Suspension test method and device based on simulation technology and computer equipment

Abstract

The invention relates to a suspension testing method and device based on a simulation technology and computer equipment. The method comprises the following steps: acquiring suspension structure data, production process information and raw material information of each suspension structure of a produced vehicle suspension, and identifying the production process and process parameter information of each suspension structure so as to generate a production digital model of each suspension structure, and based on the raw material information of each suspension structure, generating a production digital model of each suspension structure; predicting each structure parameter range of the suspension structure; based on the structure parameter range of each suspension structure and the suspension structure data, generating each sample structure model of each suspension structure, thereby generating each sample vehicle suspension model of the vehicle suspension; and collecting simulation test processes and environment demand information corresponding to each suspension test scheme, and performing simulation test processing through each sample vehicle suspension model of the vehicle suspension to obtain a suspension test result of the vehicle suspension. By adopting the method, the test efficiency and accuracy of the produced vehicle suspension can be improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a suspension testing method, device and computer equipment based on simulation technology. Background Art

[0002] During the production process of vehicle suspension, it is necessary to conduct comprehensive tests on various performances of the vehicle suspension to ensure the safety, stability, and comfort of the produced vehicle suspension. However, compared with the traditional user vehicle suspension testing method, the production vehicle suspension requires a large amount of test data and a large number of test frequencies during the suspension testing process, which often causes substantial damage to the vehicle suspension. If various performance tests are performed on each physical vehicle suspension, a large number of vehicle suspensions are often consumed, resulting in waste of resources, high testing costs, and inefficient test results. Therefore, how to improve the optimization of suspension resources and improve test efficiency when testing the production vehicle suspension is the current research focus.

[0003] The traditional method of testing the suspension of a production vehicle is to sample the vehicle suspension and then perform a variety of tests on the sampled vehicle suspension. However, when the test actually causes substantial damage to the vehicle suspension during the test, other performance tests of the vehicle suspension will be greatly affected. The accuracy of testing only part of the vehicle suspension is poor, and when a large number of vehicle suspension tests are applied, a lot of time and cost are required to test the vehicle suspension, resulting in poor testing efficiency for the suspension of production vehicles. Summary of the invention

[0004] Based on this, it is necessary to provide a suspension testing method, device, computer equipment, computer readable storage medium and computer program product based on simulation technology to address the above technical problems.

[0005] In a first aspect, the present application provides a suspension testing method based on simulation technology, comprising:

[0006] Acquire suspension structure data of each suspension structure of the produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and identify the production process of each suspension structure and process parameter information of each suspension structure based on the production process information of each suspension structure;

[0007] Based on the production process of each suspension structure and the process parameter information of each suspension structure, a production digital model of each suspension structure is generated, and based on the raw material information of each suspension structure, the range of each structural parameter of the suspension structure is predicted through the production digital model;

[0008] Generate sample structural models of each suspension structure based on the structural parameter range of each suspension structure and the suspension structural data of each suspension structure, and generate sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure;

[0009] The simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme are collected, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, simulation test processing is performed through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

[0010] Optionally, the identifying the production process of each suspension structure and the process parameter information of each suspension structure based on the production process information of each suspension structure includes:

[0011] For each suspension structure, based on the production process information of the suspension structure, identifying the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage;

[0012] Based on the stage production target of each production stage and the stage production mode of each production stage, query the sub-production process of each production stage in the digital twin database, and identify the production control parameters of each production stage based on the production parameter information of each production stage;

[0013] The sub-production process of each of the production stages is used as the production process of the suspension structure, and the production control parameters of each of the production stages are used as the process parameter information of the suspension structure.

[0014] Optionally, generating a production digital model of each suspension structure based on the production process of each suspension structure and process parameter information of each suspension structure includes:

[0015] Collecting the production structure model of each suspension structure, and performing parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure;

[0016] Based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

[0017] Optionally, the predicting of the range of each structural parameter of the suspension structure based on the raw material information of each suspension structure by using the production digital model includes:

[0018] For each suspension structure, based on the raw material information of the suspension structure, identifying a material parameter range of each raw material type of the suspension structure;

[0019] Based on the material parameter range of each raw material type, the parameter range of each structural parameter type of the suspension structure is predicted through the production digital model, and the parameter range of each structural parameter type is used as the structural parameter range of the suspension structure.

[0020] Optionally, the generating of each sample structural model of each suspension structure based on the structural parameter range of each suspension structure and each suspension structural data of each suspension structure, and generating each sample vehicle suspension model of the vehicle suspension based on each sample structural model of each suspension structure, comprises:

[0021] For each suspension structure, based on the structural parameter range of the suspension structure, identifying each structural parameter value of the suspension structure, and based on each structural parameter value of each suspension structure and suspension structure data of each suspension structure, constructing each sample structural model of each suspension structure respectively;

[0022] Based on each sample structural model of each suspension structure, each structural combination strategy of each suspension structure is generated through a single variable method strategy, and based on the sample structural model of each suspension structure corresponding to each structural combination strategy, each sample vehicle suspension model of the vehicle suspension is constructed.

[0023] Optionally, the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme are performed through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension, including:

[0024] Based on each of the simulation test processes, identifying each simulation operation parameter of the vehicle suspension, and based on each of the environmental requirement information, identifying each environmental factor value of each environmental factor type;

[0025] Generate each simulation test strategy based on each simulation operation parameter of the vehicle suspension and each environmental factor value of each environmental factor type, and simulate and obtain suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension through each sample vehicle suspension model based on each simulation test strategy;

[0026] Through the suspension test evaluation strategy, the suspension test data is evaluated and processed to obtain the test evaluation results of each suspension test data, and based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy, the suspension test results of the vehicle suspension are identified.

[0027] In a second aspect, the present application also provides a suspension testing device based on simulation technology, comprising:

[0028] an acquisition module, used for acquiring suspension structure data of each suspension structure of the produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and identifying the production process of each suspension structure and process parameter information of each suspension structure based on the production process information of each suspension structure;

[0029] A prediction module, used to generate a production digital model of each suspension structure based on the production process of each suspension structure and the process parameter information of each suspension structure, and predict the range of each structural parameter of the suspension structure through the production digital model based on the raw material information of each suspension structure;

[0030] A generating module, configured to generate sample structural models of each suspension structure based on a structural parameter range of each suspension structure and suspension structural data of each suspension structure, and to generate sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure;

[0031] The simulation module is used to collect the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, perform simulation test processing through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

[0032] Optionally, the acquisition module is specifically used to:

[0033] For each suspension structure, based on the production process information of the suspension structure, identifying the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage;

[0034] Based on the stage production target of each production stage and the stage production mode of each production stage, query the sub-production process of each production stage in the digital twin database, and identify the production control parameters of each production stage based on the production parameter information of each production stage;

[0035] The sub-production process of each of the production stages is used as the production process of the suspension structure, and the production control parameters of each of the production stages are used as the process parameter information of the suspension structure.

[0036] Optionally, the prediction module is specifically used to:

[0037] Collecting the production structure model of each suspension structure, and performing parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure;

[0038] Based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

[0039] Optionally, the prediction module is specifically used to:

[0040] For each suspension structure, based on the raw material information of the suspension structure, identifying a material parameter range of each raw material type of the suspension structure;

[0041] Based on the material parameter range of each raw material type, the parameter range of each structural parameter type of the suspension structure is predicted through the production digital model, and the parameter range of each structural parameter type is used as the structural parameter range of the suspension structure.

[0042] Optionally, the generating module is specifically used for:

[0043] For each suspension structure, based on the structural parameter range of the suspension structure, identifying each structural parameter value of the suspension structure, and based on each structural parameter value of each suspension structure and suspension structure data of each suspension structure, constructing each sample structural model of each suspension structure respectively;

[0044] Based on each sample structural model of each suspension structure, each structural combination strategy of each suspension structure is generated through a single variable method strategy, and based on the sample structural model of each suspension structure corresponding to each structural combination strategy, each sample vehicle suspension model of the vehicle suspension is constructed.

[0045] Optionally, the simulation module is specifically used for:

[0046] Based on each of the simulation test processes, identifying each simulation operation parameter of the vehicle suspension, and based on each of the environmental requirement information, identifying each environmental factor value of each environmental factor type;

[0047] Generate each simulation test strategy based on each simulation operation parameter of the vehicle suspension and each environmental factor value of each environmental factor type, and simulate and obtain suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension through each sample vehicle suspension model based on each simulation test strategy;

[0048] Through the suspension test evaluation strategy, the suspension test data is evaluated and processed to obtain the test evaluation results of each suspension test data, and based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy, the suspension test results of the vehicle suspension are identified.

[0049] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0052] The above-mentioned suspension testing method, device and computer equipment based on simulation technology obtain the suspension structure data of each suspension structure of the vehicle suspension, the production process information of each suspension structure of the vehicle suspension, and the raw material information of each suspension structure of the vehicle suspension, and based on the production process information of each suspension structure, identify the production process of each suspension structure and the process parameter information of each suspension structure; based on the production process of each suspension structure and the process parameter information of each suspension structure, generate a production digital model of each suspension structure, and based on the raw material information of each suspension structure, predict the production digital model through the production digital model. The structural parameter ranges of the suspension structure are as follows; based on the structural parameter ranges of each suspension structure and the suspension structure data of each suspension structure, each sample structural model of each suspension structure is generated, and based on each sample structural model of each suspension structure, each sample vehicle suspension model of the vehicle suspension is generated; the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme are collected, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, each sample vehicle suspension model of the vehicle suspension is used to perform simulation test processing to obtain the suspension test results of the vehicle suspension. In this solution, the production digital model of each suspension structure is constructed through the production process and raw material information of each suspension structure during production, so as to simulate the production process of each suspension structure through digital twin technology, thereby obtaining the structural parameter range of each suspension structure and constructing each sample structural model of each suspension structure. Through the above scheme, the cost loss of manual detection of the actual structural parameters of the suspension structure and the structural loss of manual testing can be avoided, and the structural parameter range of each suspension structure obtained by digital twinning improves the comprehensiveness of the identification of the various structural parameter ranges of the suspension structure produced by the current production method. Moreover, this method can avoid the problem of one-sided identification of the various structural parameter ranges of the suspension structure caused by the structural production deviation generated during actual production, or the sampling limitations during actual sampling. Then, this scheme constructs the suspension structure model respectively through the identified structural parameter ranges of the suspension structure, and then constructs each sample vehicle suspension model of the vehicle suspension, so that multiple sample vehicle suspension models of different vehicle suspensions can be generated, avoiding the problems of small sample data volume and one-sided sample data, thereby comprehensively improving the comprehensiveness of vehicle suspension testing during actual testing. Then, during the actual test, this solution constructs multiple simulation test strategies by combining the test plan and environmental requirements, and then conducts simulation tests in combination with each sample vehicle suspension model. This avoids the problem that other performance tests of the vehicle suspension will be greatly affected when the test causes substantial damage to the vehicle suspension during the physical test, thereby improving the accuracy of the vehicle suspension test.In summary, this solution not only improves the comprehensiveness of the sample vehicle suspension models of each suspension structure, but also improves the quantity satisfaction of the sample vehicle suspension models. Moreover, this solution combines the simulation test scheme with the environmental requirements to simulate and test each sample vehicle suspension model, thereby improving the accuracy and comprehensiveness of the test, and thus comprehensively improving the test efficiency and accuracy of the production vehicle suspension. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A schematic diagram of a flow chart of a suspension testing method based on simulation technology in one embodiment;

[0055] Figure 2 A schematic diagram of a flow chart of a suspension test example based on simulation technology in one embodiment;

[0056] Figure 3 is a structural block diagram of a suspension testing device based on simulation technology in one embodiment;

[0057] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0059] The suspension test method based on simulation technology provided in the embodiment of the present application can be applied to the application environment of suspension test based on simulation technology. Among them, the method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptops, medium-sized computers, etc. Among them, the terminal constructs a production digital model of each suspension structure through the production process of each suspension structure during production, and the raw material information, so as to simulate the production process of each suspension structure through the digital twin technology, so as to obtain the structural parameter range of each suspension structure, so as to construct each sample structural model of each suspension structure. Through the above scheme, the cost loss of manual detection of the actual structural parameters of the suspension structure and the structural loss of manual testing can be avoided, and the structural parameter range of each suspension structure obtained by the digital twin improves the comprehensiveness of the identification of the structural parameter range of the suspension structure produced by the current production method. Moreover, this method can avoid the problem of one-sided identification of the structural production deviation generated during actual production, or the sampling limitation during actual sampling, which leads to the problem of one-sided identification of the structural parameter range of the suspension structure. Then, this scheme constructs suspension structure models respectively through the range of each structural parameter of the identified suspension structure, and then constructs each sample vehicle suspension model of the vehicle suspension, so that multiple sample vehicle suspension models of different vehicle suspensions can be generated, avoiding the problem of small sample data volume and one-sided sample data, thereby comprehensively improving the comprehensiveness of vehicle suspension testing during actual testing. Then, during actual testing, this scheme constructs multiple simulation test strategies by combining the test scheme and environmental requirements, so as to conduct simulation tests in combination with each sample vehicle suspension model, thereby avoiding the problem that other performance tests of the vehicle suspension will be greatly affected when the test causes substantial damage to the vehicle suspension during the physical test, thereby improving the accuracy of the vehicle suspension test. In summary, this scheme not only improves the comprehensiveness of the sample vehicle suspension models of each suspension structure constructed, but also the quantitative satisfaction of the sample vehicle suspension models. Moreover, this scheme combines the simulation test scheme and environmental requirements to conduct simulation tests on each sample vehicle suspension model, thereby improving the accuracy and comprehensiveness of the test, thereby comprehensively improving the test efficiency and accuracy of the production vehicle suspension.

[0060] In an exemplary embodiment, Figure 1 As shown, a suspension test method based on simulation technology is provided, and the method is applied to a terminal as an example for explanation, including the following steps S101 to S104.

[0061] in:

[0062] Step S101, obtain suspension structure data of each suspension structure of the produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and based on the production process information of each suspension structure, identify the production process of each suspension structure and process parameter information of each suspension structure.

[0063] In this embodiment, the terminal performs three-dimensional structure scanning processing on each suspension structure of the vehicle suspension through a three-dimensional scanning device to obtain suspension structure data of each suspension structure. The suspension structure includes, but is not limited to, suspension structures such as elastic elements, shock absorbers, guide mechanisms and other auxiliary components. Then, the terminal obtains the production process information of each suspension structure. The production process information of each suspension structure is the production process corresponding to the sub-production line of each suspension structure in the vehicle suspension production line. The production process includes the stage production target, production method, and production parameters of each production stage of each suspension structure. The production parameters are adjustable parameters of each production stage when the sub-production line is produced, such as the pouring temperature range, welding times, heating time, heating temperature, etc., which can be manually adjusted or controlled by equipment. After that, the terminal obtains the raw material information of each suspension structure before production, and the raw material information includes the material parameter range of each raw material type of the suspension structure, such as the carbon content range of steel materials, the ore quality of iron ore, etc. Finally, the terminal identifies the production process of each suspension structure and the process parameter information of each suspension structure based on the production process information of each suspension structure. The specific identification process will be described in detail later.

[0064] Step S102, based on the production process of each suspension structure and the process parameter information of each suspension structure, a production digital model of each suspension structure is generated, and based on the raw material information of each suspension structure, the range of each structural parameter of the suspension structure is predicted through the production digital model.

[0065] In this embodiment, the terminal generates a production digital model of each suspension structure based on the production process of each suspension structure and the process parameter information of each suspension structure, and predicts the range of each structural parameter of the suspension structure through the production digital model based on the raw material information of each suspension structure. The specific generation process will be described in detail later.

[0066] Step S103, generating sample structural models of each suspension structure based on the structural parameter range of each suspension structure and the suspension structural data of each suspension structure, and generating sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure.

[0067] In this embodiment, the terminal generates each sample structural model of each suspension structure based on the structural parameter range of each suspension structure and the suspension structural data of each suspension structure, and generates each sample vehicle suspension model of the vehicle suspension based on each sample structural model of each suspension structure. The sample structural model is generated by arranging, combining and splicing the sample structural models of each suspension structure through a single variable strategy to obtain each sample vehicle suspension model of the vehicle suspension.

[0068] Step S104, collecting the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, performing simulation test processing through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

[0069] In this embodiment, the terminal collects the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, the simulation test process is performed through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension. Among them, the simulation test process is a test process for simulating the performance of the vehicle suspension, wherein each performance includes but is not limited to performance tests of vehicle height type, wheel alignment parameter type, wheel balance type, shock absorber performance type, spring performance type, structural wear type, suspension system rigidity type, suspension system durability type, ride comfort type, vibration attenuation effectiveness type, handling stability type, and body posture control type. And the environmental requirement information includes the environmental data range of each environmental type, and the environmental type includes but is not limited to environmental types such as temperature type, humidity type, wind speed type, road condition type, etc.

[0070] Based on the above scheme, the production digital model of each suspension structure is constructed through the production process and raw material information of each suspension structure during production, so as to simulate the production process of each suspension structure through digital twin technology, so as to obtain the structural parameter range of each suspension structure, so as to construct each sample structural model of each suspension structure. Through the above scheme, the cost loss of manual detection of the actual structural parameters of the suspension structure and the structural loss of manual testing can be avoided, and the structural parameter range of each suspension structure obtained by digital twin improves the comprehensiveness of the identification of each structural parameter range of the suspension structure produced by the current production method. Moreover, this method can avoid the problem of one-sided identification of each structural parameter range of the suspension structure caused by the structural production deviation generated during actual production or the sampling limitation during actual sampling. Then, this scheme constructs the suspension structure model respectively through the structural parameter range of each identified suspension structure, and then constructs each sample vehicle suspension model of the vehicle suspension, so as to generate multiple sample vehicle suspension models of different vehicle suspensions, avoiding the problem of small sample data volume and one-sided sample data, thereby comprehensively improving the comprehensiveness of vehicle suspension testing during actual testing. Then, during the actual test, this solution combines the test scheme and environmental requirements to build multiple simulation test strategies, so as to conduct simulation tests in combination with each sample vehicle suspension model, thereby avoiding the problem that other performance tests of the vehicle suspension will be greatly affected when the test causes substantial damage to the vehicle suspension during the physical test, thereby improving the accuracy of the vehicle suspension test. In summary, this solution not only improves the comprehensiveness of the sample vehicle suspension models of each suspension structure constructed, but also the quantitative satisfaction of the sample vehicle suspension models. Moreover, this solution combines the simulation test scheme with environmental requirements to conduct simulation tests on each sample vehicle suspension model, thereby improving the accuracy and comprehensiveness of the test, thereby comprehensively improving the test efficiency and accuracy of the production vehicle suspension.

[0071] Optionally, based on the production process information of each suspension structure, the production process of each suspension structure and the process parameter information of each suspension structure are identified, including: for each suspension structure, based on the production process information of the suspension structure, the stage production goals of each production stage of the suspension structure, the stage production methods of each production stage, and the production parameter information of each production stage are identified; based on the stage production goals of each production stage and the stage production methods of each production stage, the sub-production processes of each production stage are queried in the digital twin database, and based on the production parameter information of each production stage, the production control parameters of each production stage are identified; the sub-production processes of each production stage are used as the production process of the suspension structure, and the production control parameters of each production stage are used as the process parameter information of the suspension structure.

[0072] In this embodiment, the terminal identifies the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage for each suspension structure based on the production process information of the suspension structure. Among them, each production stage of different suspension structures can correspond to one or more stage production methods, and each stage production method is used to characterize the different production processes of the suspension structure, for example, the production method corresponding to the pouring method, or the stage generation method of constructing the suspension structure body of the suspension structure by the cutting and grinding method.

[0073] Then, based on the stage production targets and stage production methods of each production stage, the terminal queries the sub-production processes of each production stage in the digital twin database, and identifies the production control parameters of each production stage based on the production parameter information of each production stage. Among them, the digital twin database stores the sub-production processes corresponding to the different stage generation methods and different stage generation targets of different production stages. Among them, a sub-production process of each suspension structure corresponds to a production stage, a stage generation method, and a stage generation target. The production parameter information includes various control parameters for regulating production.

[0074] Afterwards, the terminal uses the sub-production process of each production stage as the production process of the suspension structure, and uses the production control parameters of each production stage as the process parameter information of the suspension structure.

[0075] Based on the above solution, by identifying the sub-production processes of each production stage of each suspension structure and the process parameter information of each suspension structure from the perspective of digital twins, the recognition efficiency and accuracy of the processes and parameters related to the digital twins of the suspension structure are improved.

[0076] Optionally, based on the production process of each suspension structure and the process parameter information of each suspension structure, a production digital model of each suspension structure is generated, including: collecting the production structure model of each suspension structure, and parameterizing the production process of each suspension structure to obtain the process design parameters of each suspension structure; based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

[0077] In this embodiment, the terminal collects the production structure model of each suspension structure, and performs parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure. Among them, the terminal presets a digital twin parameterization program, and through the digital twin parameterization program, the production process of the suspension structure is parameterized to obtain the process design parameters of each suspension structure.

[0078] Then, based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, the terminal constructs a production digital model of each suspension structure through the production structure model. The constructed production digital model is a digital twin model used to simulate the production process of the suspension structure.

[0079] Based on the above scheme, after parameterizing the production process of each suspension structure, the production process of the suspension structure is parameterized through the digital twin parameterization program to obtain the process design parameters of each suspension structure, thereby constructing a digital twin model of the production process of the suspension structure, thereby improving the construction efficiency and construction accuracy of the digital twin model.

[0080] Optionally, based on the raw material information of each suspension structure, a digital model is produced to predict the ranges of each structural parameter of the suspension structure, including: for each suspension structure, based on the raw material information of the suspension structure, identifying the material parameter ranges of each raw material type of the suspension structure; based on the material parameter ranges of each raw material type, a digital model is produced to predict the parameter ranges of each structural parameter type of the suspension structure, and using the parameter range of each structural parameter type as the structural parameter ranges of the suspension structure.

[0081] In this embodiment, the terminal identifies the material parameter range of each raw material type of the suspension structure based on the raw material information of the suspension structure for each suspension structure. Then, based on the material parameter range of each raw material type, the terminal simulates the production process of the suspension structure by producing a digital model to obtain the parameter range of each structural parameter type of the suspension structure. Finally, the terminal uses the parameter range of each structural parameter type as the structural parameter range of the suspension structure.

[0082] Based on the above scheme, the production process of the suspension structure is simulated through the material parameter range of each raw material type, and the parameter range of each structural parameter type of the suspension structure is obtained, thereby improving the accuracy of the digital twin of the production process of the suspension structure.

[0083] Optionally, based on the structural parameter range of each suspension structure and the suspension structure data of each suspension structure, each sample structural model of each suspension structure is generated, and based on the sample structural models of each suspension structure, each sample vehicle suspension model of the vehicle suspension is generated, including: for each suspension structure, based on the structural parameter range of the suspension structure, each structural parameter value of the suspension structure is identified, and based on the structural parameter value of each suspension structure and the suspension structure data of each suspension structure, each sample structural model of each suspension structure is constructed; based on the sample structural models of each suspension structure, each structural combination strategy of each suspension structure is generated through a single variable method strategy, and each sample vehicle suspension model of the vehicle suspension is constructed based on the sample structural models of each suspension structure corresponding to each structural combination strategy.

[0084] In this embodiment, the terminal identifies each structural parameter value of the suspension structure based on the structural parameter range of the suspension structure for each suspension structure, and constructs each sample structural model of each suspension structure based on each structural parameter value of each suspension structure and the suspension structure data of each suspension structure. The constructed sample structural models of each suspension structure are sample structural models corresponding to the structural parameter values ​​of different suspension structures.

[0085] Then, the terminal generates various structural combination strategies for each suspension structure based on the sample structural models of each suspension structure through the single variable method strategy, and constructs various sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure corresponding to each structural combination strategy.

[0086] Based on the above scheme, after constructing each sample structural model of each suspension structure through the structural parameter value of each suspension structure, each sample vehicle suspension model of the vehicle suspension is generated by a single variable, which improves the generation efficiency and comprehensiveness of each sample vehicle suspension model of the vehicle suspension.

[0087] Optionally, based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, simulation test processing is performed through each sample vehicle suspension model of the vehicle suspension to obtain suspension test results of the vehicle suspension, including: based on each simulation test process, identifying each simulation operating parameter of the vehicle suspension, and based on each environmental requirement information, identifying each environmental factor value of each environmental factor type; based on each simulation operating parameter of the vehicle suspension and each environmental factor value of each environmental factor type, generating each simulation test strategy, and based on each simulation test strategy, simulating through each sample vehicle suspension model to obtain suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension; through the suspension test evaluation strategy, performing data evaluation processing on the suspension test data to obtain test evaluation results of each suspension test data, and identifying the suspension test results of the vehicle suspension based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy.

[0088] In this embodiment, the terminal identifies each simulation operation parameter of the vehicle suspension based on each simulation test process, and identifies each environmental factor value of each environmental factor type based on each environmental demand information. Then, based on each simulation operation parameter of the vehicle suspension and each environmental factor value of each environmental factor type, the terminal generates environmental factor data of different environmental factor types or each simulation test strategy of different simulation operation parameters through a single variable strategy. Afterwards, based on each simulation test strategy, the terminal simulates and obtains suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension through each sample vehicle suspension model. Among them, each simulation test strategy includes different simulation operation parameters and each environmental factor value, and each simulation test strategy is generated separately through a single variable strategy.

[0089] Then, the terminal performs data evaluation processing on the suspension test data through the suspension test evaluation strategy to obtain the test evaluation results of each suspension test data. Specifically, the suspension test evaluation strategy includes sub-suspension test evaluation strategies corresponding to different suspension test schemes, and each sub-suspension test evaluation strategy includes each evaluation value of each test target of the suspension test scheme and the test data range corresponding to each evaluation value. Among them, each suspension test data includes the test data of each test target of the suspension test scheme corresponding to the suspension test data.

[0090] Finally, the terminal identifies the suspension test results of the vehicle suspension based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy. Specifically, the terminal uses the test data of each test target corresponding to the environmental data of each suspension test scheme in different environmental types as the suspension test result of the vehicle suspension. Among them, the test data of each test target corresponding to the environmental data of the same environmental type of the same suspension test scheme is the average value of the test evaluation results of each suspension test data obtained after the simulation test through each sample vehicle suspension model.

[0091] Based on the above scheme, each suspension test data is tested and evaluated through the suspension test evaluation strategy corresponding to different suspension test schemes, so as to identify the evaluation value of each test target corresponding to the environmental data of each suspension test scheme in different environmental types, thereby improving the comprehensiveness and accuracy of the suspension test evaluation.

[0092] This application also provides a suspension test example based on simulation technology, such as Figure 2 As shown, the specific processing process includes the following steps:

[0093] Step S201 , obtaining suspension structure data of each suspension structure of the produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension.

[0094] Step S202 , for each suspension structure, based on the production process information of the suspension structure, identifying the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage.

[0095] Step S203, based on the stage production goals of each production stage and the stage production methods of each production stage, query the sub-production processes of each production stage in the digital twin database, and identify the production control parameters of each production stage based on the production parameter information of each production stage.

[0096] Step S204, taking the sub-production process of each production stage as the production process of the suspension structure, and taking the production control parameters of each production stage as the process parameter information of the suspension structure.

[0097] Step S205 , collecting the production structure models of each suspension structure, and performing parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure.

[0098] Step S206 , based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

[0099] Step S207 : for each suspension structure, based on the raw material information of the suspension structure, identifying the material parameter range of each raw material type of the suspension structure.

[0100] Step S208, based on the material parameter range of each raw material type, the parameter range of each structural parameter type of the suspension structure is predicted by producing a digital model, and the parameter range of each structural parameter type is used as the structural parameter range of the suspension structure.

[0101] Step S209, for each suspension structure, based on the structural parameter range of the suspension structure, identifying the structural parameter values ​​of the suspension structure, and based on the structural parameter values ​​of each suspension structure and the suspension structure data of each suspension structure, constructing each sample structural model of each suspension structure.

[0102] Step S210, based on each sample structural model of each suspension structure, generate each structural combination strategy of each suspension structure through a single variable method strategy, and construct each sample vehicle suspension model of the vehicle suspension based on the sample structural model of each suspension structure corresponding to each structural combination strategy.

[0103] Step S211 , collecting the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme.

[0104] Step S212, based on each simulation test process, identifying each simulation operation parameter of the vehicle suspension, and based on each environmental requirement information, identifying each environmental factor value of each environmental factor type.

[0105] Step S213, based on the simulation operating parameters of the vehicle suspension and the environmental factor values ​​of each environmental factor type, generate each simulation test strategy, and based on each simulation test strategy, through each sample vehicle suspension model, simulate and obtain the suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension.

[0106] Step S214, performing data evaluation processing on the suspension test data through the suspension test evaluation strategy to obtain the test evaluation results of each suspension test data, and identifying the suspension test results of the vehicle suspension based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy.

[0107] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0108] Based on the same inventive concept, the embodiment of the present application also provides a suspension test device based on simulation technology for implementing the suspension test method based on simulation technology involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more embodiments of the suspension test device based on simulation technology provided below can refer to the limitations of the suspension test method based on simulation technology above, and will not be repeated here.

[0109] In an exemplary embodiment, Figure 3 As shown, a suspension test device based on simulation technology is provided, including: an acquisition module 310, a prediction module 320, a generation module 330 and a simulation module 340, wherein:

[0110] An acquisition module 310 is used to acquire suspension structure data of each suspension structure of the vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and identify the production process of each suspension structure and process parameter information of each suspension structure based on the production process information of each suspension structure;

[0111] A prediction module 320, for generating a production digital model of each suspension structure based on the production process of each suspension structure and the process parameter information of each suspension structure, and predicting the range of each structural parameter of the suspension structure through the production digital model based on the raw material information of each suspension structure;

[0112] A generating module 330, for generating sample structural models of each suspension structure based on a structural parameter range of each suspension structure and suspension structural data of each suspension structure, and generating sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure;

[0113] The simulation module 340 is used to collect the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, perform simulation test processing through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

[0114] Optionally, the acquisition module 310 is specifically configured to:

[0115] For each suspension structure, based on the production process information of the suspension structure, identifying the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage;

[0116] Based on the stage production target of each production stage and the stage production mode of each production stage, query the sub-production process of each production stage in the digital twin database, and identify the production control parameters of each production stage based on the production parameter information of each production stage;

[0117] The sub-production process of each of the production stages is used as the production process of the suspension structure, and the production control parameters of each of the production stages are used as the process parameter information of the suspension structure.

[0118] Optionally, the prediction module 320 is specifically used for:

[0119] Collecting the production structure model of each suspension structure, and performing parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure;

[0120] Based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

[0121] Optionally, the prediction module 320 is specifically used for:

[0122] For each suspension structure, based on the raw material information of the suspension structure, identifying a material parameter range of each raw material type of the suspension structure;

[0123] Based on the material parameter range of each raw material type, the parameter range of each structural parameter type of the suspension structure is predicted through the production digital model, and the parameter range of each structural parameter type is used as the structural parameter range of the suspension structure.

[0124] Optionally, the generating module 330 is specifically configured to:

[0125] For each suspension structure, based on the structural parameter range of the suspension structure, identifying each structural parameter value of the suspension structure, and based on each structural parameter value of each suspension structure and suspension structure data of each suspension structure, constructing each sample structural model of each suspension structure respectively;

[0126] Based on each sample structural model of each suspension structure, each structural combination strategy of each suspension structure is generated through a single variable method strategy, and based on the sample structural model of each suspension structure corresponding to each structural combination strategy, each sample vehicle suspension model of the vehicle suspension is constructed.

[0127] Optionally, the simulation module 340 is specifically used for:

[0128] Based on each of the simulation test processes, identifying each simulation operation parameter of the vehicle suspension, and based on each of the environmental requirement information, identifying each environmental factor value of each environmental factor type;

[0129] Generate each simulation test strategy based on each simulation operation parameter of the vehicle suspension and each environmental factor value of each environmental factor type, and simulate and obtain suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension through each sample vehicle suspension model based on each simulation test strategy;

[0130] Through the suspension test evaluation strategy, the suspension test data is evaluated and processed to obtain the test evaluation results of each suspension test data, and based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy, the suspension test results of the vehicle suspension are identified.

[0131] Each module in the above-mentioned suspension test device based on simulation technology can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0132] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 4As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a suspension test method based on simulation technology is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0133] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0134] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps of a suspension testing method based on simulation technology when executing the computer program.

[0135] 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 steps of a suspension testing method based on simulation technology are implemented.

[0136] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps of a suspension testing method based on simulation technology when executed by a processor.

[0137] 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 used 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 must comply with relevant regulations.

[0138] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. 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. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0139] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0140] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A suspension testing method based on simulation technology, characterized in that: The method comprises: Acquire suspension structure data of each suspension structure of the produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and identify the production process of each suspension structure and process parameter information of each suspension structure based on the production process information of each suspension structure; Based on the production process of each suspension structure and the process parameter information of each suspension structure, a production digital model of each suspension structure is generated, and based on the raw material information of each suspension structure, the range of each structural parameter of the suspension structure is predicted through the production digital model; Generate sample structural models of each suspension structure based on the structural parameter range of each suspension structure and the suspension structural data of each suspension structure, and generate sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure; The simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme are collected, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, simulation test processing is performed through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

2. The method according to claim 1, characterized in that The identifying the production process of each suspension structure and the process parameter information of each suspension structure based on the production process information of each suspension structure includes: For each suspension structure, based on the production process information of the suspension structure, identifying the stage production target of each production stage of the suspension structure, the stage production method of each production stage, and the production parameter information of each production stage; Based on the stage production target of each production stage and the stage production mode of each production stage, query the sub-production process of each production stage in the digital twin database, and identify the production control parameters of each production stage based on the production parameter information of each production stage; The sub-production process of each of the production stages is used as the production process of the suspension structure, and the production control parameters of each of the production stages are used as the process parameter information of the suspension structure.

3. The method according to claim 1, characterized in that The step of generating a production digital model of each suspension structure based on the production process of each suspension structure and the process parameter information of each suspension structure comprises: Collecting the production structure model of each suspension structure, and performing parameterization processing on the production process of each suspension structure to obtain the process design parameters of each suspension structure; Based on the process parameter information of each suspension structure and the process design parameters of each suspension structure, a production digital model of each suspension structure is constructed through the production structure model.

4. The method according to claim 1, characterized in that The method of predicting the range of each structural parameter of the suspension structure based on the raw material information of each suspension structure by using the production digital model includes: For each suspension structure, based on the raw material information of the suspension structure, identifying a material parameter range of each raw material type of the suspension structure; Based on the material parameter range of each raw material type, the parameter range of each structural parameter type of the suspension structure is predicted through the production digital model, and the parameter range of each structural parameter type is used as the structural parameter range of the suspension structure.

5. The method according to claim 1, characterized in that The generating of each sample structural model of each suspension structure based on the structural parameter range of each suspension structure and each suspension structural data of each suspension structure, and generating each sample vehicle suspension model of the vehicle suspension based on each sample structural model of each suspension structure, comprises: For each suspension structure, based on the structural parameter range of the suspension structure, identifying each structural parameter value of the suspension structure, and based on each structural parameter value of each suspension structure and suspension structure data of each suspension structure, constructing each sample structural model of each suspension structure respectively; Based on each sample structural model of each suspension structure, each structural combination strategy of each suspension structure is generated through a single variable method strategy, and based on the sample structural model of each suspension structure corresponding to each structural combination strategy, each sample vehicle suspension model of the vehicle suspension is constructed.

6. The method according to claim 5, characterized in that The simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme are performed through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension, including: Based on each of the simulation test processes, identifying each simulation operation parameter of the vehicle suspension, and based on each of the environmental requirement information, identifying each environmental factor value of each environmental factor type; Generate each simulation test strategy based on each simulation operation parameter of the vehicle suspension and each environmental factor value of each environmental factor type, and simulate and obtain suspension test data of each sample vehicle suspension model corresponding to each simulation test strategy of the vehicle suspension through each sample vehicle suspension model based on each simulation test strategy; Through the suspension test evaluation strategy, the suspension test data is evaluated and processed to obtain the test evaluation results of each suspension test data, and based on the test evaluation results of each sample vehicle suspension model corresponding to each simulation test strategy, the suspension test results of the vehicle suspension are identified.

7. A suspension test device based on simulation technology, characterized in that: The device comprises: an acquisition module, used to acquire suspension structure data of each suspension structure of a produced vehicle suspension, production process information of each suspension structure of the vehicle suspension, and raw material information of each suspension structure of the vehicle suspension, and identify the production process of each suspension structure and process parameter information of each suspension structure based on the production process information of each suspension structure; A prediction module, used to generate a production digital model of each suspension structure based on the production process of each suspension structure and the process parameter information of each suspension structure, and predict the range of each structural parameter of the suspension structure through the production digital model based on the raw material information of each suspension structure; A generating module, configured to generate sample structural models of each suspension structure based on a structural parameter range of each suspension structure and suspension structural data of each suspension structure, and to generate sample vehicle suspension models of the vehicle suspension based on the sample structural models of each suspension structure; The simulation module is used to collect the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, and based on the simulation test process corresponding to each suspension test scheme and the environmental requirement information corresponding to each suspension test scheme, perform simulation test processing through each sample vehicle suspension model of the vehicle suspension to obtain the suspension test result of the vehicle suspension.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: 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 a 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 a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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