Method and system for detecting abnormal noise of electric drive assembly, computer and storage medium

Abstract

The embodiment of the application provides a kind of electric drive assembly abnormal sound detection method, system, computer and storage medium, the electric drive assembly abnormal sound detection method includes: obtaining the analog working condition data of abnormal sound electric drive assembly;Obtain the vibration limit of the electric drive assembly on the test stand;According to the analog working condition data, the electric drive assembly to be detected on the test stand is detected, and the analog vibration peak of the electric drive assembly to be detected is obtained;The size of the analog vibration peak and the vibration limit is compared to determine whether the electric drive assembly to be detected has abnormal sound.The electric drive assembly abnormal sound detection method of the embodiment of the application can filter out the electric drive assembly with abnormal sound in advance to avoid its flow into the market.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle detection, and in particular to a detection method and system for abnormal noise of an electric drive assembly, a computer and a storage medium. BACKGROUND

[0002] In related technologies, under the working condition of low speed, high torsion and limited turning, some electric drive assemblies of vehicles produce abnormal noise, which affects the driving experience. SUMMARY

[0003] Therefore, the embodiments of the present application provide a detection method and system for abnormal noise of an electric drive assembly, a computer and a storage medium, which can filter out electric drive assemblies with abnormal noise in advance to avoid them from flowing into the market.

[0004] To achieve the above-mentioned purpose, on one hand, the embodiments of the present application provide a detection method for an electric drive assembly, comprising:

[0005] obtaining simulation working condition data of an electric drive assembly with abnormal noise;

[0006] obtaining a vibration limit value of the electric drive assembly on a test bench;

[0007] detecting the electric drive assembly on the test bench according to the simulation working condition data to obtain a simulation vibration peak value of the electric drive assembly under detection;

[0008] comparing the simulation vibration peak value with the vibration limit value to determine whether the electric drive assembly under detection has abnormal noise.

[0009] In some embodiments, the step of obtaining simulation working condition data of the electric drive assembly with abnormal noise comprises:

[0010] obtaining vibration data of a vibration measuring point of the electric drive assembly on a vehicle in an abnormal noise state;

[0011] confirming a physical field parameter of the electric drive assembly that is strongly correlated with the vibration data as a vibration observation parameter;

[0012] taking the vibration observation parameter as a variable to obtain a plurality of groups of first simulation vibration values of the electric drive assembly on the test bench;

[0013] selecting a value of the vibration observation parameter corresponding to the largest first simulation vibration value as simulation working condition data for determining abnormal noise of the electric drive assembly.

[0014] In some embodiments, the step of obtaining vibration data of a vibration measuring point of the electric drive assembly on a vehicle in an abnormal noise state comprises:

[0015] acquiring total working condition data of the electric drive assembly in an abnormal sound state on a vehicle;

[0016] acquiring an abnormal sound time point of the electric drive assembly;

[0017] According to the abnormal sound time point, the data corresponding to the peak value and the abnormal sound in the total working condition data is the vibration data.

[0018] In some embodiments, according to the abnormal sound time point, the step of acquiring the data corresponding to the peak value and the abnormal sound in the total working condition data as the vibration data includes:

[0019] According to the abnormal sound time point, the vibration values of a plurality of vibration measuring points in the total working condition data are acquired;

[0020] Among the vibration values of a plurality of vibration measuring points, the maximum vibration value is acquired as the vibration data.

[0021] In some embodiments, the step of confirming the physical field parameters of the electric drive assembly that are strongly correlated with the vibration data as vibration observation parameters includes:

[0022] acquiring a time point corresponding to a second simulated vibration peak value of the vibration data in an abnormal sound state;

[0023] sorting the numerical value changes of a plurality of physical field parameters corresponding to the time point of the second simulated vibration peak value;

[0024] selecting at least one physical field parameter with a high numerical value as the vibration observation parameter.

[0025] In some embodiments, the vibration observation parameters include the torque of the motor in the electric drive assembly and the differential rate of the differential.

[0026] In some embodiments, the step of acquiring the vibration limit value of the electric drive assembly on a test bench includes:

[0027] According to the simulated working condition data, a third simulated vibration peak value of a plurality of electric drive assemblies on a test bench is acquired;

[0028] According to the normal distribution of the third simulated vibration peak value, a plurality of electric drive assemblies are screened;

[0029] The abnormal sound data of the screened electric drive assemblies on a vehicle is acquired for regression analysis;

[0030] The vibration limit value is obtained according to the regression analysis.

[0031] In some embodiments, the step of screening a plurality of the electric drive assemblies according to the normal distribution of the third simulated vibration peak value comprises:

[0032] screening the electric drive assembly at the normal distribution probability density equant point.

[0033] In some embodiments, the step of obtaining the abnormal sound data of the screened electric drive assembly on the vehicle for regression analysis comprises:

[0034] obtaining the abnormal sound data of the electric drive assembly on the vehicle; wherein the abnormal sound data comprises a subjective abnormal sound level, a vehicle noise value, and a vehicle vibration peak value;

[0035] establishing a first coordinate system with the subjective abnormal sound level as the horizontal coordinate and the vehicle noise value as the vertical coordinate, establishing a second coordinate system with the vehicle vibration peak value as the horizontal coordinate and the vehicle noise value as the vertical coordinate, establishing a third coordinate system with the subjective abnormal sound level as the horizontal coordinate and the second simulated vibration peak value as the vertical coordinate, and establishing a fourth coordinate system with the vehicle vibration peak value as the horizontal coordinate and the second simulated vibration peak value as the vertical coordinate;

[0036] performing regression analysis in each coordinate system according to the third simulated vibration peak value and the abnormal sound data corresponding to each screened electric drive assembly to establish a regression line.

[0037] In some embodiments, the step of obtaining the vibration limit value according to the regression analysis comprises:

[0038] determining a subjective abnormal sound level value according to subjective feeling;

[0039] determining a vehicle noise value corresponding to the intersection point in the first coordinate system according to the determined subjective abnormal sound level value and the intersection point of the regression line of the first coordinate system;

[0040] determining a vehicle vibration peak value corresponding to the intersection point in the second coordinate system according to the vehicle noise value corresponding to the intersection point in the first coordinate system and the intersection point of the regression line of the second coordinate system;

[0041] determining the vibration limit value according to the vehicle vibration peak value corresponding to the intersection point in the second coordinate system and the intersection point of the regression line of the fourth coordinate system.

[0042] In another aspect, the embodiments of the present application provide a detection system for abnormal sound of an electric drive assembly, comprising:

[0043] a first obtaining module configured to obtain simulated working condition data of the electric drive assembly with abnormal sound;

[0044] a second obtaining module configured to obtain a vibration limit value of the electric drive assembly on a test bench;

[0045] detecting the electric drive assembly on the bench according to the simulation working condition data, to obtain a simulation vibration peak value;

[0046] comparing the simulation vibration peak value with the vibration limit value, to determine whether the electric drive assembly to be detected has abnormal sound.

[0047] In another aspect, an embodiment of the present application provides a computer device, comprising:

[0048] a memory for storing executable instructions;

[0049] a processor for executing the executable instructions to implement the steps of the detection method of abnormal sound of an electric drive assembly.

[0050] In another aspect, an embodiment of the present application provides a storage medium for storing computer executable instructions, which can be executed by a processor to implement the steps of the detection method of abnormal sound of an electric drive assembly.

[0051] The detection method of abnormal sound of an electric drive assembly provided by the embodiment of the present application can obtain simulation working condition data of an electric drive assembly with abnormal sound, detect an electric drive assembly to be detected on a bench, obtain a simulation vibration peak value of the electric drive assembly to be detected, and compare the obtained simulation vibration peak value with a vibration limit value to determine whether the electric drive assembly to be detected has abnormal sound. In this way, the electric drive assembly with abnormal sound can be screened out in advance, so that the possibility of abnormal sound of the electric drive assembly after being installed on a vehicle is reduced, and the electric drive assembly with abnormal sound is prevented from flowing into the market to affect the driving experience. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 FIG. 1 is a structural schematic diagram of a differential in the related art;

[0053] Figure 2 FIG. 4 is a schematic diagram of torque output characteristics of a traditional vehicle and a new energy vehicle;

[0054] Figure 3 FIG. 6 is a flowchart of the detection method of abnormal sound of an electric drive assembly according to an embodiment of the present application;

[0055] Figure 4 FIG. 8 is a statistical analysis diagram of a third simulation vibration peak value;

[0056] Figure 5 FIG. 10 is a regression analysis diagram;

[0057] Figure 6 FIG. 12 is a flowchart of the detection method of abnormal sound of an electric drive assembly according to an embodiment of the present application;

[0058] Figure 7A graph showing the changes in vibration data and data under each overall operating condition over the test period;

[0059] Figure 8 This is a graph showing the change of the first simulated vibration value over the test time.

[0060] Figure 9 This is a diagram showing the relationship between differential vibration, right half-shaft vibration, and feedback torque under abnormal noise conditions.

[0061] Explanation of reference numerals in the attached figures

[0062] Drive shaft 01; half shaft shim 02; half shaft gear 03; planetary shim 04; planetary gear 05. Detailed Implementation

[0063] The embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but should not be used to limit the scope of this application.

[0064] In the description of the embodiments of this application, it should be noted that the terms "first", "second", etc. are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0065] In related technologies, the structure of the electric drive assembly of new energy vehicles includes a drive motor and a differential, such as... Figure 1 As shown, the vehicle drive shaft 01 is used to transmit torque between the differential and the drive wheels. When the vehicle is traveling straight, there is no relative movement between the half-shaft shim 02 and the half-shaft gear 03, between the planetary shim 04 and the planetary gear 05, between the planetary shim 04 and the differential housing, and between the half-shaft shim 02 and the differential housing. However, when turning at a large angle, a friction pair will be formed between the half-shaft shim 03 and the half-shaft gear 02, and between the planetary shim 04 and the planetary gear 05. There may be a risk of stick-slip movement when the differential is turned.

[0066] Furthermore, compared to traditional gasoline vehicles, under low-speed operating conditions, on the one hand, by Figure 2 Based on the torque output characteristics of traditional and new energy vehicles, it is known that the output torque of the drive motor in new energy vehicles is significantly increased. Furthermore, the speed ratio of the reducer is larger than that of traditional internal combustion engine vehicles, resulting in a sharp increase in the torque output from the half-shaft compared to traditional fuel vehicles. Therefore, the risk of differential stick-slip is dramatically increased, even becoming unavoidable. On the other hand, since new energy vehicles are driven purely by electricity at low speeds, there is no background noise masking from the engine. Therefore, under low-speed, high-torque, and extreme cornering conditions, the contact surfaces inside the differential will experience more noticeable relative movement, leading to stick-slip. The resulting abnormal noise is easily perceived by the occupants and reduces the driving experience.

[0067] To this end, the embodiment of the present application provides a detection method for abnormal sound of an electric drive assembly, which is used to determine whether the electric drive assembly of a vehicle has abnormal sound. The detection method for abnormal sound of the electric drive assembly is mainly applicable to new energy vehicles, such as single-motor, double-motor pure electric, hybrid PHEV and HEV vehicle models.

[0068] For reference Figure 3 , the detection method for abnormal sound of the electric drive assembly comprises the following steps.

[0069] S1, obtaining simulation working condition data of an electric drive assembly with abnormal sound;

[0070] S2, obtaining a vibration limit value of the electric drive assembly on a test bench;

[0071] S3, detecting the electric drive assembly on the test bench according to the simulation working condition data to obtain a simulation vibration peak value of the electric drive assembly to be detected;

[0072] S4, comparing the simulation vibration peak value with the vibration limit value to determine whether the electric drive assembly to be detected has abnormal sound.

[0073] The step S3 refers to making the electric drive assembly to be detected on the test bench run under the simulation working condition data, and then obtaining the simulation vibration peak value of the electric drive assembly to be detected.

[0074] It can be understood that if the simulation vibration peak value is greater than the vibration limit value, it is determined that the electric drive assembly to be detected has abnormal sound, i.e. unqualified, and needs to be repaired. If the simulation vibration peak value is less than or equal to the vibration limit value, it is determined that the electric drive assembly to be detected has no abnormal sound.

[0075] It can be understood that the steps S2 and S3 in the detection method for abnormal sound of the electric drive assembly can be exchanged.

[0076] The detection method for abnormal sound of the electric drive assembly provided by the embodiment of the present application obtains the simulation working condition data of the electric drive assembly with abnormal sound, detects the electric drive assembly to be detected on the test bench, obtains the simulation vibration peak value of the electric drive assembly to be detected, and compares the obtained simulation vibration peak value with the obtained vibration limit value to determine whether the electric drive assembly to be detected has abnormal sound.

[0077] For example, refer to Figure 6 , the step S1 of obtaining the simulation working condition data of the electric drive assembly with abnormal sound comprises the following steps.

[0078] S11, obtaining vibration data of a vibration measuring point of the electric drive assembly on the vehicle in an abnormal sound state;

[0079] S12, confirming a physical field parameter of the electric drive assembly that is strongly correlated with the vibration data as a vibration observation parameter;

[0080] S13, obtaining a plurality of first simulated vibration values of the electric drive assembly on the test bench as variables of the vibration observation parameters;

[0081] S14, selecting a value of the vibration observation parameter corresponding to the maximum first simulated vibration value as the simulated working condition data for judging the abnormal sound of the electric drive assembly.

[0082] The specific embodiments of steps S11-S14 will be described in detail below.

[0083] S11, obtaining vibration data of vibration measuring points of the electric drive assembly in an abnormal sound state on a vehicle.

[0084] It can be understood that this step is to install the electric drive assembly on the vehicle, and then obtain the vibration data of the vibration measuring points of the electric drive assembly in the abnormal sound state. The vibration data obtained in this way can reflect the vibration of the electric drive assembly on the vehicle.

[0085] It should be noted that the vibration measuring points are not only the electric drive assembly, but also other structures such as the engine and the generator. That is, the vibration data of each vibration measuring point in the abnormal sound state needs to be screened to obtain the vibration data of the vibration measuring points of the electric drive assembly in the abnormal sound state.

[0086] S12, confirming the physical field parameters of the electric drive assembly that are strongly correlated with the vibration data as vibration observation parameters.

[0087] It can be understood that the physical field parameters of the electric drive assembly that are strongly correlated with the vibration data are the physical field parameters of the electric drive assembly that change at the same time when the vibration data changes, and the strength correlation of the changes of the two is strong. The vibration observation parameters are subject to experimental results, and one or more of them can be selected according to the degree of strong correlation.

[0088] The physical field parameters include the physical field parameters of the electric drive assembly and other physical field parameters. The physical field parameters of the electric drive assembly include the actual speed of the motor, the actual torque of the motor, the demand speed of the motor, the demand torque of the motor, the wheel end speed, the wheel end torque, and the oil temperature signal of the electric drive assembly. The other physical field parameters include the vehicle speed, the accelerator pedal opening, the brake signal, and the SOC power.

[0089] S13, obtaining a plurality of first simulated vibration values of the electric drive assembly on the test bench as variables of the vibration observation parameters;

[0090] Specifically, among the physical field parameters of the electric drive assembly that are strongly correlated with the vibration data, the values of the vibration observation parameters are adjusted, and a plurality of first simulated vibration values corresponding thereto are obtained.

[0091] The first simulated vibration value is a vibration acceleration peak value, a speed peak value, or a displacement peak value.

[0092] In some embodiments, a bench test condition table is formulated according to the driving motor torque and the differential rate of the differential as main variables, wherein the differential rate of the differential is determined by the differential target speed, the left half shaft speed, and the right half shaft speed. For details, refer to the following table:

[0093]

[0094] S14, selecting the value of the vibration observation parameter corresponding to the maximum first simulated vibration value as the simulated working condition data for judging the abnormal sound of the electric drive assembly.

[0095] It should be noted that the greater the first simulated vibration value, the greater the intensity of the vibration, and the more relevant the vibration condition of the electric drive assembly on the vehicle. Therefore, selecting the value of the vibration observation parameter corresponding to the maximum first simulated vibration value as the simulated working condition data for judging the abnormal sound of the electric drive assembly can more reflect the running condition of the electric drive assembly on the vehicle.

[0096] Figure 8 For illustration of step S14, Figure 8 The upper and lower graphs correspond to two values of the vibration observation parameter, respectively, and are used to show the graph of the change of the vibration acceleration with the test time. The vibration acceleration corresponding to the upper graph has no obvious change, and the vibration acceleration corresponding to the lower graph changes obviously.

[0097] In step S1, the physical field parameter strongly correlated with the vibration data is confirmed as the vibration observation parameter, and then the specific value of the vibration observation parameter is further confirmed and taken as the simulated working condition data for judging the abnormal sound of the electric drive assembly, so that the detection result under the simulated working condition data is more consistent with the detection result of the vehicle.

[0098] For example, step S11 "obtaining the vibration data of the vibration measuring point of the electric drive assembly on the vehicle in the abnormal sound state" includes:

[0099] S111, obtaining the total working condition data of the electric drive assembly on the vehicle in the abnormal sound state.

[0100] Specifically, the total working condition data is the total working condition data obtained when the electric drive assembly is on the vehicle and the vehicle is in the abnormal sound state, including the working condition data of the electric drive assembly and the working condition data of other structures of the vehicle such as the engine and the generator.

[0101] S112, obtaining the abnormal sound time point of the electric drive assembly.

[0102] The abnormal sound time point can be determined by the person who hears the abnormal sound, or can be automatically obtained by the sound collecting device. The abnormal sound time point is used to determine the working condition data corresponding to the abnormal sound time point in the total working condition data.

[0103] S113, according to the abnormal sound time point, the data corresponding to the peak value and the abnormal sound in the total working condition data is obtained as the vibration data.

[0104] That is, the vibration data is the data corresponding to the peak value and the abnormal sound in the total working condition data.

[0105] Through experiments, it is determined that the vibration data is the relevant working condition data of the electric drive assembly.

[0106] Figure 9 For example, step S11 is illustrated in the figure. The figure shows the corresponding relationship between the differential vibration, the right half shaft vibration and the feedback torque in the abnormal sound state. At the time point of the abnormal sound state, the differential vibration and the right half shaft vibration are obvious, and the feedback torque changes obviously.

[0107] In some embodiments, step S113 "according to the abnormal sound time point, the data corresponding to the peak value and the abnormal sound in the total working condition data is obtained as the vibration data" includes:

[0108] S1131, according to the abnormal sound time point, the vibration values of the plurality of vibration measuring points in the total working condition data are obtained.

[0109] That is, the sensors capable of obtaining vibration signals are arranged at different positions on the electric drive assembly, and the vibration values are confirmed in the vibration signals obtained by each sensor according to the abnormal sound time point.

[0110] S1132, in the vibration values of the plurality of vibration measuring points, the maximum vibration value is obtained as the vibration data.

[0111] Since the vibration value of the vibration has the highest vibration intensity, the obtained vibration data has a higher correlation with the abnormal sound.

[0112] It should be noted that the vibration measuring point corresponding to the maximum vibration value is the vibration measuring point corresponding to the vibration data.

[0113] For example, please refer to Figure 7 , Figure 7 The figure shows the changes of the vibration data and each total working condition data in the test time. In the figure, at the time point when the vibration data changes obviously, the corresponding changes of the differential speed and the motor torque are obvious.

[0114] For example, step S12 "confirming the physical field parameter of the electric drive assembly with strong correlation with the vibration data as the vibration observation parameter" includes:

[0115] S121, obtaining a time point corresponding to a second simulation vibration peak value of vibration data of the abnormal sound state.

[0116] S122, sorting values of a plurality of physical field parameters at the time point corresponding to the second simulation vibration peak value.

[0117] That is, the values of the vibration peaks of the plurality of physical field parameters are sorted.

[0118] S123, selecting at least one physical field parameter with a high value as a vibration observation parameter.

[0119] That is, at least one physical field parameter with the most obvious vibration at the abnormal sound time point is selected as the vibration observation parameter.

[0120] In some embodiments, the vibration observation parameter includes torque of a motor in the electric drive assembly and differential rate of a differential.

[0121] For example, referring to Figure 6 , step S2 "obtaining a vibration limit of the electric drive assembly on the test bench" includes:

[0122] S21, obtaining a third simulation vibration peak value of a plurality of electric drive assemblies on the test bench according to simulation working condition data.

[0123] In some embodiments, a simulation working condition is established on the test bench according to the simulation working condition data, and 200-300 electric drive assemblies are measured to obtain corresponding third simulation vibration peak values. By increasing the number of samples, the result is closer to the actual distribution.

[0124] S22, screening the plurality of electric drive assemblies according to a normal distribution of the third simulation vibration peak values.

[0125] It can be understood that the distribution of the third simulation vibration peak values of the screened electric drive assemblies can reflect the distribution rule of the third simulation vibration peak values of the electric drive assemblies before screening, thereby improving the accuracy of subsequent detection, and reducing the workload of subsequent steps after screening.

[0126] S23, obtaining abnormal sound data of the screened electric drive assemblies on vehicles for regression analysis, so as to associate the abnormal sound data of the electric drive assemblies on the vehicles with the third simulation vibration peak values.

[0127] S24, obtaining a vibration limit according to the regression analysis.

[0128] In some embodiments, referring to Figure 4 , Figure 4 a statistical analysis diagram of the third simulation vibration peak values.

[0129] Step S22 "selecting the plurality of electric drive assemblies according to the normal distribution of the third simulated vibration peak value" comprises:

[0130] S221, selecting the electric drive assemblies at the normal distribution probability density equidivision points according to the normal distribution of the third simulated vibration peak value.

[0131] The probability density equidivision point is the equidivision point of the area under the normal distribution curve. It can be understood that the number of electric drive assemblies distributed between adjacent equidivision points is equivalent, so that the selection result can fully reflect the distribution rule of the third simulated vibration peak value of the electric drive assemblies before selection.

[0132] In some embodiments, the plurality of electric drive assemblies are divided into four parts, and the electric drive assemblies at the 1 / 4, 2 / 4, 3 / 4 and 4 / 4 quantiles are taken respectively.

[0133] In some embodiments, please refer to Figure 5 Step S23 comprises:

[0134] S231, obtaining abnormal sound data of the electric drive assembly on the vehicle, wherein the abnormal sound data comprises a subjective abnormal sound level, a vehicle noise value and a vehicle vibration peak value.

[0135] The subjective abnormal sound level is divided according to the driving experience under the abnormal sound state.

[0136] S232, establishing a first coordinate system with the subjective abnormal sound level as the abscissa and the vehicle noise value as the ordinate, establishing a second coordinate system with the vehicle vibration peak value as the abscissa and the vehicle noise value as the ordinate, establishing a third coordinate system with the subjective abnormal sound level as the abscissa and the second simulated vibration peak value as the ordinate, and establishing a fourth coordinate system with the vehicle vibration peak value as the abscissa and the second simulated vibration peak value as the ordinate.

[0137] S233, according to the third simulated vibration peak value and the abnormal sound data of each selected electric drive assembly, regression analysis is performed in each coordinate system to establish a regression line.

[0138] Specifically, according to the third simulated vibration peak value, the subjective abnormal sound level, the vehicle noise value and the vehicle vibration peak value of each selected electric drive assembly, specific points are determined in the four coordinate systems respectively, and regression analysis is performed according to the points in each coordinate system to establish a regression line.

[0139] In some embodiments, the goodness of fit of the regression line is greater than or equal to 0.85, and on this basis, the regression line can fully reflect the distribution rule of each point.

[0140] In some embodiments, please refer to Figure 5 Step S24 comprises:

[0141] S241, determine a subjective abnormal sound level value according to the subjective feeling.

[0142] S242, determine a vehicle noise value corresponding to the intersection point in the first coordinate system according to the intersection point of the determined subjective abnormal sound level value and the regression line of the first coordinate system.

[0143] S243, determine a vehicle vibration peak value corresponding to the intersection point in the second coordinate system according to the intersection point of the vehicle noise value corresponding to the intersection point in the first coordinate system and the regression line of the second coordinate system.

[0144] S244, determine a vibration limit value according to the intersection point of the vehicle vibration peak value corresponding to the intersection point in the second coordinate system and the regression line of the fourth coordinate system.

[0145] It should be noted that the electric drive assembly to be detected is screened according to the vibration limit value, and the qualified electric drive assembly after screening may have the possibility of producing abnormal sound after being installed in the vehicle. That is, the electric drive assembly with abnormal sound can be screened out in advance by screening the electric drive assembly to be detected according to the vibration limit value, but the electric drive assembly with abnormal sound cannot be completely excluded. In some embodiments, the vibration limit value is a second simulated vibration peak value corresponding to the intersection point of the vehicle vibration peak value corresponding to the intersection point in the second coordinate system and the regression line of the fourth coordinate system.

[0146] In some embodiments, after determining the second simulated vibration peak value corresponding to the intersection point, the obtained second simulated vibration peak value is adjusted within a preset tolerance range to obtain the vibration limit value.

[0147] In some embodiments, the detection method of the abnormal sound of the electric drive assembly comprises:

[0148] S111, obtaining total working condition data of the electric drive assembly in an abnormal sound state on the vehicle.

[0149] S112, obtaining an abnormal sound time point of the electric drive assembly.

[0150] S1131, obtaining vibration values of a plurality of vibration measuring points in the total working condition data according to the abnormal sound time point.

[0151] S1132, obtaining the maximum vibration value in the vibration values of the plurality of vibration measuring points as vibration data.

[0152] S121, obtaining a time point corresponding to a second simulated vibration peak value of the vibration data in the abnormal sound state.

[0153] S122, sorting values of a plurality of physical field parameters corresponding to the time point corresponding to the second simulated vibration peak value.

[0154] S123, selecting at least one physical field parameter with a high value as a vibration observation parameter.

[0155] S13, obtain a plurality of first simulated vibration values of the electric drive assembly on the test bench as variables of the vibration observation parameters.

[0156] S14, select a value of the vibration observation parameter corresponding to the maximum first simulated vibration value as the simulated working condition data for judging the abnormal sound of the electric drive assembly.

[0157] S21, obtain a third simulated vibration peak value of a plurality of electric drive assemblies on the test bench according to the simulated working condition data.

[0158] S221, screen the electric drive assemblies at the normal distribution probability density equant points according to the normal distribution of the third simulated vibration peak value.

[0159] S231, obtain abnormal sound data of the electric drive assembly on the vehicle, wherein the abnormal sound data includes a subjective abnormal sound level, a vehicle noise value and a vehicle vibration peak value.

[0160] S232, establish a first coordinate system with the subjective abnormal sound level as the horizontal coordinate and the vehicle noise value as the vertical coordinate, establish a second coordinate system with the vehicle vibration peak value as the horizontal coordinate and the vehicle noise value as the vertical coordinate, establish a third coordinate system with the subjective abnormal sound level as the horizontal coordinate and the second simulated vibration peak value as the vertical coordinate, and establish a fourth coordinate system with the vehicle vibration peak value as the horizontal coordinate and the second simulated vibration peak value as the vertical coordinate.

[0161] S233, establish a regression line in each coordinate system according to the third simulated vibration peak value and the abnormal sound data of each screened electric drive assembly.

[0162] S241, determine the subjective abnormal sound level value according to the subjective feeling.

[0163] S242, determine the vehicle noise value corresponding to the intersection point in the first coordinate system according to the intersection point of the determined subjective abnormal sound level value and the regression line of the first coordinate system.

[0164] S243, determine the vehicle vibration peak value corresponding to the intersection point in the second coordinate system according to the intersection point of the vehicle noise value corresponding to the intersection point in the first coordinate system and the regression line of the second coordinate system.

[0165] S244, determine the vibration limit value according to the intersection point of the vehicle vibration peak value corresponding to the intersection point in the second coordinate system and the regression line of the fourth coordinate system.

[0166] S3, detect the electric drive assembly on the test bench according to the simulated working condition data to obtain a simulated vibration peak value of the electric drive assembly to be detected.

[0167] S4, compare the simulated vibration peak value with the vibration limit value to determine whether the electric drive assembly to be detected has abnormal sound.

[0168] The embodiment of the present application further provides an abnormal sound detection system of an electric drive assembly, comprising:

[0169] The first obtaining module is configured to obtain analog working condition data of the electric drive assembly with abnormal sound.

[0170] The second obtaining module is configured to obtain a vibration limit value of the electric drive assembly on the test bench.

[0171] The detection module is configured to detect the electric drive assembly on the test bench according to the analog working condition data, and obtain an analog vibration peak value.

[0172] The comparison module is configured to compare the analog vibration peak value with the vibration limit value, so as to determine whether the electric drive assembly to be detected has abnormal sound.

[0173] The embodiment of the present application further provides a computer, comprising:

[0174] The memory is configured to store executable instructions.

[0175] The processor is configured to execute the executable instructions to implement the steps of the abnormal sound detection method of the electric drive assembly.

[0176] The embodiment of the present application further provides a storage medium for storing computer executable instructions, and the executable instructions can be executed by the processor to implement the steps of the abnormal sound detection method of the electric drive assembly.

[0177] In the description of the present application, the description of the terms "some embodiments", "exemplary", and the like means that the specific features, structures, materials or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In the present application, the exemplary description of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, the different embodiments or examples described in the present application and the features of the different embodiments or examples can be combined by those skilled in the art without contradiction.

[0178] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting abnormal noise in an electric drive assembly, characterized in that, include: Obtain simulated operating condition data of the electric drive assembly exhibiting abnormal noise; Based on the simulated operating condition data, the third simulated vibration peak value of the multiple electric drive assemblies on the test bench is obtained; Based on the normal distribution of the third simulated vibration peak value, multiple electric drive assemblies are screened; Acquire abnormal noise data of the electric drive assembly in the vehicle, wherein the abnormal noise data includes subjective abnormal noise level, vehicle noise value and vehicle vibration peak value; A first coordinate system is established with the subjective abnormal noise level as the abscissa and the vehicle noise value as the ordinate; a second coordinate system is established with the vehicle vibration peak value as the abscissa and the vehicle noise value as the ordinate; a third coordinate system is established with the subjective abnormal noise level as the abscissa and the second simulated vibration peak value of the vibration data of the electric drive assembly in the abnormal noise state as the ordinate; and a fourth coordinate system is established with the vehicle vibration peak value as the abscissa and the second simulated vibration peak value as the ordinate. Based on the third simulated vibration peak value and the abnormal noise data corresponding to each of the selected electric drive assemblies, regression analysis is performed in each coordinate system to establish regression lines; The vibration limit is obtained based on the regression analysis. Based on the simulated operating condition data, the electric drive assembly to be tested on the test bench is tested to obtain the simulated vibration peak value of the electric drive assembly to be tested. The magnitude of the simulated vibration peak value is compared with the vibration limit value to determine whether there is any abnormal noise in the electric drive assembly to be tested.

2. The detection method as described in claim 1, characterized in that, The steps for obtaining simulated operating condition data of the electric drive assembly causing the abnormal noise include: Acquire vibration data from vibration measurement points of the electric drive assembly on the vehicle when it is in an abnormal noise state; The physical field parameters of the electric drive assembly that are strongly correlated with the vibration data are identified as vibration observation parameters. Using the vibration observation parameters as variables, multiple sets of first simulated vibration values ​​of the electric drive assembly on the test bench were obtained. The value of the vibration observation parameter corresponding to the largest first simulated vibration value is selected as the simulated operating condition data for judging abnormal noise from the electric drive assembly.

3. The detection method as described in claim 2, characterized in that, The step of acquiring vibration data from vibration measurement points of the electric drive assembly on the vehicle under abnormal noise conditions includes: Acquire overall operating condition data of the electric drive assembly in the vehicle under abnormal noise conditions; Obtain the time points of abnormal noise from the electric drive assembly; Based on the time point of the abnormal noise, the data corresponding to the peak value and the abnormal noise in the total operating condition data are obtained as the vibration data.

4. The detection method as described in claim 3, characterized in that, The step of obtaining the vibration data as the peak value corresponding to the abnormal noise in the total operating condition data based on the abnormal noise time point includes: Based on the time point of the abnormal noise, obtain the vibration values ​​of multiple vibration measuring points in the total operating condition data; Among the vibration values ​​at multiple vibration measurement points, the largest vibration value is taken as the vibration data.

5. The detection method as described in claim 2, characterized in that, The step of confirming the physical field parameters of the electric drive assembly that are strongly correlated with the vibration data as vibration observation parameters includes: The time point corresponding to the second simulated vibration peak value of the vibration data under abnormal noise conditions; The values ​​of multiple physical field parameters at the time points corresponding to the peak value of the second simulated vibration are sorted. At least one of the physical field parameters with a high value is selected as the vibration observation parameter.

6. The detection method as described in claim 2 or 5, characterized in that, The vibration observation parameters include the torque of the motor in the electric drive assembly and the differential rate of the differential.

7. The detection method as described in claim 1, characterized in that, The step of screening multiple electric drive assemblies based on the normal distribution of the third simulated vibration peak value includes: The electric drive assembly is selected from the points where the probability density of the normal distribution is equally divided.

8. The detection method as described in claim 1, characterized in that, The steps for obtaining the vibration limit based on the regression analysis include: The subjective abnormal noise level value is determined based on subjective perception. Based on the intersection of the determined subjective abnormal noise level value and the regression line of the first coordinate system, the vehicle noise value corresponding to the intersection point in the first coordinate system is determined; The peak value of vehicle vibration corresponding to the intersection point in the first coordinate system is determined based on the intersection point of the vehicle noise value corresponding to the intersection point in the second coordinate system and the regression line in the second coordinate system. The vibration limit is determined based on the intersection point of the vehicle vibration peak value corresponding to the intersection point in the second coordinate system and the regression line of the fourth coordinate system.

9. A detection system for abnormal noise in an electric drive assembly, used to implement the detection method according to any one of claims 1 to 8, characterized in that, include: The first acquisition module is used to acquire simulated operating condition data of the electric drive assembly that causes the abnormal noise; The second acquisition module is used to acquire the vibration limit of the electric drive assembly on the test bench; The detection module is used to detect the electric drive assembly to be tested on the test bench based on the simulated working condition data, and obtain the simulated vibration peak value; The comparison module is used to compare the simulated vibration peak value with the vibration limit value to determine whether the electric drive assembly to be tested has an abnormal noise problem.

10. A computer, characterized in that, include: Memory, used to store executable instructions; A processor for executing the executable instructions to implement the steps of the method for detecting abnormal noise from an electric drive assembly as described in any one of claims 1 to 8.

11. A storage medium, characterized in that, Used to store computer-executable instructions, which can be executed by a processor to implement the steps of the method for detecting abnormal noise in an electric drive assembly as described in any one of claims 1 to 8.

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