windshield not being lower than the driver's field of view; Obtaining vehicle engineering parameters according to the subject constraint coordinate system, constraint variables, and constraint conditions; A test module, configured to construct a wind resistance performance test model based on the vehicle engineering parameters to perform wind resistance performance measurement; The optimization module is used to obtain wind resistance performance measurement samples for wind resistance performance optimization, so as to reversely obtain optimization engineering parameters.

7. A storage medium, characterized in that: The storage medium stores one or more programs, which, when executed by the processor, implement the method for optimizing key parameters of wind resistance performance of a light truck cab as described in any one of claims 1 to 5.

8. A computer device, characterized in that: The computer device comprises a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, it implements the method for optimizing key parameters of wind resistance performance of a light truck cab as described in any one of claims 1 to 5.

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