Method and device for generating road simulation pavement spectrum signal and related equipment

Abstract

The invention discloses a road simulation pavement spectrum signal generation method and device and related equipment, and the method comprises the steps: obtaining the excitation time difference of a first group of two adjacent vibration exciters, and determining first pavement input data according to the excitation time difference; wherein the first road surface input data is road surface input data of all vibration exciters of a first group; performing correlation analysis based on the first group of vibration exciters and the second group of vibration exciters to obtain correlation data; performing calculation according to the first road surface input data and the relevancy data to obtain second road surface input data; wherein the second road surface input data is road surface input data of all vibration exciters of a second group; and fitting the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal. Through the above design, the problem that the consistency and coordination between traditional vibration exciters are not high can be solved, and the trueness of rugged roads can be simulated more truly.

Description

Technical Field

[0001] The present invention relates to the technical field of road simulation devices, and in particular, to a method and device for generating a road simulation road surface spectrum and related equipment. Background Art

[0002] Multi-axle vehicles are widely used and often need to drive on relatively complex road surfaces and will be in different vibration environments. Therefore, it is necessary to conduct vibration environment simulation experiments on the whole vehicle to evaluate various performance indicators of the vehicle under complex driving conditions and provide data for subsequent improvement work.

[0003] Currently, the methods for multi-axle vehicle experiments mainly include road tests and indoor bench tests. The experimental results of road tests are the most real, but they require a large-scale site and the laying of various different road surfaces, which will consume a lot of manpower and material resources and the experimental cost is huge. Indoor bench tests can more accurately reproduce the load and vibration excitation when the vehicle is driving on the road and can provide a controllable and repeatable load and vibration environment similar to the actual driving conditions. Therefore, indoor bench tests are often used for multi-axle vehicles in practical applications. Currently, the method of indoor bench tests is to install an exciter under each wheel of the vehicle to achieve independent excitation of each wheel to simulate the road driving conditions, and good experimental results can be achieved; However, the disadvantage of this method is that the arrangement of exciters is restricted by the wheelbase of multi-axle vehicles. If the number of wheels is large, the same number of exciters are required to complete the full excitation of all wheels, and the adaptability is not high; at the same time, the consistency and coordination among the exciters are not high, so the authenticity of simulating road roughness needs to be improved. Summary of the Invention

[0004] In order to solve the technical defects proposed in the above background art, the purpose of the present invention is to provide a method for generating a road simulation road surface spectrum signal, which can solve the problem of low consistency and coordination among traditional exciters and can more realistically simulate the authenticity of road roughness.

[0005] The present invention adopts the following technical solutions: In a first aspect, an embodiment of the present invention provides a method for generating a road simulation road surface spectrum signal, and the method for generating a road simulation road surface spectrum signal includes: Obtain the excitation time difference between the first group of two adjacent exciters, and determine the first road surface input data according to the excitation time difference; wherein, the first road surface input data is the road surface input data of all exciters in the first group; Conduct a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data; Calculate based on the first road surface input data and the correlation data to obtain second road surface input data; wherein, the second road surface input data is the road surface input data of all exciters in the second group. Perform fitting on the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal.

[0006] Optionally, the obtaining the excitation time difference between two adjacent exciters in the first group and determining the first road surface input data of all exciters in the first group according to the excitation time difference includes: Calculate based on the vehicle speed and the distance between two adjacent exciters to obtain a first time difference. Calculate according to the first time difference and the filtered white noise method to generate a first time domain model of road surface unevenness. Calculate according to the first time domain model of road surface unevenness and the correlation between each exciter in the first group to determine the first road surface input data.

[0007] Optionally, the calculating according to the first time domain model of road surface unevenness and the correlation of the remaining exciters in the first group to determine the first road surface input data of all exciters in the first group includes: Substitute the distance value between two adjacent exciters in the first group into the first time domain model of road surface unevenness for calculation to obtain the first road surface input data.

[0008] Optionally, perform correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data, including; Calculate according to the cross-spectral density and auto-spectral density between the road surface unevenness inputs of the first group of exciters and the second group of exciters to obtain first coherence data; wherein, the formula can be expressed as: , is the cross-spectral density between the road surface unevenness inputs of the first group of exciters and the second group of exciters; , are respectively the auto-spectral densities of the road surface unevenness inputs of the first group of exciters and the second group of exciters, and ω is the time angular frequency; Determine road surface relationship data through the correlation between the first group of exciters and the second group of exciters; Calculate through the first coherence data and the road surface relationship data to obtain correlation data.

[0009] Optionally, the calculating through the first coherence data and the road surface relationship data to obtain correlation data includes: Perform fitting calculation through the first coherence data and the road surface relationship data to obtain correlation data; wherein, the formula can be expressed as: , is the transfer function, representing the frequency-domain response relationship between the input of the first exciter on the right side and the input of the first exciter on the left side. is the spatial angular frequency, , n = 0.1 / m is the reference spatial frequency, B is the center-to-center distance between the left and right sets of exciters, and are the transfer functions between the road surface inputs of the first exciters in the left and right sets respectively at the spatial angular frequency . j is the complex exponential with j² = -1, used to identify the phase change in the complex frequency domain.

[0010] Optionally, the calculation based on the first road surface input data and the correlation data to obtain the second road surface input data includes: Converting the spatial angular frequency data of the correlation data into time angular frequency data to obtain the second road surface unevenness time-domain model of the first exciters in the second set; the formula can be expressed as: ; where , , , , M is the first transformation matrix, used to describe the coupling relationship between the exciter states and the time domain, ε is the second transformation matrix, used to map the input influence of the first set of exciters to the second set, X is the third transformation matrix, used to reflect the response speed of the exciters, x1 is the response of the first set of exciters, x2 is the response of the second set of exciters, V is the vehicle speed, B is the center-to-center distance between the left and right sets of exciters, λ is the projection vector, used to filter and obtain the first component, is the first road surface input data of the first exciter on the left side, and t is the input vector.

[0011] Calculating based on the first road surface unevenness time-domain model and the correlation of the remaining exciters in the second set to obtain the second road surface input data.

[0012] Optionally, the calculation based on the first road surface unevenness time-domain model and the correlation of the remaining exciters in the second set to obtain the second road surface input data includes: Substituting the distance value between two adjacent exciters in the second set into the second road surface unevenness time-domain model for calculation to obtain the first road surface input data.

[0013] In a second aspect, an embodiment of the present invention provides a road simulation road surface spectrum signal generation device, and the road simulation road surface spectrum signal generation device includes: An acquisition module, configured to acquire the excitation time difference between two adjacent exciters in the first set; A determination module, configured to determine the first road surface input data according to the excitation time difference; An analysis module for performing correlation analysis based on the first set of exciters and the second set of exciters; A calculation module for performing calculations based on the first road input data and the correlation data; A fitting module for fitting the first road input data and the second road input data.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps in the road simulation pavement spectrum signal generation method provided by the embodiment of the present invention are implemented.

[0015] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps in the road simulation pavement spectrum signal generation method provided by the embodiment of the invention are implemented.

[0016] In summary, the beneficial effects of the present invention are as follows: By obtaining the excitation time difference between two adjacent exciters in the first set and determining the first road input data according to the excitation time difference, it ensures that the input signals of each exciter have a reasonable delay relationship in the time domain, and can truly reproduce the dynamic response when a multi-axle vehicle passes through different roads. Subsequently, correlation analysis is performed based on the first set of exciters and the second set of exciters, so that correlation data can be obtained. Then, calculations are performed through the first road input data and the correlation data, so that the second road input data can be obtained. Then, the first road input data and the second road input data are fitted, and thus the pavement spectrum input signal can be obtained, which can effectively improve the accuracy of multi-axle vehicle simulation, optimize the prediction of vehicle dynamic performance, reduce test errors, and at the same time improve the consistency and coordination between each exciter, thereby improving the stability and reliability of road simulation.

[0017] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features, and advantages of the present invention more obvious and understandable, the following specifically gives preferred embodiments and, in conjunction with the drawings, is described in detail as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a specific flowchart of a road simulation pavement spectrum signal generation method provided by an embodiment of the present invention; Figure 2 is a structural diagram of a road simulation pavement spectrum signal generation device provided by an embodiment of the present invention; Figure 3 This is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Specific embodiments

[0019] In order to make the content of the present invention easier to be clearly understood, the present invention will be further described below according to specific embodiments in conjunction with the accompanying drawings.

[0020] As Figure 1 shown, Figure 1 This is a flowchart of a method for generating a road surface spectrum signal for road simulation provided by an embodiment of the present invention. The method includes the following steps: In the steps of the embodiment of the present invention, it should be noted that the distribution of the wheels of the vehicle can be analyzed first to determine the first, middle, and last pairs of wheels of the multi-axle vehicle as the excitation points. Two sets of exciters, three in each set, are arranged corresponding to each excitation point, and a transition excitation mechanism is erected on the excitation tray to carry all the wheels of the multi-axle vehicle, so that the arrangement of the exciters is not restricted by the wheelbase of the multi-axle vehicle.

[0021] S1. Obtain the excitation time difference between two adjacent exciters in the first group, and determine the first road surface input data according to the excitation time difference; wherein, the first road surface input data is the road surface input data of all exciters in the first group; In the embodiment of the present invention, by measuring the excitation time difference between two adjacent exciters in the first group, the time delay of different exciters receiving the same road surface unevenness excitation is calculated by using the vehicle driving speed and the exciter spacing, so as to determine the road surface input data of all exciters in the first group, that is, the first road surface input data. The excitation time difference refers to the time difference between adjacent exciters in the same group receiving the same road surface unevenness signal during driving, and this value is determined by the exciter spacing and the vehicle driving speed; deriving the first road surface input data through the excitation time difference reduces the dependence on actual road surface data and improves the controllability of the test.

[0022] S2. Perform a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data; In the embodiments of the present invention, a correlation analysis is performed on the left and right sets of exciters to calculate the correlation between the road surface inputs of the two sets of exciters, so as to obtain correlation data. Based on the first set of exciters and the second set of exciters, a correlation analysis is carried out to obtain correlation data. The degree of association between the two sets of exciters can be quantified through mathematical statistics and signal processing methods, so as to more accurately deduce the road surface input data of the second set of exciters. Specifically, the road surface input data of the first set of exciters and the second set of exciters comes from the contact between the tires and the road surface during vehicle driving. Affected by road unevenness, there is a certain coherence between the wheel-rail contact points on the left and right sides. However, due to factors such as the vehicle suspension system, wheelbase, and driving trajectory, the road surface inputs experienced by the left and right wheels are not exactly the same. Therefore, a correlation analysis is needed to describe this difference and correlation relationship.

[0023] S3. Calculate according to the first road surface input data and the correlation data to obtain second road surface input data; wherein, the second road surface input data is the road surface input data of all exciters in the second set. In the embodiments of the present invention, calculate according to the first road surface input data and the correlation data to obtain the second road surface input data of all exciters in the second set. It is mainly based on methods of signal processing, system identification, and statistical modeling to map the road surface input data of the first set of exciters to the second set of exciters, so as to ensure that the road surface input of the entire system conforms to the driving characteristics of the vehicle on the real road.

[0024] S4. Fit the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal.

[0025] In the embodiments of the present invention, fit the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal. It is mainly through methods of mathematical fitting, frequency domain analysis, and statistical modeling to synthesize the first road surface input data and the second road surface input data to generate a complete road surface spectrum that conforms to the characteristics of actual road unevenness.

[0026] Optionally, the obtaining of the excitation time difference between two adjacent exciters in the first set and determining the first road surface input data of all exciters in the first set according to the excitation time difference includes calculating according to the vehicle speed and the distance between two adjacent exciters to obtain a first time difference; calculating according to the first time difference and the filtered white noise method to generate a first road surface unevenness time domain model; calculating according to the first road surface unevenness time domain model and the correlation between each exciter in the first set to determine the first road surface input data.

[0027] In an embodiment of the present invention, first, obtain the excitation time difference between two adjacent exciters in the first group, that is, calculate the time delay when adjacent exciters receive the same road surface unevenness signal. This time delay is jointly determined by the vehicle driving speed and the exciter spacing, and the calculation formula is: . Wherein, Δt is the first time difference, indicating the time difference when the front and rear exciters receive the same road surface input during vehicle driving. Then, use the filtered white noise method to generate the time-domain model of the first road surface unevenness, and the formula can be expressed as: .

[0028] is the road surface unevenness input; f = 0.01 / m is the lower cut-off frequency; v is the vehicle speed; n0 = 0.1 / m is the reference spatial frequency; G q (n0) is the road surface unevenness coefficient; represents an ideal unit white noise with a mean of 0 and a power spectral density of 1, and t is the input vector. Then, by calculating according to the first road surface unevenness time-domain model and the correlation between each exciter in the first group, the first road surface data can be obtained.

[0029] Optionally, the calculation according to the first road surface unevenness time-domain model and the correlation of the remaining exciters in the first group to determine the first road surface input data of all exciters in the first group includes: substituting the spacing value between two adjacent exciters in the first group into the first road surface unevenness time-domain model for calculation to obtain the first road surface input data.

[0030] In an embodiment of the present invention, there is a spacing between adjacent exciters in the same group, and their road surface inputs are correlated. At the same time, in actual situations, the road surfaces passed by the left and right wheels of a multi-axis vehicle are different, so there is also a certain coherence between the road surface inputs of the left and right groups of exciters. Calculate the first road surface input data of all exciters in the first group through mathematical modeling to ensure that the simulation system can accurately reproduce the dynamic characteristics of the real road unevenness. Use the filtered white noise method to generate the time-domain model of the first road surface unevenness. Since the exciters in the first group are arranged in sequence in space, assuming the spacing between two adjacent exciters is d, and the vehicle is driving at a speed v, the time delay when adjacent exciters receive the same road surface input can be expressed as This time delay indicates that when the first exciter receives an input of road surface unevenness, subsequent exciters will receive the same road surface characteristics at a certain time. It can improve the authenticity of the road surface input signal. By using the filtered white noise method to generate input data that conforms to the statistical characteristics of road unevenness, the simulation system can more accurately reflect different types of road surface conditions; enhance the spatial consistency of the exciter input signal. By calculating the time delay, it ensures that the input signals of each exciter are reasonably distributed in space and time, enabling the simulation system to accurately simulate the excitation situation of the vehicle on the real road; optimize the excitation simulation of multi-axle vehicles. This method is applicable to multi-axle vehicles with more than three axles, ensuring that the input signals of all exciters are coordinated and improving the overall simulation accuracy; reduce test errors and improve simulation stability. By using correlation analysis to correct the input signal, the random error between different exciters is reduced, making the simulation system more stable and reliable. In summary, based on the exciter spacing, vehicle speed, and correlation analysis, this method can efficiently calculate the road surface input data of all exciters in the first group, ultimately improving the accuracy of road excitation simulation and making it closer to the real road conditions.

[0031] Optionally, calculating according to the first road surface unevenness time domain model and the correlation of the remaining exciters in the first group to determine the first road surface input data of all exciters in the first group includes: substituting the spacing value between two adjacent exciters in the first group into the first road surface unevenness time domain model for calculation to obtain the first road surface input data.

[0032] In the embodiment of the present invention, calculating according to the first road surface unevenness time domain model and the correlation of the remaining exciters in the first group to determine the first road surface input data of all exciters in the first group. By analyzing the spatial relationship and time delay between adjacent exciters, and combining the time domain characteristics of road surface unevenness, the road surface input data of all exciters in the same group is deduced. Among them, the formula can be expressed as:

[0033] In the formula, V represents the vehicle speed, Li is the center distance of the 2nd and 3rd exciters in the same group relative to the 1st exciter, gli(t) is the road surface unevenness of the 2nd and 3rd exciters on the left, i = 2, 3, gl1(t) is the first road surface input data, and t is the input vector.

[0034] Specifically, the first road surface unevenness time-domain model is generated based on the road surface unevenness data of the actual road and can reflect the variation law of the road surface in the time domain. By substituting the spacing values between the first group of adjacent two exciters into this model, the cross-correlation of the road surface input variation time difference between these two exciters can be calculated, thereby determining their time delay and amplitude relationship. Through this cross-correlation analysis of the variation time difference, the road surface input data of all exciters within the first group can be deduced. For example, assume that the first group includes three exciters, namely exciter A, exciter B, and exciter C. First, by analyzing the cross-correlation of the road surface input variation time difference between exciter A and exciter B, determine their time delay and amplitude relationship; then, by analyzing the cross-correlation of the road surface input variation time difference between exciter B and exciter C, determine their time delay and amplitude relationship; finally, by synthesizing these analysis results, deduce the road surface input data of exciter A, exciter B, and exciter C. This method not only simplifies the creation process of the road surface input but also ensures a high degree of consistency and coordination in the excitation between exciters within the same group, thereby improving the accuracy and reliability of the experiment. By optimizing the exciter arrangement and road surface spectrum creation, only two groups of a total of three pairs of exciters are required to achieve equivalent full excitation of multi-axle vehicles, significantly reducing the number of exciters, lowering the cost and complexity of the experimental equipment; the design of the transition excitation mechanism enables the exciter arrangement to be unrestricted by the vehicle wheelbase and is applicable to multi-axle vehicles of different sizes, improving the flexibility and applicability of the experiment; by creating the road surface spectrum through cross-correlation and coherence analysis of the variation time difference, the accuracy and coordination of the excitation are ensured, improving the reliability of the experimental results; this method is applicable not only to multi-axle vehicles with three or more axles but also to multi-axle vehicles with smaller sizes, improving the applicability of the embodiments of the present invention.

[0035] Optionally, perform a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data, including: calculate based on the cross-spectral density and auto-spectral density between the road surface unevenness inputs of the first group of exciters and the second group of exciters to obtain the first coherence data; where the formula can be expressed as:

[0036] is the cross-spectral density between the road surface unevenness inputs of the first group of exciters and the second group of exciters; , are respectively the auto-spectral densities of the road surface unevenness inputs of the first group of exciters and the second group of exciters, and ω is the time angular frequency; determine the road surface relationship data through the correlation between the first group of exciters and the second group of exciters; calculate the correlation data through the first coherence data and the road surface relationship data.

[0037] In an embodiment of the present invention, in the process of performing correlation analysis based on the first set of exciters and the second set of exciters to obtain correlation data, the core principle is to use the frequency-domain analysis method to calculate the coherence between the road surface unevenness inputs of the two sets of exciters by using the cross-spectral density and the auto-spectral density, so as to determine the dynamic relationship between them. Specifically, the cross-spectral density (CSD) and the auto-spectral density (ASD) are concepts in frequency-domain analysis, which respectively describe the correlation between two signals and the spectral characteristics of a single signal. By calculating the cross-spectral density and the auto-spectral density between the road surface unevenness inputs of the first set of exciters and the second set of exciters, the coherence data between them can be obtained, that is, the first coherence data. The coherence data reflects the correlation between the two sets of exciters in the frequency domain and can quantify the phase and amplitude relationship between them. Through the correlation degree between the first set of exciters and the second set of exciters, the road surface relationship data can be determined. The correlation degree analysis mainly considers the dynamic response characteristics of the two sets of exciters in the time domain and the frequency domain, and combines the spectral characteristics of the road surface unevenness to deduce the phase and amplitude relationship between them. For example, assuming that the first set of exciters corresponds to the left wheels of the vehicle and the second set of exciters corresponds to the right wheels of the vehicle, by analyzing the correlation degree between them, it can be determined whether the excitations received by the left and right wheels during driving are synchronized. This analysis not only considers the dynamic response characteristics of the left and right wheels, but also combines the symmetry of the actual road to ensure a high degree of consistency and coordination in the excitations between the left and right sets of exciters. By calculating through the first coherence data and the road surface relationship data, the correlation data can be obtained. The correlation data is the result of comprehensive frequency-domain and time-domain analysis and can comprehensively reflect the dynamic relationship between the two sets of exciters. For example, the correlation data can be used to adjust the excitation parameters of the exciters to ensure symmetry and coordination in the excitations between the left and right sets of exciters, thereby further improving the accuracy and reliability of the experiment. In addition, the correlation data can also be used to optimize the creation of the road surface spectrum to ensure that the road surface spectrum can accurately reflect the unevenness characteristics of the actual road and provide reliable data support for the road simulation experiment of multi-axle vehicles.

[0038] Optionally, the calculation through the first coherence data and the road surface relationship data to obtain the correlation data includes performing fitting calculation through the first coherence data and the road surface relationship data to obtain the correlation data, including: Performing fitting calculation through the first coherence data and the road surface relationship data to obtain the correlation data; where the formula can be expressed as: , is the transfer function, representing the frequency-domain response relationship between the input of the first exciter on the right and the input of the first exciter on the left, is the spatial angular frequency, , n = 0.1 / m is the reference spatial frequency, and B is the center-to-center distance between the left and right sets of exciters. and are the transfer functions between the road surface inputs of the first exciters in the left and right sets respectively at the spatial angular frequency . j is the complex exponential with j² = -1, which is used to identify the phase change in the complex frequency domain.

[0039] In the embodiment of the present invention, in the process of calculating the correlation data through the first coherence data and the road surface relationship data, the core principle is to comprehensively combine the coherence data (the first coherence data) obtained by frequency domain analysis with the road surface relationship data obtained by time domain analysis through a fitting calculation method, so as to obtain the correlation data that can comprehensively reflect the dynamic relationship between the two sets of exciters. Specifically, the first coherence data is the coherence data calculated by the frequency domain analysis method, which reflects the correlation between the two sets of exciters in the frequency domain; while the road surface relationship data is obtained by the time domain analysis method, which reflects the dynamic response characteristics of the two sets of exciters in the time domain. By performing a fitting calculation on these two types of data, a comprehensive correlation data can be obtained, which can not only quantify the correlation between the two sets of exciters, but also reflect their dynamic response characteristics under actual road excitation.

[0040] Optionally, calculating the second road surface input data of all exciters in the second group according to the first road surface input data and the correlation data includes: converting the spatial angular frequency data of the correlation data into time angular frequency data to obtain the second road surface unevenness time domain model of the first exciter in the second group; the formula can be expressed as: ; where , , , , M is the first transformation matrix used to describe the coupling relationship between the exciter state and the time domain, ε is the second transformation matrix used to map the input influence of the first group of exciters to the second group, X is the third transformation matrix used to reflect the response speed of the exciters, x1 is the response of the first group of exciters, x2 is the response of the second group of exciters, V is the vehicle speed, B is the center-to-center distance between the left and right sets of exciters, and λ is the projection vector used to filter out the first component. is the first road surface input data of the first exciter on the left, and t is the input vector.

[0041] Calculating the second road surface input data based on the second road surface unevenness time domain model and the correlation of the remaining exciters in the second group.

[0042] In the embodiment of the present application, in the process of calculating the second road surface input data of all exciters in the second group based on the first road surface input data and the correlation data, the core principle is to convert the spatial angular frequency data of the correlation data into temporal angular frequency data, and combine it with the first road surface unevenness time domain model to deduce the road surface input data of the second group of exciters. Specifically, the spatial angular frequency data of the correlation data reflects the spatial relationship between the exciters, while the temporal angular frequency data reflects the dynamic response characteristics of the exciters in the time domain. By converting the spatial angular frequency data into temporal angular frequency data, the second road surface unevenness time domain model of the first exciter in the second group can be obtained. Based on the first road surface unevenness time domain model and the correlation of the remaining exciters in the second group, the second road surface input data of all exciters in the second group can be calculated. Specifically, by analyzing the correlation between the exciters in the second group, the time delay and amplitude relationship between them can be determined, so as to deduce the road surface input data of all exciters in the second group. For example, assume that the second group includes three exciters, namely exciter D, exciter E, and exciter F. First, by analyzing the correlation between exciter D and exciter E, the time delay and amplitude relationship between them are determined; then, by analyzing the correlation between exciter E and exciter F, the time delay and amplitude relationship between them are determined; finally, by synthesizing these analysis results, the road surface input data of exciter D, exciter E, and exciter F are deduced. This method not only simplifies the creation process of the road surface input, but also ensures a high degree of consistency and coordination in the excitation between the exciters in the same group, thus improving the accuracy and reliability of the experiment.

[0043] As Figure 2 shown, Figure 2 is an architecture diagram of a road surface spectrum signal generation device for road simulation provided by an embodiment of the present invention. The device includes: An acquisition module 201, configured to acquire the excitation time difference between two adjacent exciters in the first group, and determine the first road surface input data according to the excitation time difference, where the first road surface input data is the road surface input data of all exciters in the first group; A determination module 202, configured to perform correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data; An analysis module 203, configured to calculate the second road surface input data according to the first road surface input data and the correlation data, where the second road surface input data is the road surface input data of all exciters in the second group; A calculation module 204, configured to calculate the second road surface input data according to the first road surface input data and the correlation data; A fitting module 205, configured to fit the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal.

[0044] As Figure 3 shown Figure 3 Figure 3

[0045] The electronic device provided by the embodiment of the present invention can implement each process that can be achieved by the road simulation pavement spectrum signal generation method in the above method embodiment, and can achieve the same beneficial effects. To avoid repetition, it will not be described in detail here.

[0046] The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the road simulation pavement spectrum signal generation method provided by the embodiment of the present invention, and can achieve the same technical effects. To avoid repetition, it will not be described in detail here.

[0047] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0048] The embodiments of the present specific implementation manners are all preferred embodiments of the present application, and do not limit the protection scope of the present application accordingly. The same components are denoted by the same reference numerals. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for generating a road surface spectrum signal for road simulation, characterized in that, Including: Obtain the excitation time difference between two adjacent exciters in the first group, and determine the first road surface input data according to the excitation time difference, where the first road surface input data is the road surface input data of all exciters in the first group; Perform a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data; Calculate according to the first road surface input data and the correlation data to obtain the second road surface input data, where the second road surface input data is the road surface input data of all exciters in the second group; Perform fitting on the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal.

2. A method for generating a road surface spectrum signal for road simulation according to claim 1, characterized in that, The obtaining the excitation time difference between two adjacent exciters in the first group and determining the first road surface input data of all exciters in the first group according to the excitation time difference includes: Calculate according to the vehicle speed and the distance between two adjacent exciters to obtain the first time difference; Calculate according to the first time difference and the filtered white noise method to generate a first road surface roughness time domain model; Calculate according to the first road surface roughness time domain model and the correlation between each exciter in the first group to determine the first road surface input data.

3. A method for generating a road surface spectrum signal for road simulation according to claim 2, characterized in that, The calculating according to the first road surface roughness time domain model and the correlation of the remaining exciters in the first group to determine the first road surface input data of all exciters in the first group includes: Substitute the distance value between two adjacent exciters in the first group into the first road surface roughness time domain model for calculation to obtain the first road surface input data.

4. A method for generating a road surface spectrum signal for road simulation according to claim 1, characterized in that, Performing a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data includes; Calculate based on the cross-spectral density and auto-spectral density between the road surface unevenness inputs of the first set of exciters and the second set of exciters to obtain the first coherence data; among them, the formula can be expressed as: , is the cross-spectral density between the road surface unevenness inputs of the first set of exciters and the second set of exciters; , are the auto-spectral densities of the road surface unevenness inputs of the first set of exciters and the second set of exciters respectively, and ω is the time angular frequency; Determine road surface relationship data through the correlation between the first group of exciters and the second group of exciters; Calculate through the first coherence data and the road surface relationship data to obtain correlation data.

5. A method for generating a road surface spectrum signal for road simulation according to claim 4, characterized in that The calculating through the first coherence data and the road surface relationship data to obtain correlation data includes: Performing fitting calculations using the first coherent data and the road surface relationship data to obtain correlation data; where the formula can be expressed as: , is the transfer function, representing the frequency-domain response relationship between the input of the first exciter on the right side and the input of the first exciter on the left side, is the spatial angular frequency, , n = 0.1 / m is the reference spatial frequency, B is the center-to-center distance between the left and right sets of exciters, and are the transfer functions between the road surface inputs of the first exciters in the left and right sets respectively at the spatial angular frequency , j is the complex exponential with j² = -1, used to identify the phase change in the complex frequency domain.

6. A method for generating a road surface spectrum signal for road simulation according to claim 5, characterized in that, The calculating according to the first road surface input data and the correlation data to obtain the second road surface input data includes: Convert the spatial angular frequency data of the relevance data into temporal angular frequency data to obtain the second road surface unevenness time-domain model of the first exciter in the second group; the formula can be expressed as: ; where , , , , M is the first transformation matrix for describing the coupling relationship between the exciter state and the time domain, ε is the second transformation matrix for mapping the input influence of the first group of exciters to the second group, X is the third transformation matrix for reflecting the response speed of the exciter, x1 is the response of the first group of exciters, x2 is the response of the second group of exciters, V is the vehicle speed, B is the center-to-center distance between the left and right groups of exciters, λ is the projection vector for filtering to obtain the first component, is the first road surface input data of the first exciter on the left, and t is the input vector; Calculate based on the first road surface roughness time domain model and the correlation of the remaining exciters in the second group to obtain the second road surface input data.

7. A method for generating a road surface spectrum signal for road simulation according to claim 1, characterized in that The calculating based on the first road surface roughness time domain model and the correlation of the remaining exciters in the second group to obtain the second road surface input data includes: Substitute the distance value between two adjacent exciters in the second group into the second road surface roughness time domain model for calculation to obtain the first road surface input data.

8. A road simulation pavement spectrum signal generation device, characterized in that, Including: An acquisition module for obtaining the excitation time difference between two adjacent exciters in the first group and determining the first road surface input data according to the excitation time difference, where the first road surface input data is the road surface input data of all exciters in the first group; A determination module for performing a correlation analysis based on the first group of exciters and the second group of exciters to obtain correlation data; An analysis module for calculating according to the first road surface input data and the correlation data to obtain the second road surface input data, where the second road surface input data is the road surface input data of all exciters in the second group; A calculation module, configured to perform calculations based on the first road surface input data and the relevance data to obtain second road surface input data; A fitting module, configured to perform fitting on the first road surface input data and the second road surface input data to obtain a road surface spectrum input signal.

9. An electronic device, characterized in that, Comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the steps in the method for generating a road surface spectrum signal for road simulation according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the method for generating a road surface spectrum signal for road simulation according to any one of claims 1 to 7 are implemented.

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