Data storage method and system, device, medium, product

Abstract

The application relates to a data storage method and system, equipment, medium and product. The data storage method comprises the following steps: determining a performance index of a simulation task to be executed; determining a simulation file corresponding to the simulation task, and storing the performance index in the simulation file; and in the simulation file, associating target simulation data obtained with the performance index, and storing the target simulation data in a preset database. By adopting the method, the performance index and the target simulation data of the simulation task can be automatically matched and stored, systematic management of the performance index and the target simulation data can be realized, and the accuracy of data storage and the efficiency of data entry can be improved.

Description

Technical Field

[0001] This application relates to the field of simulation technology, and in particular to a data storage method, system, device, medium, and product. Background Technology

[0002] Simulation technology, as an important technical means, is widely used in the design and optimization stages of products. By building a model and inputting various operating parameters into it, simulation technology can obtain simulation results under different operating conditions. Engineers compare the simulation results with the set performance targets to determine whether the simulation results meet the set performance targets, thereby verifying whether the product design meets the predetermined goals. For example, in the automotive industry, various operating parameters of the vehicle can be input into the model to obtain simulation results of the vehicle under different operating conditions, thereby verifying whether the vehicle design meets the predetermined goals. However, the performance targets and statistical management of simulation results in related technologies are generally still done in the form of Excel spreadsheets (Microsoft Office Excel, a spreadsheet software). Engineers need to manually enter and retrieve and verify the simulation results one by one. Manually entering simulation results is not only inefficient but also prone to data omissions and errors. Summary of the Invention

[0003] Based on this, a data storage method, system, device, medium, and product are provided to solve the problems of low efficiency and high error rate in the input of simulation results in the prior art.

[0004] On the one hand, a data storage method is provided, the method comprising:

[0005] Determine the performance metrics of the simulation task to be executed;

[0006] Determine the simulation file corresponding to the simulation task, and store the performance indicators in the simulation file;

[0007] In the simulation file, the acquired target simulation data is associated with the performance indicators and stored in a preset database.

[0008] Optionally, the performance index of the simulation task to be executed is the vehicle performance index;

[0009] The determination of the performance metrics for the simulation task to be executed includes:

[0010] Obtain vehicle simulation conditions;

[0011] Based on the first preset correspondence between the vehicle simulation conditions and the vehicle performance indicators, the vehicle performance indicators are extracted from the vehicle simulation conditions.

[0012] Optionally, determining the performance metrics of the simulation task to be executed includes:

[0013] Obtain the target simulation conditions;

[0014] The performance indicators are extracted based on the target simulation conditions according to the second preset correspondence between the target simulation conditions and the performance indicators.

[0015] Optionally, determining the simulation file corresponding to the simulation task includes:

[0016] Determine the target path corresponding to the simulation task;

[0017] The simulation file is created based on the target path.

[0018] Optionally, the performance indicators include target performance parameters and target performance values, and the target simulation data includes the target performance parameters and simulation values;

[0019] The step of associating the acquired target simulation data with the performance index in the simulation file includes:

[0020] Obtain simulation data obtained from executing the simulation task; wherein, the simulation data includes a preset correspondence between multiple sets of performance parameters and simulation data.

[0021] In the simulation data, based on the target performance parameters, query the target simulation data associated with the performance index;

[0022] The target performance parameters are used to associate the target simulation data and the performance indicators in the simulation file.

[0023] Optionally, after storing to a preset database, the process further includes:

[0024] Determine the target performance values ​​and target simulation data corresponding to the target performance parameters;

[0025] By comparing the simulated values ​​with the target performance values, the compliance information of the target simulation data is determined; wherein, the compliance information indicates whether the target simulation data meets the standard, and the target simulation data includes the simulated values.

[0026] Optionally, the step of comparing the simulation values ​​with the target performance values ​​to determine the compliance information of the target simulation data includes:

[0027] Preset conditions for obtaining the target performance value;

[0028] By comparing the simulated values ​​with the target performance values, comparison information is obtained;

[0029] In response to the comparison information meeting the preset compliance conditions, the compliance information is determined to be compliant.

[0030] Secondly, a data storage system is provided, the data storage system comprising:

[0031] The first determining module is used to determine the performance metrics of the simulation task to be executed;

[0032] The second determining module is used to determine the simulation file corresponding to the simulation task and store the performance indicators in the simulation file;

[0033] The storage module is used to associate the acquired target simulation data with the performance indicators in the simulation file and store it in a preset database.

[0034] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and for running on the processor, wherein the processor executes the computer program to implement the data storage method described in the first aspect.

[0035] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the data storage method described in the first aspect.

[0036] Fifthly, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the data storage method described in the first aspect.

[0037] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this application.

[0038] The aforementioned data storage methods, systems, devices, media, and products automatically match and store the performance indicators and target simulation data of simulation tasks, thereby achieving systematic management of performance indicators and target simulation data and improving the accuracy of data storage and the efficiency of data entry. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the first process of a data storage method in one embodiment;

[0040] Figure 2 This is a schematic diagram of the second process of a data storage method in one embodiment;

[0041] Figure 3 This is a schematic diagram of the data storage system in one embodiment;

[0042] Figure 4 This is a schematic diagram of the structure of an electronic device in one embodiment. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0044] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of this application. Therefore, the drawings only show components relevant to this application and are not drawn according to the actual number, shape, and size of components in implementation. In actual implementation, the form, quantity, and proportion of each component can be arbitrarily changed, and the component layout may also be more complex. The structures, proportions, sizes, etc., shown in the accompanying drawings are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the implementation conditions of this application. Therefore, they have no substantial technical significance. Any modification to the structure, change in the proportional relationship, or adjustment of the size, without affecting the effect and purpose that this application can produce, should still fall within the scope of the technical content disclosed in this application. At the same time, the terms such as "upper," "lower," "left," "right," "middle," and "one" used in this specification are only for clarity of description and are not intended to limit the scope of implementation of this application. Changes or adjustments in their relative relationships, without substantially changing the technical content, should also be considered within the scope of implementation of this application.

[0045] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the document does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0046] As illustrated herein, unless the context clearly indicates otherwise, the words “a,” “an,” “an,” and / or “the” do not specifically refer to the singular and may also include the plural. Generally speaking, the terms “comprising” and “including” only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0047] The definitions used herein, such as the terms “having,” “may have,” “comprising,” or “may include,” indicate the presence of the corresponding function, operation, element, etc., and do not limit the presence of one or more other functions, operations, elements, etc. Furthermore, it should be understood that the terms “comprising” or “having” as used herein indicate the presence of the features, figures, steps, operations, elements, components, or combinations thereof described in the specification, without excluding the presence or addition of one or more other features, figures, steps, operations, elements, components, or combinations thereof.

[0048] The prefixes such as "first" and "second" used in this application embodiment are merely for distinguishing different descriptive objects and do not limit the position, order, priority, quantity, or content of the described objects. The use of ordinal numbers and other prefixes used to distinguish descriptive objects in this application embodiment does not constitute a limitation on the described objects. The description of the described objects is given in the claims or the context of the embodiments, and should not constitute unnecessary restrictions due to the use of such prefixes. Furthermore, in the description of this embodiment, unless otherwise stated, "multiple" means two or more.

[0049] In the embodiments provided in this application, the simulation fields include, but are not limited to, vehicle simulation, aviation simulation, power simulation, and traffic simulation.

[0050] Figure 1 A data storage method is provided as an exemplary embodiment of this application. The data storage method includes:

[0051] S11. Determine the performance metrics of the simulation task to be executed.

[0052] The performance indicators are stored in a preset database. Performance indicators can be understood as the target that a certain performance parameter needs to achieve after the simulation task is completed. For example, the performance indicator of a certain simulation task can be torsional stiffness ≥1000 N·m, which means that after the simulation task is completed, the target that the performance parameter torsional stiffness needs to achieve is greater than or equal to 1000 N·m.

[0053] In one embodiment, a target simulation condition can be obtained first. The target simulation condition corresponds to the aforementioned simulation task to be executed, and can be extracted from a simulation condition library. Based on a second preset correspondence between the target simulation condition and performance indicators, the aforementioned performance indicators corresponding to the target simulation condition can be extracted. The second preset correspondence can be represented by a table or a database.

[0054] In simulation analysis, a simulation condition is a set of loads and boundary conditions that are applied under specific conditions. Simulation conditions can include various factors such as static loads, dynamic loads, temperature changes, pressure, and humidity. These factors can be singular or combined to simulate the complexity of real-world conditions. For example, simulation conditions under different roads, climates, and driving conditions can be combined to simulate a vehicle and evaluate its performance and safety.

[0055] In one embodiment, if the performance metric of the simulation task to be executed is a vehicle performance metric, then determining the performance metric of the simulation task to be executed includes:

[0056] Obtain vehicle simulation conditions;

[0057] Based on a first preset correspondence between vehicle simulation conditions and vehicle performance indicators, vehicle performance indicators are extracted from the vehicle simulation conditions. The first preset correspondence can be represented by a table or a database.

[0058] The performance indicators for the simulation task to be executed can be vehicle performance indicators, which can include power performance indicators, fuel performance indicators, handling performance indicators, driving performance indicators, comfort performance indicators, safety performance indicators, emission performance indicators, durability performance indicators, load-bearing performance indicators, etc. The vehicle simulation conditions and vehicle performance indicators refer to the simulation conditions obtained and the performance indicators determined when simulating the vehicle.

[0059] The following example uses vehicle simulation: When simulating a vehicle, a simulation project can be created, and simulation tasks can be created within the project. These tasks simulate the vehicle under different operating conditions. Multiple simulation tasks can be created within a single project, each simulating a different operating condition. Different vehicle models can correspond to different simulation projects, while the same vehicle model can correspond to the same project, representing simulations of different operating conditions for the same model within the same project. Alternatively, different components of the same vehicle model can correspond to a single simulation project; for example, a vehicle seat could be one simulation project, and a vehicle door another.

[0060] The simulation project indicates that the performance and behavior of a vehicle under target simulation conditions will be simulated using pre-defined simulation model computer technology and simulation software.

[0061] The following explanation continues using vehicle simulation as an example: Simulation conditions are stored in a simulation condition library. A simulation project can be created for a specific vehicle model. Then, based on the required vehicle analysis conditions, multiple preset simulation conditions can be extracted from the simulation condition library and written into the simulation project. Next, a simulation task can be created for each simulation condition within the same simulation project. Each simulation condition can correspond to multiple performance indicators; in other words, each simulation task includes multiple performance indicators, and these indicators can be analyzed simultaneously during the execution of the simulation task. It's also possible to write the same simulation condition into multiple simulation projects. For example, different vehicle models may have different door designs, so different simulation conditions for the door need to be analyzed in different simulation projects. Therefore, simulation conditions related to door performance testing can be written into different simulation projects.

[0062] For ease of understanding, the relationship between simulation projects, simulation conditions, and simulation tasks can be represented as follows:

[0063] Simulation Case Library ----- Project A ----- Simulation Case AA ---- Simulation Task

[0064] |----Performance Indicators AAA

[0065] |----Performance Indicators AAB

[0066] |----Performance Indicator AAC

[0067] -----Simulation Condition AB---Simulation Task

[0068] |----Performance Indicator ABA

[0069] |----Performance Indicators ABB

[0070] Performance Indicators ABC

[0071] Simulation Case Library ----- Project B ----- Simulation Case BA ----- Simulation Task

[0072] |----Performance Indicators BAA

[0073] |----Performance Metrics BAB

[0074] |----Performance Indicators BAC

[0075] -----Simulation Condition BB---Simulation Task

[0076] |----Performance Indicators BBA

[0077] |----Performance Indicators BBB

[0078] Performance Metrics (BBC)

[0079] In the simulation platform, firstly, multiple preset simulation conditions are extracted from the simulation condition library according to the required vehicle analysis conditions. These conditions are then written into the simulation project. Since multiple simulation conditions in the project need to be analyzed, a target simulation condition can be arbitrarily selected from these conditions, and a simulation task can be created for it. Next, intermediate performance indicators corresponding to the target simulation condition are extracted from the second preset correspondence between multiple sets of target simulation conditions and performance indicators. These intermediate performance indicators are then designated as performance indicators, and the data carried by the intermediate and performance indicators is consistent. The performance indicators are then synchronously written into the simulation task. Finally, the target simulation condition and performance indicators are written into the record corresponding to the target simulation condition in the preset database. When the second preset correspondence is represented by a database, it can be understood that the second preset correspondence can be a template database. Each time a simulation project is created, multiple simulation conditions can be obtained from the simulation condition library according to the vehicle analysis conditions required in the project, and then written into the simulation project. In a simulation project, a target simulation condition can be arbitrarily selected from multiple simulation scenarios. Then, a simulation task is created in the simulation project based on the target simulation condition. Performance metrics corresponding to the target simulation condition are retrieved from the template database, and the performance metrics and the target simulation condition are stored in the corresponding record in the preset database. This process is repeated until all simulation tasks corresponding to multiple simulation conditions in the simulation project have been executed.

[0080] For ease of understanding, as shown in Table 1, this application provides an example of a preset database table structure as follows:

[0081] Table 1 Preset Database Table Structure

[0082]

[0083] The following explanation uses a template database as an example, with the second preset correspondence. As shown in Table 2, an example of the table structure of a template database provided in this embodiment is as follows:

[0084] Table 2 Template Database Table Structure

[0085]

[0086] In a performance index, the performance parameter is denoted by k, such as a specific location on the model or the magnitude of stress; the expression is denoted by e, such as greater than or less than; the target value is denoted by v, such as 30 or 50; and the unit is denoted by u, such as N·m or s. Taking torsional stiffness:>=:1000:N·m as an example, torsional stiffness is the performance parameter, ≥ is the expression, the target value is 1000, and the unit is N·m. The performance parameter, expression, target value, and unit in the performance index are separated by colons. One simulation condition corresponds to one simulation task. After completing a simulation task, multiple performance indices may need to be achieved; therefore, a simulation task may include multiple sets of performance indices. When a simulation task includes multiple sets of performance indices, the multiple sets of performance indices are separated by semicolons.

[0087] Taking the gigabit torsional stiffness analysis as an example, the performance index corresponding to the gigabit torsional stiffness analysis is torsional stiffness ≥ 1000 N·m, as shown in Table 3. The table content in the template database is as follows:

[0088] Table 3 Template Database

[0089] id loadcaeId target 1 1 Torsional stiffness: >= 1000 N·m

[0090] In the simulation platform, a simulation project is first created with a projectId of 1. Then, based on the required vehicle operating conditions, multiple preset simulation operating conditions are extracted from the simulation operating condition library. These conditions are stored in the library as operating condition identifiers. A target simulation operating condition with a loadcaseId of 1 can be extracted from these conditions and written into the simulation project. A simulation task is then created under the simulation project based on the target operating condition. Next, the operating condition identifier is identified from a second preset correspondence. The intermediate performance index corresponding to operating condition identifier 1 is found to be torsional stiffness >= 1000 N·m. This intermediate performance index is then designated as the performance index, also with torsional stiffness >= 1000 N·m. The performance index is synchronously written into the simulation task. Finally, the operating condition identifier and performance index of the target simulation operating condition are stored in the corresponding record in the preset database.

[0091] As shown in Table 4, the table contents in the preset database are as follows:

[0092] Table 4 Preset Database

[0093]

[0094] When creating a simulation task on the simulation platform, the preset simulation conditions are written into the simulation task. The corresponding performance indicators can be written into the simulation task simultaneously. At this time, the target value v in the performance indicators can be modified, but the performance parameters, expressions, and units cannot be modified. The modified performance target value can be stored again in the preset database.

[0095] S12. Determine the simulation file corresponding to the simulation task and store the performance indicators in the simulation file.

[0096] The simulation file can be in .txt format (text file format), .json format (JavaScript Object Notation), XML format (eXtensible Markup Language), or other storage formats that can store information.

[0097] After creating a simulation project, multiple preset simulation conditions can be extracted from the simulation condition library and written into the simulation project. Then, a simulation task is created for each simulation condition within the simulation project. Each simulation task corresponds to a simulation file. The execution of a simulation task includes preprocessing, simulation calculation, and post-processing. All processes run within the same shared working directory, but different simulation tasks have their own distinct working directories. During the execution of a simulation task, calculations and other processes are performed based on the working directory.

[0098] In the simulation platform, the execution of simulation tasks takes place in the working directory corresponding to the simulation task. However, due to the lack of instruction files in the working directory, data cannot be directly extracted from the database. Therefore, a simulation file needs to be created in the working directory to facilitate information transfer between the preset database and the data in the working directory. This also prevents the original data from being accidentally modified or overwritten, maintaining data integrity. Therefore, in one embodiment, determining the simulation file corresponding to the simulation task includes:

[0099] Based on the task identifier, determine the target path corresponding to the simulation task; whereby the task identifier corresponds to the simulation task.

[0100] Create a simulation file based on the target path.

[0101] The task identifier can be the task name, task ID (IDentity), or task number. The task identifier can also be determined by specific simulation parameters, such as input conditions, model configuration, or simulation range, or by the user's login information or username. In some cases, a simulation task may depend on the output of another task; in such cases, the task identifier may be determined based on the dependency relationship.

[0102] Each simulation task has a task identifier. When creating a simulation task based on the simulation conditions, the target path corresponding to the simulation task can be determined by the task identifier. Then, simulation files are created under the target path. Each simulation file corresponds to a simulation task. Finally, the performance indicators corresponding to the simulation conditions are written into the simulation file.

[0103] Performance metrics in simulation files can be stored in the format of "performance parameter: expression: target value: unit". For example, using a .txt file, the content could be "torsional stiffness:>=:1000:N·m". When a simulation task includes multiple sets of performance metrics, these sets are separated by semicolons.

[0104] Simulation files are created in the working directory corresponding to the simulation task. Performance metrics and simulation data obtained from executing the task are stored in this working directory. Each simulation task has its own dedicated working directory, facilitating the management and access of performance metrics and simulation data, and reducing the complexity of data management. Simultaneously, it enables information transfer between a pre-set database and the working directory, achieving systematic management of performance metrics and simulation data, and improving the accuracy of data storage and the efficiency of data entry.

[0105] S13. In the simulation file, the acquired target simulation data is associated with the performance indicators and stored in the preset database.

[0106] The simulation task is executed through a simulation model. After the simulation task is completed, simulation data can be read from the simulation model through post-processing. The simulation data includes multiple simulation result values, such as stress at a specific location on the model and acceleration at a specific time. The target simulation data and performance indicators can be correlated and then stored in a preset database, with the storage time recorded. This achieves automatic correlation, matching, and storage of the simulation task's performance indicators and simulation data, improving the automation efficiency of the simulation platform and the accuracy of data storage.

[0107] To achieve automatic association and matching between performance metrics and simulation data in simulation tasks, a common key value can be found between the performance metrics and simulation data. This key value is then used to automatically match the performance metrics and simulation data, improving the accuracy and efficiency of data matching. Therefore, in one embodiment, the acquired target simulation data is associated with performance metrics in the simulation file and stored in a preset database, including:

[0108] Obtain simulation data obtained from performing simulation tasks; wherein, the simulation data includes a preset correspondence between multiple sets of performance parameters and simulation data, and the performance indicators include target performance parameters and target performance values;

[0109] In the simulation data, based on the target performance parameters, query the target simulation data associated with the performance indicators; whereby the target simulation data includes the target performance parameters and simulation values;

[0110] By using target performance parameters, target simulation data and performance indicators are associated in the simulation file.

[0111] After the simulation task is completed, simulation data can be read from the simulation model through post-processing. The simulation data includes multiple simulation result values, such as stress at a specific location on the model and acceleration at a specific time. The performance index corresponding to the simulation task can be determined from the simulation file. The performance index includes target performance parameters and target performance values. Then, the target performance parameter within the performance index is determined. For example, if the performance index is torsional stiffness >= 1000 N·m, then the target performance parameter is torsional stiffness. Next, the target simulation data in the simulation data is found based on the target performance parameter. Target simulation data includes the target performance parameter and simulation value. For example, by searching for "torsional stiffness" in the simulation file, the target simulation data corresponding to the torsional stiffness in the simulation data output by the simulation model might be 1200.

[0112] After determining the target simulation data corresponding to the target performance parameters, the target simulation data corresponding to the target performance parameters can be associated and stored in the record corresponding to the target performance parameters in the simulation file. Then, the target simulation data can be extracted from the simulation file and stored in the record of the target performance parameters in the preset database.

[0113] Alternatively, an intermediate simulation file can be created in the working directory. The intermediate simulation file can be in .json format. After determining the target simulation data based on the target performance parameters, the target simulation data and performance indicators corresponding to the target performance parameters can be associated and stored in the intermediate simulation file. An example of the content in the intermediate simulation file is shown below:

[0114]

[0115]

[0116] Taking "torsional stiffness" as the target performance parameter as an example, the content of the intermediate simulation file is shown below:

[0117]

[0118] After storing the target simulation data and performance indicators corresponding to the target performance parameters in the intermediate simulation file, the target simulation data and performance indicators can be stored in the record of the target performance parameters in the preset database according to the target performance parameters. Taking Table 4 as an example, the table after storing the target simulation data in the preset database after the simulation task is completed is shown in Table 5:

[0119] Table 5 Preset Database

[0120]

[0121] To reduce manual operation costs and improve the accuracy of determining whether simulation data meets the standards, in one embodiment, after associating the acquired target simulation data with performance indicators and storing it in a preset database in the simulation file, the method further includes:

[0122] Determine the target performance values ​​and target simulation data corresponding to the target performance parameters; among which, performance indicators include target performance values ​​and target performance parameters;

[0123] By comparing the simulated values ​​with the target performance values, and based on the relationship between the simulated values ​​and the target performance values, the compliance information of the target simulation data is determined; the compliance information indicates whether the target simulation data meets the standard, and the target simulation data includes the simulated values.

[0124] The compliance information indicates whether the target simulation data corresponding to a certain performance parameter has reached the target after the simulation task is completed. The performance index is expressed in the form of "performance parameter: expression: performance value: unit", and the target simulation data is expressed in the form of "performance parameter: simulation value". In essence, the performance parameter is a key value, which determines the target performance value and simulation value corresponding to the target performance parameter. Then, based on the relationship between the simulation value and the target performance value, it is determined whether the target simulation data meets the standard. This automatic determination of target simulation data compliance improves the accuracy of compliance assessment while reducing costs and error rates, and also reduces labor costs.

[0125] In one embodiment, comparing the simulated values ​​with the target performance values ​​to determine the compliance information of the target simulation data includes:

[0126] Preset conditions for obtaining target performance values;

[0127] By comparing the simulated values ​​with the target performance values, comparative information is obtained;

[0128] If the comparison information meets the preset compliance conditions, the compliance information is determined to be compliant.

[0129] The preset criteria can be set according to the actual situation, such as greater than or equal to, less than or equal to, or equal to.

[0130] Taking the performance index "torsional stiffness:>=:1000:N·m" in Table 5 as an example, and the target simulation data "torsional stiffness=1200", the target performance parameter is torsional stiffness, the target performance value is 1000, the preset compliance condition for the target performance value is greater than or equal to, and the simulation value is 1200. Comparing the simulation value and the target performance value, the comparison information is "greater than", which meets the preset compliance condition. Therefore, the compliance information for the target simulation data is "compliant", which can be understood as the target simulation data reaching the performance value required by the performance index. The data in the preset database can be automatically updated according to the simulation conditions and performance indexes input in the project, and the simulation data after the simulation task is completed will be automatically judged as compliant. Finally, a simulation performance target achievement table for the entire project will be generated.

[0131] The embodiments provided in this application can achieve systematic management of performance indicators and target simulation data by automatically matching and storing the performance indicators and target simulation data of the simulation task, thereby improving the accuracy of data storage and the efficiency of data entry. It can also improve the accuracy of judging whether the simulation data meets the standards while reducing the cost of manual operation.

[0132] The following is combined with Figure 2 The data storage method will be further explained below:

[0133] In the simulation platform, a simulation project is first created. Then, based on the required vehicle analysis conditions, multiple preset simulation conditions (which can be called analysis items) are extracted from the simulation condition library. These multiple simulation conditions are then written into the simulation project. Since multiple simulation conditions in the simulation project need to be analyzed, a target simulation condition can be arbitrarily selected from the multiple simulation conditions. This target simulation condition is then written into the simulation project. Next, a simulation task is created based on the target simulation condition. Then, based on the preset target correspondence between the simulation condition and performance indicators (which can be called performance targets), intermediate performance indicators corresponding to the target simulation condition are extracted from the second preset correspondence. These intermediate performance indicators are then identified as performance indicators. The data carried in the intermediate performance indicators and the performance indicators are consistent. Finally, the performance indicators corresponding to the target simulation condition are synchronously written into the simulation task. Finally, the target simulation condition and performance indicators are written into the record corresponding to the target simulation condition in the preset database.

[0134] Each simulation task corresponds to a simulation file. The execution of a simulation task includes preprocessing, simulation calculation, and post-processing. All processes are executed within the same shared working directory, although different simulation tasks have different working directories. During the execution of a simulation task, calculations and other processes are performed based on the working directory. Since the database cannot be directly read from the working directory, simulation files need to be created there to facilitate data transfer between the pre-defined database and the working directory. Each simulation task has a task identifier. When creating a simulation task based on the target simulation condition, the task identifier determines the target path, and simulation files are then created within that path. Each simulation file corresponds to one simulation task, and the performance indicators corresponding to the target simulation condition are written into the simulation file.

[0135] The simulation task is executed through a simulation model. After the simulation task is completed, simulation data can be read from the simulation model through post-processing. First, the performance indicators corresponding to the simulation task are determined from the simulation file. The performance indicators include target performance parameters and target performance values. Then, the target performance parameters are determined from the performance indicators. The target simulation data, which includes target performance parameters and simulation values, is then searched for in the simulation data. After determining the target simulation data corresponding to the target performance parameters, the target simulation data corresponding to the target performance parameters is stored in the record corresponding to the target performance parameters in the simulation file. Then, the target simulation data is extracted from the simulation file and stored in the record of the target performance parameters in a preset database. In the preset database, the target performance values ​​and simulation values ​​corresponding to the target performance parameters can be determined. Finally, based on the relationship between the simulation values ​​and the target performance values, it is determined whether the target simulation data meets the standards.

[0136] It should be understood that, although Figure 1 , Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 , Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0137] like Figure 3As shown, this application also provides a data storage system, which includes:

[0138] The first determining module 31 is used to determine the performance indicators of the simulation task to be executed;

[0139] The second determining module 32 is used to determine the simulation file corresponding to the simulation task and store the performance indicators in the simulation file;

[0140] Storage module 33 is used to associate the acquired target simulation data with the performance indicators in the simulation file and store it in a preset database.

[0141] In one embodiment, the performance index of the simulation task to be executed is a vehicle performance index; then the first determining module 31 is further configured to:

[0142] Obtain vehicle simulation conditions;

[0143] Based on the first preset correspondence between the vehicle simulation conditions and the vehicle performance indicators, the vehicle performance indicators are extracted from the vehicle simulation conditions.

[0144] In one embodiment, the first determining module 31 is further configured to:

[0145] Obtain the target simulation conditions;

[0146] The performance indicators are extracted based on the target simulation conditions according to the second preset correspondence between the target simulation conditions and the performance indicators.

[0147] In one embodiment, the second determining module 32 is further configured to:

[0148] Determine the target path corresponding to the simulation task;

[0149] The simulation file is created based on the target path.

[0150] In one embodiment, the performance indicators include target performance parameters and target performance values, and the target simulation data includes the target performance parameters and simulation values; the storage module 33 is further configured to:

[0151] Obtain simulation data obtained from executing the simulation task; wherein, the simulation data includes a preset correspondence between multiple sets of performance parameters and simulation data.

[0152] In the simulation data, based on the target performance parameters, query the target simulation data associated with the performance index;

[0153] The target performance parameters are used to associate the target simulation data and the performance indicators in the simulation file.

[0154] In one embodiment, the data storage system further includes a third determining module, configured to:

[0155] Determine the target performance value and target simulation data corresponding to the target performance parameters; the performance index includes the target performance value and the target performance parameter.

[0156] By comparing the comparative simulation value with the target performance value, the compliance information of the target simulation data is determined; wherein, the compliance information indicates whether the target simulation data meets the standard, and the target simulation data includes the simulation value.

[0157] In one embodiment, the third determining module is further configured to:

[0158] Preset conditions for obtaining the target performance value;

[0159] By comparing the simulated values ​​with the target performance values, comparison information is obtained;

[0160] In response to the comparison information meeting the preset compliance conditions, the compliance information is determined to be compliant.

[0161] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs.

[0162] Figure 4 This is a schematic diagram of the structure of an electronic device according to an example embodiment of this application. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the data storage method described in any of the above embodiments. Figure 4 The electronic device 40 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0163] like Figure 4 As shown, the electronic device 40 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 40 may include, but are not limited to: at least one processor 41, at least one memory 42, and a bus 43 connecting different system components (including memory 42 and processor 41).

[0164] Bus 43 includes a data bus, an address bus, and a control bus.

[0165] The memory 42 may include volatile memory, such as random access memory (RAM) 421 and / or cache memory 422, and may further include read-only memory (ROM) 423.

[0166] The memory 42 may also include a program tool 425 (or utility) having a set (at least one) program module 424, such program module 424 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0167] The processor 41 executes various functional applications and data processing, such as the data storage method provided in any of the above embodiments, by running a computer program stored in the memory 42.

[0168] Electronic device 40 can also communicate with one or more external devices 44 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 45. Furthermore, electronic device 40 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 46. As shown, network adapter 46 communicates with other modules of electronic device 40 via bus 43. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with electronic device 40, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0169] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0170] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the data storage method provided in any of the above embodiments.

[0171] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0172] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the data storage method described in any of the above claims.

[0173] The program code for executing the computer program product of this application can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0174] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0175] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A data storage method, characterized in that, The data storage method includes: Determine the performance metrics for the simulation task to be executed, wherein the performance metrics include target performance parameters and target performance values; A simulation file is created in the working directory corresponding to the simulation task, and the performance indicators are stored in the simulation file; wherein, different simulation tasks correspond to different working directories; Obtain simulation data obtained from executing the simulation task, wherein the simulation data includes a preset correspondence between multiple sets of performance parameters and simulation data; In the simulation data, based on the target performance parameter, target simulation data associated with the performance index is queried, and the target simulation data includes the target performance parameter and the simulation value; Using the target performance parameters, the target simulation data is associated with the performance indicators in the simulation file and stored in a preset database.

2. The data storage method as described in claim 1, characterized in that, The performance metrics for the simulation task to be executed are vehicle performance metrics. The determination of the performance metrics for the simulation task to be executed includes: Obtain vehicle simulation conditions; Based on the first preset correspondence between the vehicle simulation conditions and the vehicle performance indicators, the vehicle performance indicators are extracted from the vehicle simulation conditions.

3. The data storage method as described in claim 1, characterized in that, The determination of performance metrics for the simulation task to be executed includes: Obtain the target simulation conditions; The performance indicators are extracted based on the target simulation conditions according to the second preset correspondence between the target simulation conditions and the performance indicators.

4. The data storage method as described in claim 1, characterized in that, Creating a simulation file in the working directory corresponding to the simulation task includes: Determine the target path corresponding to the simulation task; The simulation file is created based on the target path.

5. The data storage method as described in claim 1, characterized in that, After storing in the preset database, the process also includes: Determine the target performance values ​​and target simulation data corresponding to the target performance parameters; By comparing the simulated values ​​with the target performance values, the compliance information of the target simulation data is determined; wherein, the compliance information indicates whether the target simulation data meets the standard.

6. The data storage method as described in claim 5, characterized in that, The step of comparing the simulated values ​​with the target performance values ​​to determine the compliance information of the target simulation data includes: Preset conditions for obtaining the target performance value; The simulation value and the target performance value are compared in the preset database to obtain comparison information; In response to the comparison information meeting the preset compliance conditions, the compliance information is determined to be compliant.

7. A data storage system, characterized in that, The data storage system includes: The first determining module is used to determine the performance indicators of the simulation task to be executed, the performance indicators including target performance parameters and target performance values; The second determining module is used to create a simulation file in the working directory corresponding to the simulation task and store the performance indicators in the simulation file; wherein, different simulation tasks correspond to different working directories; The storage module is configured to acquire simulation data obtained from executing the simulation task, the simulation data including a preset correspondence between multiple sets of performance parameters and simulation data; it is also configured to query target simulation data associated with the performance index based on the target performance parameter in the simulation data, the target simulation data including the target performance parameter and simulation value; and it is configured to associate the target simulation data with the performance index in the simulation file through the target performance parameter and store it in a preset database.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and for running on the processor, characterized in that, When the processor executes the computer program, it implements the data storage method according to any one of claims 1 to 6.

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

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the data storage method as described in any one of claims 1 to 6.

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