A VPG-based equivalent method for the load spectrum of commercial vehicles

Abstract

The present invention discloses a method for equivalent conversion of commercial vehicle load spectra based on VPG, which comprises the following steps: obtaining the load spectra in the test field; comparative analysis of each test signal data, and equivalent conversion of the damage from each load to the full load; obtaining the VPG simulation load spectra; optimizing the equivalent conversion of the load spectra damage; and outputting the equivalent load spectra. The present invention solves the problem of matching between the simulation data and the test data in the case of a large range of load changes of commercial vehicles, shortens the workload of model matching, has a lower difficulty, improves the accuracy of the load spectra obtained by the virtual simulation technology of commercial vehicles, and can better and more accurately predict the fatigue performance of vehicles.

Description

Technical Field

[0001] The present invention relates to the simulation application of a commercial vehicle virtual proving ground, and in particular to a method for equivalent commercial vehicle load spectrum based on VPG. Background Art

[0002] The co-simulation based on virtual road surface and vehicle multi-body dynamics model can predict the vehicle load under the virtual proving ground environment. This technology is generally called virtual proving ground technology, namely Virtual Proving Ground, abbreviated as VPG. This technology is currently widely used in passenger cars. However, for commercial vehicles, the load range varies greatly and the road conditions are more complex, which increases the difficulty of applying VPG technology to commercial vehicles. In particular, how to evaluate the data obtained by simulation and the data under different load conditions during tests, and how to consider the influence of the load change range.

[0003] In the vehicle multi-body dynamics model, some parameters are difficult to measure and can only be based on empirical values; as the first-level vibration isolation system in the vehicle that directly contacts the road surface, the modeling accuracy of the tire directly affects the accuracy of the loads of all other components; due to accuracy problems or actual road surface wear during virtual road surface scanning, etc.; all of the above may cause errors between the simulated load and the actual measurement. To reduce the errors, a large amount of benchmarking work is required to improve the accuracy of the vehicle model, including parameter measurement, tire test modeling, and performance sensitivity analysis, etc., which is time-consuming, laborious, and has a large workload and high difficulty. Summary of the Invention

[0004] Based on the above technical problems existing in the application of commercial vehicle VPG, the present invention provides a method for equivalent commercial vehicle load spectrum based on VPG with less benchmarking work between simulation data and test data and lower difficulty.

[0005] To solve the above technical problems, the technical solution of the present invention is: a method for equivalent commercial vehicle load spectrum based on VPG, comprising the following steps:

[0006] Step 1, obtaining the load spectrum of the test field:

[0007] Select the durable road surface of the test field and plan the driving sequence, and plan the load channels at the attachment points of each key component; then conduct a load test on the commercial vehicle, collect the load test signals under various loads, and obtain the test load spectrum;

[0008] Step 2, comparative analysis of the data of each test signal, and damage equivalence from each load to full load:

[0009] First, process the data of the load test signals under each load, and scale the test signals under each load to the full load state through amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, thereby forming a test load spectrum under the equivalent full load condition;

[0010] Step 3, Obtaining the VPG simulation load spectrum:

[0011] According to the actual test track of the test site, simulate each virtual road surface in sequence and screen out the simulation load channels corresponding to each actual test load channel to obtain the simulation load spectra of each simulation load channel;

[0012] Step 4, Equivalent optimization of load spectrum damage:

[0013] Based on the principle of consistent damage, use the genetic algorithm to iteratively equivalent the simulation load damage matrix of the simulation load channel to the test load damage matrix of the test load channel. The SN curve parameters remain consistent during the pseudo-damage calculation;

[0014] Step 5, Output of equivalent load spectrum:

[0015] Multiply the simulation load spectra of each simulation load channel after equivalent iteration by the corresponding equivalent coefficient in the time domain according to each road surface, and then connect them in series according to the order of each road surface to obtain the equivalent load spectrum.

[0016] As a preferred technical solution, the road surfaces in step 1 include n road surfaces such as potholed roads, twisted roads, stone roads, cobblestone roads, and washboard roads.

[0017] As a preferred technical solution, the load channels of the key component attachment points in step 1 include m load channels such as wheel center force, shock absorber displacement, and frame attachment point acceleration.

[0018] As a preferred technical solution, the commercial vehicle load test in step 1 includes tests under no-load, half-load, and full-load conditions.

[0019] As a preferred technical solution, step 2 is: comparative analysis of each test signal data, equivalent damage from no-load, half-load to full-load. First, perform data processing on the load test signal data under each load. Scale the signals of no-load and half-load to the full-load state through amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, thereby forming the test load spectrum under the equivalent full-load condition.

[0020] As a preferred technical solution, the load spectrum damage equivalent optimization in step 4 includes:

[0021] a. Perform pseudo-damage calculation on the load spectra of each simulation load channel according to the combined road surfaces respectively to obtain an m×n variable matrix

[0022]

[0023] where X mn represents the damage value of simulation load channel m on road surface n;

[0024] b. Calculate the pseudo-damage of the load spectra of each test load channel according to the combined pavement to obtain an m×1 target matrix

[0025]

[0026] where Y m represents the sum of the damage values of test load channel m on all pavements;

[0027] c. Based on the multi-objective optimization principle of the genetic algorithm, optimize and iterate the variable matrix towards the target matrix, and calculate the equivalent coefficient according to the following formula

[0028]

[0029] In the formula, is the variable matrix, which is the simulation load damage matrix; is the target matrix, which is the test load damage matrix; is the equivalent coefficient matrix, and α n is the equivalent coefficient corresponding to pavement n;

[0030] The control solution is an integer greater than zero. After iteratively solving the equivalent coefficient matrix, a solution of an n×1 matrix is obtained, that is, the equivalent coefficients corresponding to n pavements.

[0031] Due to the adoption of the above technical solution, the present invention has the following advantages: 1. Solve the problem of matching simulation data and test data in the case of a large range of commercial vehicle load changes, and the obtained load spectrum is closer to the actual test value; 2. The method of fatigue damage equivalent iteration based on the genetic algorithm of the present invention is more convenient and fast compared with the traditional method of improving the accuracy of the load spectrum, without having to pursue the accuracy of the model too much, shortening the workload of model matching and having a lower difficulty; 3. Avoid errors caused by uncertain factors such as parameters that cannot be directly measured, improve the accuracy of the load spectrum obtained by virtual simulation technology for commercial vehicles, and can better and more accurately predict the fatigue performance of vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The following drawings are only intended to illustrate and explain the present invention and do not limit the scope of the present invention. Among them:

[0033] Figure 1 is the flow chart of the present invention;

[0034] Figure 2 is the schematic diagram of virtual road simulation of the whole vehicle model of the present invention;

[0035] Figure 3 is the schematic diagram of the comparison example of the test and simulation data of the vertical force channel of the left front wheel of the present invention on the stone road;

[0036] Figure 4 It is a schematic diagram of an example of the combined road surface load spectrum after the vertical force of the left front wheel of the present invention is equivalent. Specific implementation manners

[0037] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Here, it should be noted that in the drawings, the same reference numerals are assigned to components having substantially the same structure and function, and in order to make the description of the specification more concise, redundant descriptions of substantially the same components are omitted.

[0038] As Figure 1 shown, a method for equivalent of a commercial vehicle load spectrum based on VPG includes the following steps:

[0039] Step 1, obtaining the load spectrum of the test field:

[0040] Select the durable road surface of the test field and plan the driving sequence, and plan the load channels of the attachment points of each key component; then conduct a load test on the commercial vehicle, collect the load test signals under various loads, and obtain the test load spectrum; where the road surface includes potholed roads, twisted roads, stone roads, cobblestone roads, and washboard roads, and even n road surfaces such as other roads that need to be tested; and the load channels of the attachment points of the key components include wheel center force, shock absorber displacement, frame attachment point acceleration, and even m load channels such as other components that need to be tested; and preferably, the load test on the commercial vehicle includes tests under no-load, half-load, and full-load conditions, and consistency and unity are ensured as much as possible on the premise of ensuring the accuracy of the test.

[0041] Step 2, comparative analysis of the data of each test signal, and damage equivalence from each load to full load:

[0042] First, process the data of the load test signals under each load. Scale the test signals under each load to the full-load state by amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, thereby forming a test load spectrum under the equivalent full-load condition; preferably, use comparative analysis of the data of each test signal, and damage equivalence from no-load, half-load to full load. First, process the data of the load test signals under each load. Scale the no-load and half-load signals to the full-load state by amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, and at the same time consider the mileage distribution under different loads of the test scheme, thereby forming a test load spectrum under the equivalent full-load condition.

[0043] As Figure 2 shown, perform Step 3, obtaining the VPG simulation load spectrum:

[0044] According to the actual test site test route, each virtual road surface is simulated in sequence, and the simulation load channels corresponding to each actual test load channel are screened to obtain the simulation load spectra of each simulation load channel; as Figure 3 shown in the schematic diagram of the example, which is the comparison of the test and simulation data of the vertical force channel of the left front wheel on the stone road;

[0045] Step 4, load spectrum damage equivalent optimization:

[0046] Based on the principle of consistent damage, the genetic algorithm is used to equivalently iterate the simulation load damage matrix of the simulation load channel to the test load damage matrix of the test load channel, and the SN curve parameters are kept consistent during the pseudo-damage calculation; including:

[0047] a. Calculate the pseudo-damage of the load spectra of each simulation load channel according to the combined road surface respectively to obtain a variable matrix of m×n

[0048]

[0049] where X mn represents the damage value of the simulation load channel m on the road surface n;

[0050] b. Calculate the pseudo-damage of the load spectra of each test load channel according to the combined road surface to obtain a target matrix of m×1

[0051]

[0052] where Y m represents the sum of the damage values of the test load channel m on all road surfaces;

[0053] c. Based on the multi-objective optimization principle of the genetic algorithm, optimize and iterate the variable matrix to the target matrix, and calculate the equivalent coefficient according to the following formula

[0054]

[0055] In the formula, is the variable matrix, which is the simulation load damage matrix; is the target matrix, which is the test load damage matrix; is the equivalent coefficient matrix, α n is the equivalent coefficient corresponding to the road surface n;

[0056] The control solution is an integer greater than zero. After iteratively solving the equivalent coefficient matrix, a solution matrix of n×1 is obtained, that is, the equivalent coefficients corresponding to n road surfaces;

[0057] Step 5, equivalent load spectrum output:

[0058] Multiply the simulation load spectra of each simulation load channel after equivalent iteration by the corresponding equivalent coefficient in the time domain for each road surface, and then connect them in series according to the order of each road surface to obtain the equivalent load spectrum. As Figure 4 shown in the schematic diagram of the example, it is the combined load spectrum of the road surface after the vertical force of the left front wheel is equivalent.

[0059] Figure 3 and Figure 4 The schematic diagram of the example shown is an example of the test and simulation processing of the vertical force channel of the left front wheel on a stone road. The load spectra of other components on the vehicle can also be processed according to the equivalent method of the present invention based on VPG simulation without actual testing, and the accuracy is also close to the actual vehicle test value, saving testing and calibration time.

[0060] The present invention solves the disadvantages of time-consuming and laborious simulation testing in the virtual test field of commercial vehicles and the difficulty in measuring key positions. Moreover, the load spectrum obtained through the principle of fatigue damage consistency is closer to the actual test value, ensuring that the fatigue damage caused by the simulation load and the actual test field load to each component of the commercial vehicle is as consistent as possible. By applying a damage iteration tool based on the genetic algorithm, the fatigue performance of the vehicle can be predicted more accurately. The present invention provides a key technical foundation for enterprises to quickly develop high-quality and highly reliable products and quickly seize the market.

[0061] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A VPG-based equivalent method for the load spectrum of commercial vehicles, characterized in that It includes the following steps: Step 1, obtaining the load spectrum of the test site: Select the durable road surface of the test site and plan the driving sequence, and plan the load channels of the attachment points of each key component; then conduct a load test on the commercial vehicle, collect the load test signals under various loads, and obtain the test load spectrum; Step 2, comparative analysis of each test signal data and damage equivalence from each load to full load: First, perform data processing on the load test signal data under each load, and scale the test signals under each load to the full load state through amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, thereby forming a test load spectrum under the equivalent full load condition; Step 3, obtaining the VPG simulation load spectrum: According to the actual test route of the test site, simulate each virtual road surface in sequence and screen out the simulation load channels corresponding to each actual test load channel to obtain the simulation load spectrum of each simulation load channel; Step 4, equivalent optimization of the load spectrum damage: Based on the principle of consistent damage, use the genetic algorithm to iteratively equivalent the simulation load damage matrix of the simulation load channel to the test load damage matrix of the test load channel. The SN curve parameters remain the same during the pseudo-damage calculation, and the equivalent optimization of the load spectrum damage includes: a. Calculate the pseudo-damage of the load spectrum of each simulation load channel separately according to the composite road surface to obtain an m×n variable matrix Where X mn represents the damage value of the simulation load channel m on the road surface n; b. Calculate the pseudo-damage of the load spectrum of each test load channel according to the composite road surface to obtain an m×1 target matrix Among which Y m represents the sum of the damage values of the test load channel m on all road surfaces; c. Based on the multi-objective optimization principle of the genetic algorithm, optimize and iterate the variable matrix to the target matrix, and calculate the equivalent coefficient according to the following formula In the formula, is a variable matrix, which is the simulation load damage matrix; is the target matrix, which is the test load damage matrix; is the equivalent coefficient matrix, and α n is the equivalent coefficient corresponding to pavement n; The control solution is an integer greater than zero. After iteratively solving the equivalent coefficient matrix, a solution matrix of n×1 is obtained, that is, the equivalent coefficients corresponding to n road surfaces; Step 5, output of the equivalent load spectrum: Multiply the simulation load spectrum of each simulation load channel after equivalent iteration by the corresponding equivalent coefficient in the time domain according to each road surface, and then connect them in series according to the order of each road surface to obtain the equivalent load spectrum.

2. The equivalent method of commercial vehicle load spectrum based on VPG according to claim 1, characterized in that: The road surfaces in Step 1 include n road surfaces such as potholed roads, twisted roads, stone roads, cobblestone roads, and washboard roads.

3. The equivalent method of commercial vehicle load spectrum based on VPG according to claim 1, characterized in that: The load channels of the attachment points of the key components in Step 1 include m load channels such as wheel center force, shock absorber displacement, and frame attachment point acceleration.

4. A method for equivalent of commercial vehicle load spectrum based on VPG as claimed in claim 1, characterized in that: The load test on the commercial vehicle in Step 1 includes tests under no-load, half-load, and full-load conditions.

5. The equivalent method of the commercial vehicle load spectrum based on VPG according to claim 4, characterized in that, Step 2 is: comparative analysis of each test signal data and damage equivalence from no-load, half-load to full load. First, perform data processing on the load test signal data under each load, and scale the no-load and half-load signals to the full load state through amplitude or time, so that the load damage after scaling remains the same as the load damage before scaling, thereby forming a test load spectrum under the equivalent full load condition.

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