CN116148104A - Method and equipment for determining load spectrum of wheel double-shaft fatigue test based on actual working condition - Google Patents
Method and equipment for determining load spectrum of wheel double-shaft fatigue test based on actual working condition Download PDFInfo
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- 238000001228 spectrum Methods 0.000 title claims abstract description 50
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000009661 fatigue test Methods 0.000 title claims abstract description 40
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- 230000006378 damage Effects 0.000 claims description 51
- 230000006870 function Effects 0.000 claims description 16
- 241000039077 Copula Species 0.000 claims description 15
- 238000009825 accumulation Methods 0.000 claims description 14
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- 241000894007 species Species 0.000 claims description 2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/32—Investigating strength properties of solid materials by application of mechanical stress by applying repeated or pulsating forces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
- G01M17/013—Wheels
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/0001—Type of application of the stress
- G01N2203/0005—Repeated or cyclic
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/0058—Kind of property studied
- G01N2203/0069—Fatigue, creep, strain-stress relations or elastic constants
- G01N2203/0073—Fatigue
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/02—Details not specific for a particular testing method
- G01N2203/026—Specifications of the specimen
- G01N2203/0262—Shape of the specimen
- G01N2203/0274—Tubular or ring-shaped specimens
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Abstract
The invention relates to the field of automobile fatigue tests, and discloses a method and equipment for determining a load spectrum of a wheel double-shaft fatigue test based on actual working conditions. The method comprises the following steps: firstly, defining, dividing and counting working conditions affecting the wheel hub load by acquiring actual running big data of a target user group vehicle or questionnaire investigation; and then, complete and accurate load information is supplemented through road load data acquisition with high sampling rate, and finally, the association of the wheel double-shaft fatigue test load spectrum and the actual use working condition of a specific target user group is realized. The problem that a test load spectrum in the wheel double-shaft fatigue test deviates from a load spectrum born by the wheel in a real environment is solved, the fault recurrence rate and the fault interception rate of the wheel double-shaft fatigue test are improved, and the method has important significance for improving the reliability, quality and quality of a wheel hub structure.
Description
Technical Field
The invention relates to the field of automobile fatigue tests, in particular to a method and equipment for determining a load spectrum of a wheel double-shaft fatigue test based on actual working conditions.
Background
Wheel hubs are important parts of vehicles, and their durability and reliability are directly related to the safety of the occupants of the vehicle. In order to improve and ensure the durability and reliability of the wheel hub of the vehicle, a wheel double-shaft fatigue test needs to be implemented and carried out in the vehicle engineering, and fatigue damage accumulated by the wheel hub in the actual running process of the vehicle is reproduced in the test, so that the test and examination of the durability and reliability of the wheel hub structure are completed.
However, because the load borne by the wheel hub is complex in form during the running process of the vehicle, the accumulation and formation mechanism of the fatigue damage of the wheel hub is complex, and particularly, the actual use environment, scene and working condition of the wheel hub are complex and changeable for a specific use target user group, so that the load process borne by the wheel hub presents great statistical variability. Therefore, a technical process with engineering realizability is lacking to accurately and objectively describe and quantify the fatigue damage of the wheel hub associated with the actual use working condition of a specific target user group, and the reasonable programming of the wheel biaxial fatigue test load spectrum and the test acceleration form restriction and obstacle.
In view of this, the present invention has been made.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and equipment for determining a wheel double-shaft fatigue test load spectrum based on actual working conditions, provides a feasible technical route, acquires the wheel double-shaft fatigue test load spectrum related to actual use working conditions of a specific target user group, solves the problem that the test load spectrum in the wheel double-shaft fatigue test deviates from the load spectrum born by the wheel in the actual environment, improves the fault recurrence rate and the fault interception rate of the wheel double-shaft fatigue test, and ensures the reliability of a wheel hub structure.
The embodiment of the invention provides a method for determining a load spectrum of a wheel double-shaft fatigue test based on actual working conditions, which comprises the following steps:
s1, acquiring actual running data of vehicles of a target user group;
s2, carrying out statistical analysis on the actual operation data to obtain the mean value and the variance of the duty ratio of various working conditions associated with the target user group and the correlation coefficient between the duty ratio of the mth working condition and the nth working condition;
s3, determining radial force and axial force born by the wheel hub structure under various working conditions;
s4, carrying out statistical analysis on the radial force and the axial force born by the wheel hub structure under various working conditions to obtain the driving mileage corresponding to the biaxial load of the wheel under the working condition corresponding to the preset mileage;
s5, calculating the number of damages formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage according to the driving mileage corresponding to the biaxial loads of the wheels under the working condition corresponding to the preset mileage;
s6, repeating the steps S4 and S5, obtaining a plurality of damage numbers formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage, and determining the mean value and the variance of the damage numbers based on the damage numbers;
s7, determining statistical digital characteristics of the damage number formed by accumulation of the biaxial loads of the wheels associated with the actual use working conditions of the target user group according to the mean value and the variance of the duty ratios of the working conditions in the step S2 and the correlation coefficient between the duty ratios of the m working condition and the n working condition, and the mean value and the variance of the damage number in the step S6, and determining the target damage number based on the statistical digital characteristics;
and S8, determining a load spectrum of the biaxial fatigue test of the wheel by taking the target damage number as a recurrence target.
The embodiment of the invention provides electronic equipment, which comprises:
a processor and a memory;
the processor is used for executing the step of the method for determining the load spectrum of the wheel biaxial fatigue test based on the actual working condition according to any embodiment by calling the program or the instruction stored in the memory.
The embodiment of the invention provides a computer readable storage medium, which stores a program or instructions for causing a computer to execute the steps of the method for determining the load spectrum of the wheel biaxial fatigue test based on the actual working condition according to any embodiment.
The method for determining the load spectrum of the wheel double-shaft fatigue test based on the actual working condition provided by the embodiment of the invention provides a feasible technical route, obtains the load spectrum of the wheel double-shaft fatigue test associated with the actual working condition of a specific target user group, solves the problem that the test load spectrum in the wheel double-shaft fatigue test deviates from the load spectrum born by the wheel in the actual environment, improves the fault reproduction rate and the fault interception rate of the wheel double-shaft fatigue test, and ensures the reliability of the wheel hub structure.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for determining a load spectrum of a wheel biaxial fatigue test based on actual working conditions, which is provided by the embodiment of the invention;
FIG. 2 is a schematic diagram of a fitting result of a binary normal Copula density function of radial force and axial force applied to a wheel hub structure under the working condition according to the 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
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the invention, are within the scope of the invention.
Referring to fig. 1, a flow chart of a method for determining a load spectrum of a biaxial fatigue test of a wheel based on actual working conditions is provided in an embodiment of the present invention, and the method includes the following steps:
s1, acquiring actual running data of vehicles of a target user group.
Illustratively, the S1 includes:
s11, installing data acquisition and recording equipment on a sample vehicle;
s12, putting the sample vehicle provided with the data acquisition and recording equipment into the target user group;
s13, acquiring and recording actual operation data through the data acquisition and recording equipment in the process of using the sample vehicle by the target user group, wherein the actual operation data at least comprises one or more of Global Positioning System (GPS) data, steering wheel corner data and seat cushion opening and closing sensor data.
Preferably, the volume of the data acquisition and recording equipment is as small as possible, and the data acquisition and recording equipment is installed in a hidden manner as possible, namely, a user of the vehicle cannot feel the existence of the equipment and the real use environment, working condition and driving habit are restored to the greatest extent; on the other hand, the device has self-sustaining capability including power supply, automatic triggering and the like, and can automatically record related data during the running process of the sample vehicle, and the related data can be remotely transmitted through 4G or stored in a local memory card. The recorded data includes, but is not limited to, GPS signals, CAN bus signals (including steering wheel angle signals transmitted over the CAN bus), seat cushion opening and closing sensor signals, and the like. In addition to being typically acquired at a sampling rate of no less than 5Hz for GPS signals, other signals are typically acquired at a sampling rate of no less than 20 Hz.
S2, carrying out statistical analysis on the actual operation data to obtain the mean value and the variance of the duty ratios of various working conditions associated with the target user group and the correlation coefficient between the duty ratio of the mth working condition and the nth working condition.
The working conditions can be an idle working condition (only one driver on the vehicle), a half-load working condition (the driver and 1 or 2 passengers on the vehicle), and a full-load working condition (the driver and 3 or 4 passengers on the vehicle). The vehicle load conditions have a significant and significant impact on the radial forces of the wheel hub structure.
Further, the steering angle working condition of the vehicle has important and obvious influence on the axial force of the wheel hub structure, so that the steering angle information and the vehicle speed information obtained by the CAN bus are analyzed, and the steering angle working condition of the vehicle CAN be determined.
Assuming a common definition and divisionkIndividual working conditions, use {w i }（i=1,……，k) To represent a certain working condition, the duty ratio of the working condition is a random variable and obeys Dirichlet distribution, the obtained actual operation data is analyzed, the actual use working condition of the target user group is reasonably defined, divided and counted, and finally each working condition { is outputw i Mean value of the ratioμ i Variance of
And a correlation coefficient +_for the ratio between the mth operating condition and the nth operating condition>
。
Optionally, the actual use condition of the target user group can be determined through questionnaire investigation, and further, the mean value and the variance of the duty ratio of various conditions and the correlation coefficient between the duty ratio of the mth condition and the duty ratio of the nth condition are obtained based on the actual use condition.
S3, determining radial force and axial force born by the wheel hub structure under the various working conditions.
Illustratively, the S3 includes:
s31, acquiring radial force and axial force of the wheel hub structure under each working condition through a six-component force sensor to obtain the radial force and the axial force born by the wheel hub structure under each working condition, wherein the sampling frequency is greater than or equal to 500Hz. In the acquisition process, the change of the load and the change of the rotation angle of the vehicle are required to be considered, so that the acquired data cover all working conditions.
And S4, carrying out statistical analysis on the radial force and the axial force born by the wheel hub structure under various working conditions to obtain the driving mileage corresponding to the biaxial load of the wheel under the working condition corresponding to the preset mileage.
Illustratively, the S4 includes:
s41, fitting statistical distribution characteristics of radial force and axial force born by the wheel hub structure under the working condition based on a Copula theory to obtain a binary normal Copula density function fitting result of the radial force and the axial force born by the wheel hub structure under the working condition.
Wherein the Copula theory includes, but is not limited to, a normal Copula function, a t-Copula function, or an archimedes Copula function.
S42, obtaining the driving mileage corresponding to the wheel double-shaft load under the working condition corresponding to the preset mileage based on the fitting result of the binary normal Copula density function.
Specifically, the preset mileage is marked asL Target The corresponding driving mileage is marked asLHere, a preset mileage is definedL Target The target mileage is designed for the maximum safe driving of a vehicle, and the preset mileage may be 30 ten thousand kilometers, for example. Exemplary, reference is made to a schematic diagram of a binary normal Copula density function fit of radial and axial forces experienced by a wheel hub structure under one such condition as shown in fig. 2. Assuming that the biaxial load of the wheel under the working condition is obtained based on the fitting result of the binary normal Copula density functionF t_i ，F a_i ) The probability of occurrence isγ i Double-shaft load of wheelF t_i ，F a_i ) Corresponding driving mileageL i =γ i ×L Target 。
Exemplary, the following table 1 shows the driving odometer corresponding to the biaxial load of the wheel under one of the working conditions corresponding to the preset mileage.
TABLE 1
The meaning of each data item in table 1 is: in the preset mileage, under the working condition, the radial force of the wheel double shaft is 3800, and the corresponding driving mileage is 655 when the axial force is minus 607. And further calculating the fatigue damage of the wheel double shaft based on the specific driving mileage, the specific radial force and the axial force.
And S5, calculating the number of damages formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage according to the driving mileage corresponding to the biaxial loads of the wheels under the working condition corresponding to the preset mileage.
Specifically, the number of damage accumulated by the biaxial load of the wheel under the working condition corresponding to the preset mileage is determined based on the following formulaD：
wherein ,mrepresenting the number of the driving mileage under one working condition,L i representing the first operating conditioniThe driving range is set to be the same as the driving range,F ti representing the first operating conditioniThe amount of the radial force that is applied,F ai representing the first operating conditioniThe force of the one axial direction is applied,bin order to provide an index of the fatigue strength,c t andc a to meet the requirements of
Is optionally takenc t =cosθ，c a =sinθ, where θ is the projection direction, and optionally θ is 0 °,10 °, … …,170 °, which can generally meet the engineering accuracy requirement.
In other words, it is assumed that the above table 1 is commonmLines, i.e. sharingmGroup data pair [ ]F ti ，F ai ，L i ) Determining the damage number formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage based on the above formulaD。bFor fatigue strength index, the Basquin relation N.S was used b Description of wheel hub Material =aS-NIn the curveS(amplitude of stress variation) andNin relation to (cycle of cycle), material parametersbThe index can be obtained by looking up a table according to the material of the wheel hub. Order the
Any pair satisfies the normalization condition (+)>
) Is combined with%c t ，c a ) All corresponding to a projection directionθ(generally, the accuracy requirement can be met by taking a projection direction at intervals of 10 degrees in the range of 0 to 180 degrees), provided thatj=1，……pThe projection directions are corresponding to each projection direction, and a certain working condition { corresponding to a preset mileage is required to be calculatedw i Number of damages accumulated by biaxial loads of lower wheelsD j （j=1，……p）。
S6, repeating the steps S4 and S5, obtaining a plurality of damage numbers formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage, and determining the mean value and the variance of the damage numbers based on the damage numbers.
Specifically, a certain working condition { corresponding to a certain preset mileage may be calculated through the plurality of sample data obtained in step S3w i Under the condition of }, the damage number formed by the accumulation of the biaxial load of the wheelD j Mean of (2)
Sum of variances
。
And S7, determining statistical characteristics of the damage number formed by accumulation of the biaxial loads of the wheels associated with the actual use working conditions of the target user group according to the mean value and the variance of the duty ratios of the working conditions in the step S2 and the correlation coefficient between the duty ratios of the m working condition and the n working condition in the step S6, and determining the target damage number based on the statistical characteristics.
Illustratively, the mathematical expectation and variance of the number of damage accumulated by the wheel biaxial loads associated with the actual usage conditions of the target user population is determined based on the following formula:
Var（D j ）=
wherein ,D j is shown in the firstjThe damage number E is the number of the damage formed by the accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage in the projection directionD j ) Indicating the number of lesionsD j Is a function of the mathematical expectation of (a),v ij is shown in the firstjFirst corresponding to preset mileage in each projection directioniSeed condition ofw i Number of damage accumulated by biaxial load of lower wheelD j Is used for the average value of (a),
，kthe number of seeds representing the working condition Var @D j ) Indicating the number of lesionsD j Variance of->
Represent the firstiVariance of seed condition ratio +.>
Represent the firstmSeed condition and the firstnThe correlation coefficient between the duty ratios of the species,v mj is shown in the firstjFirst corresponding to preset mileage in each projection directionmSeed condition ofw m The average value of the number of damages accumulated by the biaxial load of the lower wheel,v nj is shown in the firstjFirst corresponding to preset mileage in each projection directionnSeed condition ofw n Mean value of damage number accumulated by biaxial load of lower wheel, +.>
Is shown in the firstjFirst corresponding to preset mileage in each projection directioniSeed condition ofw i Number of damage accumulated by biaxial load of lower wheelD j Variance of->
，μ i Represent the firstiAverage value of seed condition ratio;
can be based on E%D j) and Var（D j ) To carry out the target damage number
Such as:
wherein ,
representing the target lesion number.
And S8, determining a load spectrum of the biaxial fatigue test of the wheel by taking the target damage number as a recurrence target.
Specifically, the preset load spectrum is q-order spectrum
The acceleration principle is as follows:
thereby obtaining the effect of test acceleration taking into accountbThe index effect brought by the method and principle of the acceleration of the biaxial fatigue test of the wheel can lead to
The value of (2) is sharply reduced, so that test acceleration is realized on the premise of equivalent damage of the wheel hub.
According to the technical scheme provided by the embodiment of the invention, firstly, the working conditions influencing the wheel hub load of the wheel are defined, divided and counted by acquiring the actual running big data of the target user group vehicles or by questionnaire investigation; and then, complete and accurate load information is supplemented through road load data acquisition with high sampling rate, and finally, the association of the wheel double-shaft fatigue test load spectrum and the actual use working condition of a specific target user group is realized. The problem that a test load spectrum in the wheel double-shaft fatigue test deviates from a load spectrum born by the wheel in a real environment is solved, the fault recurrence rate and the fault interception rate of the wheel double-shaft fatigue test are improved, and the method has important significance for improving the reliability, quality and quality of a wheel hub structure.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 3, electronic device 400 includes one or more processors 401 and memory 402.
The processor 401 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities and may control other components in the electronic device 400 to perform desired functions.
In one example, the electronic device 400 may further include: an input device 403 and an output device 404, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown). The input device 403 may include, for example, a keyboard, a mouse, and the like. The output device 404 may output various information to the outside, including early warning prompt information, braking force, etc. The output device 404 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device 400 that are relevant to the present invention are shown in fig. 3 for simplicity, components such as buses, input/output interfaces, etc. are omitted. In addition, electronic device 400 may include any other suitable components depending on the particular application.
In addition to the methods and apparatus described above, embodiments of the present invention may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform the steps of the method for determining a dual axle fatigue test load spectrum of a wheel based on actual conditions provided by any of the embodiments of the present invention.
The computer program product may write program code for performing operations of embodiments of the present invention in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
In addition, an embodiment of the present invention may also be a computer readable storage medium, on which computer program instructions are stored, which when executed by a processor, cause the processor to execute the steps of the method for determining a load spectrum of a wheel biaxial fatigue test based on an actual working condition provided by any embodiment of the present invention.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present application. As used in this specification, the terms "a," "an," "the," and/or "the" are not intended to be limiting, but rather are to be construed as covering the singular and the plural, unless the context clearly dictates otherwise. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, 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, 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 or apparatus comprising such elements.
It should also be noted that the positional or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the positional or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Unless specifically stated or limited otherwise, the terms "mounted," "connected," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.
Claims (9)
1. The method for determining the load spectrum of the biaxial fatigue test of the wheel based on the actual working condition is characterized by comprising the following steps of:
s1, acquiring actual running data of vehicles of a target user group;
s2, carrying out statistical analysis on the actual operation data to obtain the mean value and the variance of the duty ratio of various working conditions associated with the target user group and the correlation coefficient between the duty ratio of the mth working condition and the nth working condition;
s3, determining radial force and axial force born by the wheel hub structure under various working conditions;
s4, carrying out statistical analysis on the radial force and the axial force born by the wheel hub structure under various working conditions to obtain the driving mileage corresponding to the biaxial load of the wheel under the working condition corresponding to the preset mileage;
s5, calculating the number of damages formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage according to the driving mileage corresponding to the biaxial loads of the wheels under the working condition corresponding to the preset mileage;
s6, repeating the steps S4 and S5, obtaining a plurality of damage numbers formed by accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage, and determining the mean value and the variance of the damage numbers based on the damage numbers;
s7, determining statistical digital characteristics of the damage number formed by accumulation of the biaxial loads of the wheels associated with the actual use working conditions of the target user group according to the mean value and the variance of the duty ratios of the working conditions in the step S2 and the correlation coefficient between the duty ratios of the m working condition and the n working condition, and the mean value and the variance of the damage number in the step S6, and determining the target damage number based on the statistical digital characteristics;
and S8, determining a load spectrum of the biaxial fatigue test of the wheel by taking the target damage number as a recurrence target.
2. The method according to claim 1, wherein S1 comprises:
s11, installing data acquisition and recording equipment on a sample vehicle;
s12, putting the sample vehicle provided with the data acquisition and recording equipment into the target user group;
s13, acquiring and recording actual operation data through the data acquisition and recording equipment in the process of using the sample vehicle by the target user group, wherein the actual operation data at least comprises one or more of Global Positioning System (GPS) data, steering wheel corner data and seat cushion opening and closing sensor data.
3. The method according to claim 1, wherein S3 comprises:
s31, acquiring radial force and axial force of the wheel hub structure under each working condition through a six-component force sensor to obtain the radial force and the axial force born by the wheel hub structure under each working condition, wherein the sampling frequency is greater than or equal to 500Hz.
4. The method according to claim 1, wherein S4 comprises:
s41, fitting statistical distribution characteristics of radial force and axial force born by a wheel hub structure under the working condition based on a Copula theory to obtain a binary normal Copula density function fitting result of the radial force and the axial force born by the wheel hub structure under the working condition;
s42, obtaining the driving mileage corresponding to the wheel double-shaft load under the working condition corresponding to the preset mileage based on the fitting result of the binary normal Copula density function.
5. The method of claim 4, wherein the Copula theory is a normal Copula function, a t-Copula function, or an archimedes Copula function.
6. The method according to claim 1, wherein S5 comprises:
determining the number of damage accumulated by the biaxial load of the wheel under the working condition corresponding to the preset mileage based on the following formulaD：
wherein ,mrepresenting the number of the driving mileage under one working condition,L i representing the first operating conditioniThe driving range is set to be the same as the driving range,F ti representing the first operating conditioniRadial forces，F ai Representing the first operating conditioniThe force of the one axial direction is applied,bin order to provide an index of the fatigue strength,c t andc a to meet the requirements of
Is set of parameters.
7. The method according to claim 1, wherein the statistical signature comprises a mathematical expectation and variance of the number of injuries accumulated by the wheel biaxial loads associated with the actual usage conditions of the target user population, the S7 comprising:
determining a mathematical expectation and variance of the number of lesions accumulated by the wheel biaxial loads associated with the actual usage conditions of the target user population based on the following formula:
Var（D j ）=
wherein ,D j is shown in the firstjThe damage number E is the number of the damage formed by the accumulation of the biaxial loads of the wheels under the working condition corresponding to the preset mileage in the projection directionD j ) Indicating the number of lesionsD j Is a function of the mathematical expectation of (a),v ij is shown in the firstjFirst corresponding to preset mileage in each projection directioniSeed condition ofw i Number of damage accumulated by biaxial load of lower wheelD j Is used for the average value of (a),
，kthe number of seeds representing the working condition Var @D j ) Indicating the number of lesionsD j Variance of->
Represent the firstiVariance of seed condition ratio +.>
Represent the firstmSeed condition and the firstnThe correlation coefficient between the duty ratios of the species,v mj is shown in the firstjFirst corresponding to preset mileage in each projection directionmSeed condition ofw m The average value of the number of damages accumulated by the biaxial load of the lower wheel,v nj is shown in the firstjFirst corresponding to preset mileage in each projection directionnSeed condition ofw n Mean value of damage number accumulated by biaxial load of lower wheel, +.>
Is shown in the firstjFirst corresponding to preset mileage in each projection directioniSeed condition ofw i Number of damage accumulated by biaxial load of lower wheelD j Variance of->
，μ i Represent the firstiAverage value of seed condition ratio;
based on E%D j) and Var（D j ) To carry out the target damage number
Is set as follows:
wherein ,
representing the target lesion number.
8. The method of claim 7, wherein S8 comprises:
the preset load spectrum is q-order spectrum
The acceleration principle is as follows:
9. an electronic device, the electronic device comprising:
a processor and a memory;
the processor is used for executing the steps of the method for determining the load spectrum of the wheel biaxial fatigue test based on the actual working condition according to any one of claims 1 to 8 by calling a program or instructions stored in the memory.
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