CN113343366B - Method for determining main section parameters of vehicle body and related equipment - Google Patents
Method for determining main section parameters of vehicle body and related equipment Download PDFInfo
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- CN113343366B CN113343366B CN202110766142.9A CN202110766142A CN113343366B CN 113343366 B CN113343366 B CN 113343366B CN 202110766142 A CN202110766142 A CN 202110766142A CN 113343366 B CN113343366 B CN 113343366B
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Abstract
The invention provides a method and related equipment for determining main section parameters of a vehicle body, wherein the method for determining the main section parameters of the vehicle body comprises the following steps: in the N groups of sample data, acquiring a characteristic data group in each group of sample data, wherein the characteristic data group comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; constructing a first association model and a second association model based on the N characteristic data sets, wherein the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value; inputting a preset wheelbase value into a first correlation model to obtain a first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value; and inputting the first target value into a second association model to obtain a second target value, wherein the second target value is a parameter value of the main section parameter of the vehicle body corresponding to the first target value. The invention solves the problem of longer development period of the vehicle type.
Description
Technical Field
The invention relates to the technical field of automobile design, in particular to a method for determining main section parameters of an automobile body and related equipment.
Background
When designing a vehicle body structure of a new vehicle type, the main section of the vehicle body is a primary link of forward design of the vehicle body, and the main section directly determines the trend of the whole vehicle body in the future and is a first step for ensuring the correct final design result.
Currently, engineers typically refer to racing vehicles to build body main section models when determining body main section parameters. Because of lacking design basis between the local structure and the overall performance of the vehicle body, the rationality and the accuracy of the design of the performance of the vehicle body cannot be ensured, simulation analysis is required to be carried out on the main section of the vehicle body, and then the main section parameters of the model are repeatedly modified and debugged according to the result of the simulation analysis, so that the problem of longer development period of the vehicle type exists.
Disclosure of Invention
The embodiment of the invention provides a method for determining main section parameters of a vehicle body and related equipment, which are used for solving the problem of long development period of vehicle types.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides a method for determining a main section parameter of a vehicle body, including:
acquiring a characteristic data set in each group of sample data from N groups of sample data, wherein the characteristic data set comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; n is a positive integer;
Constructing a first association model and a second association model based on the N characteristic data sets, wherein the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value;
inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
and inputting the first target value into the second association model to obtain a corresponding second target value, wherein the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
Optionally, the step of inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value includes:
inputting the preset wheelbase value into the first correlation model to obtain a corresponding reference data value;
and determining a numerical value in a target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
Optionally, the first value corresponding to the vehicle body performance parameter includes a first sub-value corresponding to the first sub-performance parameter and a second sub-value corresponding to the second sub-performance parameter;
the step of inputting the preset wheelbase value into the first association model to obtain the corresponding first target value further comprises the following steps:
constructing a third association model based on the N characteristic data sets, wherein the third association model is used for reflecting the association relation between the first sub-value and the second sub-value;
inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
revising a second sub-target value based on the first revised value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
Optionally, the second value corresponding to the main section parameter of the vehicle body comprises a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
the step of inputting the first target value into the second association model to obtain a corresponding second target value further comprises the steps of:
Constructing a fourth association model based on the N characteristic data sets, wherein the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
inputting a third sub-target value into the fourth correlation model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
revising a fourth sub-target value based on the second revised value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value.
In a second aspect, an embodiment of the present invention provides a device for determining a main section parameter of a vehicle body, including:
the acquisition module is used for acquiring a characteristic data set in each group of sample data from N groups of sample data, wherein the characteristic data set comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; n is a positive integer;
the first construction module is used for constructing a first association model and a second association model based on N characteristic data sets, the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value;
The first input module is used for inputting a preset wheelbase value into the first association model to obtain a corresponding first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
and the second input module is used for inputting the first target value into the second association model to obtain a corresponding second target value, wherein the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
Optionally, the first input module includes:
the input unit is used for inputting the preset wheelbase value into the first association model to obtain a corresponding reference data value;
and the determining unit is used for determining the numerical value in the target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
Optionally, the first value corresponding to the vehicle body performance parameter includes a first sub-value corresponding to the first sub-performance parameter and a second sub-value corresponding to the second sub-performance parameter;
The device for determining the main section parameters of the vehicle body further comprises:
the second construction module is used for constructing a third association model based on the N characteristic data sets, and the third association model is used for reflecting the association relation between the first sub-numerical value and the second sub-numerical value;
the third input module is used for inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
a first revision module for revising the second sub-target value based on the first revision value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
Optionally, the second value corresponding to the main section parameter of the vehicle body comprises a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
the device for determining the main section parameters of the vehicle body further comprises:
the third construction module is used for constructing a fourth association model based on the N characteristic data sets, and the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
The fourth input module is used for inputting a third sub-target value into the fourth association model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
a second revision module for revising the fourth sub-target value based on the second revision value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value.
In a third aspect, an embodiment of the present invention provides an electronic device, including a processor, a memory, and a program or an instruction stored in the memory and running on the processor, where the program or the instruction is executed by the processor to implement the steps of the method for determining a main section parameter of a vehicle body.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the above-described method for determining a main section parameter of a vehicle body.
According to the method for determining the main section parameter of the vehicle body, provided by the embodiment, the rule between the parameter value of the performance parameter of the vehicle body and the parameter value of the main section parameter of the vehicle body is obtained according to the processing of the parameters of the existing vehicle type, and the design basis between the local structure of the main section and the overall performance of the vehicle body is provided, so that the parameter value of the main section parameter of the vehicle body determined by the method is more reasonable, the adjustment times of the parameter value of the main section parameter of the vehicle body are reduced, the blind exploration time during the design of the main section of the vehicle body is reduced, the development period of the vehicle type is shortened, and the development cost of the vehicle type is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for determining parameters of a main section of a vehicle body according to an embodiment of the present invention;
FIG. 2 is a schematic structural view of a device for determining parameters of a main section of a vehicle body according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which are derived by a person skilled in the art from the embodiments according to the invention without creative efforts, fall within the protection scope of the invention.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Furthermore, the use of "and/or" in the present application means at least one of the connected objects, such as a and/or B and/or C, means 7 cases including a alone a, B alone, C alone, and both a and B, both B and C, both a and C, and both A, B and C.
As shown in fig. 1, an embodiment of the present application provides a method for determining a main section parameter of a vehicle body, including:
Step 101, acquiring a characteristic data set in each group of sample data from N groups of sample data, wherein the characteristic data set comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; n is a positive integer;
the method provided by the embodiment of the invention is used for determining the main section parameters of the automobile body and is generally applied to the process of automobile design. In the field of this document, an existing vehicle model may be used as a sample, and the sample data refers to values corresponding to various design parameters of the existing vehicle model. The step of obtaining the characteristic data set in each set of the sample data can be understood as obtaining a first value corresponding to the wheel base and the vehicle body performance parameter of each existing vehicle type and a second value corresponding to the main section parameter of the vehicle body. In this embodiment, N is a positive integer, and the value of N indicates the number of samples, that is, the number of existing vehicle types.
It should be appreciated that the vehicle body performance parameters include at least one of: bending stiffness, torsional stiffness and body-in-white weight. For convenience of description, the bending stiffness, torsional stiffness and body-in-white weight may also be referred to as sub-performance parameters hereinafter. The values corresponding to each of the sub-performance parameters may be the same or different. In some embodiments, the vehicle body performance parameter further includes the wheelbase, i.e., the wheelbase may also be the sub-performance parameter.
It should be appreciated that the body main section parameters include at least one of: the cross-sectional area, the closed area, the primary moment of inertia of the first primary axis of inertia, the primary moment of inertia of the second primary axis of inertia, the cross-sectional modulus of elasticity of the first primary axis of inertia, and the cross-sectional modulus of elasticity of the second primary axis of inertia. For convenience of description, the cross-sectional area, the closed area, the main moment of inertia of the first main axis of inertia, the main moment of inertia of the second main axis of inertia, the cross-sectional elastic modulus of the first main axis of inertia, and the cross-sectional elastic modulus of the second main axis of inertia may also be referred to as sub-main cross-sectional parameters hereinafter. The values corresponding to the sub-main section parameters of each item can be the same or different.
102, constructing a first association model and a second association model based on N characteristic data sets, wherein the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value;
in general, a model refers to a formalized expression form after abstracting a certain actual problem or objective thing, law. The specific form of the first correlation model and the specific form of the second correlation model are not limited herein.
In some embodiments, the first correlation model is a mathematical model that reflects the correlation of the wheelbase and the first value by an equation. Wherein constructing a first correlation model based on the N sets of characteristic data may be understood as: first, a rectangular coordinate system is established, the axis distance is represented by the horizontal axis of the rectangular coordinate system, and the first numerical value is represented by the vertical axis of the rectangular coordinate system. Thus, each of the feature data sets may correspond to a point in a rectangular coordinate system. For example, if the wheelbase in the first feature data set is A1, the first value is B1, the wheelbase in the second feature data set is A2, and the first value is B2, then in the rectangular coordinate system, the point with coordinates (A1, B1) is the point corresponding to the first feature data set, and the point with coordinates (A2, B2) is the point corresponding to the second feature data set. It is known that the N feature data sets may correspond to N points in the rectangular coordinate system. And fitting N points in a rectangular coordinate system corresponding to the N characteristic data sets to obtain a corresponding fitting equation, wherein the fitting equation is used for reflecting the association relation between the wheelbase and the first numerical value. According to the difference of fitting precision and the difference of the number of the characteristic data sets, the line correspondingly described by the fitting equation can be a curve or a straight line. Of course, in a specific implementation, the first value may be represented by a horizontal axis of a rectangular coordinate system, and the wheelbase may be represented by a vertical axis of the rectangular coordinate system.
It should be understood that, in some embodiments, the vehicle body performance parameter includes a plurality of sub-performance parameters, and thus, the constructing a first correlation model based on the N feature data sets may be understood as constructing a first sub-correlation model based on the wheelbase and the corresponding numerical value of the sub-performance parameter in the N feature data sets, where each of the first sub-correlation models is used to reflect the correlation relationship between the wheelbase and each of the corresponding sub-performance parameters.
In some embodiments, the second correlation model is a mathematical model, the second correlation model reflecting the correlation of the wheelbase and the second numerical value by an equation. Wherein constructing a second correlation model based on the N sets of characteristic data may be understood as: first, a rectangular coordinate system is established, the axis distance is represented by the horizontal axis of the rectangular coordinate system, and the second numerical value is represented by the vertical axis of the rectangular coordinate system. Thus, each of the feature data sets may correspond to a point in a rectangular coordinate system. For example, if the wheelbase in the first feature data set is A1, the second value is C1, the wheelbase in the second feature data set is A2, and the second value is C2, in the rectangular coordinate system, the point with coordinates (A1, C1) is the point corresponding to the first feature data set, and the point with coordinates (A2, C2) is the point corresponding to the second feature data set. It is known that the N feature data sets may correspond to N points in the rectangular coordinate system. And fitting N points in a rectangular coordinate system corresponding to the N characteristic data sets to obtain a corresponding fitting equation, wherein the fitting equation is used for reflecting the association relation between the wheelbase and the second numerical value. According to the difference of fitting precision and the difference of the number of the characteristic data sets, the line correspondingly described by the fitting equation can be a curve or a straight line. Of course, in a specific implementation, the second value may be represented by a horizontal axis of a rectangular coordinate system, and the wheelbase may be represented by a vertical axis of the rectangular coordinate system.
It should be understood that, in some embodiments, the main section parameter of the vehicle body includes a plurality of sub-main section parameters, so that the constructing a second correlation model based on the N feature data sets may be understood as constructing a second sub-correlation model based on the wheelbase in the N feature data sets and the corresponding value of the sub-main section parameter, where each of the second sub-correlation models is used to reflect the correlation relationship between the wheelbase and each of the corresponding sub-main section parameters.
Step 103, inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
it should be understood that, in designing a vehicle body, the wheelbase is generally predefined, where the specific value of the preset wheelbase value is not limited herein.
The first association model is used for reflecting the association relation between the wheelbase and the first numerical value, so that after a preset wheelbase value is used as an input variable to be input into the first association model, a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value, namely the first target value, can be calculated according to the association relation between the wheelbase and the first numerical value.
Under the condition that the fitting equation is used in the first correlation model to reflect the correlation relationship between the wheelbase and the first numerical value, the inputting the preset wheelbase value into the first correlation model to obtain the corresponding first target value can be understood as follows: substituting the preset wheelbase value as an input value into the fitting equation, and calculating the output value as the corresponding first target value.
It should be understood that, in some embodiments, the vehicle body performance parameter includes a plurality of sub-performance parameters, and the inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value may be understood that inputting a preset wheelbase value into the first sub-correlation model obtains a corresponding first sub-target value, where the first sub-target value is a parameter value of the sub-performance parameter corresponding to the preset wheelbase value. In this step, the first sub-target value corresponding to each sub-performance parameter should be obtained according to the preset wheelbase value and the corresponding first sub-association model.
And 104, inputting the first target value into the second association model to obtain a corresponding second target value, wherein the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
The second correlation model is configured to reflect the correlation between the first value and the second value, so after the first target value obtained in the step 103 is input into the first correlation model as an input variable, a parameter value of the main section parameter of the vehicle body corresponding to the first target value, that is, the second target value, may be calculated according to the correlation between the first value and the second value.
In the case that the fitting equation is used in the second correlation model to reflect the correlation between the first value and the second value, the inputting the first target value into the second correlation model to obtain the corresponding second target value may be understood as: substituting the first target value as an input value into the fitting equation, and calculating the output value as the corresponding second target value.
It should be understood that, in some embodiments, the main section parameter of the vehicle body includes a plurality of sub-main section parameters, and the inputting the first target value into the second correlation model to obtain a corresponding second target value may be understood that inputting the first target value into the second sub-correlation model obtains a corresponding second sub-target value, where the second sub-target value is a parameter value of the sub-main section parameter corresponding to the first target value. In this step, the second sub-target value corresponding to each sub-main section parameter should be obtained according to the first target value and the corresponding second sub-association model.
According to the method for determining the main section parameter of the vehicle body, firstly, the association relation between the wheelbase and the parameter value of the vehicle body performance parameter is obtained through the data of the existing vehicle type, meanwhile, the association relation between the parameter value of the vehicle body performance parameter and the parameter value of the main section parameter of the vehicle body is obtained, and a reference rule is provided for determining the parameter value of the main section parameter of the vehicle body. And then calculating the parameter value of the vehicle body performance parameter through the preset wheelbase value and the first correlation model, and then calculating the parameter value of the main section parameter of the vehicle body according to the vehicle body performance parameter and the second correlation model.
According to the method for determining the main section parameter of the vehicle body, provided by the embodiment, the rule between the parameter value of the performance parameter of the vehicle body and the parameter value of the main section parameter of the vehicle body is obtained according to the processing of the parameters of the existing vehicle type, and the design basis between the local structure of the main section and the overall performance of the vehicle body is provided, so that the parameter value of the main section parameter of the vehicle body determined by the method is more reasonable, the adjustment times of the parameter value of the main section parameter of the vehicle body are reduced, the blind exploration time during the design of the main section of the vehicle body is reduced, the development period of the vehicle type is shortened, and the development cost of the vehicle type is reduced.
Optionally, the step 103 includes:
inputting the preset wheelbase value into the first correlation model to obtain a corresponding reference data value;
and inputting the preset wheelbase value into the first correlation model, and calculating to obtain a parameter value of the vehicle body performance parameter corresponding to the preset wheelbase value, namely the reference data value, according to the first correlation model. In the case where the fitting equation is used in the second correlation model to reflect the correlation between the first numerical value and the second numerical value, the reference data value obtained is typically a single numerical value.
And determining a numerical value in a target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
It should be understood that the specific value of the first preset value is not limited herein. In some embodiments, the first preset value ranges from 5% to 10% of the first target value multiplied by a first adjustment value. The specific value of the second preset value is not limited herein. In some embodiments, the second preset value ranges from 5% to 10% of the second target value multiplied by a second adjustment value. Wherein the first adjustment value and the second adjustment value may be the same or different. The first adjustment values corresponding to different sub-performance parameters may be the same or different, and the second adjustment values corresponding to different sub-performance parameters may be the same or different.
In this embodiment, a value in a target section corresponding to the reference data value is determined as the first target value. Because the first target value is all the values in the target interval, the value range of the first target value is enlarged, so that the value of the first target value can be adjusted according to different bearing type and non-bearing type vehicle body types when the vehicle is in specific implementation.
Optionally, the first value corresponding to the vehicle body performance parameter includes a first sub-value corresponding to the first sub-performance parameter and a second sub-value corresponding to the second sub-performance parameter;
after the step 103, the method further includes:
constructing a third association model based on the N characteristic data sets, wherein the third association model is used for reflecting the association relation between the first sub-value and the second sub-value;
in some embodiments, the third correlation model is a mathematical model that reflects the correlation of the first and second sub-values by an equation. Wherein constructing a third correlation model based on the N sets of characteristic data may be understood as: firstly, a rectangular coordinate system is established, a horizontal axis of the rectangular coordinate system is used for representing the first sub-value, and a vertical axis of the rectangular coordinate system is used for representing the second sub-value. Thus, each of the feature data sets may correspond to a point in a rectangular coordinate system. For example, if the first sub-value in the first feature data set is D1, the second sub-value is E1, and the first sub-value in the second feature data set is D2, and the second sub-value is E2, in the rectangular coordinate system, the point with coordinates (D1, E1) is the point corresponding to the first feature data set, and the point with coordinates (D2, E2) is the point corresponding to the second feature data set. It is known that the N feature data sets may correspond to N points in the rectangular coordinate system. And fitting N points in the rectangular coordinate system corresponding to the N characteristic data sets to obtain a corresponding fitting equation, wherein the fitting equation is used for reflecting the association relation between the first sub-numerical value and the second sub-numerical value. According to the difference of fitting precision and the difference of the number of the characteristic data sets, the line correspondingly described by the fitting equation can be a curve or a straight line. Of course, in a specific implementation, the second sub-value may be represented by a horizontal axis of a rectangular coordinate system, and the first sub-value may be represented by a vertical axis of the rectangular coordinate system.
It should be appreciated that the first sub-performance parameter is any one of the sub-performance parameters and the second sub-performance parameter is any one of the sub-performance parameters other than the first sub-performance parameter. The third correlation model is different according to the difference between the first sub-performance parameter and the second sub-performance parameter.
Inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
it should be appreciated that the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, which may be calculated in the previous step.
The third correlation model is configured to reflect the correlation between the first sub-value and the second sub-value, so after the first sub-target value obtained in the previous step is input into the third correlation model as an input variable, a parameter value of the second sub-performance parameter corresponding to the first sub-target value, that is, the first revision value, may be calculated according to the correlation between the first sub-value and the second sub-value.
Revising a second sub-target value based on the first revised value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
It should be understood that the specific modification manner of the second sub-target value based on the first modification value is not limited herein. For example, in one embodiment, the modification may be performed by replacing the second sub-target value one by one using the first revision value. In another embodiment, the modification may be performed by replacing the original second sub-target value with data in the intersection of the first modification value and the second sub-target value.
In this embodiment, the rule between the parameter values of any two sub-performance parameters is obtained and a third correlation model is constructed according to the processing of the parameter values of the parameters of the existing vehicle model. By revising the second sub-target value based on the first revised value, the parameter value of the second sub-performance parameter is optimized, and the reliability of the parameter value of the sub-performance parameter is improved.
Optionally, the second value corresponding to the main section parameter of the vehicle body comprises a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
After the step 104, the method further includes:
constructing a fourth association model based on the N characteristic data sets, wherein the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
in some embodiments, the fourth correlation model is a mathematical model, the fourth correlation model reflecting the correlation of the third and fourth sub-values by an equation. Wherein constructing a fourth correlation model based on the N sets of characteristic data may be understood as: firstly, a rectangular coordinate system is established, a horizontal axis of the rectangular coordinate system is used for representing the third sub-value, and a vertical axis of the rectangular coordinate system is used for representing the fourth sub-value. Thus, each of the feature data sets may correspond to a point in a rectangular coordinate system. For example, if the third sub-value in the first feature data set is F1, the fourth sub-value is G1, the third sub-value in the second feature data set is F2, and the fourth sub-value is G2, then in the rectangular coordinate system, the point with coordinates (F1, G1) is the point corresponding to the first feature data set, and the point with coordinates (F2, G2) is the point corresponding to the second feature data set. It is known that the N feature data sets may correspond to N points in the rectangular coordinate system. And fitting N points in a rectangular coordinate system corresponding to the N characteristic data sets to obtain a corresponding fitting equation, wherein the fitting equation is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value. According to the difference of fitting precision and the difference of the number of the characteristic data sets, the line correspondingly described by the fitting equation can be a curve or a straight line. Of course, in the specific implementation, the fourth sub-value may be represented by a horizontal axis of the rectangular coordinate system, and the third sub-value may be represented by a vertical axis of the rectangular coordinate system.
It should be understood that the first sub-main section parameter is any one of the sub-main section parameters, and the second sub-main section parameter is any one of the sub-main section parameters other than the first sub-main section parameter. And according to the difference between the first sub-main section parameter and the second sub-main section parameter, the fourth correlation model is also different.
Inputting a third sub-target value into the fourth correlation model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
it should be appreciated that the third sub-target value is a parameter value of the first sub-main section parameter corresponding to the first target value, which may be calculated in the previous step.
The fourth correlation model is configured to reflect the correlation between the third sub-value and the fourth sub-value, so after the third sub-target value obtained in the previous step is input into the fourth correlation model as an input variable, the parameter value of the second sub-main section parameter corresponding to the third sub-target value, that is, the second revised value, may be calculated according to the correlation between the third sub-value and the fourth sub-value.
Revising a fourth sub-target value based on the second revised value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value. It should be understood that the specific modification manner of the fourth sub-target value based on the second modification value is not limited herein. For example, in one embodiment, the modification may be performed by replacing the fourth sub-target value one by one using the second revision value. In another embodiment, the modification may be performed by replacing the original fourth sub-target value with data in the intersection of the second modification value and the fourth sub-target value.
In this embodiment, a rule between parameter values of any two sub-main section parameters is obtained and a fourth correlation model is constructed according to processing the parameter values of the parameters of the existing vehicle model. And revising a fourth sub-target value based on the second revised value to optimize the parameter value of the fourth sub-main section parameter, thereby improving the reliability of the parameter value of the sub-performance parameter.
As shown in fig. 2, an embodiment of the present invention provides a device 200 for determining a main section parameter of a vehicle body, including:
The acquiring module 201 is configured to acquire, from N sets of sample data, a feature data set in each set of sample data, where the feature data set includes a wheelbase, a first value corresponding to a vehicle body performance parameter, and a second value corresponding to a vehicle body main section parameter; n is a positive integer;
a first construction module 202, configured to construct a first association model and a second association model based on N feature data sets, where the first association model is used to reflect an association relationship between the wheelbase and the first numerical value, and the second association model is used to reflect an association relationship between the first numerical value and the second numerical value;
the first input module 203 is configured to input a preset wheelbase value into the first correlation model, to obtain a corresponding first target value, where the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
and a second input module 204, configured to input the first target value into the second correlation model, to obtain a corresponding second target value, where the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
Optionally, the first input module 203 includes:
the input unit is used for inputting the preset wheelbase value into the first association model to obtain a corresponding reference data value;
And the determining unit is used for determining the numerical value in the target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
Optionally, the first value corresponding to the vehicle body performance parameter includes a first sub-value corresponding to the first sub-performance parameter and a second sub-value corresponding to the second sub-performance parameter;
the apparatus 200 for determining a main section parameter of a vehicle body further includes:
the second construction module is used for constructing a third association model based on the N characteristic data sets, and the third association model is used for reflecting the association relation between the first sub-numerical value and the second sub-numerical value;
the third input module is used for inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
a first revision module for revising the second sub-target value based on the first revision value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
Optionally, the second value corresponding to the main section parameter of the vehicle body comprises a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
the apparatus 200 for determining a main section parameter of a vehicle body further includes:
the third construction module is used for constructing a fourth association model based on the N characteristic data sets, and the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
the fourth input module is used for inputting a third sub-target value into the fourth association model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
a second revision module for revising the fourth sub-target value based on the second revision value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value.
The device 200 for determining the main section parameter of the vehicle body provided by the embodiment of the present application can implement each process implemented in the method embodiment of fig. 1, and achieve the same beneficial effects, and in order to avoid repetition, the description is omitted here.
As shown in fig. 3, an embodiment of the present invention provides an electronic device 300, including a processor 302, a memory 301, and a program or an instruction stored in the memory 301 and capable of running on the processor 302, where the program or the instruction implements each process of the above embodiment of the method for determining a main section parameter of a vehicle body when executed by the processor 302, and the process can achieve the same technical effect, so that repetition is avoided, and no further description is given here.
The embodiment of the invention provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements each process of the above embodiment of the method for determining the main section parameter of the vehicle body, and can achieve the same technical effects, so that repetition is avoided, and no further description is given here. Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium such as a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
The embodiment of the present invention further provides a program product, where the program product is stored in a nonvolatile storage medium, and the program product is executed by at least one processor to implement each process of the above embodiment of the method for determining a main section parameter of a vehicle body, and the same technical effects can be achieved, so that repetition is avoided, and no redundant description is given here.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
Claims (10)
1. A method for determining main section parameters of a vehicle body is characterized by comprising the following steps:
acquiring a characteristic data set in each group of sample data from N groups of sample data, wherein the characteristic data set comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; n is a positive integer;
constructing a first association model and a second association model based on the N characteristic data sets, wherein the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value;
inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
And inputting the first target value into the second association model to obtain a corresponding second target value, wherein the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
2. The method according to claim 1, wherein the step of inputting a preset wheelbase value into the first correlation model to obtain a corresponding first target value includes:
inputting the preset wheelbase value into the first correlation model to obtain a corresponding reference data value;
and determining a numerical value in a target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
3. The method of claim 1, wherein the first value for the vehicle body performance parameter comprises a first sub-value for a first sub-performance parameter and a second sub-value for a second sub-performance parameter;
the step of inputting the preset wheelbase value into the first association model to obtain the corresponding first target value further comprises the following steps:
Constructing a third association model based on the N characteristic data sets, wherein the third association model is used for reflecting the association relation between the first sub-value and the second sub-value;
inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
revising a second sub-target value based on the first revised value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
4. The method of claim 1, wherein the second value corresponding to the main section parameter of the vehicle body comprises a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
the step of inputting the first target value into the second association model to obtain a corresponding second target value further comprises the steps of:
constructing a fourth association model based on the N characteristic data sets, wherein the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
Inputting a third sub-target value into the fourth correlation model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
revising a fourth sub-target value based on the second revised value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value.
5. A device for determining a main section parameter of a vehicle body, comprising:
the acquisition module is used for acquiring a characteristic data set in each group of sample data from N groups of sample data, wherein the characteristic data set comprises a first numerical value corresponding to a wheel base and a vehicle body performance parameter and a second numerical value corresponding to a vehicle body main section parameter; n is a positive integer;
the first construction module is used for constructing a first association model and a second association model based on N characteristic data sets, the first association model is used for reflecting the association relation between the wheelbase and the first numerical value, and the second association model is used for reflecting the association relation between the first numerical value and the second numerical value;
The first input module is used for inputting a preset wheelbase value into the first association model to obtain a corresponding first target value, wherein the first target value is a parameter value of a vehicle body performance parameter corresponding to the preset wheelbase value;
and the second input module is used for inputting the first target value into the second association model to obtain a corresponding second target value, wherein the second target value is a parameter value of a main section parameter of the vehicle body corresponding to the first target value.
6. The apparatus for determining a main section parameter of a vehicle body according to claim 5, wherein the first input module includes:
the input unit is used for inputting the preset wheelbase value into the first association model to obtain a corresponding reference data value;
and the determining unit is used for determining the numerical value in the target interval corresponding to the reference data value as the first target value, wherein the difference value between the maximum value of the target interval and the reference data value is smaller than or equal to a first preset value, and the absolute value of the difference value between the minimum value of the target interval and the reference data value is smaller than or equal to a second preset value.
7. The apparatus for determining a main section parameter of a vehicle body according to claim 5, wherein the first numerical value corresponding to the vehicle body performance parameter includes a first sub-numerical value corresponding to a first sub-performance parameter and a second sub-numerical value corresponding to a second sub-performance parameter;
The device for determining the main section parameters of the vehicle body further comprises:
the second construction module is used for constructing a third association model based on the N characteristic data sets, and the third association model is used for reflecting the association relation between the first sub-numerical value and the second sub-numerical value;
the third input module is used for inputting the first sub-target value into the third association model to obtain a first revised value; the first sub-target value is a parameter value of a first sub-performance parameter corresponding to the preset wheelbase value, and the first revised value is a parameter value of a second sub-performance parameter corresponding to the first sub-target value;
a first revision module for revising the second sub-target value based on the first revision value; the second sub-target value is a parameter value of a second sub-performance parameter corresponding to the preset wheelbase value.
8. The apparatus according to claim 5, wherein the second value corresponding to the main section parameter of the vehicle body includes a third sub-value corresponding to the first sub-main section parameter and a fourth sub-value corresponding to the second sub-main section parameter;
the device for determining the main section parameters of the vehicle body further comprises:
the third construction module is used for constructing a fourth association model based on the N characteristic data sets, and the fourth association model is used for reflecting the association relation between the third sub-numerical value and the fourth sub-numerical value;
The fourth input module is used for inputting a third sub-target value into the fourth association model to obtain a second revised value; the third sub-target value is a parameter value of a first sub-main section parameter corresponding to the first target value, and the second revised value is a parameter value of a second sub-main section parameter corresponding to the third sub-target value;
a second revision module for revising the fourth sub-target value based on the second revision value; the fourth sub-target value is a parameter value of a second sub-main section parameter corresponding to the first target value.
9. An electronic device comprising a processor, a memory and a program or instruction stored on the memory and running on the processor, which when executed by the processor, implements the steps of the method of any of claims 1-4.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-4.
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