A method, device, equipment and storage medium for establishing a vehicle wind tunnel simulation model

Abstract

The present application discloses a method, device, equipment and storage medium for establishing a vehicle wind tunnel simulation model, which relates to the technical field of automotive aerodynamics. The method includes: determining an initial simulation model of the target vehicle according to the geometric data of the target vehicle and the historical wind tunnel simulation results; setting road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle; inputting the collected sample simulation data of the target vehicle into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle; adjusting the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain a target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle. The above technical solution realizes the establishment of a wind tunnel simulation model of a vehicle on an open road surface by fully considering the real road surface conditions on the basis of wind tunnel simulation.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of automotive aerodynamics, particularly to the technical field of automotive wind tunnel testing, and specifically to a method, device, equipment, and storage medium for establishing a vehicle wind tunnel simulation model. Background Technique

[0002] During the driving process of a vehicle, it mainly overcomes driving resistance, which mainly includes air resistance, rolling resistance, driveline resistance, etc. Research shows that at high speeds, the percentage of wind resistance in the total energy consumption can be as high as over 50%. Currently, the requirements for vehicle energy conservation and emission reduction are becoming increasingly strict. To improve the aerodynamic performance of vehicles, an accurate wind resistance simulation and correction method for commercial vehicles is needed to ensure the goal of reducing wind resistance in the development process.

[0003] Currently, the main technologies for evaluating the air resistance of a whole vehicle are wind tunnel tests and numerical wind tunnel simulations, coast-down tests and open road simulations; on the one hand, affected by the blockage ratio, the existing wind tunnel test errors of commercial vehicles are relatively large, and corrections are required during the establishment of numerical wind tunnel simulations; on the other hand, the coast-down test environment deviates greatly from the real driving environment, making it difficult to accurately simulate the impact of the real environment. Summary of the Invention

[0004] The present application provides a method, device, equipment, and storage medium for establishing a vehicle wind tunnel simulation model to achieve the establishment of a wind tunnel simulation model of a vehicle on an open road.

[0005] According to one aspect of the present application, a method for establishing a vehicle wind tunnel simulation model is provided. The method includes:

[0006] Determine an initial simulation model of the target vehicle according to the geometric data of the target vehicle and historical wind tunnel simulation results;

[0007] Set road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle;

[0008] Input the collected sample simulation data of the target vehicle into the candidate simulation model to obtain wind tunnel simulation data of the target vehicle;

[0009] Adjust the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain a target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle.

[0010] According to another aspect of the present application, a device for establishing a vehicle wind tunnel simulation model is provided. The device includes:

[0011] The first model construction module is used to determine the initial simulation model of the target vehicle according to the geometric data of the target vehicle and the historical wind tunnel simulation results;

[0012] The second model construction module is used to set road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain the candidate simulation model of the target vehicle;

[0013] The model simulation module is used to input the collected sample simulation data of the target vehicle into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle;

[0014] The model adjustment module is used to adjust the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle.

[0015] According to another aspect of the present application, an electronic device is provided, and the electronic device includes:

[0016] One or more processors;

[0017] A memory for storing one or more programs;

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement any vehicle wind tunnel simulation model establishment method provided by the embodiments of the present application.

[0019] According to another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, it implements any vehicle wind tunnel simulation model establishment method provided by the embodiments of the present application.

[0020] In the present application, the initial simulation model of the target vehicle is determined according to the geometric data of the target vehicle and the historical wind tunnel simulation results; road surface simulation parameters and road surface simulation conditions are set for the initial simulation model to obtain the candidate simulation model of the target vehicle; the collected sample simulation data of the target vehicle is input into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle; the candidate simulation model is adjusted according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle. Through the above technical solutions, on the basis of wind tunnel simulation, the real road surface conditions are fully considered, and the establishment of the wind tunnel simulation model of the vehicle on the open road surface is realized. Description of the Drawings

[0021] Figure 1 is a flowchart of a vehicle wind tunnel simulation model establishment method provided by Embodiment 1 of the present application;

[0022] Figure 2 is a flowchart of a method for establishing a vehicle wind tunnel simulation model provided in Embodiment 2 of the present application;

[0023] Figure 3 is a schematic structural diagram of a device for establishing a vehicle wind tunnel simulation model provided in Embodiment 3 of the present application;

[0024] Figure 4 is a schematic structural diagram of an electronic device for implementing the method for establishing a vehicle wind tunnel simulation model of the embodiments of the present application. Detailed implementation manners

[0025] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] In addition, it should also be noted that in the technical solutions of the present application, the collection, storage, use, processing, transmission, provision, and disclosure of relevant data such as geometric data and historical wind tunnel simulation results comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0028] Embodiment 1

[0029] Figure 1It is a flowchart of a method for establishing a vehicle wind tunnel simulation model according to Embodiment 1 of the present application. This embodiment is applicable to the situation of establishing a simulation model for a vehicle's wind tunnel test on an open road surface, and can be executed by a vehicle wind tunnel simulation model establishment device. The vehicle wind tunnel simulation model establishment device can be implemented in the form of hardware and / or software, and can be configured in a computer device, such as a server. As Figure 1 shown, the method includes:

[0030] S110. Determine an initial simulation model of the target vehicle according to the geometric data of the target vehicle and the historical wind tunnel simulation results.

[0031] Among them, the target vehicle refers to a specific vehicle that needs to conduct wind tunnel simulation analysis; for example, the vehicle can be a commercial vehicle. The historical wind tunnel simulation results refer to the data information describing the shape, size, and structure of the target vehicle; these data can include the vehicle's outer contour, length, width, height, body curve, aerodynamic characteristics, etc.; the geometric data usually exists in the form of a CAD (Computer-Aided Design) model or other formats for subsequent simulation and analysis. The historical wind tunnel simulation results refer to the simulation data and results obtained in previous traditional wind tunnel experiments or computational fluid dynamics analyses; these results provide information about the aerodynamic performance of the vehicle under different flow field conditions, such as drag, lift, and airflow distribution. The initial simulation model refers to a mathematical model initially established to simulate the aerodynamic characteristics of the target vehicle during wind tunnel simulation; the initial model is usually based on the geometric data of the target vehicle and combines the historical wind tunnel simulation results to quickly generate a reasonable starting point for subsequent optimization and precise adjustment.

[0032] Exemplarily, an initial simulation model of the target vehicle is established based on CFD (Computational Fluid Dynamics) software, and the initial simulation model is corrected based on the results of traditional wind tunnel tests.

[0033] It can be understood that using traditional wind tunnel tests and simulations as the basis for model establishment has a certain degree of reliability compared to the direct modeling method, and saves the adjustment process of the initial model to a certain extent.

[0034] S120. Set road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle.

[0035] Among them, road surface simulation parameters refer to various parameter settings related to road surface characteristics during the simulation process, which may include road surface type, friction coefficient, slope, inclination, road surface temperature, etc.; the setting of these parameters is crucial for simulating the aerodynamic and dynamic performance of vehicles under different road surface conditions. Road surface simulation conditions refer to specific operating conditions or environmental parameters set in the simulation, which affect the aerodynamic performance and driving state of the vehicle; they may include speed, wind speed, wind direction, load state, etc.; by setting different conditions, the performance of the vehicle in various driving scenarios can be simulated. The candidate simulation model is an improvement of the initial model, reflecting the aerodynamic characteristics of the vehicle under specific road surface conditions and operating conditions, specifically referring to the open road surface simulation model of the target vehicle.

[0036] Exemplarily, based on the initial simulation model, appropriate road surface simulation parameters and road surface calculation conditions are set to preliminarily simulate the aerodynamic characteristics of the target vehicle on the actual road surface, and a candidate simulation model is obtained.

[0037] It should be noted that in traditional wind tunnel tests of commercial vehicles, the simulation numerical wind tunnel models are all modeled using the wind tunnel size as the boundary condition and corrected on this basis; in this application, a boundary condition much larger than the wind tunnel size is directly established in the simulation model to obtain a candidate simulation model, approximately simulating the characteristics of commercial vehicle road tests.

[0038] S130. Input the sample simulation data of the target vehicle collected into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle.

[0039] Among them, the sample simulation data refers to the data on the performance of the target vehicle obtained through various methods (such as computational fluid dynamics simulation, experimental testing, etc.), which may include multi-dimensional information such as prototype vehicle data, driving data, road conditions, and other model input parameters. The wind tunnel simulation data refers to the data on the performance of the vehicle in the airflow obtained through wind tunnel testing or simulation technology, which may include aerodynamic drag, lift coefficient, flow field characteristics, vortex and separation phenomena, etc.

[0040] Optionally, before inputting the sample simulation data of the target vehicle collected into the candidate simulation model, a large amount of wind resistance simulation data and actual test data of the target vehicle under different open road surface conditions are collected; these data include multi-dimensional information such as prototype vehicle data, driving data, road conditions, and other model input parameters; the collected data is preprocessed, including data cleaning, outlier processing, data normalization, etc., to obtain the sample simulation data.

[0041] Among them, the prototype vehicle data refers to various information and parameters related to the target vehicle, which may include vehicle set parameters, powertrain information, suspension system characteristics, weight and center position, etc. The driving data refers to the data related to the vehicle operation state and performance collected during the actual driving process of the target vehicle, which may include speed, acceleration and braking performance, fuel consumption, energy efficiency, wind speed, wind direction, load, etc. The road conditions refer to the road environment and conditions that affect the vehicle driving performance, which may include road surface type, road surface condition, slope, curvature, etc.

[0042] It should be noted that the data collection method is not limited to road tests, and it is also possible to collect the index data during the driving process of real commercial vehicle users.

[0043] S140. Adjust the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle.

[0044] Among them, the wind tunnel measured data refers to the data related to the target vehicle during the actual driving process obtained through wind tunnel experiments, which may include at least one of the vehicle performance data and vehicle dynamic data of the target vehicle, etc.; the vehicle performance data may be fuel consumption, coasting distance, etc.; the vehicle dynamic data may be the influence of acceleration, deceleration, turning, etc. on the wind resistance.

[0045] Exemplarily, use the collected vehicle performance data to compare with the wind tunnel simulation data, and at the same time additionally consider the vehicle dynamic data during the vehicle driving process, conduct a sensitivity analysis on the sample simulation data, screen out the parameters that mainly affect the accuracy of the wind resistance coefficient, and use this parameter as the main correction parameter of the model; select a suitable algorithm, use the collected real data to train the candidate simulation model, use the real data as the training sample, use the algorithm to learn the mapping relationship between the real data and the simulation data, and adjust the correction parameters and structure of the model; apply the trained algorithm to the simulation model to correct the simulation result and obtain the target simulation model.

[0046] Furthermore, the algorithm can be optimized, such as adjusting parameters such as the learning rate and the number of iterations, to obtain a better correction effect.

[0047] In an alternative implementation manner, after adjusting the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model, verify the accuracy of the target simulation model, and in the case where the accuracy verification fails, re-determine the wind tunnel simulation data of the target vehicle.

[0048] Among them, the accuracy verification refers to the verification of the generalization ability and robustness of the target simulation model.

[0049] In an embodiment of the present application, an initial simulation model of a target vehicle is determined according to the geometric data of the target vehicle and historical wind tunnel simulation results; road surface simulation parameters and road surface simulation conditions are set for the initial simulation model to obtain a candidate simulation model of the target vehicle; the collected sample simulation data of the target vehicle is input into the candidate simulation model to obtain wind tunnel simulation data of the target vehicle; the candidate simulation model is adjusted according to the measured wind tunnel data and the wind tunnel simulation data to obtain a target simulation model; the measured wind tunnel data is collected during the actual driving of the target vehicle. Through the above technical solution, on the basis of wind tunnel simulation, the real road surface conditions are fully considered, and the establishment of a wind tunnel simulation model of a vehicle on an open road surface is realized.

[0050] Embodiment 2

[0051] Figure 2 FIG. is a flowchart of a method for establishing a vehicle wind tunnel simulation model according to Embodiment 2 of the present application. On the basis of the technical solutions of the above embodiments, the step of "adjusting the candidate simulation model according to the measured wind tunnel data and the wind tunnel simulation data to obtain a target simulation model" is refined into "comparing the vehicle performance data with the wind tunnel simulation data for consistency to obtain performance comparison data; adjusting the candidate simulation model according to the performance comparison data and the vehicle dynamic data to obtain a target simulation model". It should be noted that for the parts not detailed in the embodiments of the present application, reference may be made to the relevant descriptions of other embodiments. As Figure 2 shown, the method includes:

[0052] S210. Determine an initial simulation model of the target vehicle according to the geometric data of the target vehicle and historical wind tunnel simulation results.

[0053] S220. Set road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle.

[0054] S230. Input the collected sample simulation data of the target vehicle into the candidate simulation model to obtain wind tunnel simulation data of the target vehicle.

[0055] S240. Compare the vehicle performance data with the wind tunnel simulation data for consistency to obtain performance comparison data.

[0056] Among them, the performance comparison data refers to the analysis results obtained by comparing the actual vehicle performance data with the wind tunnel simulation data. These data are used to evaluate and verify the accuracy and reliability of the wind tunnel simulation model.

[0057] Exemplarily, vehicle performance data and wind tunnel simulation data are compared to analyze their performance under the same conditions. For example, numerical comparison is used to directly compare the differences in values such as lift and drag; graphical analysis is used to draw graphs of airflow distribution, pressure distribution, etc. to observe the similarities and differences in the flow field; error analysis is used to calculate the error between the predicted value and the measured value to evaluate the accuracy of the simulation model.

[0058] It should be noted that the performance comparison data serves as a bridge between wind tunnel simulation and actual testing, providing an important basis for evaluating and validating the effectiveness of the simulation model; by analyzing the consistency between the two, engineers can be guided to optimize the design and improve the aerodynamic performance and actual performance of the vehicle.

[0059] S250. Adjust the candidate simulation model according to the performance comparison data and vehicle dynamic data to obtain the target simulation model.

[0060] Optionally, perform a sensitivity analysis on the sample simulation data according to the performance comparison data and vehicle dynamic data to obtain the correlation parameters of the candidate simulation model and the parameter weights corresponding to the correlation parameters; adjust the candidate simulation model according to the correlation parameters and parameter weights to obtain the target simulation model.

[0061] Among them, sensitivity analysis refers to systematically changing the model input parameters to evaluate the sensitivity of the output results to these input changes; its purpose is to determine which parameters have the greatest impact on the simulation results, thereby identifying the correlation parameters. Correlation parameters refer to the parameters that have a significant impact on the simulation results determined through sensitivity analysis; these parameters can significantly change the model output and are the key objects for further adjusting and optimizing the model. Parameter weight refers to the value assigned to each correlation parameter in the sensitivity analysis, reflecting the relative importance of the parameter to the model output; the weight value is usually determined by comparing the contributions of each parameter to the change in the model output.

[0062] It should be noted that the process of adjusting the model is actually a process of modifying the model, which is a step of modifying the candidate simulation model according to the results of sensitivity analysis and the weights of the correlation parameters; this process can include parameter optimization, model reconstruction, etc.

[0063] Specifically, adjusting the candidate simulation model according to the correlation parameters and parameter weights to obtain the target simulation model can be to sort the parameter weights, and determine the target parameters as the correlation parameters with the top parameter weights; determine the parameter type of the target parameters, and based on the corresponding relationship between the parameter type and the adjustment method, determine the target adjustment method of the target parameters according to the parameter type; based on the target adjustment method, adjust the target parameters in the candidate simulation model to obtain the target simulation model.

[0064] Among them, parameter weight sorting refers to sorting the correlation parameters from high to low according to the weight value of each parameter in the sensitivity analysis; this process helps identify the parameters that have the greatest impact on the model output. Target parameters refer to the correlation parameters that rank high in the parameter weight sorting; these parameters are considered to have the most significant impact on the output of the candidate simulation model, so they will be the focus of attention in the subsequent adjustment process. Parameter type refers to the correlation type of the target parameter, which can include positive correlation, negative correlation, etc. The target adjustment method refers to the specific adjustment strategy for the target parameter determined according to the parameter type; by identifying the type of the target parameter, the appropriate adjustment method is selected to ensure that the improvement of the simulation model achieves the expected effect.

[0065] Specifically, a sensitivity analysis is performed on the sample simulation data based on the performance comparison data and the vehicle dynamic data to obtain the correlation parameters of the candidate simulation model. The vehicle parameters in the sample simulation data are verified for correlation through wind tunnel simulation based on the performance comparison data and the vehicle dynamic data, and the vehicle parameters that have passed the correlation verification through wind tunnel simulation are determined as correlation parameters; the correlation parameters are verified for positive correlation with wind tunnel simulation data to obtain the parameter type of the correlation parameters.

[0066] Among them, wind tunnel simulation correlation verification refers to confirming whether there is a statistical correlation between certain parameters through experiments or data analysis methods; this usually involves comparing different data sets (such as wind tunnel simulation data and vehicle dynamics data) to determine which parameters are significantly correlated with vehicle performance. Positive correlation verification refers to the process of detecting whether vehicle performance or output results increase when a certain parameter increases; this type of verification helps to confirm which parameters should be regarded as positive correlation parameters, so that their improvement effects can be considered when optimizing the design. Parameter type usually refers to the classification of parameters into positive correlation parameters, negative correlation parameters, or irrelevant parameters based on the direction and nature of the parameter's impact on the model output; this classification helps to select appropriate adjustment strategies during model optimization and decision-making.

[0067] Further, the parameter type of the correlation parameter that has passed the positive correlation verification of the wind tunnel simulation data is determined as a positive correlation parameter; and the parameter type of the correlation parameter that has not passed the positive correlation verification of the wind tunnel simulation data is determined as a negative correlation parameter.

[0068] It can be understood that by performing sensitivity analysis on sample simulation data, parameters related to vehicle performance can be identified, and the relevance and type of these parameters can be verified through wind tunnel simulation; this process provides important data support for vehicle design and optimization, helping to improve performance and efficiency.

[0069] In the embodiment of the present application, an initial simulation model of the target vehicle is determined according to the geometric data of the target vehicle and the historical wind tunnel simulation results; road surface simulation parameters and road surface simulation conditions are set for the initial simulation model to obtain a candidate simulation model of the target vehicle; the collected sample simulation data of the target vehicle is input into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle; the vehicle performance data is compared with the wind tunnel simulation data for consistency to obtain performance comparison data; the candidate simulation model is adjusted according to the performance comparison data and the vehicle dynamic data to obtain the target simulation model. Through the above technical solution, on the basis of wind tunnel simulation, the real road surface conditions are fully considered, and the establishment of the wind tunnel simulation model of the vehicle on the open road surface is realized.

[0070] Embodiment III

[0071] Figure 3 FIG. is a schematic structural diagram of a vehicle wind tunnel simulation model establishment device provided according to Embodiment III of the present application, which is applicable to the situation of establishing a simulation model for the wind tunnel test of a vehicle on an open road surface. The vehicle wind tunnel simulation model establishment device can be implemented in the form of hardware and / or software, and the vehicle wind tunnel simulation model establishment device can be configured in a computer device, such as a server. As Figure 3 shown, the device includes:

[0072] The first model construction module 310 is used to determine an initial simulation model of the target vehicle according to the geometric data of the target vehicle and the historical wind tunnel simulation results;

[0073] The second model construction module 320 is used to set road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle;

[0074] The model simulation module 330 is used to input the collected sample simulation data of the target vehicle into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle;

[0075] The model adjustment module 340 is used to adjust the candidate simulation model according to the measured wind tunnel data and the wind tunnel simulation data to obtain the target simulation model; the measured wind tunnel data is collected during the actual driving process of the target vehicle.

[0076] In an embodiment of the present application, an initial simulation model of a target vehicle is determined according to the geometric data of the target vehicle and historical wind tunnel simulation results; road surface simulation parameters and road surface simulation conditions are set for the initial simulation model to obtain a candidate simulation model of the target vehicle; the collected sample simulation data of the target vehicle is input into the candidate simulation model to obtain wind tunnel simulation data of the target vehicle; the candidate simulation model is adjusted according to the wind tunnel measured data and the wind tunnel simulation data to obtain a target simulation model; the wind tunnel measured data is collected during the actual driving process of the target vehicle. Through the above technical solution, based on the wind tunnel simulation, the real road surface conditions are fully considered, and the establishment of the wind tunnel simulation model of the vehicle on the open road surface is realized.

[0077] Optionally, the wind tunnel measured data includes the vehicle performance data and vehicle dynamic data of the target vehicle; correspondingly, the model adjustment module 340 includes:

[0078] A data comparison unit for comparing the consistency of the vehicle performance data and the wind tunnel simulation data to obtain performance comparison data;

[0079] A model adjustment unit for adjusting the candidate simulation model according to the performance comparison data and the vehicle dynamic data to obtain a target simulation model.

[0080] Optionally, the model adjustment unit includes:

[0081] A data analysis subunit for performing sensitivity analysis on the sample simulation data according to the performance comparison data and the vehicle dynamic data to obtain the correlation parameters of the candidate simulation model and the parameter weights corresponding to the correlation parameters;

[0082] A model adjustment subunit for adjusting the candidate simulation model according to the correlation parameters and the parameter weights to obtain a target simulation model.

[0083] Optionally, the model adjustment subunit is specifically used for:

[0084] Sort the parameter weights and determine the correlation parameters with the front parameter weights as the target parameters;

[0085] Determine the parameter type of the target parameter, and based on the correspondence between the parameter type and the adjustment method, determine the target adjustment method of the target parameter according to the parameter type;

[0086] Based on the target adjustment method, adjust the target parameter in the candidate simulation model to obtain a target simulation model.

[0087] Optionally, the data analysis subunit is specifically used for:

[0088] Based on the performance comparison data and vehicle dynamic data, a correlation verification is performed on the vehicle parameters in the sample simulation data for wind tunnel simulation, and the vehicle parameters that pass the correlation verification of wind tunnel simulation are determined as correlation parameters;

[0089] Perform a positive correlation verification on the correlation parameters for the wind tunnel simulation data to obtain the parameter types of the correlation parameters.

[0090] Optionally, the data analysis subunit is specifically configured to:

[0091] Determine the parameter types of the correlation parameters that pass the positive correlation verification of the wind tunnel simulation data as positive correlation parameters;

[0092] Determine the parameter types of the correlation parameters that do not pass the positive correlation verification of the wind tunnel simulation data as negative correlation parameters.

[0093] Optionally, the device further includes a model verification module, and the model verification module is configured to:

[0094] After adjusting the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model, perform an accuracy verification on the target simulation model, and if the accuracy verification fails, re-determine the wind tunnel simulation data of the target vehicle.

[0095] The vehicle wind tunnel simulation model establishment device provided by the embodiments of the present application can execute the vehicle wind tunnel simulation model establishment method provided by any embodiment of the present application, and has the corresponding functional modules and beneficial effects for executing each vehicle wind tunnel simulation model establishment method.

[0096] Embodiment 4

[0097] Figure 4 It is a schematic structural diagram of an electronic device 410 that implements the vehicle wind tunnel simulation model establishment method of the embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0098] Such as Figure 4As shown, the electronic device 410 includes at least one processor 411 and a memory communicatively connected to the at least one processor 411, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc. The memory stores a computer program executable by the at least one processor. The processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 into the random access memory (RAM) 413. In the RAM 413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, the ROM 412, and the RAM 413 are connected to each other via a bus 414. The input / output (I / O) interface 415 is also connected to the bus 414.

[0099] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a magnetic disk, an optical disc, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0100] The processor 411 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as the method for establishing a vehicle wind tunnel simulation model.

[0101] In some embodiments, the method for establishing a vehicle wind tunnel simulation model can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 418. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the method for establishing a vehicle wind tunnel simulation model described above can be executed. Alternatively, in other embodiments, the processor 411 can be configured for the method for establishing a vehicle wind tunnel simulation model by any other appropriate means (such as, by means of firmware).

[0102] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0103] The computer programs for implementing the methods of this application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable apparatus for vehicle wind tunnel simulation model establishment, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer program can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0104] In the context of this application, a computer-readable storage medium can be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. A more specific example of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0105] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0106] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0107] The computing system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0108] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this application can be achieved, and this is not limited herein.

[0109] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims

1. A method for establishing a vehicle wind tunnel simulation model, characterized in that, include: Determining an initial simulation model of the target vehicle based on geometric data of the target vehicle and historical wind tunnel simulation results; Setting road simulation parameters and road simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle; wherein the boundary condition of the candidate simulation model is greater than the wind tunnel size; Inputting the collected sample simulation data of the target vehicle into the candidate simulation model to obtain wind tunnel simulation data of the target vehicle; wherein the sample simulation data includes wind resistance simulation data and actual test data of the target vehicle under different open road conditions; According to wind tunnel measured data and the wind tunnel simulation data, the candidate simulation model is adjusted to obtain a target simulation model; the wind tunnel measured data is collected during the actual driving of the target vehicle; the wind tunnel measured data includes vehicle performance data and vehicle dynamic data of the target vehicle; The candidate simulation model is adjusted according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model, including: Comparing the vehicle performance data with the wind tunnel simulation data for consistency to obtain performance comparison data; According to the performance comparison data and the vehicle dynamic data, the candidate simulation model is adjusted to obtain a target simulation model; The step of adjusting the candidate simulation model according to the performance comparison data and the vehicle dynamic data to obtain a target simulation model includes: Performing sensitivity analysis on the sample simulation data according to the performance comparison data and the vehicle dynamic data to obtain correlation parameters of the candidate simulation model and parameter weights corresponding to the correlation parameters; The candidate simulation model is adjusted according to the correlation parameter and the parameter weight to obtain a target simulation model.

2. The method according to claim 1, wherein The step of adjusting the candidate simulation model according to the correlation parameter and the parameter weight to obtain a target simulation model includes: Sorting the parameter weights, and determining the correlation parameters with the highest parameter weights as target parameters; Determining a parameter type of the target parameter, and based on a correspondence between the parameter type and the adjustment method, determining a target adjustment method of the target parameter according to the parameter type; Based on the target adjustment method, the target parameters in the candidate simulation model are adjusted to obtain a target simulation model.

3. The method according to claim 1, characterized in that, According to the performance comparison data and the vehicle dynamic data, a sensitivity analysis is performed on the sample simulation data to obtain correlation parameters of the candidate simulation model, including: According to the performance comparison data and the vehicle dynamic data, performing wind tunnel simulation correlation verification on the vehicle parameters in the sample simulation data, and determining the vehicle parameters that pass the wind tunnel simulation correlation verification as correlation parameters; A positive correlation verification of wind tunnel simulation data is performed on the correlation parameter to obtain a parameter type of the correlation parameter.

4. The method according to claim 3, wherein The correlation parameter is verified by positive correlation of wind tunnel simulation data to obtain parameter types of the correlation parameter, including: Determine the parameter type of the correlation parameter verified by the positive correlation of the wind tunnel simulation data as a positive correlation parameter; Determine the parameter type of the correlation parameter that fails to pass the positive correlation verification of the wind tunnel simulation data as a negative correlation parameter.

5. The method according to claim 1, characterized in that After adjusting the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain the target simulation model, it further includes: Verify the accuracy of the target simulation model, and if the accuracy verification fails, re-determine the wind tunnel simulation data of the target vehicle.

6. An apparatus for establishing a vehicle wind tunnel simulation model, characterized in that, It includes: A first model construction module for determining an initial simulation model of the target vehicle according to the geometric data of the target vehicle and historical wind tunnel simulation results; A second model construction module for setting road surface simulation parameters and road surface simulation conditions for the initial simulation model to obtain a candidate simulation model of the target vehicle; wherein, the boundary conditions of the candidate simulation model are larger than the wind tunnel size; A model simulation module for inputting the sample simulation data of the target vehicle collected into the candidate simulation model to obtain the wind tunnel simulation data of the target vehicle; wherein, the sample simulation data includes wind resistance simulation data and actual test data of the target vehicle under different open road surface conditions; A model adjustment module for adjusting the candidate simulation model according to the wind tunnel measured data and the wind tunnel simulation data to obtain a target simulation model; the wind tunnel measured data is collected during the actual driving of the target vehicle; the wind tunnel measured data includes the vehicle performance data and vehicle dynamic data of the target vehicle; Wherein, the model adjustment module includes: A data comparison unit for comparing the vehicle performance data with the wind tunnel simulation data for consistency comparison to obtain performance comparison data; A model adjustment unit for adjusting the candidate simulation model according to the performance comparison data and the vehicle dynamic data to obtain a target simulation model; Wherein, the model adjustment unit includes: A data analysis sub-unit for performing sensitivity analysis on the sample simulation data according to the performance comparison data and the vehicle dynamic data to obtain the correlation parameters of the candidate simulation model and the parameter weights corresponding to the correlation parameters; A model adjustment sub-unit for adjusting the candidate simulation model according to the correlation parameters and the parameter weights to obtain a target simulation model.

7. An electronic device, characterized in that, It includes: One or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle wind tunnel simulation model establishment method according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the vehicle wind tunnel simulation model establishment method according to any one of claims 1-5.

9. A computer program product, including a computer program, the computer program when executed by a processor implements the vehicle wind tunnel simulation model establishment method according to any one of claims 1-5.

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