CN112446092A - Vehicle structural part damage testing method, device, equipment and storage medium - Google Patents

Vehicle structural part damage testing method, device, equipment and storage medium Download PDF

Info

Publication number
CN112446092A
CN112446092A CN202011331191.1A CN202011331191A CN112446092A CN 112446092 A CN112446092 A CN 112446092A CN 202011331191 A CN202011331191 A CN 202011331191A CN 112446092 A CN112446092 A CN 112446092A
Authority
CN
China
Prior art keywords
sample
test
vehicle
working condition
damage
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202011331191.1A
Other languages
Chinese (zh)
Inventor
王世英
刘占国
董立甲
赵鹏程
张超
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
FAW Group Corp
Original Assignee
FAW Group Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by FAW Group Corp filed Critical FAW Group Corp
Priority to CN202011331191.1A priority Critical patent/CN112446092A/en
Publication of CN112446092A publication Critical patent/CN112446092A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • 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
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C5/00—Registering or indicating the working of vehicles
    • G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
    • G07C5/0808—Diagnosing performance data

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Geometry (AREA)
  • Theoretical Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The embodiment of the invention discloses a method, a device, equipment and a storage medium for testing damage of a vehicle structural part. The method comprises the following steps: acquiring sample working condition driving mileage corresponding to sample vehicle working conditions in the working condition acquisition time of the sample vehicle; acquiring the unit mileage average damage value of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle; and determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage. The embodiment of the invention realizes that the acquired objective data is adopted to replace artificial subjective judgment, so that the investigation result of the vehicle use condition of the user has authenticity, meanwhile, the vehicle working condition in the road test is consistent with the vehicle working condition in actual use, and the authenticity and the accuracy of the structural member damage prediction result are improved.

Description

Vehicle structural part damage testing method, device, equipment and storage medium
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a method, a device, equipment and a storage medium for testing damage of a vehicle structural part.
Background
When automobile manufacturers develop forward, complete automobile design and test are needed to determine the service life target of parts. The objective of determining the service life of a mechanical load structural member by mechanical load structural member damage caused by a vehicle user driving a vehicle is a universal method developed in the forward direction, which not only meets the use requirements of the user, but also prevents waste caused by over-design. The damage density of each mechanical load structural part under different working conditions of the vehicle can be obtained based on road tests of the test sample vehicle, and the damage of the mechanical load structural part can be calculated to analyze the service life target by combining the use condition of the target user on the vehicle.
In the prior art, a commonly adopted user survey method is in a questionnaire survey form, a questionnaire with certain content is formulated, multi-region random user interviews are carried out, the road use proportion of a user, such as the proportion of driving on urban roads, expressways, common roads and mountain roads, is obtained, and collected information is sorted and analyzed to obtain the use condition of the user.
However, in practical situations, users of passenger vehicles are widely distributed, driving road conditions are various, and driving styles are different, and extracting user use conditions based on questionnaire survey in mass users is a complex and arduous task. Firstly, the contents obtained through a questionnaire survey form are mostly subjective judgments of users, different users can give different sensory results for the same conditions, such as cement roads, asphalt roads, soil roads, smooth national roads, muddy bad roads and the like, and the users are difficult to accurately distinguish differences and carry out working condition judgment and statistical proportion; secondly, the user cannot obtain information of the interior of the passenger car, such as the acceleration of the vehicle, the torque of the engine, and the yaw rate of the vehicle. Therefore, the user use condition extracted based on the questionnaire cannot accurately represent the actual use condition of the vehicle by the user, and deviation occurs in calculation of the loss data of the vehicle structural part.
Disclosure of Invention
The embodiment of the invention provides a vehicle structural part damage testing method, device, equipment and storage medium, and authenticity and accuracy of a structural part damage prediction result are improved.
In a first aspect, an embodiment of the present invention provides a vehicle structural member damage testing method, including:
acquiring sample working condition driving mileage corresponding to sample vehicle working conditions in the working condition acquisition time of the sample vehicle;
acquiring the unit mileage average damage value of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle;
and determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
In a second aspect, an embodiment of the present invention further provides a vehicle structural member damage testing apparatus, including:
the working condition acquisition module is used for acquiring the sample working condition driving mileage corresponding to the sample working conditions of the sample vehicle with the set number in the working condition acquisition time;
the average damage value acquisition module is used for acquiring the average damage value of unit mileage of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle;
and the target damage acquisition module is used for determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the vehicle structural part damage testing method according to an embodiment of the present invention is implemented.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the vehicle structural part damage testing method according to the embodiment of the present invention.
According to the technical scheme of the embodiment of the invention, the working condition of the sample vehicle and the running mileage of each working condition are collected in the using process of a user to obtain the using condition of the user on the vehicle, and the damage density of the test structural member when the test vehicle runs under the same working condition is obtained, so that the damage obtained by the test structural member can be reasonably predicted after the vehicle runs for a certain mileage under the current using condition of the user, the collected objective data is adopted to replace artificial subjective judgment data, the investigation result of the using condition of the user vehicle has authenticity and reliability, meanwhile, the vehicle working condition in a road test and the vehicle working condition in actual use have consistency, and the authenticity and the accuracy of the damage prediction result of the structural member are improved.
Drawings
Fig. 1 is a flowchart of a vehicle structural member damage testing method according to an embodiment of the present invention.
Fig. 2 is a flowchart of a vehicle structural member damage testing method according to a second embodiment of the present invention.
Fig. 3 is a positioning trajectory diagram of a sample vehicle during a working condition acquisition time according to a second embodiment of the present invention.
Fig. 4 shows sample condition parameter signals and corresponding amplitude level intervals of a sample vehicle in the condition acquisition time according to the second embodiment of the present invention.
Fig. 5A is a schematic diagram of damage distribution information corresponding to the target test channel 1 according to the second embodiment of the present invention.
Fig. 5B is a schematic diagram of damage distribution information corresponding to the target test channel 2 according to the second embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a vehicle structural member damage testing device according to a third embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.
It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a vehicle structural member damage testing method according to an embodiment of the present invention. The method can be executed by the vehicle structural part damage testing device provided by the embodiment of the invention, and the device can be realized in a software and/or hardware mode and can be generally integrated in computer equipment. As shown in fig. 1, the method of the embodiment of the present invention specifically includes:
and 110, acquiring the sample working condition driving mileage corresponding to the sample vehicle working conditions in the working condition acquisition time of the sample vehicle.
The sample vehicle may be a vehicle for acquiring the use condition of the user. The condition acquisition time may be a period of time during which the condition of the sample vehicle is acquired. The sample vehicle condition may be a condition that occurs in the condition collection time of the sample vehicle, and may be characterized by various collected data of the sample vehicle and other data calculated according to the collected data, and the data for determining the sample vehicle condition may include, but is not limited to, road roughness, road gradient, vehicle steering, vehicle speed, brake strength, acceleration strength, vehicle load, and the like. The sample operating condition traveled distance may be a distance traveled by the sample vehicle under each of the sample vehicle operating conditions.
In the embodiment of the present invention, a suitable vehicle may be selected in advance as a sample vehicle according to a target vehicle for a complete vehicle design or test by an automobile manufacturer, where the sample vehicle may be a vehicle having the same or similar characteristics as the target vehicle, for example, a vehicle of any vehicle type as the target vehicle, or a vehicle of the same vehicle type as the target vehicle used by any vehicle owner in a target sales group in a main sales area of the target vehicle.
After the sample vehicle is determined, a sensor can be arranged on the sample vehicle, so that the sensor can acquire data of the sample vehicle in the working condition acquisition time, and the type of the sensor arranged on the sample vehicle can be predetermined according to the type of the data required to be acquired. The working condition acquisition time can be predetermined according to the accuracy requirement of the user vehicle use condition acquisition result, and can be a time period with any length for monitoring and acquiring data of various aspects of the vehicle while the user normally uses the sample vehicle. Optionally, the working condition acquisition time may include at least two months, and preferably, the working condition acquisition time may be a time exceeding a year period, so as to ensure that the working condition acquisition time includes special use conditions in each holiday.
And (3) calculating the acquired data to obtain working condition parameters for representing the working conditions of the sample vehicle, and/or directly taking the acquired data as the working condition parameters for representing the working conditions of the sample vehicle. Optionally, the sample vehicle operating condition at the driving time may be determined according to a range in which the value of each operating condition parameter at different driving times is located. Illustratively, when the value of the parameter A is at a1Interval, value of parameter B is in B1Interval and the value of the parameter C is in C1During the interval, the sample vehicle can be judged to be in the first sample vehicle working condition; when the value of the parameter A is changed to a2Interval, value of parameter B is in B1Interval and the value of the parameter C is in C1During the interval, it may be determined that the sample vehicle is in the second sample vehicle condition at this time.
After obtaining the working conditions of each sample vehicle, the driving mileage of the sample working conditions can be obtained by directly reading or calculating the data and/or parameters collected under the working conditions of each sample vehicle, for example, the driving mileage data recorded by an odometer when the sample vehicle drives under the working conditions of each sample vehicle can be read. Or, the vehicle speed that continuously changes with the travel time when the sample vehicle travels under each sample vehicle condition and the travel time of the sample vehicle under each sample vehicle condition may be obtained, and the vehicle speed corresponding to each sample vehicle condition is integrated within the travel time.
And 120, acquiring the unit mileage average damage value of the test structural part in the test vehicle corresponding to each sample vehicle working condition.
The test vehicle can be a vehicle for obtaining damage of the test structural member when the vehicle runs under various sample vehicle working conditions. The test structure may be a mechanical load structure in a vehicle that needs to capture damage it has acquired over a period of time in a user use situation, and may be an engine output shaft, for example. The average damage value per unit mileage corresponding to each sample vehicle operating condition may be an average damage value obtained by testing the structural member after the test vehicle travels a unit mileage distance under each sample vehicle operating condition.
Accordingly, the test vehicle may be a subject vehicle for a complete vehicle design or test by an automobile manufacturer. The setting of related sensors which are completely the same as those of the sample vehicle can be carried out on the test vehicle, and a worker who carries out whole vehicle design or test drives the test vehicle to run on a road which is the same as or similar to the road condition in the working condition of the sample vehicle, so that the running working condition of the test vehicle comprises all the working conditions of the sample vehicle. Meanwhile, the related sensors acquire the same data of the test vehicle as those of the sample vehicle, so that the same data acquisition and/or calculation are performed according to the data acquisition result, and all running conditions of the test vehicle can be obtained.
Further, the working conditions the same as the sample vehicle working conditions can be screened out from all the running working conditions of the test vehicle, the running mileage of the test vehicle in the working conditions the same as the working conditions of each sample vehicle respectively is obtained, and the damage value of the test structural member in the working conditions the same as the working conditions of each sample vehicle respectively is obtained, and then the unit mileage damage value corresponding to each sample vehicle working condition is the result of dividing the damage value corresponding to the working conditions the same as each sample vehicle working condition by the corresponding running mileage.
And step 130, determining the target damage of the test structure according to the sample working condition driving mileage and the unit mileage average damage.
Wherein the target damage may be a total damage obtained by the test structure after the sample vehicle has traveled a distance under the user's use conditions during the condition acquisition time.
Correspondingly, the damage of the test structural member after the sample vehicle runs the sample working condition running distance under each sample vehicle working condition in the working condition acquisition time can be obtained according to the sample working condition running mileage corresponding to each sample vehicle working condition and the unit mileage average damage of the test structural member. Further, the average damage of the test structural member per unit mileage traveled in the sample vehicle in the working condition acquisition time can be obtained according to the sum of the damage of the test structural member under each sample vehicle working condition and the sum of the mileage traveled in each sample working condition, and then the target damage can be obtained according to the target mileage traveled, optionally, the target mileage can be the target life mileage of the vehicle or the test structural member.
The embodiment of the invention provides a vehicle structural part damage testing method, which is characterized in that the use condition of a user on a vehicle is obtained by collecting the working condition of a sample vehicle and the running mileage of the sample vehicle under each working condition in the use process of the user, and the damage obtained by testing the structural part can be reasonably predicted after the vehicle runs for a certain mileage under the current use condition of the user by obtaining the damage density of the testing structural part when the testing vehicle runs under the same working condition.
Example two
Fig. 2 is a flowchart of a vehicle structural member damage testing method according to a second embodiment of the present invention. The embodiment of the invention is embodied on the basis of the embodiment, and the embodiment of the invention provides a specific optional implementation mode for obtaining the sample working condition driving mileage corresponding to the sample vehicle working condition in the working condition acquisition time of the sample vehicle, obtaining the unit mileage average damage value of the test structural member in the test vehicle corresponding to each sample vehicle working condition, and determining the target damage of the test structural member according to the sample working condition driving mileage and the unit mileage average damage.
As shown in fig. 2, the method of the embodiment of the present invention specifically includes:
and step 210, obtaining sample working condition driving mileage corresponding to the sample vehicle working conditions in the working condition acquisition time of the sample vehicle.
In an optional embodiment of the present invention, step 210 may specifically include:
and step 211, obtaining at least one sample working condition parameter signal of the sample vehicle in the working condition acquisition time.
Each sample operating condition parameter signal may be a continuous signal formed by each operating condition parameter of the sample vehicle changing with the travel time. The operating condition parameters may be parameters that are capable of characterizing a sample vehicle operating condition. Each sample working condition parameter signal is a time domain signal and has a fixed phase, that is, the amplitude of each sample working condition parameter signal at any driving time reflects the value of each working condition parameter of the sample vehicle at the driving time.
The working condition parameter signals of each sample can be directly measured by a sensor arranged on the sample vehicle, and can also be obtained by calculating other data signals measured by the sensor arranged on the sample vehicle. The type of the sensor arranged on the sample vehicle can be predetermined according to the type of the working condition parameter required to be acquired.
Alternatively, the operating condition parameters may include, but are not limited to, road roughness, road grade, vehicle steering, vehicle speed, brake intensity, acceleration intensity, and vehicle load. Accordingly, the sample condition parameter signals may include a road roughness signal, a road gradient signal, a vehicle steering signal, a vehicle speed signal, a brake intensity signal, an acceleration intensity signal, and a vehicle load signal of the sample vehicle during the condition acquisition time. Specifically, the road surface roughness signal is a continuous signal formed by the roughness of the road surface on which the sample vehicle runs as the running time changes. The road surface gradient signal is a continuous signal formed by the gradient of the road surface on which the sample vehicle runs as the running time changes, and the road surface gradient can be represented by the ratio of the height difference to the horizontal distance difference of the road surface. The vehicle steering signal is a continuous signal formed by the change of the steering angle and the direction of the sample vehicle in the running process along with the running time. The vehicle speed signal is a continuous signal formed by sampling the speed of the vehicle during running as the running time changes. The brake intensity signal is a continuous signal formed by the change of the brake intensity of the sample vehicle in the running process along with the running time, and the brake intensity can be represented by the deceleration speed of the sample vehicle in the braking process. The acceleration intensity signal is a continuous signal formed by changing the acceleration of the sample vehicle in the running process along with the running time. The vehicle load signal is a continuous signal formed by sampling the load of the vehicle during running as the running time changes.
Step 212, dividing at least one section of sample vehicle running time when the amplitudes of the sample working condition parameter signals are respectively in the same amplitude level interval into a sample working condition interval according to the preset amplitude level interval of each working condition parameter signal to obtain at least one sample working condition interval, so that the sample vehicle is respectively in different working conditions in each sample working condition interval, and determining the working conditions as the sample vehicle working conditions.
Wherein, each working condition parameter signal has respective amplitude grade interval respectively. The amplitude level interval of each working condition parameter signal comprises at least one parameter value range of the working condition parameter corresponding to the working condition parameter signal, the parameter value ranges are not overlapped, and the overlapped parameter value ranges can completely cover all amplitudes of the corresponding sample working condition parameter signal, namely the amplitude of each sample working condition parameter signal is in and only in one amplitude level interval corresponding to the sample working condition parameter signal at any running time of the sample vehicle in the working condition acquisition time. Each sample working condition interval can establish a one-to-one correspondence relationship with each sample vehicle working condition, and each sample working condition interval can be a set of running time of the sample vehicle under the corresponding sample vehicle working condition.
Correspondingly, in at least one section of sample vehicle running time when the amplitudes of the sample working condition parameter signals are respectively in the same amplitude grade interval, the working conditions represented by the sample working condition parameter signals are the same, the working conditions are the working conditions of the sample vehicle in the working condition acquisition time, the working conditions can be used as a sample vehicle working condition, the at least one section of running time is divided into a sample working condition interval, and the sample vehicle is in the sample vehicle working condition when running in the sample working condition interval. And (3) carrying out the same division on all the working condition acquisition time to obtain at least one sample working condition interval, wherein the sum of all the sample working condition intervals is the working condition acquisition time. The sample vehicle driving time interval is a sample vehicle driving time interval, and the sample condition parameter signals are sampled according to the sample condition level intervals.
For example, when the sample condition parameter signals include a road roughness signal, a road gradient signal, a vehicle steering signal, a vehicle speed signal, a braking intensity signal, an acceleration intensity signal and a vehicle load signal of the sample vehicle, the preset amplitude level interval of each condition parameter signal includes n of the road roughness signaliN of amplitude grade interval and road surface gradient signaljN of amplitude grade interval and vehicle steering signaloN of amplitude grade interval and vehicle speed signalpN of signal of braking intensity in interval of amplitude classqN of signal of acceleration intensity in interval of amplitude levelrAmplitude level interval and n of vehicle load signalsFor each amplitude level interval, the sample vehicle operating condition can be represented as MijopqrsWherein i is 1, 2iVehicle for displaying samplesVehicle in sample vehicle condition MijopqrsThe amplitude of the medium road roughness signal is in the ith level in the amplitude level interval, j is 1, 2jIndicating a sample vehicle operating condition MijopqrsThe amplitude of the middle road gradient signal is in the j-th level in the amplitude level interval, wherein o is 1, 2oIndicating a sample vehicle operating condition MijopqrsThe amplitude of the intermediate vehicle steering signal is in the o-th level in the amplitude level range, p being 1, 2pIndicating a sample vehicle operating condition MijopqrsThe amplitude of the medium vehicle speed signal is in the p-th level in the amplitude level interval, and q is 1, 2qIndicating a sample vehicle operating condition MijopqrsThe amplitude of the medium brake intensity signal is in the q-th level in the amplitude level interval, r is 1, 2rIndicating a sample vehicle operating condition MijopqrsThe amplitude of the medium acceleration intensity signal is in the r-th level in the amplitude level interval, s is 1, 2sIndicating a sample vehicle operating condition MijopqrsThe amplitude of the medium vehicle load signal is at the s-th level in its amplitude level interval. Further, obtaining a sample vehicle operating condition MijopqrsEach section of running time in the lower running is divided into a sample working condition interval TijopqrsAnd obtaining the working condition interval T of each sampleijopqrsAnd the following relational expression of the working condition acquisition time T:
Figure BDA0002795872550000111
optionally, the amplitude level interval of each working condition parameter signal may be preset, the value of the amplitude level interval that can averagely divide the amplitude variation range of the sample working condition parameter signal corresponding to the working condition parameter signal into a preset number of amplitude level intervals may be selected, two endpoints of the amplitude variation range may be used as the endpoints of each amplitude level interval, a special value range of the working condition parameter corresponding to the sample working condition parameter signal may be used as the amplitude level interval, or the endpoints of each amplitude level interval may be selected in any other realizable manner to obtain the amplitude level interval of the working condition parameter signal. Exemplarily, if the amplitude variation range of the obtained vehicle speed signal of the sample vehicle is 20-120 km/h, namely the parameter value variation of the vehicle speed is 20-120 km/h, the amplitude level intervals of the vehicle speed signal can be set to include 20-40 km/h, 40-60 km/h, 60-80 km/h, 80-100 km/h and 100-120 km/h, so as to averagely divide the amplitude variation range into five amplitude level intervals; the amplitude level intervals of the vehicle speed signals can also be set to include 0-10 km/h, 10-20 km/h, 20-40 km/h, 40-60 km/h and 60-120 km/h, so as to obtain five amplitude level intervals respectively corresponding to the speed ranges of the first gear, the second gear, the third gear, the fourth gear and the fifth gear of the vehicle.
And step 213, determining the sample working condition driving mileage of the sample vehicle corresponding to each sample vehicle working condition according to the sample vehicle driving time corresponding to each sample working condition interval.
The sample operating condition mileage may be the mileage of the sample vehicle under each sample vehicle operating condition, that is, the mileage of the sample vehicle in each sample operating condition interval.
Correspondingly, the driving mileage of the sample vehicle in the sample working condition interval can be obtained by obtaining the driving mileage information or the vehicle speed information of each sample vehicle driving time in the sample working condition interval. Optionally, the vehicle speed signal in the sample working condition parameter signal may be subjected to integral operation in each sample working condition interval, so as to obtain the driving mileage of each sample working condition corresponding to each sample working condition interval.
And step 220, acquiring the unit mileage average damage value of the test structural part in the test vehicle corresponding to each sample vehicle working condition.
In an optional embodiment of the present invention, step 220 may specifically include:
and 221, acquiring the test working condition intervals of the test vehicle and the test working condition driving mileage corresponding to each test working condition interval.
Each test working condition interval corresponds to one sample vehicle working condition, and the test working condition interval can be a set of at least one period of test vehicle running time under the same working condition of the test vehicle running corresponding to the corresponding sample vehicle working condition. The driving mileage of each test working condition can be the driving mileage of the test vehicle in each test working condition interval, namely the driving mileage of the test vehicle under the same working condition of each sample vehicle working condition.
Correspondingly, data acquisition and/or calculation can be carried out on data collected by a sensor arranged on the test vehicle, working condition parameters of the test vehicle for representing working conditions are obtained, the working condition parameters are the same as the working condition parameters of the sample vehicle, and then the working conditions of the test vehicle under the running time can be determined according to the numerical values of the working condition parameters of the test vehicle under different running times. Optionally, when the range of the value of each working condition parameter is the same as the range of the value of each working condition parameter corresponding to any sample vehicle working condition, it may be determined that the test vehicle is running under the working condition the same as the sample vehicle working condition.
Furthermore, the running time of the test vehicle with the same working condition as the same sample vehicle can be divided into a test working condition interval, and then the whole running time of the test vehicle is divided, so that the test working condition intervals corresponding to the working conditions of the vehicle in each sample can be obtained. Correspondingly, the driving mileage of the test vehicle in the test working condition interval can be obtained by acquiring the driving mileage information or the vehicle speed information of each test vehicle in the test working condition interval.
In an optional embodiment of the present invention, before the obtaining of the test condition interval of the test vehicle and the test condition driving range corresponding to each test condition interval, the method further includes: obtaining test working condition parameter signals of the test vehicle in damage test time, wherein each test working condition parameter signal is a continuous signal formed by each working condition parameter of the test vehicle along with the change of running time; dividing at least one section of running time of the test vehicle when the amplitudes of the test working condition parameter signals are respectively in the same amplitude level interval into a running working condition interval according to the preset amplitude level interval of each working condition parameter signal, and acquiring at least one test working condition interval from the running working condition interval so as to enable the test vehicle to be respectively in different sample vehicle working conditions in each test working condition interval.
The damage testing time can be a period of time for collecting the working condition of the test vehicle and the damage of the test structural member in the test vehicle. The test condition parameter signals can be continuous signals formed by the change of the test vehicle condition parameters along with the running time, and the condition parameters corresponding to the test condition parameter signals are the same as the condition parameters corresponding to the sample condition parameter signals. The driving condition intervals can be in one-to-one correspondence with the working conditions of the test vehicle, and each test working condition interval can be a set of driving time of the test vehicle under the corresponding working condition. The test condition interval is a subset of the driving condition interval, and the test condition interval may be a condition interval corresponding to a condition identical to the condition of each sample vehicle among all the driving condition intervals.
Correspondingly, each test working condition parameter signal can be directly measured by a sensor arranged on the test vehicle, and can also be obtained by calculating other data signals measured by the sensor arranged on the test vehicle. The placement of the sensors on the test vehicle may be exactly the same as the placement of the sensors on the sample vehicle, including but not limited to the same number of sensors, the same model, and the same mounting location. Optionally, when the sample condition parameter signal may include a road roughness signal, a road gradient signal, a vehicle steering signal, a vehicle speed signal, a brake strength signal, an acceleration strength signal, and a vehicle load signal of the sample vehicle during the condition acquisition time, the test condition parameter may include a road roughness signal, a road gradient signal, a vehicle steering signal, a vehicle speed signal, a brake strength signal, an acceleration strength signal, and a vehicle load signal of the test vehicle during the damage test time.
And in at least one section of test vehicle running time when the amplitudes of the test working condition parameter signals are respectively in the same amplitude grade interval, and the working conditions represented by the test working condition parameter signals are the same, dividing the at least one section of test vehicle running time into a running working condition interval, wherein the test vehicle is in the working condition when running in the running working condition interval. And carrying out the same division on all the damage testing time to obtain at least one running working condition interval, wherein the sum of all the running working condition intervals is the damage testing time. And if the amplitude level intervals in which the amplitude of at least one test working condition parameter signal in the test working condition parameter signals in the different running working condition intervals is different, the working conditions of the test vehicle in the running time in the different running working condition intervals are different. And further, determining a running working condition interval of the test vehicle corresponding to the working condition which is the same as the working condition of any sample vehicle as the test working condition interval.
And step 222, determining the total test damage of the test structural part corresponding to each test working condition interval.
The total test damage can be obtained by the test structural part in each test working condition interval respectively, and can be obtained by measuring the test structural part through a damage test tool.
Correspondingly, the instantaneous damage and/or the accumulated damage of the test structural member corresponding to different running time can be measured and recorded in the running process of the test vehicle, and the instantaneous damage and/or the accumulated damage of the test structural member corresponding to the running time of the test vehicle in any test working condition interval are obtained and calculated after any test working condition interval is determined, so that the damage of the test structural member in the test working condition interval is obtained.
In an optional embodiment of the present invention, the determining the total damage of the test structural component corresponding to each of the test working condition intervals includes: acquiring stress data generated by a target test channel of the test structural member under the working condition state of each sample vehicle; the stress data comprises at least one stress value and the occurrence number of each stress value; determining target cycle times corresponding to the stress values according to the stress values and an S-N curve of the target test channel; and obtaining the total test damage of the test structural part under the working conditions of the sample vehicles according to the ratio of the occurrence frequency of each stress value corresponding to the working conditions of the sample vehicles to the corresponding target cycle frequency.
Wherein the target test channel may be a damage test site predetermined according to the shape and configuration of the test structure, such that the damage measured at the test site may represent damage to the test structure. The stress value can be a stress value generated by damage of a target test channel of the test structural member at any running time in the test working condition interval. The number of occurrences of any stress value may be the number of times the stress value is acquired when the stress value is acquired in each test condition interval. The S-N curve can be determined according to the material of the target test channel of the test structural member, can represent the fatigue performance of the target test channel, and can represent the maximum times that the target test channel can be repeatedly damaged under the damage corresponding to the stress with different sizes. The target cycle number may be the maximum number of times that the target test channel may be repeatedly damaged under the damage corresponding to each stress value, respectively.
Correspondingly, the working conditions of the test vehicle are different under different running times, and the stress is different when the damage of the target test channel of the test structural member is different. The stress values of the target test channel in different running time can be measured in each test working condition interval, and the occurrence frequency of each stress value is counted. And determining the target cycle times corresponding to the stress values on the S-N curve of the target test channel, wherein the total damage accounts for 100% of the bearable maximum damage when the damage corresponding to the stress value repeatedly obtained by the target test channel reaches the target cycle times. Furthermore, the ratio of the occurrence frequency of each stress value in each test working condition interval to the corresponding target cycle frequency can represent the proportion of the damage corresponding to each stress value in each test working condition interval in the bearable maximum damage. And summing all the ratios to obtain the total test damage of the test structural part under each sample vehicle working condition corresponding to each test working condition interval, wherein the total test damage can be represented by the proportion of the total test damage in the bearable maximum damage.
Illustratively, in response to sample vehicle operating conditions MijopqrsTest condition interval T'ijopqrsIn (1), n stresses are obtainedValue F1～Fn. Wherein the stress value FiNumber of occurrences of Fi0The target cycle number determined on the S-N curve is FiAnd i is 1, 2, n, the test structural member is in the sample vehicle working condition MijopqrsTotal Damage D 'of test'ijopqrsThe expression of (a) is:
Figure BDA0002795872550000161
wherein i, j, o, p, q, r and s respectively represent the amplitude level intervals where the amplitudes of the road roughness signal, the road gradient signal, the vehicle steering signal, the vehicle speed signal, the brake intensity signal, the acceleration intensity signal and the vehicle load signal of the test vehicle are located.
And 223, determining the unit mileage average damage value of the test structural part corresponding to each sample vehicle working condition according to the test working condition driving mileage and the test total damage.
Correspondingly, after the test working condition driving mileage and the test total damage in each test working condition interval are obtained respectively, the calculation of dividing the test total damage by the corresponding test working condition driving mileage can be carried out, and the unit mileage average damage value of each sample vehicle working condition corresponding to each test working condition interval is obtained.
Illustratively, the test vehicle is operating in a manner corresponding to a sample vehicle operating condition MijopqrsTest condition interval T'ijopqrsThe running mileage of the test working condition is S'ijopqrsTest condition interval T'ijopqrsD 'is total damage of the medium test structural member'ijopqrsThen the average damage value D of unit mileage in the test working condition interval can be obtainedijopqrsThe expression of (a) is:
Figure BDA0002795872550000171
wherein i, j, o, p, q, r and s respectively represent the amplitude level intervals where the amplitudes of the road roughness signal, the road gradient signal, the vehicle steering signal, the vehicle speed signal, the brake intensity signal, the acceleration intensity signal and the vehicle load signal of the test vehicle are located.
And step 230, determining the target damage of the test structure according to the sample working condition driving mileage and the unit mileage average damage.
In an optional embodiment of the present invention, step 230 may specifically include:
and 231, determining a sample total damage according to the average damage of each unit mileage and the sample working condition driving mileage corresponding to the average damage of each unit mileage.
Wherein, the total damage of the sample can be the damage of a test structural part in the sample vehicle in the working condition acquisition time.
Correspondingly, the product of the unit mileage average damage corresponding to the same sample vehicle working condition and the sample working condition travel mileage can be calculated, and the damage of the test structural member in the sample vehicle under each sample vehicle working condition is obtained. And summing the damage corresponding to all the sample vehicle working conditions to obtain the total damage of the sample.
Exemplary, corresponding to sample vehicle operating conditions MijopqrsThe average damage value per unit mileage is DijopqrsThe sample working condition is SijopqrsThen the expression for the sample total lesion D' may be:
Figure BDA0002795872550000172
Figure BDA0002795872550000173
wherein i, j, o, p, q, r and s respectively represent amplitude level intervals in which the amplitudes of the road roughness signal, the road gradient signal, the vehicle steering signal, the vehicle speed signal, the brake intensity signal, the acceleration intensity signal and the vehicle load signal of the sample vehicle are located.
And step 232, determining the average damage of the sample according to the total damage of the sample and the working condition acquisition time.
The sample average damage can be an average value of damage of a test structural part in the sample vehicle obtained in each unit of mileage in working condition acquisition time.
Correspondingly, the total damage of the sample can be divided by the total driving range in the working condition acquisition time to obtain the average damage of the sample.
Exemplary, corresponding to sample vehicle operating conditions MijopqrsThe sample operating mode mileage is SijopqrsThen, the expression of the total driving range S in the working condition collection time is:
Figure BDA0002795872550000181
the expression for the sample mean damage D is:
Figure BDA0002795872550000182
wherein i, j, o, p, q, r and s respectively represent amplitude level intervals in which the amplitudes of the road roughness signal, the road gradient signal, the vehicle steering signal, the vehicle speed signal, the brake intensity signal, the acceleration intensity signal and the vehicle load signal of the sample vehicle are located.
Step 233, determining the target damage according to the sample average damage and the target mileage.
Wherein the target mileage may be a total mileage expected to be driven by the sample vehicle. Alternatively, the target mileage may be a target mileage of life of the sample vehicle or the test structure.
Accordingly, the product of the sample average damage and the target mileage can be calculated to obtain the target damage.
Illustratively, when the target mileage is L, the target damage D is obtainedMThe expression of (a) is:
Figure BDA0002795872550000183
wherein i, j, o, p, q, r and s respectively represent amplitude level intervals in which the amplitudes of the road roughness signal, the road gradient signal, the vehicle steering signal, the vehicle speed signal, the brake intensity signal, the acceleration intensity signal and the vehicle load signal of the sample vehicle are located.
In an optional embodiment of the present invention, after the determining the target damage of the test structure according to the sample operating condition mileage and the mileage average damage, the method further comprises: acquiring statistical damages of test structural members in a preset number of sample vehicles in the target driving mileage respectively; and acquiring the damage distribution information of the statistical damage in a preset damage value interval.
The preset number can be set according to actual requirements, and the embodiment of the invention does not limit the specific numerical value of the preset number. The statistical damage may be a set of target damages of the test structural member in each sample vehicle, and optionally, may be a set of target damages of the test structural member in each sample vehicle, which are obtained according to a plurality of preset target test channels of the test structural member, which correspond to each target test channel. The preset damage value interval may include at least one value range of the target damage. The damage distribution information may be the probability and/or the accumulated probability that the target damage of the test structural members in all the sample vehicles is in any preset damage value interval.
Correspondingly, a plurality of suitable vehicles can be selected in advance as sample vehicles according to the target vehicles for the whole vehicle design or test of an automobile manufacturer, one or more target test channels of the test structural member are preset, and the target damage of the test structural member in each sample vehicle is obtained according to the one or more target test channels. And respectively collecting the target damage corresponding to each target test channel as statistical damage. And obtaining damage distribution information corresponding to each target test channel according to the probability and/or the accumulated probability that the target damage in each statistical damage is in the preset damage value interval.
The embodiment of the invention provides a vehicle structural part damage testing method, which is characterized in that the use condition of a user on a vehicle is obtained by collecting the working condition of a sample vehicle and the running mileage of the sample vehicle under each working condition in the use process of the user, and the damage obtained by testing the structural part can be reasonably predicted after the vehicle runs for a certain mileage under the current use condition of the user by obtaining the damage density of the testing structural part when the testing vehicle runs under the same working condition.
Exemplarily, the second embodiment of the present invention further provides a specific implementation manner of the present invention. FIG. 3 is a plot of a sample vehicle position trace during a condition acquisition time, provided by an embodiment of the present invention. As shown in fig. 3, the anchor point a is the travel start point of the sample vehicle, and the anchor point g is the travel end point of the sample vehicle. The sample vehicle runs on an urban road from a positioning point a to a positioning point b, runs on an expressway from the positioning point b to a positioning point c, runs on a rural road from the positioning point c to a positioning point d, runs on the expressway from the positioning point d to a positioning point e, runs on a mountain road from the positioning point e to a positioning point f, and runs on the rural road from the positioning point f to a positioning point g. Correspondingly, fig. 4 shows sample operating condition parameter signals and corresponding amplitude level intervals of the sample vehicle in the operating condition acquisition time according to the embodiment of the present invention. The sample working condition parameter signals comprise a vehicle speed signal, a road surface gradient signal and a vehicle load signal of a sample vehicle, and the amplitude level interval of the vehicle speed signal comprises Av、Bv、CvAnd DvThe amplitude grade interval of the road surface gradient signal comprises Ak、Bk、CkAnd DkThe amplitude level interval of the vehicle load signal comprises Ag、BgAnd Cg。
As shown in FIG. 4, the working condition acquisition time can be divided into ten intervals t according to the amplitude variation of each sample working condition parameter signal1～t10. Specifically, the sample vehicle is in the section t after the start of the travel1The amplitude of the vehicle speed signal is kept at AvIn the grade interval, the road gradient signal is kept at AkIn the stage interval, the vehicle load signal is kept at AgWithin a stage interval; reaches the interval t during the running time1At the end of the period, the amplitude of the vehicle speed signal changes from the Av level interval to BvThe interval of the stages is set to be,enter the interval t2(ii) a Reaches the interval t during the running time2At the end of the time interval, the amplitude of the vehicle speed signal is from BvStep interval changed to AvStage section, entry section t3(ii) a Reaches the interval t during the running time3At the end of the time interval, the amplitude of the vehicle speed signal is from AvStage interval change to DvStep interval and road surface gradient signal from AkStep interval change to CkStage section, entry section t4(ii) a Reaches the interval t during the running time4At the end of the time interval, the amplitude of the vehicle speed signal is from DvStage interval change to BvGrade interval and road surface gradient signal slave CkStage interval change to BkStage section and vehicle load signal from AgStep interval change to CgStage section, entry section t5(ii) a Reaches the interval t during the running time5At the end of the time interval, the amplitude of the vehicle speed signal is from BvStep interval change to CvStage section, entry section t6(ii) a Reaches the interval t during the running time6At the end of the time interval, the amplitude of the vehicle speed signal is from CvStage interval change to BvStep section and road surface gradient signal from BkStep interval change to CkStage section, entry section t7(ii) a Reaches the interval t during the running time7At the end of the time interval, the amplitude of the vehicle speed signal is from BvStage interval change to DvStep section and road surface gradient signal slave CkStep interval changed to AkStage section, entry section t8(ii) a Reaches the interval t during the running time8At the end of time, road slope signal from AkStage interval change to DkStage section, entry section t9(ii) a Reaches the interval t during the running time9At the end of the time interval, the amplitude of the vehicle speed signal is from DvStage interval change to BvStep section and road surface gradient signal from DkStage interval change to BkStage section, entry section t10Until the end of the stroke.
According to the interval t1～t10The amplitude level interval of each corresponding sample working condition parameter signal can be divided into different sample working condition intervals. Specifically, let t1And t3Divided into sample operating regime intervals TAAAThe sample vehicle runs in a first urban road working condition in the sample working condition interval; will t2Divided into sample operating regime intervals TBAAThe sample vehicle runs on the second urban road working condition in the working condition interval; will t4Divided into sample operating regime intervals TDCAThe sample vehicle runs on a first highway working condition in the sample working condition interval; will t5And t10Divided into sample operating regime intervals TBBCThe sample vehicle runs on the first rural road condition in the sample condition interval; will t6Divided into sample operating regime intervals TCBCThe sample vehicle runs on the second country road condition in the sample condition interval; will t7Divided into sample operating regime intervals TBCCThe sample vehicle runs on the road working condition of the third country in the sample working condition interval; will t8Divided into sample operating regime intervals TDACThe sample vehicle runs on a second highway working condition in the sample working condition interval; will t9Divided into sample operating regime intervals TDDCAnd the sample vehicle runs on the mountain road condition in the sample condition interval. And the working condition acquisition time T is the sum of all the working condition intervals of the samples.
Furthermore, the speed signal of the sample vehicle is integrated in each interval or each sample working condition interval, so that the sample working condition driving mileage of the working condition acquisition vehicle in each sample working condition interval can be obtained. The resulting driving range s of the sample vehicle in each section is shown in fig. 41～s10. The sample working condition driving mileage of the sample vehicle in each sample working condition interval can be obtained according to the interval in each sample working condition interval, specifically, the sample working condition interval TAAASample operating mode mileage SAAAIs equal to s1And s3Sum, sample operating mode interval TBAASample operating mode mileage SBAAIs equal to s2Sample condition interval TDCASample operating mode mileage SDCAIs equal to s4Sample condition interval TBBCSample operating mode mileage SBBCIs equal to s5And s10Sum, sample operating mode interval TCBCSample operating mode mileage SCBCIs equal to s6Sample condition interval TBCCSample operating mode mileage SBCCIs equal to s7Sample condition interval TDACSample operating mode mileage SDACIs equal to s8Sample condition interval TDDCSample operating mode mileage SDDCIs equal to s9. The total driving mileage S is the sum of the driving mileage of all the sample working conditions.
In the damage testing time, the test vehicle is driven to run under various different working conditions, and the working condition of the test vehicle is the same as the working condition of the sample vehicle as much as possible. Correspondingly, a vehicle speed signal, a road surface gradient signal and a vehicle load signal of the test vehicle in the damage test time are collected to obtain a test working condition parameter signal. Processing the test working condition parameter signal by the processing mode of the sample working condition parameter signal to obtain a test working condition interval T 'of the test vehicle running under the working condition of the first city road in the damage test time'AAARunning in test working condition interval T 'under working condition of second urban road'BAARunning in test working condition interval T 'under first highway working condition'DCARunning in test working condition interval T 'under working condition of first country road'BBCAnd running in a test working condition interval T 'under a working condition of a second country road'CBCAnd running in a test working condition interval T 'under a working condition of a road of a third village'BCCRunning in test working condition interval T 'under second expressway working condition'DACAnd running in test working condition interval T 'under mountain area highway working condition'DDC. Correspondingly, obtaining the running mileage S 'of each test working condition interval'AAA、S′BAA、S′DCA、S′BBC、S′CBC、S′BCC、S′DACAnd S'DDC。
Further, when the test vehicle runs in each test working condition interval in the damage test time, the stress of the target test channel 1 of the test structural member is collected, and the stress number corresponding to the target test channel 1 is obtainedAccordingly, the first test total damage D 'of the test structural member corresponding to the target test channel 1 can be obtained by combining the S-N curve corresponding to the target test channel 1'AAA、D′BAA、D′DCA、D′BBC、D′CBC、D′BCC、D′DACAnd D'DDC. Therefore, according to the method and the expression provided by the embodiment of the invention, for the preset target driving mileage, the first unit mileage average damage value, the first sample total damage, the first sample average damage and the first target damage of the test structure corresponding to the target test channel 1 can be obtained step by step according to the obtained data.
Similarly, when the test vehicle runs in each test working condition interval in the damage test time, the same acquisition and calculation are performed on the target test channel 2 of the test structural member, and finally, the second target damage of the test structural member corresponding to the target test channel 2 can be obtained.
Further, obtaining statistical damage corresponding to the test structural members in the preset number of sample vehicles in the target driving mileage respectively, and obtaining damage distribution information of the statistical damage in a preset damage value interval. Fig. 5A is a schematic diagram of damage distribution information corresponding to a target test channel 1 according to an embodiment of the present invention, and fig. 5B is a schematic diagram of damage distribution information corresponding to a target test channel 2 according to an embodiment of the present invention.
EXAMPLE III
Fig. 6 is a schematic structural diagram of a vehicle structural member damage testing apparatus according to a third embodiment of the present invention, and as shown in fig. 6, the apparatus includes: a condition obtaining module 310, an average damage value obtaining module 320, and a target damage obtaining module 330.
The working condition obtaining module 310 is configured to obtain sample working condition driving miles corresponding to the sample vehicle working conditions in the working condition collecting time.
The average damage value obtaining module 320 is configured to obtain an average damage value of a unit mileage of a test structure in a test vehicle, where the test structure corresponds to each of the sample vehicle operating conditions.
And the target damage obtaining module 330 is configured to determine the target damage of the test structure according to the sample working condition driving mileage and the unit mileage average damage.
In an optional implementation manner of the embodiment of the present invention, the operating condition obtaining module 310 is specifically configured to: acquiring at least one sample working condition parameter signal of the sample vehicle in the working condition acquisition time, wherein each sample working condition parameter signal is a continuous signal formed by each working condition parameter of the sample vehicle along with the change of running time; dividing at least one section of sample vehicle running time when the amplitudes of the sample working condition parameter signals are respectively in the same amplitude level interval into a sample working condition interval according to the preset amplitude level interval of each working condition parameter signal to obtain at least one sample working condition interval, so that the sample vehicle is respectively in different working conditions in each sample working condition interval, and determining the working conditions as sample vehicle working conditions; and determining the sample working condition driving mileage of the sample vehicle corresponding to each sample vehicle working condition according to the sample vehicle driving time corresponding to each sample working condition interval.
In an optional implementation manner of the embodiment of the present invention, the average damage value obtaining module 320 includes: the test working condition acquisition submodule is used for acquiring a test working condition interval of the test vehicle and the test working condition driving mileage corresponding to each test working condition interval; each test working condition interval corresponds to one sample vehicle working condition; the testing total damage determining submodule is used for determining the testing total damage of the testing structural part corresponding to each testing working condition interval; and the average damage value determining submodule is used for determining the unit mileage average damage value of the test structural member corresponding to each sample vehicle working condition according to the test working condition driving mileage and the test total damage.
In an optional implementation manner of the embodiment of the present invention, the average damage value obtaining module 320 further includes: the test working condition parameter signal acquisition submodule is used for acquiring test working condition parameter signals of the test vehicle in damage test time, and each test working condition parameter signal is a continuous signal formed by each working condition parameter of the test vehicle along with the change of running time; and the test working condition interval obtaining submodule is used for dividing at least one section of test vehicle running time when the amplitude of each test working condition parameter signal is respectively in the same amplitude level interval into a running working condition interval according to the preset amplitude level interval of each working condition parameter signal, and obtaining at least one test working condition interval from the running working condition interval so as to enable the test vehicle to be respectively in different sample vehicle working conditions in each test working condition interval.
In an optional implementation manner of the embodiment of the present invention, the total damage testing determination submodule is specifically configured to: acquiring stress data generated by a target test channel of the test structural member under the working condition state of each sample vehicle; the stress data comprises at least one stress value and the occurrence number of each stress value; determining target cycle times corresponding to the stress values according to the stress values and an S-N curve of the target test channel; and obtaining the total test damage of the test structural part under the working conditions of the sample vehicles according to the ratio of the occurrence frequency of each stress value corresponding to the working conditions of the sample vehicles to the corresponding target cycle frequency.
In an optional implementation manner of the embodiment of the present invention, the target damage obtaining module 330 is specifically configured to: determining sample total damage according to the average damage of each unit mileage and the sample working condition driving mileage corresponding to the average damage of each unit mileage; determining the average damage of the sample according to the total damage of the sample and the working condition acquisition time; determining the target damage according to the sample average damage and the target mileage.
In an optional implementation of the embodiment of the present invention, the apparatus further comprises: the statistical damage obtaining module is used for obtaining statistical damages corresponding to the test structural parts in the preset number of sample vehicles in the target driving mileage; and the damage distribution information acquisition module is used for acquiring the damage distribution information of the statistical damage in a preset damage value interval.
The device can execute the vehicle structural part damage testing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the vehicle structural part damage testing method.
The embodiment of the invention provides a vehicle structural part damage testing device, which is characterized in that the use condition of a user on a vehicle is obtained by acquiring the working condition of a sample vehicle and the driving mileage under each working condition in the use process of the user, and the damage obtained by testing a structural part can be reasonably predicted after the vehicle drives for a certain mileage under the current use condition of the user by acquiring the damage density of the testing structural part when the testing vehicle drives under the same working condition.
Example four
Fig. 7 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention. FIG. 7 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in fig. 7 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present invention.
As shown in FIG. 7, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors 16, a memory 28, and a bus 18 that connects the various system components (including the memory 28 and the processors 16).
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, and commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
Computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with computer device 12, and/or with any devices (e.g., network card, modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, computer device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with the other modules of computer device 12 via bus 18. It should be appreciated that although not shown in FIG. 7, other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor 16 executes various functional applications and data processing by running the program stored in the memory 28, so as to implement the vehicle structural part damage testing method provided by the embodiment of the invention: acquiring sample working condition driving mileage corresponding to sample vehicle working conditions in the working condition acquisition time of the sample vehicle; acquiring the unit mileage average damage value of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle; and determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
EXAMPLE five
Fifth, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where when the computer program is executed by a processor, the method for testing damage to a structural member of a vehicle according to the fifth embodiment of the present invention is implemented: acquiring sample working condition driving mileage corresponding to sample vehicle working conditions in the working condition acquisition time of the sample vehicle; acquiring the unit mileage average damage value of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle; and determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, 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 computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or computer device. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A vehicle structural member damage testing method is characterized by comprising the following steps:
acquiring sample working condition driving mileage corresponding to sample vehicle working conditions in the working condition acquisition time of the sample vehicle;
acquiring the unit mileage average damage value of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle;
and determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
2. The method of claim 1, wherein obtaining the sample operating condition driving mileage of the sample vehicle corresponding to the respective sample vehicle operating condition in the operating condition acquisition time comprises:
acquiring at least one sample working condition parameter signal of the sample vehicle in the working condition acquisition time, wherein each sample working condition parameter signal is a continuous signal formed by each working condition parameter of the sample vehicle along with the change of running time;
dividing at least one section of sample vehicle running time when the amplitudes of the sample working condition parameter signals are respectively in the same amplitude level interval into a sample working condition interval according to the preset amplitude level interval of each working condition parameter signal to obtain at least one sample working condition interval, so that the sample vehicle is respectively in different working conditions in each sample working condition interval, and determining the working conditions as sample vehicle working conditions;
and determining the sample working condition driving mileage of the sample vehicle corresponding to each sample vehicle working condition according to the sample vehicle driving time corresponding to each sample working condition interval.
3. The method of claim 1, wherein obtaining an average damage per unit of mileage for a test structure in a test vehicle corresponding to each of the sample vehicle operating conditions comprises:
acquiring a test working condition interval of the test vehicle and a test working condition driving mileage corresponding to each test working condition interval; each test working condition interval corresponds to one sample vehicle working condition;
determining the total test damage of the test structural part corresponding to each test working condition interval;
and determining the unit mileage average damage value of the test structural part corresponding to each sample vehicle working condition according to the test working condition driving mileage and the test total damage.
4. The method of claim 3, wherein prior to said obtaining the test condition intervals of the test vehicle and the test condition range corresponding to each of the test condition intervals, further comprising:
obtaining test working condition parameter signals of the test vehicle in damage test time, wherein each test working condition parameter signal is a continuous signal formed by each working condition parameter of the test vehicle along with the change of running time;
dividing at least one section of running time of the test vehicle when the amplitudes of the test working condition parameter signals are respectively in the same amplitude level interval into a running working condition interval according to the preset amplitude level interval of each working condition parameter signal, and acquiring at least one test working condition interval from the running working condition interval so as to enable the test vehicle to be respectively in different sample vehicle working conditions in each test working condition interval.
5. The method according to claim 3, wherein the determining of the total damage to the test structure corresponding to each test condition interval comprises:
acquiring stress data generated by a target test channel of the test structural member under the working condition state of each sample vehicle; the stress data comprises at least one stress value and the occurrence number of each stress value;
determining target cycle times corresponding to the stress values according to the stress values and an S-N curve of the target test channel;
and obtaining the total test damage of the test structural part under the working conditions of the sample vehicles according to the ratio of the occurrence frequency of each stress value corresponding to the working conditions of the sample vehicles to the corresponding target cycle frequency.
6. The method of claim 1, wherein determining the target damage to the test structure based on the sample operating range mileage and the mileage average damage comprises:
determining sample total damage according to the average damage of each unit mileage and the sample working condition driving mileage corresponding to the average damage of each unit mileage;
determining the average damage of the sample according to the total damage of the sample and the working condition acquisition time;
determining the target damage according to the sample average damage and the target mileage.
7. The method of claim 1, further comprising, after the determining the target damage to the test structure from the sample operating range mileage and the mileage average damage:
acquiring statistical damages of test structural members in a preset number of sample vehicles in the target driving mileage respectively;
and acquiring the damage distribution information of the statistical damage in a preset damage value interval.
8. A vehicle structural member damage testing device, comprising:
the working condition acquisition module is used for acquiring sample working condition driving mileage corresponding to the sample vehicle working conditions in the working condition acquisition time;
the average damage value acquisition module is used for acquiring the average damage value of unit mileage of a test structural part in the test vehicle corresponding to the working condition of each sample vehicle;
and the target damage acquisition module is used for determining the target damage of the test structural part according to the sample working condition driving mileage and the unit mileage average damage.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the vehicle structural damage testing method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a vehicle structural part damage testing method according to any one of claims 1 to 7.
CN202011331191.1A 2020-11-24 2020-11-24 Vehicle structural part damage testing method, device, equipment and storage medium Pending CN112446092A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011331191.1A CN112446092A (en) 2020-11-24 2020-11-24 Vehicle structural part damage testing method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011331191.1A CN112446092A (en) 2020-11-24 2020-11-24 Vehicle structural part damage testing method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN112446092A true CN112446092A (en) 2021-03-05

Family

ID=74738552

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011331191.1A Pending CN112446092A (en) 2020-11-24 2020-11-24 Vehicle structural part damage testing method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN112446092A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114518234A (en) * 2022-02-17 2022-05-20 浙江吉利控股集团有限公司 Damage detection method for electric drive of whole vehicle, server and computer readable storage medium

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103902820A (en) * 2014-03-22 2014-07-02 淮阴工学院 Equivalence coefficient method of vehicle structure fatigue damage calculation under combined road conditions
US20160116587A1 (en) * 2014-10-27 2016-04-28 Nacco Materials Handling Group, Inc. Vehicle and environmental detection system
CN107331182A (en) * 2017-07-13 2017-11-07 北京航空航天大学 Automatic Pilot method for controlling driving speed under a kind of net connection environment towards continuous signal intersection
US20180100783A1 (en) * 2016-10-11 2018-04-12 Hunter Engineering Company Method and Apparatus For Vehicle Inspection and Safety System Calibration Using Projected Images
CN109766624A (en) * 2019-01-04 2019-05-17 北京航空航天大学 A kind of prediction technique of cementing structure adhesive layer fatigue life under the conditions of high/low temperature cold cycling
CN111461358A (en) * 2020-03-17 2020-07-28 中国第一汽车股份有限公司 Vehicle maintenance reminding method and device, vehicle-mounted terminal equipment and medium
WO2020157172A1 (en) * 2019-01-30 2020-08-06 Continental Automotive Gmbh Methods and devices for predictive maintenance of road vehicle components
CN111623997A (en) * 2020-05-26 2020-09-04 湖南行必达网联科技有限公司 Method and device for constructing vehicle test field, electronic equipment and readable storage medium

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103902820A (en) * 2014-03-22 2014-07-02 淮阴工学院 Equivalence coefficient method of vehicle structure fatigue damage calculation under combined road conditions
US20160116587A1 (en) * 2014-10-27 2016-04-28 Nacco Materials Handling Group, Inc. Vehicle and environmental detection system
US20180100783A1 (en) * 2016-10-11 2018-04-12 Hunter Engineering Company Method and Apparatus For Vehicle Inspection and Safety System Calibration Using Projected Images
CN107331182A (en) * 2017-07-13 2017-11-07 北京航空航天大学 Automatic Pilot method for controlling driving speed under a kind of net connection environment towards continuous signal intersection
CN109766624A (en) * 2019-01-04 2019-05-17 北京航空航天大学 A kind of prediction technique of cementing structure adhesive layer fatigue life under the conditions of high/low temperature cold cycling
WO2020157172A1 (en) * 2019-01-30 2020-08-06 Continental Automotive Gmbh Methods and devices for predictive maintenance of road vehicle components
CN111461358A (en) * 2020-03-17 2020-07-28 中国第一汽车股份有限公司 Vehicle maintenance reminding method and device, vehicle-mounted terminal equipment and medium
CN111623997A (en) * 2020-05-26 2020-09-04 湖南行必达网联科技有限公司 Method and device for constructing vehicle test field, electronic equipment and readable storage medium

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
王世英 等: ""基于用户路面及驾驶方式分布的用户目标损伤确定方法"", 《2020年中国汽车工程学会年会论文集》, 31 October 2020 (2020-10-31), pages 2824 - 2830 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114518234A (en) * 2022-02-17 2022-05-20 浙江吉利控股集团有限公司 Damage detection method for electric drive of whole vehicle, server and computer readable storage medium
CN114518234B (en) * 2022-02-17 2023-08-15 浙江吉利控股集团有限公司 Damage detection method for whole vehicle electric drive, server and computer readable storage medium

Similar Documents

Publication Publication Date Title
CN110689723B (en) Truck overload identification method based on power distribution and self-learning
Chen et al. A graphical modeling method for individual driving behavior and its application in driving safety analysis using GPS data
US8862346B2 (en) System and method for simulating the performance of a virtual vehicle
CN107330217B (en) Mesoscopic oil consumption prediction method based on RBFNN
CN101044386B (en) Tire wear analysis method
Staniek Road pavement condition diagnostics using smartphone-based data crowdsourcing in smart cities
CN107953888B (en) Road type identification method and system
CN111833604B (en) Vehicle load state identification method and device based on driving behavior feature extraction
CN110304068B (en) Method, device, equipment and storage medium for collecting automobile driving environment information
CN104792937A (en) Bridge head bump detection evaluation method based on vehicle-mounted gravitational acceleration sensor
KR102498441B1 (en) Autonomous vehicle test method and apparatus, electronic device, computer-readable storage medium, and computer program
JP2015102883A (en) Vehicle failure information providing system, vehicle failure information providing method and failure information providing program
CN110243384B (en) Method, device, equipment and medium for determining actual driving emission test route
CN110852542B (en) Road flatness calculation method and system
EP3812218A1 (en) Indication diagnosis device and method
CN112446092A (en) Vehicle structural part damage testing method, device, equipment and storage medium
Na et al. Quantifying fuel-saving benefit of low-rolling-resistance tyres from heavy goods vehicle in-service operations
CN112466004B (en) Vehicle use information acquisition method, device, equipment and storage medium
CN115964905B (en) Method and medium for constructing emission test working conditions of mountain roads in highland
CN114323512B (en) Heavy-load vehicle identification method and system
CN116740940A (en) Severe weather high-impact road section risk prediction and safety management method, device and equipment
Staniek Repeatability of road pavement condition assessment based on three-dimensional analysis of linear accelerations of vehicles
Jackson et al. Analysis of real-world lead vehicle operation for modal emissions and traffic simulation models
KR20160063652A (en) Economic driving analysis system
CN112729863B (en) Vehicle actual measurement road selection method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20210305