CN111414715A - Body-in-white input load determination method, body-in-white input load determination device, computer equipment and storage medium - Google Patents
Body-in-white input load determination method, body-in-white input load determination device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to the field of automobile development, in particular to a body-in-white input load determining method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by actually testing a real vehicle corresponding to the target automobile in a test field; establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of a target vehicle; determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model; and performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile. The embodiment of the invention can test the input load of the body-in-white more conveniently.
Description
Technical Field
The application relates to the field of automobile development, in particular to a body-in-white input load determining method, a body-in-white input load determining device, a computer device and a storage medium.
Background
The light weight of the automobile is one of the important directions of the current automobile technology development, however, the light weight of the automobile body directly leads the white automobile body to be subjected to alternating load during the whole automobile road driving process to cause fatigue failure of the white automobile body, and the white automobile body refers to an automobile body structural member and a covering part welding assembly and comprises a front wing plate, an automobile door, an engine hood and a trunk lid, but does not comprise accessories and decorative parts. The fatigue failure of the body-in-white mainly shows the problems of the cracking of welding spots of the body-in-white and the like, so that the fatigue life prediction analysis of the body-in-white structure is required during the design and improvement of the body-in-white so as to ensure that the fatigue failure of the body-in-white does not occur after the design and the light weight of the body-in-white structure.
The method has the advantages that the method is long in test period, considerable labor cost is required, and the method is relatively dependent on actual sample vehicles, and the test can be carried out only after physical sample pieces are manufactured.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a body-in-white input load determining method, a body-in-white input load determining device, computer equipment and a storage medium.
The present invention provides according to a first aspect a body-in-white input load determination method, which in one embodiment comprises:
acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by actually testing a real vehicle corresponding to the target automobile in a test field;
establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of a target vehicle;
determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model;
and performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
In one embodiment, establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of a target vehicle comprises:
acquiring chassis parameters of a target automobile, and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters;
establishing a body-in-white finite element model of the target automobile;
and establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
In one embodiment, determining signal correlation information of a vehicle model includes:
inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal;
and determining signal correlation information of the whole vehicle model according to the first driving signal and the first response signal.
In one embodiment, the iterative simulation test of the entire vehicle model is performed according to the actual measurement signal and the signal correlation information, and comprises the following steps:
1) inputting a random white noise signal generated by a program as a system input signal into a first preset position in a finished automobile model to obtain a system output signal generated by a second preset position in the finished automobile model due to the system input signal;
2) comparing the system output signal with the actual measurement signal to obtain a comparison result;
3) judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
4) correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again);
5) and determining the system input signal as a finally obtained iteration simulation test result.
In one embodiment, comparing the system output signal with the actual measurement signal to obtain a comparison result comprises:
determining information of a system output signal and an actual measurement signal on preset contrast items respectively, wherein the preset contrast items comprise at least one contrast item of a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item;
and comparing the information of the system output signal and the actual measurement signal on the preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
In one embodiment, the preset condition is a preset condition corresponding to a contrast item included in the preset contrast item;
judging whether the comparison result meets a preset condition or not, including:
and judging whether the comparison result corresponding to the comparison item included in the preset comparison item meets the preset condition corresponding to the comparison item.
In one embodiment, the first preset position is at four wheel shock absorbers of the whole vehicle model;
the second preset position is the shaft heads of four wheels of the whole vehicle model and the mass center of the vehicle body;
the actual measurement signals comprise displacement signals respectively generated at four wheel vibration absorbers in a real vehicle corresponding to the target automobile, acceleration signals respectively generated at four wheel shaft heads and acceleration signals generated at the center of mass of the automobile body.
The present invention provides according to a second aspect a body-in-white input load determining apparatus, which in one embodiment comprises:
the actual measurement signal acquisition module is used for acquiring an actual measurement signal of the target automobile, wherein the actual measurement signal is data generated by actual test of an actual vehicle corresponding to the target automobile in a test field;
the whole vehicle model building module is used for building a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle;
the system comprises a correlation information determining module, a correlation information determining module and a correlation information determining module, wherein the correlation information determining module is used for determining signal correlation information of a whole vehicle model, and the signal correlation information represents a correlation relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model;
and the input load determining module is used for performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
The present invention provides according to a third aspect a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of an embodiment of any of the methods described above when executing the computer program.
The present invention provides according to a fourth aspect a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the embodiments of the method of any one of the above.
In the embodiment of the invention, when the input load of a target body-in-white needs to be determined, the actual measurement signal of a target automobile is obtained firstly; establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of a target vehicle; determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model; and then carrying out iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile, thereby realizing more convenient test of the body-in-white input load in the test process.
Drawings
FIG. 1 is a schematic flow chart of a body-in-white input load determination method in one embodiment;
FIG. 2 is a schematic diagram of a rigid-flexible coupled multi-body dynamic vehicle model in one embodiment;
FIG. 3 is a schematic view of a mechanical system in one embodiment;
FIG. 4 is a schematic diagram of an iterative simulation test flow of a vehicle model in one embodiment;
FIG. 5 is a block diagram showing the structure of a body-in-white input load determining apparatus according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Referring to fig. 1, a body-in-white input load determination method is provided according to an embodiment of the present invention, and the body-in-white input load can be used for predicting the fatigue life of a body-in-white. Further, the method may be applied to a server (including a single server, a server cluster composed of multiple servers, etc.), a smart mobile terminal (including but not limited to a smart phone, a tablet computer, a personal computer, etc.), and the following description will take the application of the method to a background server as an example. The method comprises the following steps:
step S110: and acquiring an actual measurement signal of the target automobile, wherein the actual measurement signal is data generated by actually testing the real vehicle corresponding to the target automobile in a test field.
In this embodiment, a tester needs to place a real vehicle corresponding to a target vehicle on a strengthened durable road of a test field for testing, and then collects signals generated by the real vehicle in the testing process for multiple times. After testing the real vehicle of the target automobile, the tester transmits the acquired data to the background server, and the background server performs subsequent processing. In order to improve the data quality of the data collected by the tester, the tester may process the data after collecting the data, such as performing filtering processing, deburring processing, and the like. Possibly, the tester can directly send the collected data to the background server, and the background server processes the data.
Specifically, the signals to be collected may include acceleration signals at four wheel axle heads (also referred to as wheel centers) of a real vehicle, an acceleration signal at a center of mass of a vehicle body (also referred to as a center of mass in the vehicle), and displacement signals of four wheel shock absorbers. The wheel vibration absorber is a vibration absorber arranged at the axle head of the wheel. The displacement signal and the acceleration signal can be acquired by installing a sensor of a corresponding type on a real vehicle. For example, the type of sensor to be installed on a real vehicle and the installation location thereof may be as shown in table one.
Table one:
| sensor type | Measuring signal | Mounting location |
| Displacement sensor | Upper and lower end displacement of shock absorber | Two ends of the shock absorber |
| Acceleration sensor | Acceleration in one direction | Wheel support |
| Acceleration sensor | Acceleration in one direction | Steering knuckle |
| Acceleration sensor | Three-directional acceleration | Vehicle body mass center |
The strengthened durable road of the test field can comprise belgium roads, inclined irregular roads, stone roads, washboard roads and other roads, and the target automobile refers to an automobile needing to test the white body input load, specifically can refer to an automobile of a certain type, and can also refer to an automobile of a certain type.
Step S120: and establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle.
In this embodiment, the background server needs to establish a multi-body dynamic model of the target vehicle to perform the simulation test. When a multi-body dynamic model is established, the components in the model are of two types, namely a rigid body and a flexible body, the rigid body component cannot deform under the action of external force, and the flexible body component deforms under the action of external force. Therefore, in order to improve the accuracy of model simulation and further improve the accuracy of simulation test results, the present embodiment establishes a rigid-flexible coupled multi-body dynamic whole vehicle model for the target vehicle, that is, the whole vehicle model includes both rigid body members and flexible body members.
In one embodiment, the step of establishing, by the background server, a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle includes:
acquiring chassis parameters of a target automobile, and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters;
establishing a body-in-white finite element model of the target automobile;
and establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
Specifically, an ADAMS (Automatic Dynamic Analysis of mechanical systems) software can be used to build a multi-body kinetic model. The tester can upload the chassis parameters of various types or types of automobiles to the background server in advance and store the chassis parameters in the database, and when the background server needs to acquire the chassis parameters, the tester can acquire the chassis parameters corresponding to the target automobile from the database. The chassis parameters may include geometrical parameters of the automotive part, as well as performance parameters of some of the elastic elements. And combining the chassis multi-body dynamic model established by the background server according to the chassis parameters, which belongs to a rigid body model, and the white body finite element model, which belongs to a flexible body model, to obtain a rigid-flexible coupled multi-body dynamic whole vehicle model. The resulting full vehicle model is shown in fig. 2, in which the powertrain and the counterweight are represented as static mass loads, and in this example, the load signal at the axle head of the wheel is used as the input signal of the full vehicle model, so the model of the tire is not included in the full vehicle model shown in fig. 2.
In order to further improve the accuracy of the whole vehicle model, the whole vehicle model may be verified and corrected for multiple times, for example, static and dynamic calibration may be performed on the whole vehicle model, a simulation test result obtained by performing a simulation test on the whole vehicle model is compared with the actual measurement signal of the target vehicle obtained in step S110, and if a difference between the simulation test result and the actual measurement signal is found to be increased after the comparison, a response result generated by the whole vehicle model may be substantially the same as a response result generated by the real vehicle when a load excitation received by the whole vehicle model is the same as a load excitation received by the real vehicle by adjusting damping parameters in the whole vehicle model and changing some parts in the whole vehicle model from a rigid body to a flexible body.
Step S130: and determining signal correlation information of the whole vehicle model, wherein the signal correlation information represents the correlation between the signal at the first preset position and the signal at the second preset position in the whole vehicle model.
In this embodiment, the whole vehicle model is regarded as a system, a signal at a first preset position in the whole vehicle model is used as a system input signal (i.e., a signal of a system of externally inputting the whole vehicle model), and a signal at a second preset position in the whole vehicle model is used as a system output signal (i.e., a signal of the system of the whole vehicle model which is externally output). The signal correlation information refers to a load transfer characteristic matrix of the whole vehicle model and is used for describing a correlation between a system input signal and a system output signal of the whole vehicle model.
In one embodiment, the step of determining signal correlation information of the entire vehicle model includes:
inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal;
and determining signal correlation information of the whole vehicle model according to the first driving signal and the first response signal.
Specifically, after the whole vehicle model is established, a simulation test needs to be performed to determine a load transfer characteristic matrix of the whole vehicle model. When the simulation test is performed, a white noise signal can be randomly generated through a program, and then the white noise signal is input to a first preset position of a whole vehicle model as a driving signal (i.e., a first driving signal), which is equivalent to that the whole vehicle model is placed on a road to run, at this time, the whole vehicle model generates a response signal due to the driving signal, and specifically, the response signal (i.e., the first response signal) generated at a second preset position of the whole vehicle model after the driving signal is input needs to be collected.
Further, in one embodiment, the first preset position refers to four wheel shock absorbers of the whole vehicle model; the second preset position refers to the shaft heads of four wheels and the mass center of the vehicle body of the whole vehicle model.
And after the first response signal is acquired, the first driving signal is used as a system input signal, the first response signal is used as a system output signal, and a load transfer characteristic matrix of the whole vehicle model is determined according to the system input signal and the system output signal.
Currently, commonly used methods for estimating the load transfer characteristic matrix of the system include estimation methods H1, H2, H3, H4, Hc, Hl, and Hv. In application, the above estimation methods each have limitations. For example, the H1 estimation method is only applicable to cases where there is no or little input measurement noise; the H2 estimation method is only applicable to cases where the output measurement noise is zero or small; the H3 estimation method can be unbiased estimation only when the input-output signal-to-noise ratios are equal; the H4 estimation method loses phase information again; although the two estimation methods of Hc and Hl are unbiased estimation, a third signal needs to be introduced into the system, which increases the complexity of a test system, and introduces a new test error to increase the complexity of the test work, so that the practical application in engineering is difficult; the Hv estimation method also has a bias in its estimation of the load transfer characteristic matrix due to the presence of the self-spectral terms of the input noise. The estimation method is relatively dependent on the test precision, and when the test precision is not high enough, the precision of the load transfer characteristic matrix obtained by estimation is greatly influenced.
In order to obtain a load transfer characteristic matrix with higher precision, the present embodiment estimates the load transfer characteristic matrix of the entire vehicle model by using an improved estimation method. The entire vehicle model can be regarded as an input/output noisy system (hereinafter referred to as an entire vehicle system) as shown in fig. 3. The whole vehicle system is tested for N times, random interference signals measured each time are irrelevant to the real input load and the real output load of the whole vehicle system, and in addition, the test carried out on the whole vehicle system can be a real test carried out on a real vehicle or a simulation test carried out on a whole vehicle model. The ith test of the whole vehicle system can obtain an expression shown in an expression (1).
Wherein, { InI is the measured input load vector; { OmI is trueMeasuring a response load vector; { NiMeasuring an interference signal input vector (measuring noise interference); { MmI is a measurement interference signal output vector (measurement noise interference); [ H (f)]mn is a load transfer function matrix of the system; { In}i＝{Fn}i+{Nn}i；{Om}i＝{Pm}i+{Mm}i；i＝1，2，…N-1；
From equation (1), for each i, the equation is right-multiplied on both sides simultaneously
(j ═ i +1, i +2, …, N), N × (N-1)/2 equations can be obtained, and then the power spectrum equation shown in equation (2) is obtained.
In formula (2):
wherein, [ MI]HIs [ MI ]]The conjugate transpose of (c).
Equation (3) can be derived by calculating the expected value of equation (2) and dividing by the analysis time T.
According to the nature of the cross-power spectrum, the cross-power spectrum of uncorrelated signals approaches after multiple averagingZero, i.e.:
further, the estimation expression of the load transfer characteristic matrix of the whole vehicle system can be deduced to be formula (4), namely
According to the formula (4), under the condition that extra input signals and energy are not needed, N × (N-1)/2 times of averaging is carried out through N times of same tests, the estimation expression is completely represented by the input and output load signal cross power spectrum, therefore, the influence of the existence of the interference noise signal self power spectrum item in the calculation process can be eliminated, and the precision of the estimated load transfer characteristic matrix is improved.
Step S140: and performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
In this embodiment, the whole vehicle model or the real vehicle corresponding to the target vehicle can be regarded as a mechanical system. The purpose of performing the iterative simulation test on the whole vehicle model corresponding to the target vehicle is to reversely calculate an external driving load (i.e., a body-in-white input load) on a real vehicle corresponding to the target vehicle in the driving process, i.e., an iterative simulation test result obtained through the iterative simulation test is the external driving load. The external driving load can be a physical quantity such as force and/or displacement, and the response of the two mechanical systems of the whole vehicle model or the real vehicle due to the external driving load can be a physical quantity such as displacement, speed and/or acceleration.
Considering the case where the driving signal that applies force to the multi-body dynamic model will cause the model to drift or roll over, the present embodiment selects the displacement signals at the four wheel shock absorbers in the entire vehicle model and the real vehicle as the body-in-white input loads to be calculated.
In one embodiment, as shown in fig. 4, the step of performing an iterative simulation test on the entire vehicle model according to the actual measurement signal and the signal correlation information includes:
step 1): inputting a random white noise signal generated by a program as a system input signal into a first preset position in a finished automobile model to obtain a system output signal generated by a second preset position in the finished automobile model due to the system input signal;
step 2): comparing the system output signal with the actual measurement signal to obtain a comparison result;
step 3): judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
step 4): correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again);
step 5): and determining the system input signal as a finally obtained iteration simulation test result.
Specifically, in this embodiment, the first preset position refers to four wheel shock absorbers of the entire vehicle model, and the second preset position refers to four wheel spindle heads and a center of mass of the vehicle body of the entire vehicle model.
Random white noise signals input to the four wheel shock absorbers in the whole vehicle model are equivalent to displacement signals at the shaft heads of the four wheels, and serve as initial driving signals in the iterative simulation test process. After the random white noise signal is input, system output signals of a whole vehicle model can be obtained, wherein the system output signals comprise acceleration signals generated at shaft heads of four wheels and acceleration signals generated at a mass center of a vehicle body. The obtained system output signal is then compared with the previously obtained actual measurement signal to obtain a comparison result.
In one embodiment, comparing the system output signal with the actual measurement signal to obtain a comparison result comprises:
determining information of a system output signal and an actual measurement signal on preset contrast items respectively, wherein the preset contrast items comprise at least one contrast item of a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item;
and comparing the information of the system output signal and the actual measurement signal on the preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
Specifically, when comparing the system output signal with the actual measurement signal, information corresponding to the system output signal and the actual measurement signal in each comparison item is determined. For example, the preset contrast item includes three contrast items, namely a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item, it is necessary to determine crossing frequency information corresponding to the crossing frequency contrast item of the system output signal and the actual measurement signal, power spectral density information corresponding to the power spectral density contrast item, and pseudo-damage information corresponding to the pseudo-damage contrast item, then compare the crossing frequency information of the system output signal and the crossing frequency information of the actual measurement signal to obtain a crossing frequency comparison result, compare the power spectral density information of the system output signal and the power spectral density information of the actual measurement signal to obtain a power spectral density comparison result, and compare the pseudo-damage information of the system output signal and the pseudo-damage information of the actual measurement signal to obtain a pseudo-damage comparison result.
More specifically, the system output signals in the embodiment specifically include acceleration signals generated at the four wheel axle heads and acceleration signals generated at the center of mass of the vehicle body. Therefore, when comparing the system output signal with the actual measurement signal, specifically, comparing the acceleration signal generated at each wheel axle head of the whole vehicle model with the acceleration signal generated at each wheel axle head of the real vehicle, and comparing the acceleration signal generated at the body mass center of the whole vehicle model with the acceleration signal generated at the body mass center of the real vehicle, and specifically, comparing the acceleration signal of the whole vehicle model with the information of the acceleration signal of the real vehicle on each comparison item during comparison, as described above, the detailed comparison process is not repeated here.
After obtaining the comparison result between the system output signal and the actual measurement signal, step 3) is executed, i.e. whether the comparison result meets the preset condition is judged. It should be noted that the preset condition refers to a preset condition corresponding to a comparison item included in the preset comparison item, and the determining whether the comparison result meets the preset condition refers to determining whether the comparison result corresponding to the comparison item included in the preset comparison item meets the preset condition corresponding to the comparison item. That is to say, each comparison item has a corresponding preset condition, and the preset condition corresponding to each comparison item can be set by a tester according to the actual situation. For example, in the present embodiment, the pseudo damage contrast term refers to a damage ratio, as shown in equation (5).
μ＝Di/Daimi(5)
Wherein μmeans the relative injury ratio, DiFor a certain transfer path load pseudo-damage after the ith iteration, DaimFor the load target pseudo damage value of the transmission path, the relative damage ratio of the iteration signals of each transmission path is defined to be between 0.5 and 2.0, namely the transmission path is considered to meet the preset condition. It should be noted that only when the preset conditions corresponding to all the preset comparison terms are satisfied, it can be determined that the comparison result between the system output signal and the actual measurement signal satisfies the preset conditions.
Because the mechanical system belongs to a nonlinear system, and the load transfer characteristic matrix describes the incidence relation between the input and the output of the linear system, multiple iterations are needed to enable the comparison result between the system output signal and the actual measurement signal to meet the preset condition.
Specifically, if it is determined that the comparison result between the system output signal and the actual measurement signal does not satisfy the preset condition, the system input signal is corrected according to the comparison result to obtain a corrected signal; then substituting the corrected signal as a system input signal into a load transfer characteristic matrix of the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and jumping to the step 2) to start execution. And when the comparison result between the system output signal and the actual measurement signal does not meet the preset condition, jumping to the step 5) to start execution, namely determining the system input signal in the current iteration as a finally obtained iteration simulation test result.
In one embodiment, the system input signal is modified according to the comparison result to obtain a modified signal, and the modified signal may be specifically modified by equation (6).
Uk+1(jω)＝Uk(jω)+γH-1(jω)ek(jω) (6)
The method comprises the steps of obtaining a displacement signal of a wheel shock absorber in an actual measurement signal, wherein Uk +1(j omega) is a (k + 1) th iteration signal, Uk (j omega) is a driving signal of a k th iteration, gamma is an iteration step length, H (j omega) is a load transfer characteristic matrix obtained through estimation, and ek (j omega) is an error signal which is compared with the displacement signal of the wheel shock absorber in the actual measurement signal after the k th iteration. The value of the iteration step is between 0 and 1, and the specific value can be set by a detector according to different test scenes.
In one embodiment, as shown in FIG. 5, there is provided a body-in-white input load determination apparatus comprising the following modules:
the actual measurement signal acquisition module is used for acquiring an actual measurement signal of the target automobile, wherein the actual measurement signal is data generated by actual test of an actual vehicle corresponding to the target automobile in a test field;
the whole vehicle model building module is used for building a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle;
the system comprises a correlation information determining module, a correlation information determining module and a correlation information determining module, wherein the correlation information determining module is used for determining signal correlation information of a whole vehicle model, and the signal correlation information represents a correlation relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model;
and the input load determining module is used for performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
In one embodiment, the entire vehicle model building module includes:
the chassis model establishing submodule is used for acquiring chassis parameters of the target automobile and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters;
the body-in-white model establishing submodule is used for establishing a body-in-white finite element model of the target automobile;
and the whole vehicle model establishing submodule is used for establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
In one embodiment, the association information determination module includes:
the response signal acquisition submodule is used for inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal;
and the associated information determining submodule is used for determining the signal associated information of the whole vehicle model according to the first driving signal and the first response signal.
In one embodiment, the input load determination module is further configured to:
1) inputting a random white noise signal generated by a program as a system input signal into a first preset position in a finished automobile model to obtain a system output signal generated by a second preset position in the finished automobile model due to the system input signal;
2) comparing the system output signal with the actual measurement signal to obtain a comparison result;
3) judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
4) correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again);
5) and determining the system input signal as a finally obtained iteration simulation test result.
In one embodiment, the input load determining module is further configured to determine information of each of the system output signal and the actual measurement signal on a preset contrast term, where the preset contrast term includes at least one of a cross-over time contrast term, a power spectral density contrast term, and a pseudo-damage contrast term; and comparing the information of the system output signal and the actual measurement signal on the preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
In one embodiment, the preset condition is a preset condition corresponding to a contrast item included in the preset contrast item;
the input load determining module is further configured to determine whether a comparison result corresponding to a comparison item included in the preset comparison item meets a preset condition corresponding to the comparison item.
In one embodiment, the first preset position is at four wheel shock absorbers of the whole vehicle model;
the second preset position is the shaft heads of four wheels of the whole vehicle model and the mass center of the vehicle body;
the actual measurement signals comprise displacement signals respectively generated at four wheel vibration absorbers in a real vehicle corresponding to the target automobile, acceleration signals respectively generated at four wheel shaft heads and acceleration signals generated at the center of mass of the automobile body.
For specific definition of the body-in-white input load determination device, reference may be made to the above definition of the body-in-white input load determination method, which is not described herein again. The various modules in the body-in-white input load determination device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, the internal structure of which may be as shown in FIG. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for actually measuring data such as signals. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a body-in-white input load determination method.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by actually testing a real vehicle corresponding to the target automobile in a test field; establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of a target vehicle; determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model; and performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
In one embodiment, when the processor executes the computer program to realize the establishment of the rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle, the following steps are also realized:
acquiring chassis parameters of a target automobile, and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters; establishing a body-in-white finite element model of the target automobile; and establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
In one embodiment, when the processor executes the computer program to determine the signal correlation information of the entire vehicle model, the following steps are further implemented:
inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal; and determining signal correlation information of the whole vehicle model according to the first driving signal and the first response signal.
In one embodiment, the processor executes the computer program to perform the following steps when performing the iterative simulation test on the entire vehicle model according to the actual measurement signal and the signal correlation information:
1) inputting a random white noise signal generated by a program as a system input signal into a first preset position in a finished automobile model to obtain a system output signal generated by a second preset position in the finished automobile model due to the system input signal;
2) comparing the system output signal with the actual measurement signal to obtain a comparison result;
3) judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
4) correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again);
5) and determining the system input signal as a finally obtained iteration simulation test result.
In one embodiment, the processor executes the computer program to compare the system output signal with the actual measurement signal, and when a comparison result is obtained, the following steps are further implemented:
determining information of a system output signal and an actual measurement signal on preset contrast items respectively, wherein the preset contrast items comprise at least one contrast item of a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item; and comparing the information of the system output signal and the actual measurement signal on the preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
In one embodiment, the preset condition is a preset condition corresponding to a contrast item included in the preset contrast item; the processor executes the computer program to judge whether the comparison result meets the preset condition, and further realizes the following steps:
and judging whether the comparison result corresponding to the comparison item included in the preset comparison item meets the preset condition corresponding to the comparison item.
In one embodiment, the first preset position is at four wheel shock absorbers of the whole vehicle model; the second preset position is the shaft heads of four wheels of the whole vehicle model and the mass center of the vehicle body; the actual measurement signals comprise displacement signals respectively generated at four wheel vibration absorbers in a real vehicle corresponding to the target automobile, acceleration signals respectively generated at four wheel shaft heads and acceleration signals generated at the center of mass of the automobile body.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by actually testing a real vehicle corresponding to the target automobile in a test field; establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of a target vehicle; determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model; and performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
In one embodiment, the computer program is executed by the processor, and when establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle, the following steps are further implemented:
acquiring chassis parameters of a target automobile, and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters; establishing a body-in-white finite element model of the target automobile; and establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
In one embodiment, the computer program is executed by the processor, and when determining the signal correlation information of the entire vehicle model, the following steps are further implemented:
inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal; and determining signal correlation information of the whole vehicle model according to the first driving signal and the first response signal.
In one embodiment, the computer program is executed by the processor, and when performing an iterative simulation test on the entire vehicle model according to the actual measurement signal and the signal correlation information, further performs the following steps:
1) inputting a random white noise signal generated by a program as a system input signal into a first preset position in a finished automobile model to obtain a system output signal generated by a second preset position in the finished automobile model due to the system input signal;
2) comparing the system output signal with the actual measurement signal to obtain a comparison result;
3) judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
4) correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again);
5) and determining the system input signal as a finally obtained iteration simulation test result.
In one embodiment, the computer program is executed by a processor for comparing the system output signal with the actual measurement signal, and when a comparison result is obtained, further implementing the following steps:
determining information of a system output signal and an actual measurement signal on preset contrast items respectively, wherein the preset contrast items comprise at least one contrast item of a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item; and comparing the information of the system output signal and the actual measurement signal on the preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
In one embodiment, the preset condition is a preset condition corresponding to a contrast item included in the preset contrast item; the computer program is executed by the processor, and when judging whether the comparison result meets the preset condition, the following steps are also realized:
and judging whether the comparison result corresponding to the comparison item included in the preset comparison item meets the preset condition corresponding to the comparison item.
In one embodiment, the first preset position is at four wheel shock absorbers of the whole vehicle model; the second preset position is the shaft heads of four wheels of the whole vehicle model and the mass center of the vehicle body; the actual measurement signals comprise displacement signals respectively generated at four wheel vibration absorbers in a real vehicle corresponding to the target automobile, acceleration signals respectively generated at four wheel shaft heads and acceleration signals generated at the center of mass of the automobile body.
It will be understood by those of ordinary skill in the art that all or a portion of the processes of the methods of the embodiments described above may be implemented by a computer program that may be stored on a non-volatile computer-readable storage medium, which when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A body-in-white input load determination method, comprising:
acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by real test of a real vehicle corresponding to the target automobile in a test field;
establishing a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle;
determining signal correlation information of the whole vehicle model, wherein the signal correlation information represents the correlation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model;
and performing iterative simulation test on the whole vehicle model according to the actual measurement signal and the signal correlation information, and determining a finally obtained iterative simulation test result as the body-in-white input load of the target vehicle.
2. The body-in-white input load determining method according to claim 1,
the establishing of the rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle comprises the following steps:
acquiring chassis parameters of the target automobile, and establishing a chassis multi-body dynamic model of the target automobile according to the chassis parameters;
establishing a body-in-white finite element model of the target automobile;
and establishing a rigid-flexible coupling multi-body dynamic whole vehicle model of the target vehicle according to the chassis multi-body dynamic model and the body-in-white finite element model.
3. The body-in-white input load determining method according to claim 1,
the determining the signal correlation information of the whole vehicle model comprises the following steps:
inputting a first driving signal to a first preset position in the whole vehicle model to obtain a first response signal generated by a second preset position in the whole vehicle model due to the first driving signal;
and determining signal correlation information of the whole vehicle model according to the first driving signal and the first response signal.
4. The body-in-white input load determining method according to claim 1,
the iterative simulation test of the whole vehicle model according to the actual measurement signal and the signal correlation information comprises the following steps:
1) inputting a random white noise signal generated by a program as a system input signal into a first preset position in the whole vehicle model to obtain a system output signal generated by a second preset position in the whole vehicle model due to the system input signal;
2) comparing the system output signal with the actual measurement signal to obtain a comparison result;
3) judging whether the comparison result meets a preset condition or not;
if yes, executing step 5);
if not, executing step 4);
4) correcting the system input signal according to the comparison result to obtain a corrected signal; substituting the correction signal as a system input signal into a load transfer characteristic matrix corresponding to the whole vehicle model for calculation to obtain a calculation result; determining the calculation result as a system output signal, and executing 2 again;
5) and determining the system input signal as a finally obtained iteration simulation test result.
5. The body-in-white input load determining method according to claim 4,
the comparing the system output signal with the actual measurement signal to obtain a comparison result includes:
determining information of the system output signal and the actual measurement signal on preset contrast items respectively, wherein the preset contrast items comprise at least one of a crossing frequency contrast item, a power spectral density contrast item and a pseudo-damage contrast item;
and comparing the information of the system output signal and the actual measurement signal on a preset comparison item respectively to obtain a comparison result between the system output signal and the actual measurement signal on the preset comparison item, wherein the comparison result is a comparison result corresponding to the comparison item included in the preset comparison item and comprises at least one comparison result of a crossing frequency comparison result, a power spectral density comparison result and a pseudo-damage comparison result.
6. The body-in-white input load determining method according to claim 5,
the preset condition is a preset condition corresponding to a contrast item included in the preset contrast item;
the judging whether the comparison result meets a preset condition includes:
and judging whether a comparison result corresponding to a comparison item included in the preset comparison item meets a preset condition corresponding to the comparison item.
7. The body-in-white input load determining method according to claim 1,
the first preset positions are positions of four wheel shock absorbers of the whole vehicle model;
the second preset positions are the shaft heads of four wheels of the whole vehicle model and the mass center of the vehicle body;
the actual measurement signals comprise displacement signals respectively generated at four wheel shock absorbers in a real vehicle corresponding to the target vehicle, acceleration signals respectively generated at four wheel shaft heads and acceleration signals generated at a vehicle body mass center.
8. A body-in-white input load determination apparatus, comprising:
the actual measurement signal acquisition module is used for acquiring an actual measurement signal of a target automobile, wherein the actual measurement signal is data generated by actually testing a real vehicle corresponding to the target automobile in a test field;
the whole vehicle model building module is used for building a rigid-flexible coupling multi-body dynamics whole vehicle model of the target vehicle;
the association information determining module is used for determining signal association information of the whole vehicle model, wherein the signal association information represents an association relation between a signal at a first preset position and a signal at a second preset position in the whole vehicle model;
and the input load determining module is used for performing iterative simulation test on the whole automobile model according to the actual measurement signal and the signal correlation information and determining a finally obtained iterative simulation test result as the body-in-white input load of the target automobile.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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