Method and device for testing automobile air suspension control model

Abstract

The invention relates to the technical field of automobile model testing, in particular to a testing method and device for an automobile air suspension control model. The method comprises the following steps: acquiring external parameter data and control feedback data of a real vehicle, wherein the external parameter data comprises vehicle condition data, road condition data and vehicle hardware design parameters; converting the external parameter data and the control feedback data into an application format adapted to the model in-loop test, and taking the external parameter data and the control feedback data after format conversion as input data of the control model to be tested; in the testing process, testing result data of a real vehicle are collected; and replacing the control feedback data with test result data, taking the external parameter data and the test result data as input data of the to-be-tested control model, and replacing the vehicle model with a real vehicle to perform model in-loop test on the to-be-tested control model. By adopting the method, the model in-loop test accuracy of the control model of the automobile air suspension can be improved.

Description

Technical Field

[0001] This application relates to the technical field of automotive model testing, and particularly to a method and device for testing an automotive air suspension control model. Background Art

[0002] In the design of automobiles, for some high-quality automobiles, which need to consider both the comfort of sedans and the passing performance of off-road vehicles, an air suspension is generally installed on the chassis. According to different requirements, the air suspension can adjust the ground clearance of the chassis.

[0003] In the development stage, for the model-in-the-loop (MIL) test of the control model of the automotive air suspension, it is difficult to build the vehicle model. It is very difficult to accurately describe the actuators such as shock absorbers and air springs included in the air suspension with physical formulas due to the influence of vehicle installation deviation and bushing factors. However, for the air suspension control model, it involves height sensors, acceleration sensors, and road spectrum signals. These signals have strong coordination and dependence. Assigning values based on experience cannot guarantee the accuracy of the signals and will affect the test results.

[0004] Therefore, there is an urgent need for a method and device for testing an automotive air suspension control model to improve the accuracy of the model-in-the-loop test of the automotive air suspension control model. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method and device for testing an automotive air suspension control model that can improve the accuracy of the model-in-the-loop test of the automotive air suspension control model.

[0006] In a first aspect, this application provides a method for testing an automotive air suspension control model, including:

[0007] Obtain the external parameter data and control feedback data of the real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0008] Convert the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and the control feedback data after the conversion format as the input data of the control model to be tested;

[0009] During the test, collect the test result data of the real vehicle;

[0010] Replace the control feedback data with the test result data, use the external parameter data and the test result data as the input data of the control model to be tested, and use the real vehicle to replace the vehicle model to perform a model-in-the-loop test on the control model to be tested.

[0011] In one embodiment, the storage formats of the external parameter data, the control feedback data, and the test result data are all Mf4 format files. The conversion of the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing includes:

[0012] Select a data channel for reading the Mf4 format file, and read the corresponding Mf4 format file through the selected data channel;

[0013] According to the Mf4 format file, obtain the parameter names and parameter values corresponding to different test parameters;

[0014] Construct a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters;

[0015] Obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested;

[0016] Import the target test parameter data table into the control model to be tested.

[0017] In one embodiment, after obtaining the target test parameter data table of the control model to be tested by performing screening according to the target test parameters and the vehicle test parameter data table, it further includes:

[0018] Obtain the historical import data of the control model to be tested;

[0019] In the case where it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0020] In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screen according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0021] In one embodiment, the import of the target test parameter data table into the control model to be tested includes:

[0022] According to the preset calibration parameters, convert the target test parameter data table into a program code file suitable for MATLAB language;

[0023] Import the program code file into the control model to be tested.

[0024] In one embodiment, the method further includes:

[0025] Run the program code file to obtain a set of workspace parameters, where the set of workspace parameters includes the parameter names and parameter values of at least one test parameter;

[0026] Obtain the data dictionary in the test environment of the model-in-the-loop test;

[0027] Traverse the parameter names in the workspace dataset, and when there is the same parameter name in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain the data dictionary after assignment;

[0028] Perform a model-in-the-loop test on the to-be-tested control model according to the data dictionary after assignment and the external parameter data.

[0029] In one embodiment, the method further includes:

[0030] Traverse the parameter names in the workspace dataset, and when there is no same parameter name in the data dictionary, delete the parameter names and parameter values in the workspace dataset.

[0031] In a second aspect, the present application further provides a test device for an automotive air suspension control model, including:

[0032] A data acquisition module, configured to acquire external parameter data and control feedback data of a real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0033] A model test module, configured to convert the external parameter data and the control feedback data into an application format suitable for a model-in-the-loop test, and use the external parameter data and the control feedback data after the conversion format as input data of the to-be-tested control model;

[0034] The data acquisition module is further configured to collect the test result data of the real vehicle during the test;

[0035] The model test module is further configured to replace the control feedback data with the test result data, use the external parameter data and the test result data as input data of the to-be-tested control model, and perform a model-in-the-loop test on the to-be-tested control model by using a real vehicle to replace the vehicle model.

[0036] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0037] Obtain external parameter data and control feedback data of a real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0038] Convert the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and the control feedback data after the conversion format as the input data for the control model to be tested.

[0039] During the testing process, collect the test result data of the actual vehicle.

[0040] Replace the control feedback data with the test result data, use the external parameter data and the test result data as the input data for the control model to be tested, and use the actual vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0041] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0042] Obtain the external parameter data and control feedback data of the actual vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0043] Convert the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and the control feedback data after the conversion format as the input data for the control model to be tested.

[0044] During the testing process, collect the test result data of the actual vehicle.

[0045] Replace the control feedback data with the test result data, use the external parameter data and the test result data as the input data for the control model to be tested, and use the actual vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0046] In a fifth aspect, the present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0047] Obtain the external parameter data and control feedback data of the actual vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0048] Convert the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and the control feedback data after the conversion format as the input data for the control model to be tested.

[0049] During the testing process, collect the test result data of the actual vehicle.

[0050] Replace the control feedback data with the test result data, use the external parameter data and the test result data as the input data of the control model to be tested, and use an actual vehicle to replace the vehicle model to perform a model-in-the-loop test on the control model to be tested.

[0051] The above-mentioned test method and device for an automotive air suspension control model can more accurately simulate actual scenarios and conditions by using an actual vehicle to replace the vehicle model and using the external parameter data of the vehicle as input data, thereby improving the accuracy of the test. During the test, the test result data of the actual vehicle is collected and imported into the control model to be tested, and a model-in-the-loop test is performed in combination with the external parameter data. In this way, the true performance and data of the actual vehicle can be obtained, and the parameters of the control model can be adjusted during the test to achieve the desired output result, making the test result more reliable. By using the external parameter data and test result data of the actual vehicle to perform a model-in-the-loop test, the accuracy and precision of the control model to be tested can be better verified and corrected, and the model can be further improved and optimized. In summary, the test method and device for the automotive air suspension control model can improve the accuracy of the model-in-the-loop test of the air suspension control model, increase data reliability, and improve model precision. Description of the Drawings

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0053] Figure 1 It is an application environment diagram of the test method for an automotive air suspension control model in an embodiment;

[0054] Figure 2 It is a schematic flowchart of the test method for an automotive air suspension control model in an embodiment;

[0055] Figure 3 It is a working principle diagram of a model-in-the-loop test in an embodiment;

[0056] Figure 4 It is a schematic flowchart of the test method for an automotive air suspension control model in another embodiment;

[0057] Figure 5 It is a structural block diagram of the test device for an automotive air suspension control model in an embodiment;

[0058] Figure 6 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0059] In order to make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the following further elaborates on the present application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely used to explain the present application and are not used to limit the present application.

[0060] The test method for the automotive air suspension control model provided by the embodiments of the present application can be applied to an application environment as Figure 1 shown. Among them, the terminal 102 communicates with the server 104 through a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed in the cloud or on other network servers.

[0061] The server 104 obtains the external parameter data and control feedback data of the real vehicle. The external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters; converts the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and uses the external parameter data and control feedback data after the conversion format as the input data of the control model to be tested; during the testing process, collects the test result data of the real vehicle; replaces the control feedback data with the test result data, uses the external parameter data and test result data as the input data of the control model to be tested, and uses the real vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0062] Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0063] In an exemplary embodiment, as Figure 2 shown, a test method for an automotive air suspension control model is provided. Taking the method applied to the Figure 1 server in it as an example for description, it includes the following steps S202 to step S208. Among them:

[0064] Step S202, obtain the external parameter data and control feedback data of the real vehicle. The external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters.

[0065] Among them, the vehicle condition data refers to the state parameters of the vehicle itself. For example, the steering wheel angle, driving and braking torque, driving mode (suspension softness and hardness) selected by the driver, vehicle mass, suspension system state, etc. These data reflect the current state and operating conditions of the vehicle and are very important for the testing of the suspension control model.

[0066] The road condition data refers to the road environment information where the vehicle travels. For example, the unevenness of the road surface, slope, curve radius, road surface friction coefficient, etc. These data describe the road conditions where the vehicle is located and also have an important impact on the testing of the suspension control model.

[0067] The vehicle hardware design parameters refer to the chassis parameters, and in this application, mainly refer to the suspension hardware parameters. For example, the unsprung mass of the front and rear suspensions, the designed height of the air spring in different height modes, the height sensor parameters, the shock absorber characteristic parameters, etc. These parameters determine the handling performance, stability, and smoothness effect of the vehicle. Tire parameters: including tire type, size, tire pressure, etc. These parameters determine the grip of the vehicle, driving comfort, and the working state of the suspension system. Body parameters: including body structure, nominal load, wheelbase and track width, sensor installation position. These parameters determine the aerodynamic performance, stability, and body motion posture of the vehicle.

[0068] Obtaining these external parameter data is for more accurate testing of the suspension control model. By replacing the abstract vehicle model with a real vehicle, compared with using a vehicle model for suspension control testing in traditional technologies, using the real vehicle condition data, road condition data, and vehicle hardware design parameters of a real vehicle can better simulate the actual driving environment and use these data as inputs for model testing. Among them, the real vehicle external parameter data and control feedback data can provide more accurate and reliable inputs, thus making the test results of the suspension control model more accurate and reliable. Compared with the abstract vehicle model, real vehicle data can better reflect the behavior and response of the vehicle during actual driving. This can more accurately test the performance of the suspension control model under real road conditions, discover potential problems, and improve the performance of the suspension control model.

[0069] The control feedback data includes control response results. For example, the lateral, longitudinal, and vertical speeds and accelerations of the body, the roll, pitch, and roll angles and angular velocities of the body, the vertical displacements of the four wheels, the actual current of the shock absorber, etc.

[0070] Step S204, convert the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and control feedback data after the conversion format as the input data for the control model to be tested.

[0071] Among them, the collected data is subjected to format conversion to make it meet the input requirements of the control model to be tested. This may involve converting data from different units to standard units, or converting data from different data types to the data types required by the model.

[0072] Specifically, in traditional model-in-the-loop testing, abstract mathematical models or simulation models are often used as input data. However, this method may not be able to fully and accurately simulate the actual driving environment. Therefore, this method uses a real vehicle instead of an abstract model, takes the external parameter data of the vehicle as input, and improves the accuracy of the test. By using a real vehicle, the real situations and conditions in the actual driving process can be better simulated. The input data of the real vehicle is transmitted into the control model to be tested to simulate the real-time suspension control process, so as to conduct model-in-the-loop testing. In this way, the performance and capabilities of the control model to be tested under actual driving conditions can be evaluated more accurately.

[0073] Through this method, model-in-the-loop testing can be carried out more accurately, improving the reliability and practicality of the test. At the same time, by using a real vehicle for testing, the real responses and data of the real vehicle can be obtained, providing important references for further model optimization and improvement.

[0074] Step S206, during the test, collect the test result data of the real vehicle.

[0075] Specifically, CANape (CAN Application Programming Environment) is a comprehensive tool software for ECU measurement, calibration, diagnosis, and data recording verification. It can collect various signals and data of the vehicle in real time by connecting to the CAN bus on the vehicle. Therefore, during the test, CANape can be used to collect relevant data of the real vehicle during the suspension control test, such as sensor data, suspension system status, etc.

[0076] Specifically, the data collected by CANape can be imported into the control model to be tested as the input or reference data of the model. In this way, the real test results of the real vehicle can be compared and verified with the prediction results of the model to evaluate the accuracy and performance of the model. Using CANape to collect the test result data of the real vehicle and importing the data into the control model to be tested can provide more real and reliable test results. The data collected by the data acquisition device during the actual driving process of the vehicle can reflect the changes in the vehicle suspension height, vehicle speed, and lateral and longitudinal accelerations with the road surface and driver operations. By comparing with the data of the real vehicle, the performance of the control model to be tested can be evaluated and verified more accurately. This can help developers optimize and improve the model to make it more suitable for the actual suspension control requirements.

[0077] Step S208: Replace the control feedback data with the test result data, use the external parameter data and the test result data as the input data for the control model to be tested, and use the real vehicle to replace the vehicle model to perform the model-in-the-loop test on the control model to be tested.

[0078] Specifically, as Figure 3 shown, first, it is necessary to obtain the test result data collected during the suspension control test of the real vehicle. These data include the sensor data of the vehicle, such as the lateral, longitudinal, and vertical speeds and accelerations of the vehicle body, the roll, pitch, and roll angles and angular velocities of the vehicle body, the vertical displacements of the four wheels, the actual current of the shock absorber, etc. At the same time, it is necessary to obtain the external parameter data related to the real vehicle test environment. These data will be used to simulate the actual driving situation. Import the above test result data and external parameter data into the control model to be tested as the input data of the model. In this way, the model can obtain the real vehicle state and environmental information from the outside and simulate the actual driving situation. Use the control model to be tested with the imported data to perform the model-in-the-loop test. The model will perform the simulation of the suspension control according to the input real vehicle state and environmental information. Then, the output result of the model is compared and verified with the test result of the real vehicle. According to the comparison between the output result of the model and the test result of the real vehicle, evaluate the performance of the control model to be tested. The accuracy, stability, response time and other indicators of the model can be analyzed to judge whether the model meets the design and test requirements.

[0079] In the above test method of the automotive air suspension control model, by using the real vehicle to replace the vehicle model and using the external parameter data of the vehicle as the input data, the actual scenario and conditions can be simulated more accurately, thereby improving the accuracy of the test. During the test process, collect the test result data of the real vehicle, import these data into the control model to be tested, and perform the model-in-the-loop test in combination with the external parameter data. In this way, the real performance and data of the real vehicle can be obtained, and the parameters of the control model can be adjusted during the test process to achieve the expected output result, making the test result more reliable. By using the external parameter data and test result data of the real vehicle to perform the model-in-the-loop test, the accuracy and precision of the control model to be tested can be better verified and corrected, and the model can be further improved and optimized. In summary, the test method and device of the automotive air suspension control model can improve the accuracy of the model-in-the-loop test of the air suspension control model, increase the data reliability, and improve the model accuracy.

[0080] In one of the embodiments, as Figure 4 shown, the storage formats of the external parameter data, the control feedback data, and the test result data are all Mf4 format files. Convert the external parameter data and the control feedback data into an application format suitable for the model-in-the-loop test, including:

[0081] Step S402: Select the data channel for reading the Mf4 format file, and read the corresponding Mf4 format file through the selected data channel.

[0082] Step S404: Obtain the parameter names and parameter values corresponding to different test parameters according to the Mf4 format file.

[0083] Step S406: Construct a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters.

[0084] Step S408: Obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0085] Step S410: Import the target test parameter data table into the control model to be tested.

[0086] Specifically, according to the need, select the data channels in the Mf4 format file, and these data channels correspond to different test parameters. The channels to be read can be determined by the name or index of the data channel. Use the corresponding program or software library (such as the Mdf function of the MATLAB programming language) to read the Mf4 format file corresponding to the selected data channel in CANape, and the sampling period can be 2 ms. Read according to the selected channels to obtain the corresponding test result data. According to the structure and tag information of the Mf4 format file, parse the test parameter names and corresponding parameter values corresponding to the specific channels in the file. In this way, the mapping relationship between the parameter names and parameter values can be established. According to the parsed parameter names and parameter values, construct a vehicle test parameter data table, where the column names are different test parameter names and each row is the corresponding parameter value. Determine the target test parameters concerned by the control model to be tested, which can be specific parameter names or parameter properties. According to these target test parameters, screen the corresponding parameter values in the vehicle test parameter data table. According to the screened target test parameter values, construct a target test parameter data table, where the column names are the target test parameter names and each row is the corresponding parameter value. This target test parameter data table is in excel format and can be recognized by simulink. Import the data in the target test parameter data table into the control model to be tested as the input of the model. In this way, the model can use these parameter values for testing and simulation to evaluate the performance and accuracy of the model.

[0087] In this embodiment, by selecting an appropriate data channel according to requirements, reading the Mf4 format file, extracting the required data, and parsing the names and corresponding values of different test parameters in the Mf4 format file. The parsed parameter names and values are combined into a vehicle test parameter data table. According to the target test parameters of the control model to be tested, relevant parameters and their values are screened out from the vehicle test parameter data table. The screened target test parameter data table is imported into the control model to be tested as the input data of the model. This helps to extract and manage the test parameter data in the Mf4 format file and effectively import this data into the control model to be tested for verification and evaluation. In this way, an automated parameter data processing and model testing process can be achieved, improving work efficiency and accuracy.

[0088] In one embodiment, after screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested, it further includes:

[0089] Obtain the historical import data of the control model to be tested;

[0090] In the case where it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0091] In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screen according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0092] Specifically, obtain the historical import data of the control model to be tested from a database or other data storage. These data will include the previously imported target test parameter data table and other relevant records. Check whether the target test parameter data table has been established according to the historical import data. If the target test parameter data table has been imported previously, delete the currently obtained target test parameter data table and re-obtain the target test parameter data table; if not, import the data screened according to the target test parameters and the vehicle test parameter data table into the control model to be tested as a new target test parameter data table. At the same time, pop up a prompt message to inform the user that the import is completed.

[0093] In this embodiment, after screening according to the target test parameters and the vehicle test parameter data table, the target test parameter data table of the control model to be tested can be obtained, and corresponding processing and notifications are carried out according to different situations of the historical import data. This can ensure that the latest target test parameter data is obtained and imported into the control model to be tested for use.

[0094] In one embodiment, importing the target test parameter data table into the control model to be tested includes:

[0095] Convert the target test parameter data table into a program code file suitable for the MATLAB language according to the preset calibration parameters; import the program code file into the control model to be tested.

[0096] Specifically, convert the data in the target test parameter data table into a program code file suitable for the MATLAB language according to the preset calibration parameters. This can be achieved using a script or programming language to convert the parameters and corresponding values in the target test parameter data table into variables and assignment statements in MATLAB code. Import the generated MATLAB program code file into the control model to be tested. This can be achieved through a file import function or by referencing the program code file in the relevant source files of the control model to be tested. After import, the variables and assignment statements defined in the program code file will be applied during the operation of the control model to be tested.

[0097] In this embodiment, the target test parameter data table can be converted into a MATLAB program code file according to the preset calibration parameters, and then this file is imported into the control model to be tested. In this way, the target test parameters can be applied to the control model to be tested, enabling it to use these parameters for testing and evaluation during operation.

[0098] In one of the embodiments, the method further includes:

[0099] Run the program code file to obtain a set of workspace parameters, where the set of workspace parameters includes the parameter names and parameter values of at least one test parameter;

[0100] Obtain the data dictionary in the test environment of the model-in-the-loop test;

[0101] Traverse the parameter names in the workspace data set, and when there is the same parameter name in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain the data dictionary after assignment;

[0102] Perform a model-in-the-loop test on the control model to be tested according to the data dictionary after assignment and the external parameter data.

[0103] Specifically, executing the program code file can load the set of workspace parameters defined therein into the MATLAB workspace. These parameters will be stored as variables in the workspace and have corresponding parameter names and parameter values. In the test environment of the model-in-the-loop test, obtain the corresponding data dictionary. The data dictionary contains all the parameters required for the model to run and their corresponding values. This data dictionary can be a data structure stored in a file or a data structure directly defined in the test environment. Traverse each parameter name in the workspace parameter set and check if there is the same parameter name in the data dictionary. If there is the same parameter name (such as acceleration), then assign the corresponding test parameter in the data dictionary (such as 0.5 m / s 2 ), so that it is consistent with the parameter value in the workspace parameter set.

[0104] After completing the parameter assignment, obtain the data dictionary after assignment. This data dictionary will contain all the parameters required for the model to run and the parameter values after assignment. Combine the data dictionary after assignment with the external parameter data to provide the complete test environment parameters. Then, use these parameters to conduct the model-in-the-loop test. This may involve steps such as loading the model, running test cases, and obtaining test results to evaluate the performance and functionality of the control model under test.

[0105] In this embodiment, the program code file can be run to obtain the set of workspace parameters, then obtain the data dictionary for the model-in-the-loop test, and assign the parameters in the workspace parameter set to the test parameters in the data dictionary. Finally, use the data dictionary after assignment and the external parameter data to conduct the model-in-the-loop test. This can comprehensively test and evaluate the control model under test.

[0106] In one of the embodiments, the method further includes:

[0107] Traverse the parameter names in the workspace data set. In the case where there is no same parameter name in the data dictionary, delete the parameter name and parameter value in the workspace data set.

[0108] Specifically, traverse each parameter name in the workspace data set. For each parameter name in the workspace data set, check in the data dictionary to see if there is the same parameter name. If the workspace parameter name does not exist in the data dictionary, that is, the parameter name cannot find the corresponding parameter in the data dictionary, delete the parameter name and parameter value in the workspace data set. This can be achieved by deleting the corresponding variable from the workspace or setting its value to null or empty, depending on the programming language and environment used. Then, conduct the model-in-the-loop test according to the data dictionary.

[0109] In this embodiment, when traversing the parameter names in the workspace parameter set, it is possible to check whether they exist in the data dictionary, and delete the parameter names and parameter values of the workspace parameter set when the same parameter names do not exist in the data dictionary. This can ensure the consistency and accuracy of the data, thus better performing the model-in-the-loop test. Please ensure that when performing the deletion operation, carefully consider its impact on subsequent test steps and model performance.

[0110] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0111] Based on the same inventive concept, an embodiment of the present application further provides a test device for an automotive air suspension control model for implementing the above-mentioned test method for an automotive air suspension control model. The solution provided by this device for solving problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the test device for an automotive air suspension control model provided below can refer to the limitations on the test method for an automotive air suspension control model in the above text, and will not be repeated here.

[0112] In an exemplary embodiment, as Figure 5 shown, a test device for an automotive air suspension control model is provided, including:

[0113] A data acquisition module 502, configured to acquire external parameter data and control feedback data of a real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0114] A model test module 504, configured to convert the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and control feedback data after the conversion format as input data for the control model to be tested;

[0115] The data acquisition module 502 is further configured to collect test result data of the real vehicle during the test;

[0116] The model test module 504 is further configured to replace the control feedback data with test result data, use the external parameter data and the test result data as the input data of the control model to be tested, and use an actual vehicle to replace the vehicle model to perform a model-in-the-loop test on the control model to be tested.

[0117] In one embodiment, the storage formats of the external parameter data, the control feedback data, and the test result data are all Mf4 format files. The data acquisition module 502 is further configured to select a data channel for reading the Mf4 format file, and read the corresponding Mf4 format file through the selected data channel;

[0118] The data acquisition module 502 is further configured to obtain the parameter names and parameter values corresponding to different test parameters according to the Mf4 format file;

[0119] The data acquisition module 502 is further configured to construct a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters;

[0120] The data acquisition module 502 is further configured to obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested;

[0121] The data acquisition module 502 is further configured to import the target test parameter data table into the control model to be tested.

[0122] In one embodiment, the data acquisition module 502 is further configured to obtain the historical import data of the control model to be tested;

[0123] The data acquisition module 502 is further configured to, when it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0124] The data acquisition module 502 is further configured to, when it is determined according to the historical import data that the target test parameter data table has been established, re-perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0125] In one embodiment, the data acquisition module 502 is further configured to convert the target test parameter data table into a program code file applicable to the MATLAB language according to the preset calibration parameters;

[0126] The data acquisition module 502 is further configured to import the program code file into the control model to be tested.

[0127] In one embodiment, the model testing module 504 is further configured to run a program code file to obtain a set of workspace parameters, where the set of workspace parameters includes the parameter names and parameter values of at least one test parameter;

[0128] The data acquisition module 502 is further configured to obtain a data dictionary in the test environment of the model-in-the-loop test;

[0129] The data acquisition module 502 is further configured to traverse the parameter names of the workspace data set, and when the same parameter name exists in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain an assigned data dictionary;

[0130] The model testing module 504 is further configured to perform a model-in-the-loop test on the control model to be tested according to the assigned data dictionary and the external parameter data.

[0131] In one embodiment, the data acquisition module 502 is further configured to traverse the parameter names of the workspace data set, and when the same parameter name does not exist in the data dictionary, delete the parameter names and parameter values of the workspace data set.

[0132] Each module in the above test device for the vehicle air suspension control model can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0133] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the external parameter data and test result data of the vehicle. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a test method for a vehicle air suspension control model.

[0134] Those skilled in the art can understand that Figure 6 The structure shown in Figure 6 is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0135] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0136] Obtain the external parameter data and control feedback data of the real vehicle. The external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0137] Convert the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and control feedback data after the conversion format as the input data of the control model to be tested;

[0138] During the testing process, collect the test result data of the real vehicle;

[0139] Replace the control feedback data with the test result data, use the external parameter data and test result data as the input data of the control model to be tested, and use the real vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0140] In an embodiment, when the processor executes the computer program, the following steps are further implemented:

[0141] The storage formats of the external parameter data, control feedback data, and test result data are all Mf4 format files. Converting the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing includes:

[0142] Select the data channels for reading the Mf4 format files, and read the corresponding Mf4 format files through the selected data channels;

[0143] According to the Mf4 format files, obtain the parameter names and parameter values corresponding to different test parameters;

[0144] Construct a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters;

[0145] Obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested;

[0146] Import the target test parameter data table into the control model to be tested.

[0147] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0148] After screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested, the following steps are further included:

[0149] Obtain the historical import data of the control model to be tested;

[0150] In the case where it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0151] In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screen according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0152] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0153] Importing the target test parameter data table into the control model to be tested includes:

[0154] According to the preset calibration parameters, convert the target test parameter data table into a program code file suitable for MATLAB language;

[0155] Import the program code file into the control model to be tested.

[0156] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0157] Run the program code file to obtain the workspace parameter set, and the workspace parameter set includes the parameter names and parameter values of at least one test parameter;

[0158] Obtain the data dictionary in the test environment of the model-in-the-loop test;

[0159] Traverse the parameter names in the workspace data set, and in the case where the same parameter name exists in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain the data dictionary after assignment;

[0160] According to the data dictionary after assignment and the external parameter data, perform a model-in-the-loop test on the control model to be tested.

[0161] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0162] Traverse the parameter names of the workspace dataset, and delete the parameter names and parameter values of the workspace dataset if the same parameter names do not exist in the data dictionary.

[0163] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0164] Obtain the external parameter data and control feedback data of the actual vehicle. The external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0165] Convert the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and control feedback data after the conversion format as the input data of the control model to be tested.

[0166] During the testing process, collect the test result data of the actual vehicle;

[0167] Replace the control feedback data with the test result data, use the external parameter data and test result data as the input data of the control model to be tested, and use the actual vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0168] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0169] The storage formats of the external parameter data, control feedback data, and test result data are all Mf4 format files. Converting the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing includes:

[0170] Select the data channels for reading the Mf4 format files, and read the corresponding Mf4 format files through the selected data channels;

[0171] According to the Mf4 format files, obtain the parameter names and parameter values corresponding to different test parameters;

[0172] Construct a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters;

[0173] Obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested;

[0174] Import the target test parameter data table into the control model to be tested.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0176] After screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested, it further includes:

[0177] Obtain the historical import data of the control model to be tested;

[0178] In the case where it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0179] In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screen according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0180] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0181] Import the target test parameter data table into the control model to be tested, including:

[0182] According to the preset calibration parameters, convert the target test parameter data table into a program code file suitable for MATLAB language;

[0183] Import the program code file into the control model to be tested.

[0184] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0185] Run the program code file to obtain the workspace parameter set, and the workspace parameter set includes the parameter names and parameter values of at least one test parameter;

[0186] Obtain the data dictionary in the test environment of the model-in-the-loop test;

[0187] Traverse the parameter names in the workspace data set, and in the case where the same parameter name exists in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain the data dictionary after assignment;

[0188] According to the data dictionary after assignment and the external parameter data, perform a model-in-the-loop test on the control model to be tested.

[0189] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0190] Traverse the parameter names in the workspace data set, and in the case where the same parameter name does not exist in the data dictionary, delete the parameter names and parameter values in the workspace data set.

[0191] In one embodiment, a computer program product is provided, including a computer program which, when executed by a processor, implements the following steps:

[0192] Obtain the external parameter data and control feedback data of the actual vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters;

[0193] Convert the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and control feedback data after the conversion format as the input data for the control model to be tested;

[0194] During the testing process, collect the test result data of the actual vehicle;

[0195] Replace the control feedback data with the test result data, use the external parameter data and test result data as the input data for the control model to be tested, and use the actual vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

[0196] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0197] The storage formats of the external parameter data, control feedback data, and test result data are all Mf4 format files. Converting the external parameter data and control feedback data into an application format suitable for model-in-the-loop testing includes:

[0198] Select the data channels for reading the Mf4 format files, and through the selected data channels, read the corresponding Mf4 format files;

[0199] According to the Mf4 format files, obtain the parameter names and parameter values corresponding to different test parameters;

[0200] According to the parameter names and parameter values corresponding to different test parameters, construct a vehicle test parameter data table;

[0201] Obtain the target test parameters of the control model to be tested, and perform screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested;

[0202] Import the target test parameter data table into the control model to be tested.

[0203] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0204] After obtaining the target test parameter data table of the control model to be tested by performing screening according to the target test parameters and the vehicle test parameter data table, it further includes:

[0205] Obtain the historical import data of the control model to be tested;

[0206] In the case where it is determined according to the historical import data that the target test parameter data table has not been established, import the target test parameter data table into the control model to be tested, and pop up a prompt message indicating that the import is completed;

[0207] In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screen according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

[0208] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0209] Importing the target test parameter data table into the control model to be tested includes:

[0210] According to the preset calibration parameters, convert the target test parameter data table into a program code file suitable for MATLAB language;

[0211] Import the program code file into the control model to be tested.

[0212] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0213] Run the program code file to obtain a work space parameter set, where the work space parameter set includes the parameter names and parameter values of at least one test parameter;

[0214] Obtain the data dictionary in the test environment of the model-in-the-loop test;

[0215] Traverse the parameter names in the work space data set. In the case where the same parameter name exists in the data dictionary, assign values to the corresponding test parameters in the data dictionary to obtain the data dictionary after assignment;

[0216] According to the data dictionary after assignment and the external parameter data, perform a model-in-the-loop test on the control model to be tested.

[0217] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0218] Traverse the parameter names in the work space data set. In the case where the same parameter name does not exist in the data dictionary, delete the parameter names and parameter values in the work space data set.

[0219] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0220] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0221] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0222] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A test method for an automotive air suspension control model, characterized in that, The method includes: Obtaining external parameter data and control feedback data of a real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters; Converting the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and using the external parameter data and the control feedback data after the conversion format as input data for the control model to be tested; During the testing process, collecting the test result data of the real vehicle; Replacing the control feedback data with the test result data, using the external parameter data and the test result data as input data for the control model to be tested, and using the real vehicle to replace the vehicle model to perform model-in-the-loop testing on the control model to be tested.

2. The method according to claim 1, characterized in that, The storage formats of the external parameter data, the control feedback data, and the test result data are all Mf4 format files. The conversion of the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing includes: Selecting a data channel for reading the Mf4 format file, and reading the corresponding Mf4 format file through the selected data channel; Obtaining the parameter names and parameter values corresponding to different test parameters according to the Mf4 format file; Constructing a vehicle test parameter data table according to the parameter names and parameter values corresponding to different test parameters; Obtaining the target test parameters of the control model to be tested, and screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested; Importing the target test parameter data table into the control model to be tested.

3. The method according to claim 2, wherein After obtaining the target test parameter data table of the control model to be tested by screening according to the target test parameters and the vehicle test parameter data table, it further includes: Obtaining the historical import data of the control model to be tested; In the case where it is determined according to the historical import data that the target test parameter data table has not been established, importing the target test parameter data table into the control model to be tested and popping up a prompt message indicating the import is completed; In the case where it is determined according to the historical import data that the target test parameter data table has been established, re-screening according to the target test parameters and the vehicle test parameter data table to obtain the target test parameter data table of the control model to be tested.

4. The method according to claim 2, wherein The importing of the target test parameter data table into the control model to be tested includes: Converting the target test parameter data table into a program code file suitable for MATLAB language according to preset calibration parameters; Importing the program code file into the control model to be tested.

5. The method according to claim 4, characterized in that, The method further includes: Running the program code file to obtain a work space parameter set, where the work space parameter set includes the parameter names and parameter values of at least one test parameter; Obtaining a data dictionary in the test environment of the model-in-the-loop testing; Traversing the parameter names in the work space data set, and in the case where the same parameter name exists in the data dictionary, assigning values to the corresponding test parameters in the data dictionary to obtain an assigned data dictionary; Perform a model-in-the-loop test on the to-be-tested control model according to the data dictionary after assignment and the external parameter data.

6. The method according to claim 5, wherein The method further includes: Traverse the parameter names of the workspace dataset, and delete the parameter names and parameter values of the workspace dataset if the same parameter names do not exist in the data dictionary.

7. An automotive air suspension control model device, characterized in that, The device includes: A data acquisition module, configured to acquire external parameter data and control feedback data of a real vehicle, where the external parameter data includes vehicle condition data, road condition data, and vehicle hardware design parameters; A model test module, configured to convert the external parameter data and the control feedback data into an application format suitable for model-in-the-loop testing, and use the external parameter data and the control feedback data after the conversion format as input data of the to-be-tested control model; The data acquisition module is further configured to collect the test result data of the real vehicle during the test; The model test module is further configured to replace the control feedback data with the test result data, use the external parameter data and the test result data as input data of the to-be-tested control model, and perform a model-in-the-loop test on the to-be-tested control model by using a real vehicle to replace the vehicle model.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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