CN114462188A - Road load testing method and device, electronic equipment and storage medium - Google Patents
Road load testing method and device, electronic equipment and storage medium Download PDFInfo
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- G06F30/20—Design optimisation, verification or simulation
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
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- G06F2119/04—Ageing analysis or optimisation against ageing
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- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The application relates to the technical field of load testing, in particular to a road load testing method, a road load testing device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring pavement data of a preset test field; inputting road surface data into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, and combining a preset tire model to obtain load data of the current vehicle; load data for each vehicle component is simulated based on load data for the current vehicle. From this, it needs to spend a large amount of time preparation mule car, six component data acquisition adapters among the correlation technique to have solved, arranges various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in dedicated experimental place, need to spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
Description
Technical Field
The present disclosure relates to load testing technologies, and in particular, to a road load testing method and apparatus, an electronic device, and a storage medium.
Background
In the related technology, the road load testing technology is that at the initial stage of a project, as shown in fig. 1, according to the design scheme of the whole vehicle, a mule vehicle needs to be manufactured, parameters such as the wheelbase, the suspension form, the suspension rigidity and the whole vehicle posture of the mule vehicle are required to be consistent with those of the designed vehicle, and then road spectrum collection is carried out on a specified durable road surface of a test field; meanwhile, in this stage, a design vehicle multi-body Dynamic model (Automatic Dynamic Analysis of Mechanical Systems, ADAMS for short) is also required to be established according to design parameters and relevant test parameters of the standard vehicle, the collected road spectrum load is subjected to load decomposition, and then subsequent structural fatigue Analysis work of parts such as a vehicle body, a chassis part and the like is carried out.
However, this method needs to spend a large amount of time making mule car, six component force data acquisition adapters, arranges various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in special experimental place, need to spend a large amount of manual works and time, need to solve urgently.
Content of application
The application provides a road load test method, device, electronic equipment and storage medium, need to spend a large amount of time preparation mule car in solving the correlation technique, six component data acquisition adapters, arrange various data acquisition's sensor, and need professional driver and load tester to take professional equipment to test in dedicated experimental place, need to spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
An embodiment of a first aspect of the present application provides a road load testing method, including the following steps:
acquiring pavement data of a preset test field;
inputting the road surface data into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, and combining a preset tire model to obtain load data of the current vehicle; and
and simulating to obtain the load data of each vehicle component based on the load data of the current vehicle.
Optionally, the method in the embodiment of the present application further includes:
calculating the fatigue strength estimated value of each part according to the load data of each vehicle part;
and generating a corresponding improvement strategy according to the fatigue strength estimated value of each part.
Optionally, the acquiring road surface data of the preset test field includes:
acquiring a virtual test field file of a preset test field, and extracting the road surface data from the virtual test field file;
or receiving road surface information input by a user, and generating the road surface data according to the road surface information.
Optionally, before inputting the road data into a full vehicle multi-body dynamic model established by relevant parameters of the current vehicle, the method further includes:
simulating to obtain initial acceleration, initial displacement and reference load based on an initial whole vehicle multi-body dynamic model;
taking the initial acceleration and the initial displacement as target loads, and iterating to obtain actual loads;
comparing the reference load with the actual load to obtain a corrected value of a model transfer function;
and correcting the initial finished automobile multi-body dynamic model by using the correction value to obtain the finished automobile multi-body dynamic model.
Optionally, the comparing the reference load with the actual load to obtain a correction value of the model transfer function includes:
respectively extracting time domain characteristics and frequency domain characteristics of the reference load and the actual load;
comparing the time domain and frequency domain characteristics of the reference load and the actual load to obtain a comparison result;
and when the comparison result does not meet the preset condition, generating the correction value according to a preset correction strategy.
An embodiment of a second aspect of the present application provides a road load testing device, including:
the acquisition module is used for acquiring road surface data of a preset test field;
the input module is used for inputting the road surface data into a whole vehicle multi-body dynamic model established by the related parameters of the current vehicle and obtaining the load data of the current vehicle by combining a preset tire model; and
and the test module is used for simulating to obtain the load data of each vehicle component based on the load data of the current vehicle.
Optionally, the apparatus according to the embodiment of the present application further includes:
the calculation module is used for calculating the fatigue strength estimation value of each part according to the load data of each vehicle part;
and the generating module is used for generating a corresponding improvement strategy according to the fatigue strength estimated value of each part.
Optionally, the obtaining module is specifically configured to:
acquiring a virtual test field file of a preset test field, and extracting the road surface data from the virtual test field file;
or receiving road surface information input by a user, and generating the road surface data according to the road surface information.
Optionally, before inputting the road data into the full vehicle multi-body dynamic model established by the relevant parameters of the current vehicle, the input module is further configured to:
simulating to obtain initial acceleration, initial displacement and reference load based on an initial whole vehicle multi-body dynamic model;
taking the initial acceleration and the initial displacement as target loads, and iterating to obtain actual loads;
comparing the reference load with the actual load to obtain a corrected value of a model transfer function;
and correcting the initial finished automobile multi-body dynamic model by using the correction value to obtain the finished automobile multi-body dynamic model.
Optionally, the input module is further configured to:
respectively extracting time domain characteristics and frequency domain characteristics of the reference load and the actual load;
comparing the time domain and frequency domain characteristics of the reference load and the actual load to obtain a comparison result;
and when the comparison result does not meet the preset condition, generating the correction value according to a preset correction strategy.
An embodiment of a third aspect of the present application provides a vehicle, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the road load testing method as described in the above embodiments.
A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, the program being executed by a processor for implementing the road load testing method as described in the above embodiments.
Therefore, road surface data of a preset test field can be obtained, the road surface data are input into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, load data of the current vehicle are obtained by combining a preset tire model, and load data of each vehicle component are obtained through simulation based on the load data of the current vehicle. From this, it needs to spend a large amount of time preparation mule car, six component data acquisition adapters among the correlation technique to have solved, arranges various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in dedicated experimental place, need to spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of a road load testing method in the related art;
FIG. 2 is a schematic diagram of another road load testing method in the related art;
fig. 3 is a flowchart of a road load testing method according to an embodiment of the present application;
FIG. 4 is a flow chart of a road load testing method according to one embodiment of the present application;
FIG. 5 is a flow chart of a road load testing method according to another embodiment of the present application;
FIG. 6 is an exemplary diagram of a road load testing device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
A road load testing method, apparatus, electronic device, and storage medium according to embodiments of the present application are described below with reference to the accompanying drawings.
Before introducing the road load testing method of the embodiment of the application, a road load testing method capable of solving some problems in the related art is briefly introduced.
Specifically, as shown in fig. 2, the road load testing method utilizes a virtual test field technology and an automobile virtual test field load testing technology, and is based on a virtual test field load spectrum acquisition technology, wherein a physical test field road surface is subjected to digital processing, and automobile load data is acquired in a dynamic simulation mode by combining a tire model and a whole automobile multi-body dynamic model. The method can save the link of manufacturing mule cars at the initial stage of design, cancel the real car road spectrum acquisition work of a test field, only need to establish a multi-body dynamic model of the whole car of the design car according to design parameters and relevant test parameters of the car-marking, combine an Ftire tire model and a physical test field digital road surface, acquire the load data of each part in a dynamic simulation mode, and then perform subsequent structural fatigue analysis work
However, although the virtual test field technology is utilized, a mule vehicle does not need to be manufactured, only a dynamic model, a tire and a road surface need to be established, the load can be obtained for fatigue simulation work, compared with a test field load testing method in the related technology, the development cost can be saved, the development period can be shortened, the precision same as that of an actual spectrum mining vehicle needs to be achieved, and an accurate multi-body dynamic model and a tire model need to be provided! Due to various deviations in the whole test field load test process, the virtual test has the following defects:
(1) the method comprises the steps of generating a tire attribute file through an identification software tool for subsequent load extraction work, wherein the tire model is an internationally recognized endurance working condition model with the highest precision, and multiple tests such as static test, longitudinal sliding test, lateral deviation test and the like need to be carried out on the tire model. Since different tires need to be modeled or purchased directly from technical companies, the development costs are high.
(2) A multi-body dynamic model needs to be established, the multi-body dynamic model of the whole vehicle is established based on parameter information of the designed whole vehicle, wherein the attribute input of elastic elements such as a lining, a spring, a shock absorber, a limiting block and the like is an important parameter for ensuring the characteristics of the model of the whole vehicle, and the elastic elements also greatly influence the precision of a load in the process of virtual load simulation extraction. The elastic element comprises a dynamic stiffness test and a static stiffness test of the bushing, a spring stiffness test and a damping characteristic test of the shock absorber. Therefore, the measurement of the elastic element parameters requires a lot of cost and time.
(3) Because the detailed modeling and the measurement test of the tire inevitably generate errors, the accuracy of the load test decomposed on parts can be greatly influenced by the whole vehicle model through error accumulation, and therefore the accuracy of the load test of the virtual test field is greatly influenced by the error accumulation.
Based on the above problems, the present application provides a road load testing method, in which road data of a preset test field can be obtained, the road data is input into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, load data of the current vehicle is obtained by combining a preset tire model, and load data of each vehicle component is obtained by simulation based on the load data of the current vehicle. From this, it needs to spend a large amount of time preparation mule car, six component data acquisition adapters among the correlation technique to have solved, arranges various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in dedicated experimental place, need to spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
Specifically, fig. 3 is a schematic flow chart of a road load testing method provided in the embodiment of the present application.
As shown in fig. 3, the road load testing method includes the steps of:
in step S301, road surface data of a preset test field is acquired.
Optionally, in some embodiments, acquiring road surface data of a preset test field includes: acquiring a virtual test field file of a preset test field, and extracting road surface data from the virtual test field file; or receiving road surface information input by a user, and generating road surface data according to the road surface information.
It should be understood that there are many ways to obtain the road surface data of the preset experimental field, for example, the embodiment of the present application may extract the road surface data from the relevant file, and may also receive data input by the user, which is not limited herein.
As a possible implementation manner, in some embodiments, the embodiment of the present application may obtain a virtual test field file of a preset test field, and extract road surface data from the virtual test field file. The virtual test field file of the preset test field can be an actual test field pavement file.
As another possible implementation manner, in some embodiments, the embodiment of the present application may receive road surface information input by a user, and generate road surface data according to the road surface information. That is, the user can manually input the road surface information after manually measuring the road surface information, so as to use the road surface information as the road surface data of the preset test field.
In step S302, road surface data is input into a complete vehicle multi-body dynamic model established by the relevant parameters of the current vehicle, and load data of the current vehicle is obtained by combining a preset tire model.
Specifically, according to the embodiment of the application, a complete vehicle multi-body dynamic model can be established according to related parameters of a current vehicle, and then road surface data is extracted from a virtual experimental field file or generated according to road surface information input by a user and input into the complete vehicle multi-body dynamic model
Optionally, in some embodiments, before inputting the road surface data into the full vehicle multi-body dynamic model established by the relevant parameters of the current vehicle, the method further includes: simulating to obtain initial acceleration, initial displacement and reference load based on an initial whole vehicle multi-body dynamic model; taking the initial acceleration and the initial displacement as target loads, and iterating to obtain actual loads; comparing the reference load with the actual load to obtain a corrected value of the model transfer function; and correcting the initial whole vehicle multi-body dynamic model by using the correction value to obtain a whole vehicle multi-body dynamic model.
Optionally, in some embodiments, comparing the reference load with the actual load to obtain a correction value of the model transfer function includes: respectively extracting time domain characteristics and frequency domain characteristics of the reference load and the actual load; comparing the time domain and frequency domain characteristics of the reference load and the actual load to obtain a comparison result; and when the comparison result does not meet the preset condition, generating a correction value according to a preset correction strategy.
Specifically, the embodiment of the application can obtain the spindle nose acceleration (namely initial acceleration), the displacement signal (namely initial displacement) and the spindle nose decomposition load (namely reference load) based on the initial finished automobile multi-body dynamic model simulation, the sample automobile provided with the six-component and spindle nose acceleration sensors is arranged on a 24-channel rack, the initial acceleration and the initial displacement are used as target loads, the iterative test is carried out to obtain the spindle nose six-component load (namely actual load), the time domain and frequency domain comparison is carried out on the reference load obtained by the simulation and the actual load obtained by the rack iteration, if the precision does not meet the test requirement (namely the comparison result does not meet the preset condition), a correction value is generated according to the preset correction strategy, for example, the embodiment of the application can correct the finished automobile multi-body dynamic model transfer function, the steps are repeated until the comparison result meets the preset condition, thereby obtaining the whole vehicle multi-body dynamic model.
In step S303, load data of each vehicle component is simulated based on the load data of the current vehicle.
Specifically, after the comparison result meets the preset condition, the whole vehicle multi-body dynamic model can be obtained, and therefore the decomposed load file of each vehicle component can be output to the whole vehicle multi-body dynamic model for simulation analysis.
In addition, in one embodiment of the present application, after the load data of each vehicle component is obtained based on the load data simulation of the current vehicle, the fatigue strength estimation value of each component can be calculated according to the load data, so that a corresponding improvement strategy is generated according to the fatigue strength estimation value of each component, and not only can the performance optimization of the vehicle be realized, but also the fatigue strength evaluation and improvement of the components can be realized.
In order to further understand the road load testing method according to the embodiment of the present application, the following embodiments are combined and detailed below.
Referring to fig. 4 and 5, the road load testing method includes the following steps:
s401, road surface data (virtual road surface files in the figure 5) of a preset test field are obtained and input into the ADAMS vehicle model.
S402, decomposing the load through simulation analysis to obtain the spindle nose decomposed load, the spindle nose acceleration and the initial displacement.
And S403, loading the sample car provided with the six-component and shaft head acceleration sensor into a 24-channel rack, and performing iterative test by taking the initial acceleration and the initial displacement as target loads.
And S404, obtaining the six-component load of the shaft head.
S405, judging whether the test requirements are met or not according to the time domain and frequency domain comparison result of the spindle nose decomposition load and the spindle nose six-component load, if so, executing S406, otherwise, obtaining a correction value of the model transfer function according to the comparison result, and executing S402 after adjusting the ADAMS vehicle model parameters by using the correction value.
And S406, outputting an analysis load file.
According to the road load testing method provided by the embodiment of the application, the road data of a preset test field can be obtained, the road data is input into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, the load data of the current vehicle is obtained by combining a preset tire model, and the load data of each vehicle component is obtained through simulation based on the load data of the current vehicle. From this, solved need spend a large amount of time preparation mule car, six component data acquisition adapters among the correlation technique, arranged various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in dedicated test site, need spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
Next, a road load testing device proposed according to an embodiment of the present application is described with reference to the drawings.
Fig. 6 is a block schematic diagram of a road load testing device according to an embodiment of the present application.
As shown in fig. 6, the road load testing device 10 includes: an acquisition module 100, an input module 200, and a test module 300.
The acquisition module 100 is configured to acquire road surface data of a preset test field;
the input module 200 is used for inputting road surface data into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, and obtaining load data of the current vehicle by combining a preset tire model; and
the test module 300 is used to simulate the load data for each vehicle component based on the load data of the current vehicle.
Optionally, the apparatus 10 according to the embodiment of the present application further includes:
the calculation module is used for calculating the fatigue strength estimation value of each part according to the load data of each vehicle part;
and the generating module is used for generating a corresponding improvement strategy according to the fatigue strength estimated value of each part.
Optionally, the obtaining module 100 is specifically configured to:
acquiring a virtual test field file of a preset test field, and extracting road surface data from the virtual test field file;
or receiving road surface information input by a user and generating road surface data according to the road surface information.
Optionally, before inputting the road data into the full vehicle multi-body dynamic model established by the relevant parameters of the current vehicle, the input module 200 is further configured to:
simulating to obtain initial acceleration, initial displacement and reference load based on an initial whole vehicle multi-body dynamic model;
taking the initial acceleration and the initial displacement as target loads, and iterating to obtain actual loads;
comparing the reference load with the actual load to obtain a corrected value of the model transfer function;
and correcting the initial whole vehicle multi-body dynamic model by using the correction value to obtain a whole vehicle multi-body dynamic model.
Optionally, the input module 200 is further configured to:
respectively extracting time domain characteristics and frequency domain characteristics of the reference load and the actual load;
comparing the time domain and frequency domain characteristics of the reference load and the actual load to obtain a comparison result;
and when the comparison result does not meet the preset condition, generating a correction value according to a preset correction strategy.
It should be noted that the explanation of the embodiment of the road load testing method is also applicable to the road load testing device of the embodiment, and is not repeated herein.
According to the road load testing device provided by the embodiment of the application, the road data of a preset test field can be obtained, the road data is input into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, the load data of the current vehicle is obtained by combining a preset tire model, and the load data of each vehicle component is obtained through simulation based on the load data of the current vehicle. From this, it needs to spend a large amount of time preparation mule car, six component data acquisition adapters among the correlation technique to have solved, arranges various data acquisition's sensor to need professional driver and load tester to take professional equipment to test in dedicated experimental place, need to spend a large amount of manual works and the problem of time, practice thrift load test cost, very big reduction work load can guarantee load test's accuracy.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
The processor 702, when executing the program, implements the road load testing method provided in the above-described embodiments.
Further, the electronic device further includes:
a communication interface 703 for communication between the memory 701 and the processor 702.
A memory 701 for storing computer programs operable on the processor 702.
The memory 701 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 7, but that does not indicate only one bus or one type of bus.
Optionally, in a specific implementation, if the memory 701, the processor 702, and the communication interface 703 are integrated on a chip, the memory 701, the processor 702, and the communication interface 703 may complete mutual communication through an internal interface.
The processor 702 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
The present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the road load testing method as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
Claims (10)
1. A road load testing method is characterized by comprising the following steps:
acquiring pavement data of a preset test field;
inputting the road surface data into a whole vehicle multi-body dynamic model established by relevant parameters of a current vehicle, and combining a preset tire model to obtain load data of the current vehicle; and
and simulating to obtain the load data of each vehicle component based on the load data of the current vehicle.
2. The method of claim 1, further comprising:
calculating the fatigue strength estimated value of each part according to the load data of each vehicle part;
and generating a corresponding improvement strategy according to the fatigue strength estimated value of each part.
3. The method of claim 1, wherein the obtaining road surface data of a predetermined test field comprises:
acquiring a virtual test field file of a preset test field, and extracting the road surface data from the virtual test field file;
or receiving road surface information input by a user, and generating the road surface data according to the road surface information.
4. The method of claim 1, prior to inputting the road surface data into a full vehicle multi-body dynamics model established from relevant parameters of a current vehicle, further comprising:
simulating to obtain initial acceleration, initial displacement and reference load based on an initial whole vehicle multi-body dynamic model;
taking the initial acceleration and the initial displacement as target loads, and iterating to obtain actual loads;
comparing the reference load with the actual load to obtain a corrected value of a model transfer function;
and correcting the initial finished automobile multi-body dynamic model by using the correction value to obtain the finished automobile multi-body dynamic model.
5. The method of claim 4, wherein comparing the reference load to the actual load to obtain a correction to the model transfer function comprises:
respectively extracting time domain characteristics and frequency domain characteristics of the reference load and the actual load;
comparing the time domain and frequency domain characteristics of the reference load and the actual load to obtain a comparison result;
and when the comparison result does not meet the preset condition, generating the correction value according to a preset correction strategy.
6. A road load testing device, comprising:
the acquisition module is used for acquiring road surface data of a preset test field;
the input module is used for inputting the road surface data into a whole vehicle multi-body dynamic model established by the related parameters of the current vehicle and obtaining the load data of the current vehicle by combining a preset tire model; and
and the test module is used for simulating to obtain the load data of each vehicle component based on the load data of the current vehicle.
7. The apparatus of claim 6, further comprising:
the calculation module is used for calculating the fatigue strength estimation value of each part according to the load data of each vehicle part;
and the generating module is used for generating a corresponding improvement strategy according to the fatigue strength estimated value of each part.
8. The apparatus of claim 6, wherein the obtaining module is specifically configured to:
acquiring a virtual test field file of a preset test field, and extracting the road surface data from the virtual test field file;
or receiving road surface information input by a user, and generating the road surface data according to the road surface information.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the road load testing method according to any one of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a road load testing method according to any one of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114861335A (en) * | 2022-07-11 | 2022-08-05 | 岚图汽车科技有限公司 | Calibration method of automobile dynamics calculation model and related equipment |
| CN116579187A (en) * | 2023-07-12 | 2023-08-11 | 岚图汽车科技有限公司 | Calibration method and device for vehicle simulation test and real vehicle test |
-
2021
- 2021-12-22 CN CN202111580149.8A patent/CN114462188A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114861335A (en) * | 2022-07-11 | 2022-08-05 | 岚图汽车科技有限公司 | Calibration method of automobile dynamics calculation model and related equipment |
| CN116579187A (en) * | 2023-07-12 | 2023-08-11 | 岚图汽车科技有限公司 | Calibration method and device for vehicle simulation test and real vehicle test |
| CN116579187B (en) * | 2023-07-12 | 2023-09-19 | 岚图汽车科技有限公司 | Calibration method and device for vehicle simulation test and real vehicle test |
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