Intelligent suspension abnormal sound identification method

Abstract

The application discloses a kind of intelligent suspension abnormal sound identification methods.Method synchronous acquisition abnormal sound condition under the suspension swing arm vibration acceleration, shock absorber piston rod vibration acceleration, vehicle body vibration acceleration, suspension stroke displacement, in-vehicle sound signal and chassis suspension ECU and solenoid valve driving current and other multi-source signals;Correlation analysis is carried out on the collected signals in time domain and frequency domain, the suspension working stroke is locked at the abnormal sound time by correlating the collected sound signal with the suspension stroke displacement, the vibration source with the strongest correlation with abnormal sound is locked by correlating sound with vibration, further correlation analysis is carried out on the vibration signal and solenoid valve current, and the sudden change of solenoid valve current caused by ECU control strategy defect is identified as the root cause of abnormal sound;Based on the positioning result, an improvement scheme is generated and a real vehicle is verified in a closed loop.The application traces the intelligent suspension abnormal sound to the electric control strategy level, realizes the complete closed-loop identification from signal acquisition, root positioning to scheme verification.

Description

Technical Field

[0001] This invention relates to the field of automotive NVH technology, specifically to an intelligent method for identifying abnormal noises in suspension systems. Background Technology

[0002] With the rapid development of intelligent electric vehicles, customer demands for vehicle performance are increasing daily. Compared to the vibration and noise (NVH) problems of traditional vehicle chassis, the NVH problems of intelligent chassis in new energy vehicles are more prominent. At the same time, resolving abnormal noises from intelligent chassis in new energy vehicles is becoming increasingly difficult and complex, posing a pressing issue for OEMs and related component manufacturers. In actual use, vehicles equipped with active suspension, air suspension, and other intelligent suspension systems may experience unnecessary movements and abnormal noises due to their frequent active adjustments. Some owners have reported issues such as logical inconsistencies and persistent abnormal noises from intelligent suspension systems. Industry analysis indicates that as air suspension and intelligent suspension gradually become standard equipment in mid-range electric vehicles, related abnormal noise problems are on the rise.

[0003] Currently, research on abnormal noises in automotive suspensions, both domestically and internationally, mainly focuses on the identification of noises from traditional passive suspensions, while research on the identification of abnormal noises from intelligent suspensions and shock absorbers in next-generation electric vehicles is relatively limited. Some publicly available information uses a combination of bench tests and CAE simulations to diagnose abnormal noises from hydraulic suspension shock absorbers, but the identification results lack closed-loop verification and mechanism analysis. Other approaches combine bench tests and whole-vehicle testing to identify and analyze abnormal noises from suspension shock absorbers, employing a weighted coefficient method to extract key characteristics of these noises, achieving some success, but lacking further analysis of the noise mechanism.

[0004] Among the currently disclosed patent technologies, CN121298287A proposes a method for predicting abnormal noise in vehicle shock absorbers, mainly exploring a subjective and objective evaluation method combining bench testing and whole-vehicle testing; CN120439731A discloses a method for suppressing abnormal noise in shock absorbers based on road surface pre-aiming, suppressing abnormal noise through algorithms; CN119958884A provides a method for diagnosing abnormal noise in vehicle shock absorbers, using a frequency method for noise identification; and CN119312579A discloses an optimization and control method for abnormal noise in automotive shock absorbers, mainly improving abnormal noise through adjustments and optimizations to the vehicle body and bushings. However, the above-mentioned prior art still has the following shortcomings: Research primarily focuses on traditional suspension systems, with limited coverage of abnormal noise identification in intelligent suspension systems. There is a lack of systematic analysis of the causes of abnormal noise at the control strategy level of intelligent suspension systems. Furthermore, existing methods lack depth in analyzing the causes of abnormal noise, often remaining at the level of mechanical component diagnosis, failing to effectively correlate abnormal noise with the control logic of the intelligent suspension electronic control system, solenoid valve drive current, and other electronic control parameters. Existing methods have significant limitations, often only applicable to specific engineering problems and lacking universality for different types of abnormal noise issues. Current solutions lack a complete closed-loop identification process from data acquisition and multi-dimensional correlation analysis to cause identification and solution verification, resulting in insufficient closed-loop verification for confirming the causes of abnormal noise. Summary of the Invention

[0005] This invention aims to address the shortcomings of existing solutions, such as limited identification of abnormal noises in intelligent suspensions and a lack of analysis of the causes of these noises. Existing methods are also limited and lack universality. This invention provides a method for identifying abnormal noises in intelligent suspensions, comprising: Simultaneously collect multi-source objective signal data under abnormal noise conditions. The multi-source objective signal data includes at least: suspension lower control arm vibration acceleration signal, shock absorber piston rod vibration acceleration signal, vehicle body vibration acceleration signal, suspension shock absorber stroke displacement signal, in-vehicle sound signal, and chassis suspension ECU and shock absorber solenoid valve current signal. Perform time-domain and / or frequency-domain analysis on the multi-source objective signal data, including: performing time-domain correlation analysis on the sound signal and the travel displacement signal to pinpoint the suspension damper working stroke at the moment the abnormal noise occurs, and performing acoustic-vibration correlation analysis on each vibration acceleration signal and the sound signal to determine the vibration source most strongly associated with the abnormal noise; The sound signal at the time of the abnormal noise is correlated with each vibration acceleration signal and the solenoid valve current signal to determine the cause of the abnormal noise; An improvement plan for the abnormal noise is generated based on the causes of the abnormal noise.

[0006] Furthermore, the multi-source objective signal data collected under abnormal noise conditions includes: A first acceleration sensor is placed on the lower control arm of the vehicle suspension to collect the under-suspension vibration acceleration signal, a second acceleration sensor is placed on the piston rod of the suspension damper to collect the piston rod vibration acceleration signal, and a third acceleration sensor is placed on the body to collect the body vibration acceleration signal. Displacement sensors are arranged along the direction of shock absorber movement to collect suspension travel displacement signals; Microphones were placed inside the vehicle to collect sound signals; The chassis suspension ECU signal and the shock absorber solenoid valve current signal are acquired via CAN bus. Under abnormal noise conditions, the acceleration signal, sound signal, stroke displacement signal, ECU signal and solenoid valve current signal are collected simultaneously.

[0007] Furthermore, the step of performing time-domain and / or frequency-domain analysis or time-frequency-domain analysis on the multi-source objective signal data also includes: The sound signal is filtered and played back for analysis to identify the abnormal noise frequency range, and the noise type is determined based on the abnormal noise frequency range.

[0008] Furthermore, the step of performing time-domain correlation analysis between the sound signal and the travel displacement signal to pinpoint the suspension damper's working stroke at the moment the abnormal noise occurs includes: Based on the direction and rate of change of the suspension travel displacement signal at the moment the abnormal noise occurs, it is determined that the suspension is in the compression stroke and not at the moment of reversal; The suspension operating speed at the moment the abnormal noise occurred was determined to be within a preset speed range.

[0009] Furthermore, the step of performing acoustic-vibration correlation analysis between each vibration acceleration signal and the sound signal to determine the vibration source most strongly associated with the abnormal noise includes: By performing time-frequency correlation analysis on the vibration acceleration of the lower control arm, the vibration acceleration of the shock absorber piston rod, the vibration acceleration of the vehicle body, and the in-vehicle sound signal, the vibration source with the strongest correlation to the abnormal noise was identified as the abnormal vibration of the shock absorber piston rod.

[0010] Furthermore, the correlation analysis of the vibration signal from the vibration source, the solenoid valve current signal, and the stroke displacement signal includes: Based on the identification of abnormal vibration of the shock absorber piston rod as the strongest vibration source associated with the abnormal noise, the piston rod vibration signal, solenoid valve current signal, and stroke displacement signal were correlated and analyzed to identify the correlation between the abnormal noise and the solenoid valve current change. It was determined that the current change was the main cause of the abnormal vibration of the piston rod, which in turn led to the abnormal noise. The current change was manifested as a deviation of the current value from the preset control target value, or a current change rate exceeding a preset threshold. Moreover, the suspension shock absorber was in the compression stroke at the time of the abnormal noise. This current change caused the shock absorber piston rod to vibrate abnormally, thus locating the root cause of the abnormal noise to the chassis suspension ECU control strategy level.

[0011] Furthermore, the method for generating an improvement scheme for the abnormal noise based on the cause of the abnormal noise includes: Abnormal noise can be eliminated by adjusting the control parameters of the solenoid valve, including controlling the solenoid valve of the vibration damper with a fixed current.

[0012] Furthermore, the proposed improvement scheme based on the cause of the abnormal noise also includes: Add anti-sudden change control logic to the control strategy of the chassis suspension ECU. The logic includes setting a dead zone when the suspension travel speed is in the low to medium speed range and performing vehicle calibration on the dead zone to suppress sudden changes in solenoid valve current.

[0013] Furthermore, it also includes: The proposed noise improvement scheme is tested, evaluated, and verified. If the noise is eliminated and the suspension performance meets the requirements, the cause of the noise is confirmed, and the closed-loop locking is completed.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for identifying abnormal noises in intelligent suspension systems. By simultaneously collecting multi-source objective signal data such as the acceleration of the lower control arm of the suspension, the acceleration of the shock absorber piston rod, the vehicle body acceleration, the suspension travel displacement, the sound signal from the in-vehicle microphone, and the current signal from the chassis ECU and solenoid valves through the chassis CAN bus, it achieves comprehensive information acquisition under abnormal noise conditions of intelligent suspension, making up for the shortcomings of existing technologies in the research on abnormal noise identification of intelligent suspension.

[0015] This invention, through filtering and playback analysis of sound signals, can accurately pinpoint the frequency range of abnormal noises and determine the type of noise (structural noise or airborne noise), providing a clear direction for subsequent source tracing of abnormal noises.

[0016] This invention performs time-domain correlation analysis between sound signals and suspension travel displacement signals, which can accurately pinpoint the suspension working stroke (compression / tension stroke, running speed, and whether it is at the moment of reversal) at the time of abnormal noise occurrence, thus achieving accurate location of abnormal noise conditions.

[0017] This invention performs time-frequency correlation analysis on the sound signal at the time of the abnormal noise and various vibration acceleration signals, which can accurately pinpoint the vibration source most strongly associated with the abnormal noise, thus achieving precise source tracing from "hearing the abnormal noise" to "finding the vibration source".

[0018] This invention innovatively correlates and analyzes the sound signal, vibration acceleration signal and shock absorber solenoid valve drive current signal at the moment of abnormal noise. It reveals for the first time the intrinsic relationship between abnormal noise in intelligent suspension and sudden change in solenoid valve drive current, and locates the root cause of abnormal noise at the level of chassis suspension ECU control strategy, providing a brand-new analytical approach and technical path for the radical solution of abnormal noise in intelligent suspension.

[0019] This invention proposes an engineering improvement scheme based on the cause of abnormal noise—by adding low-to-medium speed dead zone logic to the chassis suspension ECU control strategy to suppress sudden changes in solenoid valve current, the actual vehicle verification has been verified to effectively eliminate abnormal noise and ensure acceptable suspension performance. It forms a complete abnormal noise identification and resolution process from problem discovery to cause analysis to solution verification and final closed-loop locking, which has significant engineering application value.

[0020] The method of the present invention has strong universality. It is not only applicable to the specific intelligent suspension noise problem involved in the current embodiment, but can also be extended to the identification and analysis of noise in other types of intelligent suspension systems, providing a reference methodology for the systematic solution of intelligent chassis NVH problems. Attached Figure Description

[0021] Figure 1 This is a flowchart of the intelligent suspension noise identification method of the present invention; Figure 2 The method for identifying abnormal noise in intelligent suspension according to the present invention is based on the vibration curve of the shock absorber and the suspension travel curve at the time of the abnormal noise. Figure 3 This is a time-frequency diagram of an in-vehicle microphone obtained during the operation of the intelligent suspension noise identification method of the present invention; Figure 4 The vibration time-frequency diagram of the shock absorber piston rod obtained during the operation of the intelligent suspension abnormal noise identification method of the present invention; Figure 5 The time-frequency diagram of the unsprung lower control arm acceleration obtained during the operation of the intelligent suspension abnormal noise identification method of the present invention; Figure 6 The image shows the vehicle body acceleration time-frequency diagram obtained during the operation of the intelligent suspension abnormal noise identification method of this invention. Figure 7 The method for identifying abnormal noises in intelligent suspensions of this invention includes the time of abnormal noise, acceleration of suspension dampers, suspension travel, and correlation curves between chassis ECU and drive current of damper solenoid valves, all obtained during operation. Figure 8 The method for identifying abnormal noises in intelligent suspension according to the present invention uses the current and shock absorber piston rod acceleration curves of the chassis ECU after applying dead-zone logic through the suspension travel during operation. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0024] It should also be understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0026] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. Example

[0029] This embodiment uses a certain electric vehicle equipped with an intelligent suspension system as the test object, such as... Figure 1 As shown, the abnormal noise problem of the suspension generated by the vehicle under specific working conditions is identified and analyzed in the whole vehicle state.

[0030] To achieve synchronous acquisition of multi-source data under abnormal noise conditions, the sensors are arranged as follows in this embodiment: like Figures 2-6As shown, a first acceleration sensor is positioned at the lower control arm of the vehicle suspension to collect under-suspension vibration acceleration signals; a second acceleration sensor is positioned at the top of the shock absorber piston rod to collect piston rod vibration acceleration signals; and a third acceleration sensor is positioned on the vehicle body near the shock absorber mounting point to collect vehicle body vibration acceleration signals. Simultaneously, a wire-type displacement sensor is positioned along the shock absorber piston rod's movement direction to collect suspension travel displacement signals. A microphone is positioned at the driver's right ear to collect in-vehicle sound signals. Furthermore, a data acquisition system is connected via the vehicle's CAN bus to collect real-time drive current signals and related control command signals between the chassis suspension ECU and the shock absorber solenoid valve.

[0031] All the aforementioned accelerometers, displacement sensors, microphones, and CAN bus signals are connected to the same multi-channel data acquisition front-end. A unified sampling clock is set to achieve synchronous acquisition of signals from each channel. The acquisition frequency is set to 12.8kHz to meet the requirement of capturing the high-frequency components of the abnormal noise signal. When the vehicle is traveling under typical conditions where abnormal noise occurs (such as passing over a specific bumpy road surface at medium to low speed), the acquisition system is activated to continuously record all the above signals. The acquisition duration covers the complete process before, during, and after the abnormal noise occurs.

[0032] The collected in-vehicle microphone audio signals and suspension travel displacement signals are subjected to time-domain correlation analysis. Specifically, the time-domain waveforms of the audio signals and the displacement signals are aligned and superimposed on the same time coordinate system to identify time points in the audio signals where obvious pulses or energy surges occur, and the corresponding displacement signal values ​​and directions of change are read simultaneously at those moments.

[0033] Analysis results indicate that at the moment the abnormal noise occurred, the suspension travel displacement signal was in the compression direction and the displacement was continuously increasing, rather than at the instant of reversal between tension and compression. Further differential calculation of the displacement signal revealed that the suspension operating speed at the time of the abnormal noise was approximately 0.18 m / s, falling within the low-to-medium speed range. Therefore, the suspension damper working stroke at the time of the abnormal noise was determined to be: compression stroke, low-to-medium speed operation, and not at the instant of reversal.

[0034] The sound signal captured by the in-vehicle microphone is subjected to Fourier Transform (FFT) to obtain the sound signal's spectrum. Simultaneously, the sound signal undergoes bandpass filtering playback processing; that is, different frequency bands are set to filter the original sound signal before playback, and the frequency components with the most obvious abnormal noises are determined by manual listening.

[0035] After filtering and playback analysis, the abnormal noise was mainly concentrated in the frequency range of 80Hz to 260Hz. This frequency band belongs to the typical frequency band of structural vibration radiation noise, rather than aerodynamic noise (the latter usually exhibits higher frequency or broadband characteristics). Therefore, it is determined that the abnormal noise is structural noise, that is, caused by the structural vibration of a component of the suspension system transmitted to the vehicle interior through the structural path.

[0036] The vibration acceleration signals of the lower control arm, the shock absorber piston rod, and the vehicle body were correlated with the in-vehicle microphone audio signal using time-frequency correlation analysis. Specifically, the Short Time Fourier Transform (STFT) method was used to convert each vibration signal and audio signal to a time-frequency spectrum, and the consistency between the time-frequency distribution characteristics of the energy of each vibration signal at the time of abnormal noise and the time-frequency distribution characteristics of the audio signal was compared.

[0037] Analysis revealed that at the moment the abnormal noise occurred, the vibration acceleration signal of the shock absorber piston rod exhibited a significant energy peak in the 80Hz-260Hz frequency band. Its time-frequency distribution characteristics highly matched the time-frequency distribution characteristics of the in-vehicle sound signal at the time of the abnormal noise, showing the highest correlation coefficient. In contrast, the energy changes of the lower control arm vibration and body vibration in this frequency band showed a weaker correlation with the sound signal. Therefore, the abnormal vibration of the shock absorber piston rod was identified as the vibration source most strongly associated with the abnormal noise.

[0038] Further observation of the time-domain waveform of the piston rod vibration acceleration revealed that at the moment of the abnormal noise, the piston rod was subjected to two large impact excitations in a short time window. This abnormal double impact mode caused the piston rod to vibrate violently, which in turn radiated the abnormal noise.

[0039] like Figure 7 As shown, based on the strong correlation between the locked abnormal noise and the abnormal vibration of the shock absorber piston rod, a time-domain correlation analysis was further performed on the piston rod vibration acceleration signal, the chassis ECU and shock absorber solenoid valve drive current signal, and the suspension travel displacement signal.

[0040] Specifically, the three signals were aligned on the same time coordinate system, with a focus on the changes in each signal near the moment of the abnormal noise. Analysis revealed that at the precise moment the abnormal noise occurred, the suspension damper was in its compression stroke. Simultaneously, the drive current signal output from the chassis ECU to the damper solenoid valve experienced a sharp drop lasting approximately tens of milliseconds—the current value rapidly decreased from approximately 1.2A to approximately 0.3A, a drop exceeding 75%, and the rate of change far exceeded the fluctuation range during normal control. The moment of this current abrupt change perfectly coincided with the moment the piston rod experienced abnormal double-impact vibration, indicating a strong temporal correlation between the two.

[0041] Based on the above analysis, the root cause of the abnormal noise is preliminarily determined to be: under specific working conditions, the control strategy of the chassis suspension ECU has defects, which causes an unexpected sudden change in the drive current output to the shock absorber solenoid valve. This sudden change causes the solenoid valve core to move abnormally, which in turn excites the shock absorber piston rod to produce abnormal vibration, and finally radiates structural noise.

[0042] To verify the above judgment, this embodiment adopts the following verification scheme: A forced command is sent to the chassis suspension ECU through the diagnostic interface to fix the drive current of the shock absorber solenoid valve to a constant value (e.g., 1.0A), so that the solenoid valve no longer responds to the real-time adjustment command of the ECU. Subsequently, the vehicle is driven through the same abnormal noise condition road section again, and all signals are collected repeatedly.

[0043] like Figure 8 As shown in the verification test results, after adopting fixed current control, the solenoid valve drive current signal remained stable and no longer exhibited abrupt drops; the piston rod vibration acceleration signal no longer showed abnormal double-impact vibration at the corresponding moment; and the abnormal noise in the in-vehicle microphone sound signal disappeared. Therefore, the closed-loop conclusion is that the sudden change in the solenoid valve drive current is the direct cause of this abnormal noise in the intelligent suspension, and the root cause lies in the control strategy of the chassis suspension ECU.

[0044] Based on the above closed-loop verification results, this embodiment proposes an engineering improvement scheme: In the control strategy of the chassis suspension ECU, for the working condition where the suspension travel speed is in the low-to-medium speed range (e.g., 0.1m / s~0.3m / s), dead zone processing is added to the current closed-loop control logic. That is, when the suspension running speed falls into this range, the ECU no longer adjusts the solenoid valve drive current in real time, but maintains the current value constant output, thereby avoiding sudden current changes due to over-adjustment of the control strategy.

[0045] The modified control strategy was flashed to the chassis suspension ECU, and the vehicle was tested again on a test track with abnormal noises. The test results showed that after adding dead-zone logic, the solenoid valve drive current remained stable under low and medium speed conditions, and the sudden current phenomenon was completely eliminated; the piston rod vibration acceleration amplitude returned to normal level; the abnormal noises inside the vehicle were completely eliminated, and the adjustment error of the suspension damping force remained within the design tolerance range without being significantly affected.

[0046] Thus, this embodiment completes the entire closed-loop identification process for abnormal noises in intelligent suspensions, from data collection, multi-dimensional correlation analysis, cause identification to solution verification and engineering implementation.

[0047] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for identifying abnormal noises in intelligent suspension systems, characterized in that, include: Simultaneously collect multi-source objective signal data under abnormal noise conditions. The multi-source objective signal data includes at least: suspension lower control arm vibration acceleration signal, shock absorber piston rod vibration acceleration signal, vehicle body vibration acceleration signal, suspension shock absorber stroke displacement signal, in-vehicle sound signal, and chassis suspension ECU and shock absorber solenoid valve current signal. Perform time-domain and / or frequency-domain analysis on the multi-source objective signal data, including: performing time-domain correlation analysis on the sound signal and the travel displacement signal to pinpoint the suspension damper working stroke at the moment the abnormal noise occurs, and performing correlation analysis on each vibration acceleration signal and the sound signal to determine the vibration source most strongly associated with the abnormal noise; The sound signal at the time of the abnormal noise is correlated with each vibration acceleration signal and the solenoid valve current signal to determine the cause of the abnormal noise; An improvement plan for the abnormal noise is generated based on the causes of the abnormal noise.

2. The intelligent suspension abnormal noise identification method according to claim 1, characterized in that, The multi-source objective signal data collected under abnormal noise conditions includes: A first acceleration sensor is placed on the lower control arm of the vehicle suspension to collect the under-suspension vibration acceleration signal, a second acceleration sensor is placed on the piston rod of the suspension damper to collect the piston rod vibration acceleration signal, and a third acceleration sensor is placed on the body to collect the body vibration acceleration signal. Displacement sensors are arranged along the direction of shock absorber movement to collect suspension travel displacement signals; Microphones were placed inside the vehicle to collect sound signals; The chassis suspension ECU signal and the shock absorber solenoid valve current signal are acquired via CAN bus. Under abnormal noise conditions, the acceleration signal, sound signal, stroke displacement signal, ECU signal and solenoid valve current signal are collected simultaneously.

3. The intelligent suspension abnormal noise identification method according to claim 1, characterized in that, The time-domain and / or frequency-domain analysis of the multi-source objective signal data further includes: The sound signal is filtered and played back for analysis to identify the abnormal noise frequency range, and the noise type is determined based on the abnormal noise frequency range.

4. The intelligent suspension abnormal noise identification method according to claim 1, characterized in that, The step of performing time-domain correlation analysis between the sound signal and the travel displacement signal to pinpoint the suspension damper's working stroke at the moment the abnormal noise occurs includes: The suspension travel and operating speed are determined based on the direction and rate of change of the suspension travel displacement signal at the moment the abnormal noise occurs.

5. The intelligent suspension noise identification method according to claim 1, characterized in that, The step of performing vibration-sound correlation analysis between each vibration acceleration signal and the sound signal to determine the vibration source most strongly associated with the abnormal noise includes: By performing time-frequency correlation analysis on the vibration acceleration of the lower control arm, the vibration acceleration of the shock absorber piston rod, the vibration acceleration of the vehicle body, and the in-vehicle sound signal, the source of vibration most strongly associated with abnormal noise was identified.

6. The intelligent suspension abnormal noise identification method according to claim 5, characterized in that, The correlation analysis of the vibration signal from the vibration source, the solenoid valve current signal, and the stroke displacement signal includes: Based on the fact that the vibration source most strongly associated with the abnormal noise is the abnormal vibration of the damper piston rod, the piston rod vibration signal, the solenoid valve current signal and the stroke displacement signal are correlated and analyzed to lock the correlation between the abnormal noise and the sudden change in the solenoid valve current. It is determined that the sudden change in current is the main reason for the abnormal vibration of the piston rod, which in turn leads to the abnormal noise. The current mutation manifests as a deviation of the current value from the preset control target value, or a current change rate exceeding a preset threshold, and the suspension damper is in the compression stroke at the time of the abnormal noise. This current mutation causes the piston rod of the damper to vibrate abnormally, thereby locating the root cause of the abnormal noise to the chassis suspension ECU control strategy level.

7. The intelligent suspension abnormal noise identification method according to claim 1, characterized in that, The proposed solution for improving the abnormal noise based on the cause of the abnormal noise includes: Abnormal noise can be eliminated by adjusting the control parameters of the solenoid valve, including controlling the solenoid valve of the vibration damper with a fixed current.

8. The intelligent suspension abnormal noise identification method according to claim 7, characterized in that, The proposed solution for improving the abnormal noise based on the cause of the abnormal noise also includes: Add anti-sudden change control logic to the control strategy of the chassis suspension ECU. The logic includes setting a dead zone when the suspension travel speed is in the low-to-medium speed range and calibrating the dead zone for the whole vehicle to suppress abnormal sudden changes in the current of the chassis ECU and solenoid valve.

9. The intelligent suspension abnormal noise identification method according to claim 1, characterized in that, Also includes: The proposed noise improvement scheme is tested, evaluated, and verified. If the noise is eliminated and the suspension performance meets the requirements, the cause of the noise is confirmed, and the closed-loop locking is completed.

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