Electric drive assembly NVH simulation damping parameter prediction method and system

Abstract

The invention discloses an electric drive assembly NVH simulation damping parameter prediction method and system, and belongs to the field of automobile electric drive assembly NVH simulation calculation. The method comprises the following steps: carrying out modal test on a sub-part of the electric drive assembly to obtain a modal damping value of the sub-part; finite element modal simulation calculation is conducted on the sub-parts, and the modal effective mass ratio of the sub-parts is obtained to serve as the weight; and utilizing a weighted harmonic average algorithm to predict damping parameters of the electric drive assembly according to the modal damping values and the corresponding weights of the sub-parts. According to the method, the damping parameters of the new material electric drive assembly can be accurately predicted in the early stage of design, the simulation precision is improved, the development period is shortened, the test cost is saved, the influence of material change and structure change on the NVH performance can be evaluated, and an effective tool is provided for NVH optimization of the electric drive assembly.

Description

Technical Field

[0001] The present invention belongs to the field of NVH simulation calculation of automotive electric drive assemblies, and specifically relates to a method and system for predicting NVH simulation damping parameters of an electric drive assembly. Background Art

[0002] As a core sub-component of new energy electric vehicles, the electric drive assembly directly affects the power, energy consumption and overall performance of the vehicle. NVH (Noise, Vibration, Harshness) is one of the important indicators for measuring the design level of electric drive assemblies. Excellent NVH performance can improve users' evaluation of products, and the NVH performance is closely related to the driving experience. Due to the complexity of the electric drive assembly structure and the diversity of material properties, in the face of an electric drive assembly with new materials, traditional NVH simulation analysis methods must rely on test data for setting damping parameter values, assign damping parameter values according to modal test data, or directly use the damping value settings of the previous generation product, ignoring the influence of materials on damping.

[0003] Regarding the method for obtaining the NVH simulation damping parameter values of electric drives, the current mainstream methods are as follows:

[0004] For the iterative project of the previous generation product, where there is no change in the electric drive product material and no major change in the structure, the simulation damping parameter values can be kept the same as those of the previous generation product.

[0005] For a newly designed electric drive assembly, where there are significant changes in the product structure and materials, it is necessary to wait until all sub-components are sampled and the electric drive can work properly, then conduct a modal test on the entire assembly. After processing the test data, extract the modal damping data and input it into the simulation software for NVH simulation calculation to obtain the sound pressure distribution and noise level.

[0006] However, the existing technologies have the following disadvantages:

[0007] First, the damping parameters are affected by various factors such as material properties, structural design, environmental conditions, etc. For the iterative products within the company, directly using the damping setting values of the previous generation product for NVH calculation often makes it difficult to accurately predict the true electric drive level.

[0008] Second, for the new products of the company, especially the electric drive products with new materials, it is impossible to accurately predict the damping values of the electric drive assembly in the early stage of design. It is necessary to wait until the prototype is sampled to obtain the damping values. By then, the NVH level can already be evaluated through NVH tests, and the CAE simulation cannot play any role, and it is impossible to identify NVH problems in the early stage of design, increasing the design cycle.

[0009] Third, the modal test has high costs, long time consumption, and it is difficult to cover all working conditions, and it cannot accurately predict the NVH performance under actual working conditions. Summary of the Invention

[0010] Aiming at the problems existing in the background technology, the purpose of the present invention is to provide an NVH simulation damping parameter prediction method and system for an electric drive assembly, which can accurately predict the damping parameter values in the early stage of design, improve the simulation accuracy, shorten the development cycle, and save the test cost.

[0011] To achieve the above object, in the first aspect, the present invention provides an NVH simulation damping parameter prediction method for an electric drive assembly, including:

[0012] Conduct modal testing on the sub-components of the electric drive assembly to obtain the modal damping values of the sub-components;

[0013] Conduct finite element modal simulation calculation on the sub-components to obtain the modal effective mass ratio of the sub-components as the weight;

[0014] Use the weighted harmonic mean algorithm to predict the damping parameters of the electric drive assembly according to the modal damping values and corresponding weights of the sub-components.

[0015] In some optional embodiments of the present invention, the conducting modal testing on the sub-components of the electric drive assembly includes:

[0016] Conduct geometric modeling on the sub-components;

[0017] Define degrees of freedom, determine the measurement direction, and select the test points of the sub-components to be measured;

[0018] Suspend the sub-components to be measured in a free-free state, and paste vibration sensors at the model measurement points;

[0019] Conduct impact testing on the sub-components, and collect data through vibration sensors;

[0020] Conduct transfer function calculation on the test data to obtain the modal structure resonance frequency, modal vibration mode, and calculate the damping value;

[0021] Identify the authenticity of the modal calculation through the MAC value, and record the damping values corresponding to different frequencies.

[0022] Preferably, the conducting geometric modeling on the sub-components is required to be able to describe the contour of the sub-components.

[0023] Preferably, the defining degrees of freedom, determining the measurement direction, and selecting the test points of the sub-components to be measured are required such that the measurement direction and the measured points can reflect the main vibration modes.

[0024] Preferably, the conducting impact testing on the sub-components and collecting data through vibration sensors are required such that the test data has good coherence, no burrs and abnormal points.

[0025] Preferably, the authenticity calculated by the MAC value recognition mode requires the absence of false modes and spatial aliasing phenomena.

[0026] In some alternative embodiments of the present invention, the finite element modal simulation calculation of the sub-components includes:

[0027] Meshing the sub-components to be measured;

[0028] Assigning corresponding material properties;

[0029] Outputting the modal effective mass through finite element modal simulation calculation.

[0030] In some alternative embodiments of the present invention, the prediction of the damping parameter of the electric drive assembly based on the modal damping value and the corresponding weight of the sub-components by using the weighted harmonic mean algorithm includes:

[0031] Setting data points and corresponding frequencies in the calculation program;

[0032] Inputting the weight value according to the modal effective mass;

[0033] Inputting the main frequency value and the damping value at the main frequency value;

[0034] Predicting the damping parameter of the electric drive assembly according to the modal damping value and the corresponding weight of the sub-components by using the weighted harmonic mean algorithm.

[0035] In some alternative embodiments of the present invention, the method further includes: inputting the predicted damping parameter into an acoustic calculation software to perform NVH simulation calculation of the electric drive assembly.

[0036] Preferably, inputting the predicted damping parameter into an acoustic calculation software to perform NVH simulation calculation of the electric drive assembly includes:

[0037] Inputting the predicted damping value to participate in acoustic calculation during electromagnetic excitation and structure coupling calculation;

[0038] Setting vibration measurement points and microphone measurement points;

[0039] Calculating the sound pressure level at the measurement points and comparing it with the test data.

[0040] In a second aspect, the present invention provides an NVH simulation damping parameter prediction system for an electric drive assembly, including:

[0041] A modal test module for performing modal tests on the sub-components of the electric drive assembly to obtain the modal damping values of the sub-components;

[0042] A simulation calculation module, which is used to perform finite element modal simulation calculations on the sub-components and obtain the modal effective mass ratio of the sub-components as weights;

[0043] A damping parameter prediction module, which is used to predict the damping parameters of the electric drive assembly by using the weighted harmonic mean algorithm according to the modal damping values and corresponding weights of the sub-components.

[0044] In some alternative embodiments of the present invention, the modal test module includes:

[0045] A geometric modeling unit, which is used to perform geometric modeling on the sub-components and describe the profiles of the sub-components;

[0046] A test setup unit, which is used to define degrees of freedom, determine the measurement direction, and select test points of the sub-components to be measured;

[0047] A test execution unit, which is used to suspend the sub-components to be measured in a free-free state, paste vibration sensors at the model measurement points, perform hammer tests on the sub-components, and collect data through the vibration sensors;

[0048] A data processing unit, which is used to perform transfer function calculations on the test data, obtain the modal structure resonance frequencies, modal vibration modes, calculate the damping values, identify the authenticity of the modal calculations through the MAC value, and record the damping values corresponding to different frequencies.

[0049] In some alternative embodiments of the present invention, the simulation calculation module includes:

[0050] A mesh generation unit, which is used to perform mesh generation on the sub-components to be measured and assign corresponding material properties;

[0051] A finite element calculation unit, which is used to output the modal effective mass through finite element modal simulation calculations;

[0052] A weight calculation unit, which is used to use the ratio of the modal effective mass as the weighted weight.

[0053] In some alternative embodiments of the present invention, the damping parameter prediction module includes:

[0054] An input setup unit, which is used to set data points and corresponding frequencies in the calculation program; and input weight values according to the modal effective mass; and is used to input the main frequency value and the damping value at the main frequency value in the damping prediction program;

[0055] A parameter prediction unit, which is used to predict the damping parameters of the electric drive assembly by using the weighted harmonic mean algorithm according to the modal damping values and corresponding weights of the sub-components.

[0056] In some alternative embodiments of the present invention, the system further includes:

[0057] The NVH simulation module is used to apply the predicted damping parameters to the NVH simulation calculation of the electric drive assembly.

[0058] Preferably, the NVH simulation module includes:

[0059] A parameter input unit for inputting the predicted damping value to participate in the acoustic calculation during the electromagnetic excitation and structure coupling calculation;

[0060] A measuring point setting unit for setting vibration measuring points and microphone measuring points;

[0061] A result analysis unit for calculating the sound pressure level at the measuring point and comparing it with the test data.

[0062] In a third aspect, the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; the memory is used to store a computer program; when the processor executes the program stored in the memory, the method described in the first aspect is implemented.

[0063] In a fourth aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] 1. By performing weighted harmonic averaging on the damping values calculated through the testing of individual electric drive sub-components to obtain the predicted value of the assembly damping parameter, it is possible to accurately predict the impact of new material changes and structural changes on the damping value, thereby evaluating the change in the NVH level caused by material changes and structural changes. Compared with the traditional method of using empirical values or the unified values used in the previous generation of products, the accuracy of prediction is greatly improved.

[0066] 2. Through the prediction of the damping value of the electric drive assembly, it is possible to evaluate the NVH risk of the electric drive assembly by means of CAE simulation in the early stage of design, identify the main problems existing in the development stage, optimize the product for the identified problems, and then conduct prototype testing after meeting the customer standards, effectively shortening the development cycle.

[0067] 3. Through the prediction of the damping value of the electric drive assembly, the modal test of the electric drive assembly is omitted, saving man-hours and test costs, more accurately simulating the actual operating conditions of the electric drive, improving the accuracy of the simulation model, and making the acoustic and vibration result data have better correspondence with the measured data. Description of the Drawings

[0068] To more clearly illustrate the technical solutions of the disclosed embodiments of the present invention, the accompanying drawings of the embodiments will be briefly introduced below. These drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention.

[0069] Figure 1 It is a flowchart of the method for predicting the NVH simulation damping parameters of the electric drive assembly of the present invention;

[0070] Figure 2 It is a modal test model of the rear end cover of the electric drive of a certain platform described in the specific implementation manner;

[0071] Figure 3 It is a damping solution diagram during the modal test calculation of the rear end cover of the electric drive of a certain platform described in the specific implementation manner;

[0072] Figure 4 It is the NVH simulation damping parameter prediction packaging interface written using Python software described in the specific implementation manner;

[0073] Figure 5 It is a comparison diagram of simulation and test of a certain platform described in the specific implementation manner;

[0074] Figure 6 It is a schematic diagram of an electronic device provided by an embodiment of the present invention. Specific implementation manner

[0075] The technical solutions (including the preferred technical solutions) of the present invention will be further described in detail below by means of the accompanying drawings and by listing some optional embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0076] Embodiment 1

[0077] As Figure 1 shown, the method for predicting the NVH simulation damping parameters of the electric drive assembly provided by the present invention includes three main steps: data acquisition and processing, damping parameter processing, and NVH simulation and data processing.

[0078] I. Data acquisition and processing

[0079] Using data acquisition and analysis software, such as Artemis software, conduct modal tests on some sub-components of the electric drive system and process the data to calculate the modal damping value. Specifically, it includes the following steps:

[0080] Step 1: Conduct geometric modeling on the sub-components, requiring the ability to describe the outline of the sub-components.

[0081] In this step, it is necessary to establish a geometric model for the sub-components to be tested (such as the housing, end cover, bracket, etc.). This model should be able to accurately reflect the external dimensions and characteristics of the sub-components, so as to facilitate the selection of subsequent test points and the analysis of modal vibration modes. Geometric modeling can be completed using CAD software (such as CATIA, SolidWorks, etc.), or directly in Artemis software.

[0082] Step 2: Define the degrees of freedom, determine the measurement directions, and select the test points of the sub-components to be measured, requiring that the measurement directions and the measured points can reflect the main vibration modes.

[0083] In this step, it is necessary to clarify the degrees of freedom of measurement (generally the three directions of XYZ), select appropriate measurement directions (usually select the direction with the minimum structural stiffness as the main measurement direction), and select suitable test points on the sub-components. The selection of test points should consider the symmetry of the structure, the stiffness distribution, and the expected main vibration mode form, ensuring that the selected measurement points can reflect the main vibration characteristics of the sub-components. Usually, the number and density of test points should be determined according to the complexity and size of the sub-components. Generally speaking, more complex structures require more test points.

[0084] Step 3: Suspend the sub-components to be measured in a free-free state, paste vibration sensors at the model measurement points, and connect the test equipment, requiring that the range and sensitivity of the test sensors can meet the test requirements.

[0085] In this step, the sub-components need to be in a free-free state (i.e., without fixed constraints), usually achieved by using soft elastic ropes or sponge supports for suspension. Then, paste vibration sensors (such as acceleration sensors) at the pre-determined test points, and connect the sensors to the data acquisition system. The selection of sensors should be determined according to the expected frequency range and vibration amplitude, ensuring that their range and sensitivity meet the test requirements. Generally speaking, the test frequency range is 0 - 6400Hz, and the resolution is 1Hz or higher.

[0086] The free-free state suspension means that during modal testing, the component to be measured is suspended so that it is in a free state in space. Specifically, it means that during the suspension process of the component, it will not be subjected to any additional binding forces or reaction forces, thus avoiding the interference of these external forces on the test results.

[0087] To achieve the free-free state, some special suspension devices are usually used, such as elastic ropes, suspension devices, etc. The design purpose of these devices is to enable the component to vibrate freely during the suspension process without being restricted by the suspension device itself. For example, using an elastic rope to suspend the component, the elastic characteristics of the elastic rope can reduce the restriction on the vibration of the component.

[0088] Step Four: Conduct a hammering test on the sub-components, collect data through vibration sensors, and require that the test data has good coherence, no burrs and abnormal points.

[0089] In this step, use an impact hammer (with a hammer head of moderate hardness) to hammer the sub-components to excite their vibration, and at the same time collect vibration response data through vibration sensors. The hammering should be carried out at each predetermined measuring point, and at least 3 - 5 hammerings should be performed at each point to obtain the average value and reduce random errors. During the test, attention should be paid to the coherence of the data. Generally, it is required that the coherence coefficient is greater than 0.9, the response curve should be smooth without burrs, and there should be no obvious abnormal points. If there are bad data, the hammering test should be carried out again.

[0090] Step Five: Conduct transfer function calculation on the test data to obtain the modal structure resonance frequency, modal shape, and obtain the damping by the relative relationship of the amplitude positions of each point at a specific modal frequency.

[0091] In this step, use Artemis software to perform frequency response function (FRF) analysis on the collected hammering test data, and extract the natural frequency, modal shape, and damping ratio of the sub-components. The damping ratio is usually extracted from the frequency response function by the half-power method or curve fitting method. For each identified mode, its frequency, mode shape, and corresponding damping ratio need to be recorded.

[0092] Convert the time-domain signal to the frequency-domain signal through fast Fourier transform (FFT), and calculate the frequency response function (FRF) between the input excitation (hammering force) and the output response (vibration acceleration). The FRF describes the input-output relationship of the system at different frequencies. Using the FRF data, identify the modal structure resonance frequency, modal shape, and damping ratio through modal analysis algorithms (such as the least squares complex frequency domain method, etc.).

[0093] At a specific modal frequency, analyze the relative relationship of the amplitudes of each test point. By observing the characteristics of vibration decay, the damping value can be calculated. According to the identified modal parameters and the relative relationship of amplitudes, calculate the damping ratio for each mode.

[0094] Step Six: Identify the authenticity of the modal calculation through the MAC value, and record the corresponding damping values at different frequencies, and require that there are no false modes and spatial aliasing phenomena.

[0095] In this step, the reliability of the modal analysis results is verified by calculating the Modal Assurance Criterion (MAC) value. A MAC value close to 1 indicates good modal identification, and close to 0 indicates good orthogonality between modes. It is necessary to check for the existence of spurious modes (i.e., mathematical solutions that do not represent actual physical vibrations) or spatial aliasing phenomena (where high-order modes cannot be correctly identified due to insufficient measurement points) to ensure the accuracy of the modal analysis results. Finally, record the damping values corresponding to different frequencies as the basic data for subsequent prediction of the damping value of the electric drive assembly.

[0096] II. Damping Parameter Processing

[0097] Using Python software, write a damping prediction program according to the weighted harmonic mean algorithm. The true modal damping values calculated from the modal tests of sub-components are input into the damping prediction device to obtain the simulated damping prediction values of the electric drive assembly. The specific steps are as follows:

[0098] Step 1: Mesh the component to be measured. Through finite element modal simulation calculation, output effmass during the calculation, and use the ratio of the modal effective mass as the weight for weighted calculation.

[0099] In this step, it is necessary to use finite element software (such as ANSYS, Abaqus, etc.) to establish a finite element model of the sub-component to be measured and perform reasonable meshing. The mesh size should fully consider the balance between calculation accuracy and calculation efficiency. Generally speaking, for complex structures, mesh refinement should be carried out in key areas. Then, perform modal analysis calculation and output the effective mass (effective mass, abbreviated as effmass) of each order of mode to determine the contribution degree of each mode to the overall vibration response. The ratio of the modal effective mass will be used as the weight for subsequent weighted harmonic mean calculation.

[0100] Step 2: Use the weighted harmonic mean calculation formula in Python. The first row of the list contains 100 data points, the second row contains the frequencies corresponding to the data points in the first row, and the third row of weight values is input according to the modal effective mass.

[0101] In this step, use the Python programming language to implement the weighted harmonic mean calculation. The weighted harmonic mean is a special method for calculating the average value, especially suitable for processing ratio-type data such as damping ratios. In the Python program, prepare three lists or arrays: the first contains damping value data points (usually about 100 points, covering the frequency range of interest); the second contains the frequencies corresponding to each damping value; the third contains the weight of each data point (based on the previously calculated modal effective mass). Then, use the weighted harmonic mean algorithm to calculate the comprehensive damping value.

[0102] Step 3: Use the tkinter library in Python to create a window and buttons for interface encapsulation, which is beneficial for damping value prediction in all new projects and makes the operation more convenient.

[0103] In this step, to improve the usability of the damping prediction tool, the tkinter library of Python is used to develop a graphical user interface (GUI). The interface should include basic elements such as a data input area, a calculation button, a result display area, as well as necessary labels and prompt messages. The interface design should be simple and clear for engineers to use. By encapsulating it into a GUI application, the damping parameter prediction tool can be conveniently applied to various new projects.

[0104] Step 4: Input the main frequency value and the damping value at the main frequency value, submit the calculation to obtain the simulated damping prediction value of the electric drive assembly.

[0105] In this step, the user inputs the damping value measured by the sub-component at the main frequency through the GUI interface, clicks the calculation button, and the program automatically performs a weighted harmonic average calculation to obtain the predicted damping value of the electric drive assembly. The calculation result should be displayed on the interface and can be exported as a text file or directly copied for use in the simulation software.

[0106] III. NVH Simulation and Data Processing

[0107] By calculating the damping values of the sub-components, the damping value of the electric drive assembly is obtained and input into the acoustic calculation software to calculate the sound pressure level and sound power of the electric drive assembly. The specific steps are as follows:

[0108] Step 1: Input the predicted damping value during the electromagnetic excitation and structure coupling calculation to participate in the acoustic calculation, and set vibration measurement points and microphone measurement points.

[0109] In this step, input the damping parameter values predicted previously into the NVH simulation model of the electric drive assembly. First, perform electromagnetic excitation calculation to obtain the electromagnetic excitation force, then use the excitation force as the input for structural vibration analysis, and at the same time set the previously predicted damping parameters. After the structural vibration analysis, set appropriate vibration measurement points (for verifying the structural vibration response) and microphone measurement points (for evaluating the sound pressure level). The positions of these measurement points should be consistent with the actual test positions for subsequent comparison and verification.

[0110] Step 2: Calculate the sound pressure level at the measurement point and compare it with the test data.

[0111] In this step, acoustic calculations are performed based on the structural vibration response to obtain the sound pressure levels at the positions of each microphone measurement point. Then, the calculated sound pressure levels are compared and analyzed with the actual test data to evaluate the accuracy of the predicted damping parameters. By comparing the magnitudes, spectral characteristics, harmonic components, etc. of the sound pressure levels, it can be determined whether the predicted damping parameters are reasonable, and necessary adjustments and optimizations can be made to the prediction method.

[0112] Example 2

[0113] In this example, taking the electric drive assembly of a certain platform as an example, the implementation process of the method of the present invention will be described in detail.

[0114] Data acquisition and processing steps:

[0115] First, select the rear end cover of the electric drive assembly of a certain platform as the test object. As Figure 2 shown, geometric modeling is performed on the rear end cover plate, and the modeling requirements are to accurately describe the contour of the rear end cover plate.

[0116] Then, define the output degrees of freedom in the X, Y, and Z directions, determine the measurement direction as the Y direction, and select a total of 16 test points on the rear end cover plate. The selection of the measurement direction and test points needs to be able to reflect the main vibration modes of the rear end cover plate.

[0117] Next, suspend the rear end cover plate in a free-free state using rubber elastic ropes, and paste vibration sensors at the model measurement points and connect the test equipment. The measurement range of the test sensor is selected as 0 - 6400 Hz, the resolution is 1 Hz, and a force exponential window is added during the test. Here, the free-free state means that the rear end cover plate has no fixed constraints, simulating the actual working state.

[0118] Then, use a rigid hammer to perform a hammering test on the rear end cover plate, and collect data through the vibration sensors. During the test process, it is required that the coherence curve is greater than 0.9 and the response curve has no burrs or abnormalities to ensure the effectiveness and accuracy of the test data.

[0119] Next, perform transfer function calculations on the test data to obtain the structural resonance frequencies and modal vibration modes of the rear end cover plate. As Figure 3 shown, damping is obtained through the relative relationship of the amplitude positions of each point at a specific modal frequency. This step is the key step to obtain the actual damping value of the sub-component.

[0120] Finally, identify the authenticity of the modal calculation through the MAC value, and record the corresponding damping values at different frequencies. The MAC value is an index of modal similarity, and the authenticity of the mode is judged by calculating the similarity of the modal vibration mode vectors. It is required that there are no false modes and spatial aliasing phenomena to ensure the accuracy of the obtained damping values.

[0121] Damping parameter processing steps:

[0122] First, mesh the tested rear end cover plate and assign it the material properties of magnesium alloy, which are provided by the supplier. The modal solution frequency is 0 - 6400 Hz, and effmass is output during the calculation. Through finite element modal simulation calculation, the modal frequencies obtained from the simulation are corresponded one by one with the test frequencies, and the ratio of the modal effective mass output from the simulation calculation is used as the weight for weighted average during the prediction of the total assembly damping and input.

[0123] Then, use the weighted harmonic average calculation formula in Python. The weighted harmonic average is a special average method applicable to processing rate - type data. The first row of the list contains 100 data points, the second row contains the frequencies corresponding to the data points in the first row, and the weight values in the third row are input according to the modal effective mass.

[0124] Next, as Figure 4 shown, use the tkinter library in python to create a window and buttons for interface encapsulation, so as to facilitate the prediction of damping values for all new projects and make the operation more convenient. The interface design is simple and clear, facilitating engineers to input parameters and obtain prediction results.

[0125] Finally, input the main frequency values corresponding to the simulation and the damping values at each main frequency value in the interface of the damping prediction device, click the "calculate" button, and submit to calculate the simulated damping prediction value of the electric drive assembly.

[0126] NVH simulation and data processing steps:

[0127] First, input the damping prediction value of the electric drive assembly calculated in the previous step into the acoustic calculation software for electromagnetic excitation and structural coupling calculation, and set the vibration measurement points and microphone measurement points. In this embodiment, a semi - anechoic test is simulated, and microphone detection points are set at 1 m above, to the left, to the right, in front, and behind.

[0128] Then, calculate the sound pressure level at the detection points and compare it with the actual test data for verification. As Figure 5 shown, using the damping value obtained by the prediction method of the present invention for simulation calculation, the results are more fitting to the test data, and both the amplitude and the trend are consistent with the test.

[0129] To further verify the effectiveness of the method of the present invention, a comparative test was also carried out. Using the traditional method based on empirical damping values for simulation calculation, the results show obvious differences from the test data, proving the superiority of the method of the present invention.

[0130] Embodiment 3

[0131] The present invention provides an NVH simulation damping parameter prediction system for an electric drive assembly, including:

[0132] A modal test module is used to conduct modal tests on the sub-components of an electric drive assembly to obtain the modal damping values of the sub-components. The modal test module includes:

[0133] A geometric modeling unit is used to perform geometric modeling on the sub-components and describe the profiles of the sub-components;

[0134] A test setting unit is used to define degrees of freedom, determine the measurement direction, and select test points for the sub-components to be measured;

[0135] A test execution unit is used to suspend the sub-components to be measured in a free-free state, paste vibration sensors at the model measurement points, conduct impact tests on the sub-components, and collect data through the vibration sensors;

[0136] A data processing unit is used to perform transfer function calculations on the test data, obtain the modal structure resonance frequencies, modal vibration modes, calculate the damping values, identify the authenticity of the modal calculations through MAC values, and record the damping values corresponding to different frequencies.

[0137] A simulation calculation module is used to perform finite element modal simulation calculations on the sub-components to obtain the modal effective mass ratio of the sub-components as the weight. The simulation calculation module includes:

[0138] A mesh generation unit is used to generate meshes for the sub-components to be measured and assign corresponding material properties;

[0139] A finite element calculation unit is used to output the modal effective mass through finite element modal simulation calculations;

[0140] A weight calculation unit is used to use the ratio of the modal effective mass as the weight for weighting.

[0141] A damping parameter prediction module is used to predict the damping parameters of the electric drive assembly by using the weighted harmonic mean algorithm based on the modal damping values and corresponding weights of the sub-components. The damping parameter prediction module includes:

[0142] An input setting unit is used to set data points and corresponding frequencies in the calculation program; and input weight values according to the modal effective mass; and input the main frequency values and the damping values at the main frequency values in the damping prediction program;

[0143] A parameter prediction unit is used to predict the damping parameters of the electric drive assembly by using the weighted harmonic mean algorithm based on the modal damping values and corresponding weights of the sub-components.

[0144] Example 4

[0145] Based on Embodiment 3, the NVH simulation damping parameter prediction system for the electric drive assembly provided in this embodiment further includes: an NVH simulation module, which is used to apply the predicted damping parameters to the NVH simulation calculation of the electric drive assembly. The NVH simulation module includes:

[0146] A parameter input unit, which is used to input the predicted damping value during the electromagnetic excitation and structure coupling calculation to participate in the acoustic calculation;

[0147] A measuring point setting unit, which is used to set vibration measuring points and microphone measuring points;

[0148] A result analysis unit, which is used to calculate the sound pressure level at the measuring points and compare it with the test data.

[0149] Embodiment 5

[0150] The present invention provides an electronic device, which includes a processor 1, a communication interface 2, a memory 3, and a communication bus 4. Among them, the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4; the memory 4 is used to store a computer program; when the processor 1 executes the program stored on the memory 3, it realizes the electric drive assembly NVH simulation damping parameter prediction method described in Embodiment 1.

[0151] The processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0152] The memory may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0153] The memory can be a volatile memory, such as a random-access memory (RAM); the memory can also be a non-volatile memory, such as a read-only memory, a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), or the memory is any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory can be a combination of the above memories.

[0154] Embodiment 6

[0155] The present invention provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, it is the NVH simulation damping parameter prediction method of the electric drive assembly as described in Embodiment 1.

[0156] The present invention can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a server, or a data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, etc. that includes one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state disk (SSD)).

[0157] It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present invention and does not limit the present invention. Any modifications, combinations, substitutions, improvements, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for predicting the NVH simulation damping parameters of an electric drive assembly, characterized in that Including: Performing modal tests on the sub-components of the electric drive assembly to obtain the modal damping values of the sub-components; Performing finite element modal simulation calculations on the sub-components to obtain the modal effective mass ratio of the sub-components as weights; Using the weighted harmonic mean algorithm, based on the modal damping values and corresponding weights of the sub-components, to predict the damping parameters of the electric drive assembly.

2. The NVH simulation damping parameter prediction method for the electric drive assembly according to claim 1, wherein The performing modal tests on the sub-components of the electric drive assembly includes: Performing geometric modeling on the sub-components; Defining degrees of freedom, determining the measurement directions, and selecting the test points of the sub-components to be measured; Suspending the sub-components to be measured in a free-free state and pasting vibration sensors at the model measurement points; Performing impact tests on the sub-components and collecting data through vibration sensors; Performing transfer function calculations on the test data to obtain the modal structure resonance frequencies, modal vibration modes, and calculating the damping values; Identifying the authenticity of the modal calculations through MAC values and recording the damping values corresponding to different frequencies.

3. The method for predicting the NVH simulation damping parameters of the electric drive assembly according to claim 2, wherein: The performing geometric modeling on the sub-components requires being able to describe the contour of the sub-components; The defining degrees of freedom, determining the measurement directions, and selecting the test points of the sub-components to be measured requires that the measurement directions and the measured points can reflect the main vibration modes; The performing impact tests on the sub-components and collecting data through vibration sensors requires that the test data has good coherence, no burrs and abnormal points; The identifying the authenticity of the modal calculations through MAC values requires that there are no false modes and spatial aliasing phenomena.

4. The NVH simulation damping parameter prediction method for the electric drive assembly according to claim 1, wherein, The performing finite element modal simulation calculations on the sub-components includes: Performing mesh division on the sub-components to be measured; Assigning corresponding material properties; Outputting the modal effective mass through finite element modal simulation calculations.

5. The NVH simulation damping parameter prediction method for the electric drive assembly according to claim 1, wherein The using the weighted harmonic mean algorithm, based on the modal damping values and corresponding weights of the sub-components, to predict the damping parameters of the electric drive assembly includes: Setting data points and corresponding frequencies in the calculation program; Inputting the weight values according to the modal effective mass; Inputting the main frequency values and the damping values at the main frequency values; Using the weighted harmonic mean algorithm, based on the modal damping values and corresponding weights of the sub-components, to predict the damping parameters of the electric drive assembly.

6. The NVH simulation damping parameter prediction method for an electric drive assembly according to claim 1, wherein The method further includes: inputting the predicted damping parameters into the acoustic calculation software to perform NVH simulation calculations on the electric drive assembly; the inputting the predicted damping parameters into the acoustic calculation software to perform NVH simulation calculations on the electric drive assembly includes: Inputting the predicted damping values to participate in acoustic calculations during electromagnetic excitation and structure coupling calculations; Setting vibration measurement points and microphone measurement points; Calculating the sound pressure levels at the measurement points and comparing with the test data.

7. An NVH simulation damping parameter prediction system for an electric drive assembly, characterized in that, Including: A modal test module, used for performing modal tests on the sub-components of the electric drive assembly to obtain the modal damping values of the sub-components; A simulation calculation module, used for performing finite element modal simulation calculations on the sub-components to obtain the modal effective mass ratio of the sub-components as weights; A damping parameter prediction module, used for using the weighted harmonic mean algorithm, based on the modal damping values and corresponding weights of the sub-components, to predict the damping parameters of the electric drive assembly.

8. The NVH simulation damping parameter prediction system for an electric drive assembly according to claim 7, wherein The modal test module includes: A geometric modeling unit for geometrically modeling sub-components and describing the profiles of the sub-components; A test setup unit for defining degrees of freedom, determining the measurement directions, and selecting test points of the sub-components to be measured; A test execution unit for suspending the sub-components to be measured in a free-free state, pasting vibration sensors at the model measurement points, performing impact tests on the sub-components, and collecting data through the vibration sensors; A data processing unit for performing transfer function calculations on the test data, obtaining the resonance frequencies and modal shapes of the modal structure, calculating the damping values, and identifying the authenticity of the modal calculations through the MAC value, and recording the damping values corresponding to different frequencies.

9. The NVH simulation damping parameter prediction system for an electric drive assembly according to claim 7, wherein The simulation calculation module includes: A mesh generation unit for meshing the sub-components to be measured and assigning corresponding material properties; A finite element calculation unit for outputting the modal effective mass through finite element modal simulation calculations; A weight calculation unit for using the ratio of the modal effective masses as the weighting weights.

10. The NVH simulation damping parameter prediction system for an electric drive assembly according to claim 7, wherein The damping parameter prediction module includes: An input setup unit for setting data points and corresponding frequencies in the calculation program; and inputting weight values according to the modal effective masses; for inputting the main frequency values and the damping values at the main frequency values in the damping prediction program; A parameter prediction unit for predicting the damping parameters of the electric drive assembly according to the modal damping values and corresponding weights of the sub-components through a weighted harmonic mean algorithm.

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