Steering functional safety simulation model construction method, device, medium and equipment

Abstract

The present application provides a method, device, medium and equipment for constructing a steering function safety simulation model, by obtaining a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; based on the characteristic data set, extracting the operating parameters of the target vehicle; based on the operating parameters, calculating the response values ​​corresponding to each group of operating parameters; constructing a steering function safety simulation model based on the characteristic data set and the response values; that is, by obtaining the characteristic data set of the target vehicle, and extracting the operating parameters of the target vehicle based on the characteristic data set, calculating the output value of the steering function safety according to the operating parameters, thereby obtaining a sample combination composed of the characteristic data set and the response value, and constructing a steering function safety simulation model based on the sample combination, so as to realize the rapid construction of the steering function safety simulation model, thereby improving the efficiency of the steering function safety simulation.

Description

Technical Field

[0001] The present application relates to the technical field of automobile steering function safety simulation, and in particular to a method, device, medium and equipment for constructing a steering function safety simulation model. Background Art

[0002] In the process of developing the safety performance of the steering function of automobiles, testing and simulation analysis have become important development means, especially in the early stage of product development, which can provide engineers with solution decisions. Carsim (Vehicle Dynamics Simulation Software) is one of the most widely used simulation tools in the industry for testing and analyzing the performance-based steering function of automobiles. When using Carsim, engineers need to input the performance parameters of various systems of the automobile for calculation, including vehicle size and mass, steering system characteristics, suspension system K&C characteristics, and tire characteristics. In order to verify the effects of different solutions in actual development, it is necessary to re-import the simulation of different parameters into Carsim to generate the model and perform calculations, which requires a lot of repetitive modeling work, thereby reducing work efficiency. Therefore, there is an urgent need for a method to speed up the simulation of automobile steering functions. Summary of the invention

[0003] In order to solve the above technical problems, the present application is proposed. The embodiments of the present application provide a method, device, medium and equipment for constructing a steering functional safety simulation model.

[0004] According to one aspect of the present application, a method for constructing a steering function safety simulation model is provided, including: obtaining a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; based on the characteristic data set, extracting operating parameters of the target vehicle; based on the operating parameters, calculating response values ​​corresponding to each group of operating parameters; wherein each group of operating parameters corresponds to a group of characteristic data, and the response value represents a steering function safety output value corresponding to the operating parameter; based on the characteristic data set and the response value, constructing a steering function safety simulation model.

[0005] In one embodiment, obtaining a characteristic data set of a target vehicle includes: obtaining existing characteristic data of the target vehicle; wherein the existing characteristic data includes a plurality of existing vehicle mass characteristic data, a plurality of existing steering system characteristic data, a plurality of existing suspension system characteristic data and a plurality of existing tire characteristic data; based on the existing characteristic data, generalizing a characteristic data set of the target vehicle; wherein the characteristic data set includes a plurality of vehicle mass characteristic curves, a plurality of steering system characteristic curves, a plurality of suspension system characteristic curves and a plurality of tire characteristic curves, wherein the vehicle mass characteristic curve includes a plurality of vehicle mass characteristic data, the steering system characteristic curve includes a plurality of steering system characteristic data, the suspension system characteristic curve includes a plurality of suspension system characteristic data and the tire characteristic curve includes a plurality of tire characteristic data.

[0006] In one embodiment, the method of generalizing the characteristic data set of the target vehicle based on the existing characteristic data includes: fitting an existing characteristic curve based on the existing characteristic data; calculating an upper limit value and a lower limit value of generalized characteristic data based on the existing characteristic curve; determining physical characteristics of the generalized characteristic data based on the category of the existing characteristic curve; and calculating the generalized characteristic data based on the physical characteristics, upper limit value and lower limit value of the generalized characteristic data.

[0007] In one embodiment, the suspension system characteristic curve includes a loading characteristic curve and an unloading characteristic curve; wherein, the calculating the upper limit value and the lower limit value of the generalized characteristic data based on the existing characteristic curve includes: calculating the upper limit value and the lower limit value of the generalized loading characteristic data based on the existing loading characteristic curve; calculating the upper limit value and the lower limit value of the generalized unloading characteristic data based on the existing unloading characteristic curve; the calculating the generalized characteristic data based on the physical characteristics, upper limit value and lower limit value of the generalized characteristic data includes: calculating the generalized loading characteristic data based on the physical characteristics, upper limit value and lower limit value of the generalized loading characteristic data; calculating the generalized unloading characteristic data based on the physical characteristics, upper limit value and lower limit value of the generalized unloading characteristic data.

[0008] In one embodiment, the calculation of the upper limit value and the lower limit value of the generalized loading characteristic data based on the existing loading characteristic curve includes: shifting the existing loading characteristic curve upward by a first preset proportion to obtain the upper limit value curve of the generalized loading characteristic data; shifting the existing loading characteristic curve downward by a second preset proportion to obtain the lower limit value curve of the generalized loading characteristic data; the calculation of the upper limit value and the lower limit value of the generalized unloading characteristic data based on the existing unloading characteristic curve includes: shifting the existing unloading characteristic curve upward by a third preset proportion to obtain the upper limit value curve of the generalized unloading characteristic data; shifting the existing unloading characteristic curve downward by a fourth preset proportion to obtain the lower limit value curve of the generalized unloading characteristic data.

[0009] In one embodiment, the generalized loading characteristic data is calculated based on the physical characteristics, upper limit and lower limit of the generalized loading characteristic data, including: calculating the starting point and end point of the generalized loading characteristic curve based on the starting point and end point of the existing loading characteristic curve; calculating the middle point of the generalized loading characteristic curve based on the starting point and end point of the generalized loading characteristic curve and the loading characteristic curve; the generalized unloading characteristic data is calculated based on the physical characteristics, upper limit and lower limit of the generalized unloading characteristic data, including: calculating the starting point and end point of the generalized unloading characteristic curve based on the starting point and end point of the existing unloading characteristic curve; calculating the middle point of the generalized unloading characteristic curve based on the starting point and end point of the generalized unloading characteristic curve and the unloading characteristic curve.

[0010] In one embodiment, the suspension system characteristic curve includes a camber angle curve; wherein, the calculating the upper limit value and the lower limit value of the generalized characteristic data based on the existing characteristic curve includes: calculating the upper limit value and the lower limit value of the generalized camber angle data based on the existing camber angle curve; the calculating the generalized characteristic data based on the physical characteristics, the upper limit value and the lower limit value of the generalized characteristic data includes: calculating the generalized camber angle data based on the physical characteristics, the upper limit value and the lower limit value of the camber angle data.

[0011] According to another aspect of the present application, a device for constructing a steering function safety simulation model is provided, including: a characteristic data acquisition module, used to obtain a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; an operating condition parameter extraction module, used to extract the operating condition parameters of the target vehicle based on the characteristic data set; a response value calculation module, used to calculate the response value corresponding to each group of operating condition parameters based on the operating condition parameters; wherein each group of operating condition parameters corresponds to a group of characteristic data, and the response value represents the steering function safety output value corresponding to the operating condition parameter; a simulation model construction module, used to construct a steering function safety simulation model based on the characteristic data set and the response value.

[0012] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute any of the above methods.

[0013] According to another aspect of the present application, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; and the processor is used to execute any of the above-described methods.

[0014] The method, device, medium and equipment for constructing a steering function safety simulation model provided in the present application obtain a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; based on the characteristic data set, the operating parameters of the target vehicle are extracted; based on the operating parameters, the response values ​​corresponding to each group of operating parameters are calculated; wherein each group of operating parameters corresponds to a group of characteristic data, and the response value represents the steering function safety output value corresponding to the operating parameter; based on the characteristic data set and the response value, a steering function safety simulation model is constructed; that is, by obtaining the characteristic data set of the target vehicle, and extracting the operating parameters of the target vehicle based on the characteristic data set, calculating the output value of the steering function safety according to the operating parameters, thereby obtaining a sample combination consisting of the characteristic data set and the response value, and constructing a steering function safety simulation model based on the sample combination, so as to realize the rapid construction of the steering function safety simulation model, thereby improving the efficiency of the steering function safety simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0016] Figure 1 It is a flowchart of a method for constructing a steering function safety simulation model provided by an exemplary embodiment of the present application.

[0017] Figure 2 It is a structural schematic diagram of a loading characteristic curve and an unloading characteristic curve provided by an exemplary embodiment of the present application.

[0018] Figure 3 It is a structural schematic diagram of a camber angle curve provided by an exemplary embodiment of the present application.

[0019] Figure 4 It is a structural schematic diagram of a device for constructing a steering function safety simulation model provided by an exemplary embodiment of the present application.

[0020] Figure 5 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0021] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described here.

[0022] Figure 1 FIG. 1 is a flow chart of a method for constructing a steering function safety simulation model provided by an exemplary embodiment of the present application. Figure 1 As shown, the method for constructing the steering functional safety simulation model includes the following steps:

[0023] Step 110: Obtain a characteristic data set of the target vehicle.

[0024] The characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data. This application uses vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data (including suspension system K&C characteristics) and tire characteristic data as the basic data of the steering function safety simulation model to build and train the steering function safety simulation model.

[0025] Step 120: Extracting operating parameters of the target vehicle based on the characteristic data set.

[0026] To implement simulation in Carsim, it is necessary to establish a whole vehicle model. Therefore, this application combines the whole vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data to construct multiple whole vehicle models (corresponding to different working condition parameters). Specifically, this application can extract working condition parameters by generating a simulation drive file of a certain working condition of automobile steering in Carsim; taking the lateral acceleration index in the step steering working condition as an example, first select a set of data in Carsim to establish a whole vehicle simulation model, set the step working condition parameters and indicator output calculation and generate the analysis drive Par file of the working condition. The file defines the basic working condition information used in the step working condition analysis process and the Par information of each level. The Par files of each level contain the various parameter information of the working condition, so that when the sample is generated through the experimental design for calculation in the future, the relevant parameters of the working condition can be directly called for calculation.

[0027] Step 130: Based on the operating condition parameters, calculate the response value corresponding to each group of operating condition parameters.

[0028] Among them, each set of operating condition parameters corresponds to a set of characteristic data, and the response value represents the steering function safety output value corresponding to the operating condition parameters. This application imports the operating condition parameter update into the Carsim model for calculation, extracts the calculation results to obtain relevant indicators, and forms a vehicle steering function safety response value corresponding to the set of operating condition parameters.

[0029] Step 140: Construct a steering functional safety simulation model based on the characteristic data set and the response value.

[0030] The steering function safety simulation model in this application can be a five-layer neural network model, which uses the above-mentioned characteristic data and corresponding response values ​​as training samples for model training to obtain all weight coefficients of the neural network model. The number of nodes in the input layer is equal to the number of variables (i.e., the number of categories in the characteristic data set), the hidden layer selects the tansig function as the activation function, and the output layer selects the purelin function as the activation function; the number of nodes in the output layer is 1 (i.e., one result is output), and supervised learning training is performed on this model to obtain the weight coefficients of the neural network model, and finally form a steering function safety simulation model.

[0031] The method for constructing a steering function safety simulation model provided in the present application is by obtaining a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; based on the characteristic data set, the operating parameters of the target vehicle are extracted; based on the operating parameters, the response values ​​corresponding to each group of operating parameters are calculated; wherein each group of operating parameters corresponds to a group of characteristic data, and the response value represents the steering function safety output value corresponding to the operating parameter; based on the characteristic data set and the response value, a steering function safety simulation model is constructed; that is, by obtaining the characteristic data set of the target vehicle, and extracting the operating parameters of the target vehicle based on the characteristic data set, calculating the output value of the steering function safety according to the operating parameters, thereby obtaining a sample combination composed of the characteristic data set and the response value, and constructing a steering function safety simulation model based on the sample combination, so as to realize the rapid construction of the steering function safety simulation model, thereby improving the efficiency of the steering function safety simulation.

[0032] In one embodiment, the specific implementation method of the above step 110 can be: obtaining existing characteristic data of the target vehicle; wherein the existing characteristic data includes multiple existing vehicle mass characteristic data, multiple existing steering system characteristic data, multiple existing suspension system characteristic data and multiple existing tire characteristic data; based on the existing characteristic data, generalizing to obtain a characteristic data set of the target vehicle; wherein the characteristic data set includes multiple vehicle mass characteristic curves, multiple steering system characteristic curves, multiple suspension system characteristic curves, and multiple tire characteristic curves, the vehicle mass characteristic curve includes multiple vehicle mass characteristic data, the steering system characteristic curve includes multiple steering system characteristic data, the suspension system characteristic curve includes multiple suspension system characteristic data, and the tire characteristic curve includes multiple tire characteristic data.

[0033] The present application is based on the existing multiple vehicle mass characteristic data, multiple steering system characteristic data, multiple suspension system characteristic data and multiple tire characteristic data, and generalizes them to obtain more vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data, thereby obtaining a characteristic data set.

[0034] In one embodiment, the specific implementation method of the above step 110 can be: based on the existing characteristic data, fitting an existing characteristic curve; based on the existing characteristic curve, calculating the upper limit value and the lower limit value of the generalized characteristic data; based on the category of the existing characteristic curve, determining the physical characteristics of the generalized characteristic data; based on the physical characteristics, upper limit value and lower limit value of the generalized characteristic data, calculating the generalized characteristic data.

[0035] The present application can obtain existing characteristic curves by fitting existing vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data, and calculate the upper limit and lower limit of generalized characteristic data according to the existing characteristic curves, determine the physical characteristics of the existing characteristic curves in combination with their categories, and randomly generate generalized characteristic data in combination with the physical characteristics of the characteristic curves within the range of the upper limit and lower limit to improve the generalization ability and generalization range.

[0036] In one embodiment, the suspension system characteristic curve includes a loading characteristic curve and an unloading characteristic curve; wherein, the specific implementation method of the above step 110 may be: based on the existing loading characteristic curve, calculating the upper limit value and the lower limit value of the generalized loading characteristic data; based on the existing unloading characteristic curve, calculating the upper limit value and the lower limit value of the generalized unloading characteristic data; based on the physical characteristics, upper limit value and lower limit value of the generalized characteristic data, calculating the generalized characteristic data includes: based on the physical characteristics, upper limit value and lower limit value of the generalized loading characteristic data, calculating the generalized loading characteristic data; based on the physical characteristics, upper limit value and lower limit value of the generalized unloading characteristic data, calculating the generalized unloading characteristic data.

[0037] Taking the generalization of suspension system characteristic data as an example, the present application calculates the upper limit and lower limit of the loading characteristic data and the unloading characteristic data respectively based on the existing loading characteristic curve and unloading characteristic curve, and calculates the generalized loading characteristic data according to the physical characteristics, upper limit and lower limit of the generalized loading characteristic data, and calculates the generalized unloading characteristic data according to the physical characteristics, upper limit and lower limit of the generalized unloading characteristic data.

[0038] In one embodiment, the specific implementation method of the above-mentioned step 110 can be: shifting the existing loading characteristic curve upward by a first preset proportion to obtain an upper limit value curve of the generalized loading characteristic data; shifting the existing loading characteristic curve downward by a second preset proportion to obtain a lower limit value curve of the generalized loading characteristic data; based on the existing unloading characteristic curve, calculating the upper limit value and the lower limit value of the generalized unloading characteristic data includes: shifting the existing unloading characteristic curve upward by a third preset proportion to obtain an upper limit value curve of the generalized unloading characteristic data; shifting the existing unloading characteristic curve downward by a fourth preset proportion to obtain a lower limit value curve of the generalized unloading characteristic data.

[0039] The present application determines the upper limit value curve and the lower limit value curve of the generalized loading characteristic data based on the existing loading characteristic curve. For example, the curves obtained by translating the existing loading characteristic curve upward by 20% and downward by 20% can be used as the upper limit value curve and the lower limit value curve respectively, and randomly select values ​​between the upper limit value curve and the lower limit value curve to obtain the generalized loading characteristic data. Similarly, the curves obtained by translating the existing unloading characteristic curve upward by 20% and downward by 20% can be used as the upper limit value curve and the lower limit value curve respectively, and randomly select values ​​between the upper limit value curve and the lower limit value curve to obtain the generalized unloading characteristic data.

[0040] In one embodiment, the specific implementation of the above step 110 may be: based on the starting point and end point of the existing loading characteristic curve, calculating the starting point and end point of the generalized loading characteristic curve; based on the starting point and end point of the generalized loading characteristic curve and the loading characteristic curve, calculating the middle point of the generalized loading characteristic curve; based on the physical characteristics, upper limit value and lower limit value of the generalized unloading characteristic data, calculating the generalized unloading characteristic data includes: based on the starting point and end point of the existing unloading characteristic curve, calculating the starting point and end point of the generalized unloading characteristic curve; based on the starting point and end point of the generalized unloading characteristic curve and the unloading characteristic curve, calculating the middle point of the generalized unloading characteristic curve.

[0041] Specifically, the present application uses the abscissas of the starting point and the end point of the loading characteristic curve as the abscissas of the starting point and the end point of the generalized loading characteristic curve, and randomly obtains the ordinate of the end point of the generalized loading characteristic curve within a first preset range (which may be a specific ratio of the ordinate of the end point of the loading characteristic curve) of the ordinate of the end point of the loading characteristic curve, and randomly obtains the ordinate of the starting point of the generalized loading characteristic curve within a second preset range of the ordinate of the starting point of the loading characteristic curve, wherein the second preset range is positively correlated with the ordinate of the end point of the loading characteristic curve and is positively correlated with the ratio of the first slope and the second slope, wherein the first slope represents the slope of the line connecting the starting point and the first middle point of the loading characteristic curve, and the second slope represents the slope of the line connecting the end point and the last middle point of the loading characteristic curve. Furthermore, according to the starting point and the end point of the generalized loading characteristic curve and the loading characteristic curve, the middle point of the generalized loading characteristic curve is calculated, wherein the middle point of the generalized loading characteristic curve is calculated according to the middle point corresponding to the loading characteristic curve, and the slope of the line connecting each adjacent middle point of the generalized loading characteristic curve is less than the slope of the line connecting the starting point and the end point. Similarly, the starting point, end point and middle point of the unloading characteristic curve can be calculated. The value results are as follows: Figure 2 shown.

[0042] In one embodiment, the suspension system characteristic curve includes a camber angle curve; wherein, the specific implementation method of the above step 110 may be: based on the existing camber angle curve, calculating the upper limit value and the lower limit value of the generalized camber angle data; based on the physical characteristics, the upper limit value and the lower limit value of the generalized characteristic data, calculating the generalized characteristic data includes: based on the physical characteristics, the upper limit value and the lower limit value of the camber angle data, calculating the generalized camber angle data.

[0043] For the camber angle of the suspension system characteristics, this application uses the camber angle value of 1.5° in the Carsim model as a benchmark, sets the upper and lower floating range to ±0.3°, takes the maximum and minimum values ​​that can be achieved as the upper and lower limits, calls the Latin hypercube function for random sampling, and obtains sample results that fall within the range of 1.2° to 1.8°. Specifically, this application calculates the upper and lower limits of generalized camber angle data based on existing camber angle curves. For example, with 0° as the rotation center, clockwise rotation of 20° as the upper limit, and counterclockwise rotation of 20° as the lower limit, the generalized camber angle data and the corresponding curve are obtained by random rotation within the range of the upper and lower limits. The value-taking results are as follows: Figure 3 shown.

[0044] Figure 4 Schematic diagram of a device for constructing a steering function safety simulation model provided by an exemplary embodiment of the present application. Figure 4 As shown, the construction device 40 of the steering function safety simulation model includes: a characteristic data acquisition module 41, used to obtain a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; an operating condition parameter extraction module 42, used to extract the operating condition parameters of the target vehicle based on the characteristic data set; a response value calculation module 43, used to calculate the response value corresponding to each group of operating condition parameters based on the operating condition parameters; wherein each group of operating condition parameters corresponds to a group of characteristic data, and the response value represents the steering function safety output value corresponding to the operating condition parameter; a simulation model construction module 44, used to construct a steering function safety simulation model based on the characteristic data set and the response value.

[0045] The device for constructing a steering function safety simulation model provided in the present application obtains a characteristic data set of a target vehicle through a characteristic data acquisition module 41; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; a working condition parameter extraction module 42 extracts working condition parameters of the target vehicle based on the characteristic data set; a response value calculation module 43 calculates a response value corresponding to each group of working condition parameters based on the working condition parameters; wherein each group of working condition parameters corresponds to a group of characteristic data, and the response value represents the steering function safety output value corresponding to the working condition parameter; a simulation model construction module 44 constructs a steering function safety simulation model based on the characteristic data set and the response value; that is, by obtaining the characteristic data set of the target vehicle, and extracting the working condition parameters of the target vehicle based on the characteristic data set, and calculating the output value of the steering function safety according to the working condition parameters, thereby obtaining a sample combination composed of the characteristic data set and the response value, and constructing a steering function safety simulation model based on the sample combination, so as to realize the rapid construction of the steering function safety simulation model, thereby improving the efficiency of the steering function safety simulation.

[0046] In one embodiment, the characteristic data acquisition module 41 can be further configured to: acquire existing characteristic data of the target vehicle; wherein the existing characteristic data includes a plurality of existing vehicle mass characteristic data, a plurality of existing steering system characteristic data, a plurality of existing suspension system characteristic data and a plurality of existing tire characteristic data; based on the existing characteristic data, generalize and obtain a characteristic data set of the target vehicle; wherein the characteristic data set includes a plurality of vehicle mass characteristic curves, a plurality of steering system characteristic curves, a plurality of suspension system characteristic curves and a plurality of tire characteristic curves, the vehicle mass characteristic curve includes a plurality of vehicle mass characteristic data, the steering system characteristic curve includes a plurality of steering system characteristic data, the suspension system characteristic curve includes a plurality of suspension system characteristic data and the tire characteristic curve includes a plurality of tire characteristic data.

[0047] In one embodiment, the characteristic data acquisition module 41 can be further configured as follows: based on the existing characteristic data, fitting an existing characteristic curve; based on the existing characteristic curve, calculating the upper limit and lower limit of generalized characteristic data; based on the category of the existing characteristic curve, determining the physical characteristics of the generalized characteristic data; based on the physical characteristics, upper limit and lower limit of the generalized characteristic data, calculating the generalized characteristic data.

[0048] In one embodiment, the suspension system characteristic curve includes a loading characteristic curve and an unloading characteristic curve; wherein the characteristic data acquisition module 41 can be further configured as follows: based on the existing loading characteristic curve, calculating the upper limit value and the lower limit value of the generalized loading characteristic data; based on the existing unloading characteristic curve, calculating the upper limit value and the lower limit value of the generalized unloading characteristic data; based on the physical characteristics, upper limit value and lower limit value of the generalized characteristic data, calculating the generalized characteristic data includes: based on the physical characteristics, upper limit value and lower limit value of the generalized loading characteristic data, calculating the generalized loading characteristic data; based on the physical characteristics, upper limit value and lower limit value of the generalized unloading characteristic data, calculating the generalized unloading characteristic data.

[0049] In one embodiment, the characteristic data acquisition module 41 can be further configured as follows: shifting the existing loading characteristic curve upward by a first preset proportion to obtain an upper limit value curve of the generalized loading characteristic data; shifting the existing loading characteristic curve downward by a second preset proportion to obtain a lower limit value curve of the generalized loading characteristic data; based on the existing unloading characteristic curve, calculating the upper limit value and the lower limit value of the generalized unloading characteristic data include: shifting the existing unloading characteristic curve upward by a third preset proportion to obtain an upper limit value curve of the generalized unloading characteristic data; shifting the existing unloading characteristic curve downward by a fourth preset proportion to obtain a lower limit value curve of the generalized unloading characteristic data.

[0050] In one embodiment, the characteristic data acquisition module 41 can be further configured as follows: based on the starting point and end point of the existing loading characteristic curve, the starting point and end point of the generalized loading characteristic curve are calculated; based on the starting point and end point of the generalized loading characteristic curve and the loading characteristic curve, the middle point of the generalized loading characteristic curve is calculated; based on the physical characteristics, upper limit and lower limit of the generalized unloading characteristic data, the generalized unloading characteristic data is calculated, including: based on the starting point and end point of the existing unloading characteristic curve, the starting point and end point of the generalized unloading characteristic curve are calculated; based on the starting point and end point of the generalized unloading characteristic curve and the unloading characteristic curve, the middle point of the generalized unloading characteristic curve is calculated.

[0051] In one embodiment, the suspension system characteristic curve includes a camber angle curve; wherein the characteristic data acquisition module 41 may be further configured as: based on the existing camber angle curve, calculating the upper limit value and the lower limit value of the generalized camber angle data; based on the physical characteristics, the upper limit value and the lower limit value of the generalized characteristic data, calculating the generalized characteristic data includes: based on the physical characteristics, the upper limit value and the lower limit value of the camber angle data, calculating the generalized camber angle data.

[0052] Below, reference Figure 5 The electronic device according to the embodiment of the present application is described. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the collected input signal from them.

[0053] Figure 5 A block diagram of an electronic device according to an embodiment of the present application is illustrated.

[0054] like Figure 5 As shown, the electronic device 10 includes one or more processors 11 and a memory 12 .

[0055] The processor 11 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0056] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage medium.

[0057] In one example, the electronic device 10 may further include: an input device 13 and an output device 14 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0058] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector, which is used to receive the collected input signals from the first device and the second device.

[0059] In addition, the input device 13 may also include, for example, a keyboard, a mouse, and the like.

[0060] The output device 14 can output various information to the outside, including the determined distance information, direction information, etc. The output device 14 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0061] Of course, to simplify, Figure 5 Only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device 10 may also include any other appropriate components.

[0062] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present application described in the above-mentioned "Exemplary Method" section of this specification.

[0063] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0064] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the method according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0065] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0066] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0067] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0068] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0069] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0070] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for constructing a steering functional safety simulation model, characterized in that: include: Acquire a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; Based on the characteristic data set, extracting the operating parameters of the target vehicle; Based on the operating condition parameters, a response value corresponding to each group of operating condition parameters is calculated; wherein each group of operating condition parameters corresponds to a group of characteristic data, and the response value represents a steering function safety output value corresponding to the operating condition parameter; Based on the characteristic data set and the response value, construct a steering function safety simulation model; The step of obtaining a characteristic data set of a target vehicle includes: Acquire existing characteristic data of the target vehicle; wherein the existing characteristic data includes a plurality of existing vehicle mass characteristic data, a plurality of existing steering system characteristic data, a plurality of existing suspension system characteristic data and a plurality of existing tire characteristic data; Based on the existing characteristic data, a characteristic data set of the target vehicle is obtained by generalization; wherein the characteristic data set includes a plurality of vehicle mass characteristic curves, a plurality of steering system characteristic curves, a plurality of suspension system characteristic curves, and a plurality of tire characteristic curves, the vehicle mass characteristic curve includes a plurality of vehicle mass characteristic data, the steering system characteristic curve includes a plurality of steering system characteristic data, the suspension system characteristic curve includes a plurality of suspension system characteristic data, and the tire characteristic curve includes a plurality of tire characteristic data; The characteristic data set of the target vehicle is obtained by generalizing the existing characteristic data, including: Based on the existing characteristic data, fitting to obtain an existing characteristic curve; Based on the existing characteristic curve, calculating the upper limit and lower limit of the generalized characteristic data; Determining the physical characteristics of the generalized characteristic data based on the category of the existing characteristic curve; The generalized characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized characteristic data; The suspension system characteristic curve includes a loading characteristic curve and an unloading characteristic curve; wherein, based on the existing characteristic curve, calculating the upper limit value and the lower limit value of the generalized characteristic data includes: Based on the existing loading characteristic curve, the upper limit and lower limit of the generalized loading characteristic data are calculated; Based on the existing unloading characteristic curve, the upper limit and lower limit of the generalized unloading characteristic data are calculated; The generalized characteristic data is obtained by calculating the generalized characteristic data based on the physical characteristic, the upper limit value and the lower limit value, including: The generalized loading characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized loading characteristic data; The generalized offloading characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized offloading characteristic data.

2. The method for constructing a steering function safety simulation model according to claim 1, characterized in that: The calculating of the upper limit and the lower limit of the generalized loading characteristic data based on the existing loading characteristic curve includes: Shifting the existing loading characteristic curve upward by a first preset ratio to obtain an upper limit value curve of the generalized loading characteristic data; Shifting the existing loading characteristic curve downward by a second preset ratio to obtain a lower limit value curve of the generalized loading characteristic data; The calculating of the upper limit and the lower limit of the generalized unloading characteristic data based on the existing unloading characteristic curve includes: Shifting the existing unloading characteristic curve upward by a third preset ratio to obtain an upper limit value curve of the generalized unloading characteristic data; The existing unloading characteristic curve is translated downward by a fourth preset ratio to obtain a lower limit value curve of the generalized unloading characteristic data.

3. The method for constructing a steering function safety simulation model according to claim 1, characterized in that: The generalized loading characteristic data is obtained by calculating the generalized loading characteristic data based on the physical characteristics, the upper limit value and the lower limit value, including: Based on the starting point and the end point of the existing loading characteristic curve, calculating the starting point and the end point of the generalized loading characteristic curve; Based on the starting point and the end point of the generalized loading characteristic curve and the loading characteristic curve, calculating the middle point of the generalized loading characteristic curve; The generalized offloading characteristic data is obtained by calculating the generalized offloading characteristic data based on the physical characteristics, the upper limit value and the lower limit value, including: Based on the starting point and the end point of the existing unloading characteristic curve, calculating the starting point and the end point of the generalized unloading characteristic curve; Based on the starting point and the end point of the generalized unloading characteristic curve and the unloading characteristic curve, a middle point of the generalized unloading characteristic curve is calculated.

4. The method for constructing a steering function safety simulation model according to claim 1, characterized in that: The suspension system characteristic curve includes a camber angle curve; wherein, based on the existing characteristic curve, calculating the upper limit value and the lower limit value of the generalized characteristic data includes: Based on the existing camber angle curve, the upper limit and lower limit of the generalized camber angle data are calculated; The generalized characteristic data is obtained by calculating the generalized characteristic data based on the physical characteristic, the upper limit value and the lower limit value, including: The generalized camber angle data is calculated based on the physical characteristics, the upper limit value and the lower limit value of the camber angle data.

5. A device for constructing a steering functional safety simulation model, characterized in that: include: A characteristic data acquisition module, used to acquire a characteristic data set of a target vehicle; wherein the characteristic data set includes vehicle mass characteristic data, steering system characteristic data, suspension system characteristic data and tire characteristic data; A working condition parameter extraction module, used for extracting the working condition parameters of the target vehicle based on the characteristic data set; A response value calculation module, used to calculate a response value corresponding to each group of operating condition parameters based on the operating condition parameters; wherein each group of operating condition parameters corresponds to a group of characteristic data, and the response value represents a steering function safety output value corresponding to the operating condition parameter; A simulation model building module, used to build a steering functional safety simulation model based on the characteristic data set and the response value; The characteristic data acquisition module is further configured as follows: Acquire existing characteristic data of the target vehicle; wherein the existing characteristic data includes a plurality of existing vehicle mass characteristic data, a plurality of existing steering system characteristic data, a plurality of existing suspension system characteristic data and a plurality of existing tire characteristic data; Based on the existing characteristic data, a characteristic data set of the target vehicle is obtained by generalization; wherein the characteristic data set includes a plurality of vehicle mass characteristic curves, a plurality of steering system characteristic curves, a plurality of suspension system characteristic curves, and a plurality of tire characteristic curves, the vehicle mass characteristic curve includes a plurality of vehicle mass characteristic data, the steering system characteristic curve includes a plurality of steering system characteristic data, the suspension system characteristic curve includes a plurality of suspension system characteristic data, and the tire characteristic curve includes a plurality of tire characteristic data; The characteristic data acquisition module is further configured as follows: Based on the existing characteristic data, fitting to obtain an existing characteristic curve; Based on the existing characteristic curve, calculating the upper limit and lower limit of the generalized characteristic data; Determining the physical characteristics of the generalized characteristic data based on the category of the existing characteristic curve; The generalized characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized characteristic data; The suspension system characteristic curve includes a loading characteristic curve and an unloading characteristic curve; wherein the characteristic data acquisition module is further configured as follows: Based on the existing loading characteristic curve, the upper limit and lower limit of the generalized loading characteristic data are calculated; Based on the existing unloading characteristic curve, the upper limit and lower limit of the generalized unloading characteristic data are calculated; The generalized loading characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized loading characteristic data; The generalized offloading characteristic data is obtained by calculation based on the physical characteristics, the upper limit value and the lower limit value of the generalized offloading characteristic data.

6. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 4.

7. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is used to execute the method described in any one of claims 1 to 4.

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