Vehicle frequency response characteristic evaluation method, device and system and medium

Abstract

The invention relates to the technical field of vehicles, in particular to a vehicle frequency response characteristic evaluation method, device and system and a medium, and the method comprises the steps: obtaining an unsprung signal obtained through the uniform acceleration simulation of a long-wave road surface; extracting a low-pass filtering signal in the unsprung signal, and identifying an upper envelope line and a lower envelope line of the low-pass filtering signal; processing the unsprung signals based on the upper and lower envelope lines to obtain time-frequency spectrums, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrums of all the unsprung signals; calculating an evaluation index of a target frequency band in the frequency-vehicle response characteristic curve; through frequency conversion excitation signal processing, the frequency response characteristics of the vehicle under different road conditions and vehicle speeds are accurately reflected, and the comprehensiveness and accuracy of evaluation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a vehicle frequency response characteristic evaluation method, device, system and medium. BACKGROUND

[0002] The comfort evaluation of vehicles driving on undulating road surface belongs to the category of low-order smoothness evaluation. The evaluation road conditions in the related art mainly focus on long-wave road surfaces, but the evaluation method is usually constant-speed driving. This method needs multiple test simulations to obtain data at different speeds, and the evaluation of body pitch and body undulation is too focused on a specific speed. However, the user's driving road conditions are not standard long-wave road surfaces, and the performance at a specific speed may differ, causing evaluation deviation.

[0003] In the test and simulation signal processing of long-wave road surfaces, the signal of variable frequency excitation is usually difficult to process, because the signal of the change of road surface excitation frequency with time is usually difficult to extract. Therefore, fixed excitation frequency is usually used for experiments or simulations, and the related evaluation indicators are processed more simply. SUMMARY

[0004] Therefore, the purpose of the embodiments of the present application is to provide a vehicle frequency response characteristic evaluation method, device, system and medium, which aims to accurately reflect the frequency response characteristics of vehicles under different road conditions and speeds through variable frequency excitation signal processing, and improve the comprehensiveness and accuracy of evaluation.

[0005] In one aspect, the embodiments of the present application provide a vehicle frequency response characteristic evaluation method, which comprises the following steps: obtaining a non-sprung signal obtained by uniform acceleration simulation on a long-wave road surface; extracting a low-pass filtered signal in the non-sprung signal, and identifying upper and lower envelope lines of the low-pass filtered signal; processing the non-sprung signal based on the upper and lower envelope lines to obtain a time-frequency spectrum, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all non-sprung signals; calculating an evaluation indicator of a target frequency band in the frequency-vehicle response characteristic curve.

[0006] Optionally, the extraction of the low-pass filtered signal in the non-sprung signal and the identification of the upper and lower envelope lines of the low-pass filtered signal comprise: low-pass filtering the non-sprung signal to filter out high-frequency vibrations and white noise in the non-sprung signal, to obtain a low-pass filtered signal; performing upper and lower envelope processing on the low-pass filtered signal, and eliminating peak points in the upper and lower envelope lines that are determined as coupling peaks, to obtain the upper and lower envelope lines of the low-pass filtered signal.

[0007] Optionally, the upper and lower envelope processing of the low-pass filtered signal is performed, and peak points determined as coupling peaks in the upper and lower envelope are removed to obtain upper and lower envelope lines of the low-pass filtered signal, including: upper and lower envelope lines of the low-pass filtered signal are obtained by performing upper and lower envelope processing on the low-pass filtered signal, positions of each extreme point in the first upper and lower envelope lines are determined, and if a smaller value of a distance between the extreme point and two envelope lines in the first upper and lower envelope lines exceeds a distance threshold, the extreme point is removed; second upper and lower envelope lines are obtained by performing envelope processing on the remaining extreme points, and if a distance between an extreme point in the second upper envelope line and adjacent extreme points on the left and right exceeds a distance threshold, a smaller extreme point among the adjacent extreme points is removed, and envelope processing is performed on the remaining extreme points to obtain upper and lower envelope lines of the low-pass filtered signal.

[0008] Optionally, the non-sprung signal is processed based on the upper and lower envelope lines to obtain a time-frequency spectrum, including: The non-sprung signal is normalized based on the upper and lower envelope lines, and the normalized non-sprung signal is processed by short-time Fourier transform to obtain a time-frequency spectrum.

[0009] Optionally, the frequency-vehicle response characteristic curve is generated based on the time-frequency spectrum of all non-sprung signals, including: A high-gain region in the time-frequency spectrum is extracted, and a time-frequency fitting curve is generated, a deviation degree of the time-frequency fitting curve of all non-sprung signals is checked, and a frequency-vehicle response characteristic curve is generated.

[0010] Optionally, the high-gain region in the time-frequency spectrum is extracted, and the time-frequency fitting curve is generated, including: A first discrete point greater than a gain threshold in the time-frequency spectrum is found as a current fitting point; Discrete points adjacent to the fitting point in frequency are read respectively, and a discrete point with the largest gain is selected as a fitting point at the next time; All discrete points are traversed to obtain a curve to be fitted, and the curve to be fitted is linearly fitted to obtain a time-frequency curve fitting.

[0011] Optionally, the deviation degree of the time-frequency fitting curve of all non-sprung signals is checked to generate the frequency-vehicle response characteristic curve, including: A two-dimensional array is constructed based on frequency values of all time-frequency fitting curves, a three-dimensional array is constructed by repeating a third dimension based on the constructed two-dimensional array; The dimension of the constructed two-dimensional array is reversed, the three-dimensional array is subtracted from the two-dimensional array in a two-dimensional array direction in a three-dimensional space, and a one-dimensional vector is obtained by dimension reduction and mean value calculation on the three-dimensional array. The time-frequency fitting curves exceeding the deviation threshold are removed, and the time-frequency fitting curves meeting the requirements are averaged to obtain a fitted frequency curve; A frequency-vehicle response characteristic curve is established based on the fitted frequency curve and the upper and lower envelope lines.

[0012] In another aspect, an embodiment of the present application provides a vehicle frequency response characteristic evaluation device, comprising: A first module is configured to obtain a non-sprung signal obtained by simulating long-wave road surface uniform acceleration; A second module is configured to extract a low-pass filtered signal from the non-sprung signal and identify upper and lower envelope lines of the low-pass filtered signal; A third module is configured to process the non-sprung signal based on the upper and lower envelope lines to obtain a time-frequency spectrum, and generate a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all non-sprung signals; A fourth module is configured to calculate an evaluation index of a target frequency band in the frequency-vehicle response characteristic curve.

[0013] In another aspect, an embodiment of the present application provides a vehicle frequency response characteristic evaluation system, comprising: At least one processor; At least one memory configured to store at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned method.

[0014] In another aspect, an embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a processor executable program, and the processor executable program is used to execute the above-mentioned method when executed by a processor.

[0015] Embodiments of the present application include the following beneficial effects: The present application provides a vehicle frequency response characteristic evaluation method, device, system and medium, which effectively identifies the response characteristics of the vehicle at different frequency bands by accurately analyzing the time-frequency of the non-sprung signal, improves the accuracy and reliability of the evaluation system, and provides an important basis for vehicle design and optimization. The method accurately reflects the frequency response characteristics of the vehicle under different road conditions and speeds by processing the variable frequency excitation signal, and improves the comprehensiveness and accuracy of the evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a step flowchart of a vehicle frequency response characteristic evaluation method provided by an embodiment of the present application; Figure 2 is an envelope line extraction diagram of a non-sprung force signal provided by an embodiment of the present application; Figure 3is a time-frequency spectrum diagram provided by an embodiment of the present application; Figure 4 is a five fitting frequency curve diagram provided by an embodiment of the present application; Figure 5 is a deviation degree calculation diagram of five fitting curves provided by an embodiment of the present application; Figure 6 is an acceleration time-domain sweep signal diagram provided by an embodiment of the present application; Figure 7 is a frequency-vehicle response characteristic curve diagram obtained after processing an acceleration time-domain sweep signal provided by an embodiment of the present application; Figure 8 is a structural block diagram of a vehicle frequency response characteristic evaluation device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0018] It should be noted that although the module division is made in the device schematic diagram, and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a manner different from the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification and claims and the above-described drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

[0020] In addition, the described features, structures or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the present application. However, one skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail to avoid obscuring the aspects of the present application.

[0021] The block diagrams shown in the drawings are merely functional entities, and do not necessarily correspond to physically independent entities. That is, the functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0022] The flowcharts shown in the drawings are merely exemplary illustrations, and do not necessarily include all contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to actual conditions.

[0023] As shown in Figure 1 and Figure 2 , a vehicle frequency response characteristic evaluation method is provided for an embodiment of the present application, and the method comprises the following steps: Figure 1 S100, obtaining a non-sprung signal obtained by performing long-wave road surface uniform acceleration simulation; Specifically, the simulation test data of the non-sprung signal obtained by performing long-wave road surface uniform acceleration simulation includes four non-sprung vertical acceleration signals, a vehicle body vertical acceleration signal, a vehicle body pitch angle signal, etc. It should be pointed out that the simulation signal can also include other non-sprung signals required for evaluation, and the acceleration of simulation / test should generally be less than 0.5 m / s2. S200, extracting a low-pass filtered signal in the non-sprung signal, and identifying upper and lower envelope lines of the low-pass filtered signal;

[0024] Specifically, the processing signal is low-pass filtered, and the filter passband frequency band should at least cover the low-order smoothness concerned frequency band, filter out high-frequency vibration signals, and prevent interference with subsequent signal processing. S300, processing the non-sprung signal based on the upper and lower envelope lines to obtain a time-frequency spectrum, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all non-sprung signals;

[0025] Specifically, the upper and lower envelope lines are further analyzed, the relationship between time and frequency is extracted, and a time-frequency spectrum is formed. The time-frequency spectra of all non-sprung signals are integrated to generate a curve that can reflect the frequency response characteristic of the vehicle. The curve can be used to evaluate the dynamic response performance of the vehicle at different frequencies, and provide data support for subsequent evaluation. S400, calculating an evaluation index of a target frequency band in the frequency-vehicle response characteristic curve.

[0026]

[0027] ​Specifically, the evaluation indicators of the target frequency band are calculated, including: peak response frequency, peak maximum response, and gain within the frequency band, and the low-order ride comfort of the vehicle is evaluated based on the calculated indicators; It should be noted that the target frequency band in the present invention is the frequency band where the user experiences more low-order smoothness scenarios during normal driving. In addition, it can also be other frequency bands of interest; the calculation indicators usually use the vehicle's vertical displacement, vertical acceleration and body pitch angle, in addition to other signals of interest.

[0028] Steps S100 to S400, as illustrated in the embodiments of this application, propose a method for evaluating vehicle frequency response characteristics for long-wave roads. By processing the vehicle body and unsprung signals from a vehicle traveling on a long-wave road at uniform acceleration, the frequency domain characteristics of the vehicle body response are obtained. The vehicle's low-order ride comfort is then assessed by evaluating the vehicle body response characteristic curve in a specific frequency domain. This method extracts the required signals with a single simulation / test run, and the evaluation metrics focus on the vehicle response characteristics within a specific excitation frequency band, making the evaluation results more representative of typical user conditions. The present invention also provides a method for processing long-wave swept-frequency simulation / test signals, providing data processing support for the evaluation method and metrics by processing the amplitude using upper and lower envelopes and the time-frequency signal using short-time Fourier transforms.

[0029] In some embodiments, extracting a low-pass filtered signal from the unsprung signal and identifying upper and lower envelopes of the low-pass filtered signal includes: S210 , performing low-pass filtering on the unsprung signal to remove high-frequency vibration and white noise in the unsprung signal to obtain a low-pass filtered signal; S220 , performing upper and lower envelope processing on the low-pass filtered signal, removing peak points determined as coupling peaks in the upper and lower envelopes, and obtaining upper and lower envelopes of the low-pass filtered signal.

[0030] Specifically, if Figure 2 The following figure shows the envelope extraction of the unsprung force signal (avoiding coupling extreme points). The upper and lower envelopes of the low-pass filtered signal are calculated, and coupling peaks are determined at the extreme points where the upper and lower envelopes pass. The coupling peaks are then removed during the enveloping process.

[0031] In some embodiments, performing upper and lower envelope processing on the low-pass filtered signal, removing peak points determined as coupling peaks in the upper and lower envelopes, and obtaining upper and lower envelopes of the low-pass filtered signal include: S221, performing upper and lower envelope processing on the low-pass filtered signal to obtain first upper and lower envelopes, S222, determining the position of each extreme point in the first upper and lower fuzzy envelopes, and if the smaller value of the distance between the extreme point and two envelopes in the first upper and lower envelopes exceeds a distance threshold, removing the extreme point; S223, performing envelope processing on the remaining extreme value points to obtain second upper and lower envelope lines, if it is determined that the distance between the extreme value point in the second upper envelope line and the left and right adjacent extreme value points exceeds the distance threshold, the extreme value point with smaller distance is removed from the adjacent extreme value points, and envelope processing is performed on the remaining extreme value points to obtain the upper and lower envelope lines of the low-pass filtered signal.

[0032] Specifically, the judgment step of the coupling peak value includes calculating the upper and lower fuzzy envelope lines of the signal, calculating the position of each extreme value point on the upper and lower fuzzy envelope lines, judging the position of the extreme value point, and determining that it is a coupling extreme value point if the distance from the nearest envelope line is too far; distance judgment is performed on the non-coupling extreme value points, for example, in the non-coupling extreme value points of the upper envelope line, the distance between the left and right extreme value points is determined, if the left and right distance difference is large, the smaller extreme value point in the adjacent extreme value points is determined as the coupling extreme value point, and envelope processing is performed on the non-coupling extreme value points to obtain the upper and lower envelope lines. Through this method, the accuracy of signal processing is effectively improved, the reliability of simulation / test results is ensured, and a solid data foundation is provided for engineering application.

[0033] In some embodiments, the processing of the non-sprung signal based on the upper and lower envelope lines to obtain a time-frequency spectrum includes: normalizing the non-sprung signal based on the upper and lower envelope lines, and performing short-time Fourier transform processing on the normalized non-sprung signal to obtain a time-frequency spectrum.

[0034] As shown in Figure 3 the normalized non-sprung acceleration signal is subjected to short-time Fourier transform processing to obtain a time-frequency spectrum. Through the time-frequency spectrum, the frequency components of the non-sprung signal and their trends over time can be clearly identified, and the dynamic characteristics of the system can be further analyzed to provide a reliable basis for optimization design.

[0035] In some embodiments, the generation of a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all non-sprung signals includes: extracting a high-gain region in the time-frequency spectrum and generating a time-frequency fitting curve, checking the deviation degree of the time-frequency fitting curve of all non-sprung signals, and generating a frequency-vehicle response characteristic curve.

[0036] Specifically, the high-gain region in the time-frequency spectrum is subjected to time-frequency curve fitting, the deviation degree of the time-frequency fitting curve of all non-sprung signals is checked, the fitting curve with large deviation is removed, and a frequency-vehicle response characteristic curve is generated; by removing the fitting curve with large deviation, the accuracy and reliability of the frequency-vehicle response characteristic curve are ensured, and the design and performance evaluation of the vehicle suspension system are further optimized.

[0037] In some embodiments, the high-gain area in the time-frequency spectrum is extracted and a time-frequency fitting curve is generated, including: Finding the first discrete point greater than the gain threshold in the time-frequency spectrum as the current fitting point; Respectively reading the discrete points adjacent to the fitting point in frequency, and selecting the discrete point with the maximum gain as the fitting point at the next time; Traversing all discrete points to obtain a curve to be fitted, and performing linear fitting on the curve to be fitted to obtain a time-frequency curve fitting.

[0038] Specifically, as shown in Figure 4 extracting the high-gain part in the time-frequency and performing linear fitting, the specific method is: starting from t=0 time, first finding the initial high-gain point, for each next time point, respectively reading the gain of the discrete points adjacent to the fitting point in frequency, selecting the discrete point with the maximum gain as the fitting point at the next time, traversing all discrete time points to obtain a curve to be fitted, and d) performing linear fitting on the curve to be fitted to obtain a frequency fitting curve. It should be noted that a target optimization function can also be constructed and an optimization algorithm can be used to obtain the fitting curve, such as gradient descent method or particle swarm algorithm. It should be noted that the present application uses uniform acceleration linear motion for simulation / testing, and for non-uniform acceleration motion / testing, other fitting functions can be used, such as polynomial fitting.

[0039] In some embodiments, the time-frequency fitting curve of all non-sprung signals is checked for deviation, and a frequency-vehicle response characteristic curve is generated, including: Based on the frequency values of all time-frequency fitting curves, a two-dimensional array is constructed, and based on the constructed two-dimensional array, a third dimension is repeated to construct a three-dimensional array; Reversing the dimensions of the constructed two-dimensional array, and subtracting the two-dimensional array from the two-dimensional array in the three-dimensional space, and performing dimension reduction mean calculation on the three-dimensional array to obtain a one-dimensional vector; Eliminating time-frequency fitting curves exceeding the deviation threshold, and averaging the time-frequency fitting curves meeting the requirements to obtain a fitted frequency curve; Based on the fitted frequency curve and the upper and lower envelope lines, a frequency-vehicle response characteristic curve is established.

[0040] As shown in Figure 5As shown, for all non-sprung curves, the deviation degree check screening is carried out, and the specific steps are as follows: a two-dimensional array is constructed based on the frequency values of all fitting curves, a three-dimensional array is constructed based on the constructed two-dimensional array repeated to the third dimension, the dimension of the constructed two-dimensional array is reversed, the three-dimensional array is subtracted from the two-dimensional array, the three-dimensional array is subjected to dimension reduction mean calculation, and a one-dimensional vector is obtained, wherein the i th value represents the deviation degree of the i th fitting curve, the curve with large deviation degree is removed, and the required curve is averaged to obtain the fitted frequency curve; as shown Figure 6 and Figure 7 As shown, the frequency-vehicle response characteristic curve is established based on the fitted frequency curve and the upper and lower envelope lines. By integrating the fitted frequency curve and the upper and lower envelope lines, the final curve capable of accurately reflecting the frequency response characteristics of the vehicle is generated. The curve can be used for further analysis of the dynamic performance of the vehicle in different frequency ranges, and provides a quantitative basis for optimizing the design of the vehicle. In addition, after generating the frequency-vehicle response characteristic curve, the advantages and disadvantages of different working conditions or different vehicle models in low-order smoothness can be evaluated by comparing the curve characteristics, thereby providing support for decision-making in engineering practice.

[0041] Reference Figure 8 As shown, the embodiment of the present application also provides a vehicle frequency response characteristic evaluation device, comprising: A first module for obtaining a non-sprung signal obtained by simulating long-wave road uniform acceleration; Specifically, the simulation test data obtained by simulating long-wave road uniform acceleration includes four non-sprung vertical acceleration signals, a vehicle body vertical acceleration signal, a vehicle body pitch angle signal and the like. It should be pointed out that the simulation signal can also include other non-sprung signals required for evaluation, and the acceleration of simulation / test should generally be less than 0.5 m / s2.

[0042] A second module for extracting a low-pass filtered signal from the non-sprung signal and identifying upper and lower envelope lines of the low-pass filtered signal; Specifically, the processing signal is subjected to low-pass filtering, and the filter passband frequency band should at least cover the low-order smoothness frequency band of interest, so as to filter out high-frequency vibration signals and prevent interference on subsequent signal processing.

[0043] A third module for processing the non-sprung signal based on the upper and lower envelope lines to obtain a time-frequency spectrum, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all non-sprung signals; Specifically, the upper and lower envelope lines are further analyzed to form a time-frequency spectrum by extracting the relationship between time and frequency. The time-frequency spectrum of all non-sprung signals is integrated to generate a curve that can reflect the frequency response characteristics of the vehicle. The curve can be used to evaluate the dynamic response performance of the vehicle at different frequencies and provide data support for subsequent evaluation.

[0044] The fourth module is configured to calculate an evaluation index of the target frequency band in the frequency-vehicle response characteristic curve.

[0045] Specifically, the evaluation index of the target frequency band includes a peak response frequency, a peak maximum response, and a gain amount in the frequency band, and the low-order ride comfort of the vehicle is evaluated based on the calculated index. It should be noted that the target frequency band in the present application is a frequency band in which the user experiences more low-order ride comfort scenarios during normal driving, and in addition to this, it can also be other frequency bands of interest; the calculation index usually uses the vertical displacement, vertical acceleration and body pitch angle of the vehicle, and in addition to this, it can also be other signals of interest.

[0046] The embodiment of the present application also provides a vehicle frequency response characteristic evaluation system, which comprises a memory, a processor and a program stored in the memory and executable on the processor, and the program is executed by the processor to realize the method of the above-mentioned embodiment.

[0047] For example, the processor and the memory in the vehicle controller can be connected through a bus. The memory as a non-transitory computer readable storage medium can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one disk memory, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the control processor, and these remote memories can be connected to the control device through a network.

[0048] The non-transitory software programs and instructions required to realize the method of the above-mentioned embodiment are stored in the memory, and when executed by the processor, the method in the above-mentioned embodiment is executed.

[0049] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, that is, they can be located in one place, or can also be distributed on multiple network units. According to actual needs, part or all of the modules can be selected to achieve the purpose of the present embodiment scheme.

[0050] The embodiment of the present application also provides a vehicle comprising the control device of the above-mentioned embodiment.

[0051] The vehicle can be a private car, such as a sedan, an SUV, an MPV, or a pickup truck, etc. The vehicle can also be an operating vehicle, such as a van, a bus, a small truck, or a large trailer, etc. The vehicle needs to have an electric motor that can output power or store mechanical energy as a generator. When the vehicle is a new energy vehicle, it can be a hybrid vehicle or a pure electric vehicle.

[0052] Since the vehicle applies all the technical solutions of the above control device or vehicle controller, it at least has all the beneficial effects brought by the technical solutions of the above embodiments, which will not be repeated here.

[0053] In addition, an embodiment of the present application also provides a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions are used to execute the above method.

[0054] It is worth noting that since the computer readable storage medium of the embodiment of the present application can execute the method of any of the above embodiments, the specific implementation and technical effects of the computer readable storage medium of the embodiment of the present application can be referred to the specific implementation and technical effects of the method of any of the above embodiments.

[0055] In addition, an embodiment of the present application also provides a computer program product, which includes a computer program or computer instructions, the computer program or computer instructions are stored in a computer readable storage medium, a processor of a computer device reads the computer program or computer instructions from the computer readable storage medium, and the processor executes the computer program or computer instructions, so that the computer device executes the above method.

[0056] It is worth noting that since the computer program product of the embodiment of the present application can execute the method of any of the above embodiments, the specific implementation and technical effects of the computer program product of the embodiment of the present application can be referred to the specific implementation and technical effects of the method of any of the above embodiments.

[0057] As will be appreciated by one of ordinary skill in the art, all or some steps, systems of the above-disclosed methods can be implemented as software, firmware, hardware, or suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on computer readable media, which can comprise computer storage media (or non-transitory media), and communication media (or transitory media). As is well known to those of ordinary skill in the art, the term computer storage media includes both volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Further, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media.

[0058] The apparatus embodiments described above are merely illustrative for separate units described as separate components can or can not be physically separate, i.e. can be located in one place or can be distributed over a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the purposes of the embodiments.

Claims

1. A method for evaluating vehicle frequency response characteristics, characterized in that: The method comprises: Obtain the unsprung signal from a long-wave road uniform acceleration simulation; extracting a low-pass filtered signal from the unsprung signal, and identifying upper and lower envelopes of the low-pass filtered signal; The unsprung signal is processed based on the upper and lower envelopes to obtain a time-frequency spectrum, and a frequency-vehicle response characteristic curve is generated based on the time-frequency spectrum of all unsprung signals; Calculate the evaluation index of the target frequency band in the frequency-vehicle response characteristic curve.

2. The method according to claim 1, characterized in that Extracting the low-pass filtered signal from the unsprung signal and identifying the upper and lower envelopes of the low-pass filtered signal include: performing low-pass filtering on the unsprung signal to remove high-frequency vibration and white noise in the unsprung signal to obtain a low-pass filtered signal; The low-pass filtered signal is subjected to upper and lower envelope processing, and the peak points determined as coupling peaks in the upper and lower envelopes are removed to obtain the upper and lower envelopes of the low-pass filtered signal.

3. The method according to claim 2, characterized in that The step of performing upper and lower envelope processing on the low-pass filtered signal, removing peak points determined as coupling peaks in the upper and lower envelopes, and obtaining upper and lower envelopes of the low-pass filtered signal includes: Perform upper and lower envelope processing on the low-pass filtered signal to obtain the first upper and lower envelopes. Determine the position of each extreme point in the first upper and lower fuzzy envelopes, and if the smaller value of the distance between the extreme point and two envelopes in the first upper and lower envelopes exceeds a distance threshold, remove the extreme point; The remaining extreme points are subjected to envelope processing to obtain the second upper and lower envelopes. If it is determined that the distance between the extreme point in the second upper envelope and the left and right adjacent extreme points exceeds the distance threshold, the extreme points with a smaller distance among the adjacent extreme points are eliminated, and the remaining extreme points are subjected to envelope processing to obtain the upper and lower envelopes of the low-pass filtered signal.

4. The method according to claim 1, wherein The step of processing the unsprung signal based on the upper and lower envelopes to obtain a time-frequency spectrum includes: The unsprung signal is normalized based on the upper and lower envelopes, and the normalized unsprung signal is processed by short-time Fourier transform to obtain the time-frequency spectrum.

5. The method according to claim 1, wherein The generating of a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all unsprung signals includes: The high-gain region in the time-frequency spectrum is extracted and a time-frequency fitting curve is generated. The time-frequency fitting curves of all unsprung signals are checked for deviation and a frequency-vehicle response characteristic curve is generated.

6. The method according to claim 5, characterized in that The extracting of the high-gain region in the time-frequency spectrum and generating the time-frequency fitting curve comprises: Find the first discrete point in the time-frequency spectrum that is greater than the gain threshold as the current fitting point; Read the discrete points whose frequencies are close to the fitting point respectively, and select the discrete point with the largest gain as the fitting point at the next moment; Traverse all discrete points to obtain the curve to be fitted, and perform linear fitting on the curve to be fitted to obtain the time-frequency curve fitting.

7. The method according to claim 5, characterized in that The step of performing a deviation check on the time-frequency fitting curves of all unsprung signals to generate a frequency-vehicle response characteristic curve includes: constructing a two-dimensional array based on the frequency values ​​of all time-frequency fitting curves, and repeating the constructed two-dimensional array toward the third dimension to construct a three-dimensional array; Reverse the dimension of the constructed two-dimensional array, subtract the two-dimensional array from the three-dimensional array in the three-dimensional space, perform dimensionality reduction mean calculation on the three-dimensional array, and obtain a one-dimensional vector; Eliminate the time-frequency fitting curves that exceed the deviation threshold, average the time-frequency fitting curves that meet the requirements, and obtain the fitted frequency curve; A frequency-vehicle response characteristic curve is established based on the fitted frequency curve and upper and lower envelopes.

8. A vehicle frequency response characteristic evaluation device, characterized in that: The device comprises: The first module is used to obtain the unsprung signal obtained by performing a long-wave road uniform acceleration simulation; a second module configured to extract a low-pass filtered signal from the unsprung signal and identify upper and lower envelopes of the low-pass filtered signal; a third module for processing the unsprung signal based on the upper and lower envelopes to obtain a time-frequency spectrum, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrum of all unsprung signals; The fourth module is used to calculate the evaluation index of the target frequency band in the frequency-vehicle response characteristic curve.

9. A vehicle frequency response characteristic evaluation system, characterized in that: The method comprises a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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