Method and device for predicting noise of in-vehicle compressor and electronic equipment

Abstract

The invention relates to the technical field of noise prediction, and discloses a method and device for predicting noise of an in-vehicle compressor and electronic equipment, and the method comprises the steps: obtaining compressor vibration force and compressor noise data of a to-be-tested electric compressor at different frequencies; according to the vibration force of the compressor and the inherent frequency of the vibration isolation system, the system response force of the vibration isolation system under different frequencies is determined; according to the system attenuation coefficient and the system response force of the vibration isolation system, vehicle body vibration force transmitted to the vehicle body under different frequencies is determined; and according to the compressor noise data and the vehicle body vibration force, the sound pressure level of the vehicle interior compressor noise at different frequencies is determined. According to the method, the compressor vibration force and the compressor noise data of the electric compressor under different frequencies are obtained, the inherent frequency and the system attenuation coefficient of the vibration isolation system are combined, a prediction model based on actual test data is constructed, and the sound pressure level of the noise of the compressor in the vehicle can be predicted in advance in the research and development stage of the electric vehicle.

Description

Technical Field

[0001] This application relates to the field of noise prediction technology, such as a method, apparatus, and electronic device for predicting in-vehicle compressor noise. Background Technology

[0002] With the development of the new energy vehicle industry, electric compressors are finding increasingly wider applications. Electric vehicles require electric compressors to achieve overall vehicle thermal management control. Unlike traditional internal combustion engine power systems where the engine drives the compressor, the electric compressor in an electric vehicle is a relatively independent source of vibration and noise. In-vehicle noise related to electric compressors has become a major point of user complaint. Based on the different transmission paths of vibration and noise energy, in-vehicle electric compressor noise can be divided into two main categories: airborne noise and structural noise. Airborne noise is the noise radiated by the electric compressor itself, which is attenuated by the vehicle's sound insulation components and then transmitted to the interior. Structural noise, on the other hand, is the noise generated by the vibration force produced by the electric compressor during operation, which is attenuated by vibration isolation components such as rubber bushings and then transmitted to the vehicle body, where it is generated by the combined action of the vehicle body panels and the interior acoustic cavity. Typically, the noise of an electric compressor mainly comes from the mechanical friction and vibration of the rotor and turntable driven by the drive motor. Its corresponding operating noise frequency band is the low-frequency range within 200Hz. The control of in-vehicle noise within this frequency band is closely related to the selection of the compressor unit, the design of vibration isolation components, and the target setting of the vehicle body structural sound transfer function. Therefore, by predicting the noise of the in-vehicle compressor, the appropriate electric compressor model, reasonable rubber vibration isolation components, and precise sound transfer function target of the vehicle body structure can be selected in advance during the design stage of electric vehicles, thereby reducing both product development cycle and cost.

[0003] In related technologies, a method for predicting compressor noise is disclosed, specifically including: constructing an acoustic boundary element model of the compressor casing based on a three-dimensional geometric model of the compressor casing; discretizing the geometric model into boundary element elements; identifying the main noise sources inside and outside the compressor; loading the identified noise sources as boundary conditions into the acoustic boundary element model; setting acoustic boundary conditions according to the actual working environment and material properties of the compressor casing; solving the acoustic boundary element model; calculating the acoustic response of the compressor casing surface; and predicting the noise of the compressor casing based on the calculated acoustic response of the compressor casing surface.

[0004] In the process of implementing the embodiments of this disclosure, at least the following problems were found in the related art: Related technologies predict noise levels by identifying the main noise sources of the compressor unit, but it is difficult to predict the in-vehicle compressor noise level after the compressor is installed in an electric vehicle.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0007] This disclosure provides a method, apparatus, and electronic device for predicting in-vehicle compressor noise, in order to predict in-vehicle compressor noise levels during the development phase of electric vehicles.

[0008] In some embodiments, a method for predicting in-vehicle compressor noise includes: acquiring compressor vibration force and compressor noise data of the electric compressor under test at different frequencies; determining the system response force of the vibration isolation system at different frequencies based on the compressor vibration force and the natural frequency of the vibration isolation system; wherein the vibration isolation system is constructed based on the electric compressor under test and preset vibration isolation element parameters; determining the vehicle body vibration force transmitted to the vehicle body at different frequencies based on the system attenuation coefficient and system response force of the vibration isolation system; and determining the sound pressure level of the in-vehicle compressor noise at different frequencies based on the compressor noise data and the vehicle body vibration force.

[0009] Optionally, the vibration force and noise data of the electric compressor under test at different frequencies are acquired, including: in an anechoic laboratory environment, controlling the electric compressor under test to rotate at different frequencies, acquiring the excitation force of multiple mounting points of the electric compressor under test at different frequencies, and the noise data of the compressor at a preset distance from the electric compressor under test; wherein the electric compressor under test is rigidly connected to multiple force sensors through multiple mounting points; based on the excitation force of multiple mounting points at different frequencies, the resultant force of multiple excitation forces in the x, y, and z directions is determined to obtain the vibration force of the compressor at different frequencies.

[0010] Optionally, the method for predicting in-vehicle compressor noise further includes filtering out data with frequencies higher than a preset frequency from the compressor noise data after obtaining the compressor noise data.

[0011] Optionally, the natural frequency of the vibration isolation system is determined as follows: the physical inertia of the electric compressor under test is obtained, and the mass matrix is ​​determined based on the physical inertia and total mass of the electric compressor under test; the system stiffness matrix is ​​determined based on the parallel stiffness, torsional stiffness, and co-stiffness in the parameters of the vibration isolation element; and the natural frequency of the vibration isolation system is determined based on the mass matrix and the system stiffness matrix.

[0012] Optionally, the system response force of the vibration isolation system at different frequencies is determined based on the compressor vibration force and the natural frequency of the vibration isolation system, including: determining the amplitude response coefficient of the vibration isolation system at different frequencies based on the vibration frequency and natural frequency of the vibration isolation system; and determining the system response force of the vibration isolation system at different frequencies based on the compressor vibration force and the amplitude response coefficient.

[0013] Alternatively, the amplitude response coefficient can be determined according to the following formula:

[0014] Among them, T M ζ is the amplitude response coefficient, λ is the ratio of the vibration frequency to the natural frequency of the vibration isolation system, and ζ is the system damping ratio.

[0015] Optionally, the system attenuation coefficient of the vibration isolation system can be determined as follows: determine the vibration isolation amount at different frequencies; and determine the system attenuation coefficient of the vibration isolation system at different frequencies based on the vibration isolation amount.

[0016] Alternatively, the sound pressure level of the in-vehicle compressor noise can be determined according to the following formula:

[0017] Among them, y k The sound pressure level (NTF) of the in-vehicle compressor noise. ik For structural acoustic transfer function, NTF jk Let F be the airborne sound transfer function. Ri For vehicle body vibration force, P j Here are the compressor noise data, where n is the number of structural sound transmission paths and m is the number of airborne sound transmission paths.

[0018] In some embodiments, the apparatus for predicting in-vehicle compressor noise includes a processor and a memory storing program instructions, the processor being configured to execute the method for predicting in-vehicle compressor noise as described above when the program instructions are executed.

[0019] In some embodiments, the electronic device includes: an electronic device body; and the means for predicting in-vehicle compressor noise, as described above, is mounted on the electronic device body.

[0020] The method, apparatus, and electronic device for predicting in-vehicle compressor noise provided in this disclosure can achieve the following technical effects: In this embodiment, by acquiring compressor vibration force and noise data of the electric compressor at different frequencies, and combining this with the natural frequency and system attenuation coefficient of the vibration isolation system, a predictive model based on actual test data is constructed. This model can predict the sound pressure level of the compressor noise inside the vehicle during the R&D stage of electric vehicles, thereby avoiding design modifications and cost increases caused by noise problems later. Furthermore, by predicting the noise of the compressor inside the vehicle, the performance of different electric compressor models and vibration isolation components can be quickly evaluated based on different vibration isolation component parameters and system design goals. This allows for the selection of the most suitable electric compressor model and vibration isolation components during the design stage, ensuring that their noise performance in actual applications meets expectations, and thus optimizing the NVH (Noise, Vibration, Harshness) performance of the entire vehicle.

[0021] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0022] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein: Figure 1 This is a schematic diagram of a method for predicting in-vehicle compressor noise provided in an embodiment of this disclosure; Figure 2 This is a schematic diagram of another method for predicting in-vehicle compressor noise provided in an embodiment of this disclosure; Figure 3 This is a schematic diagram of a compressor bench test provided in an embodiment of this disclosure; Figure 4 This is a vibration force response spectrum diagram showing the change of vibration force amplitude with frequency, provided in an embodiment of this disclosure; Figure 5 This is a vehicle noise spectrum diagram showing the sound pressure level of an in-vehicle compressor as a function of frequency, provided in an embodiment of this disclosure. Figure 6 This is a schematic diagram of a device for predicting in-vehicle compressor noise provided in an embodiment of this disclosure. Detailed Implementation

[0023] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0024] The terms "first," "second," etc., used in the technical solutions described in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0025] Unless otherwise stated, the term "multiple" means two or more.

[0026] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0027] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0028] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0029] Combination Figure 1 As shown, this disclosure provides a method for predicting in-vehicle compressor noise. The execution subject of this method may be a processor, and the method includes: S101, acquire compressor vibration force and compressor noise data of the electric compressor under test at different frequencies.

[0030] S102, based on the compressor vibration force and the natural frequency of the vibration isolation system, determine the system response force of the vibration isolation system at different frequencies.

[0031] The vibration isolation system is constructed based on the parameters of the electric compressor under test and the preset vibration isolation components.

[0032] S103, based on the system attenuation coefficient and system response force of the vibration isolation system, determine the body vibration force transmitted to the vehicle body at different frequencies.

[0033] S104, based on compressor noise data and vehicle body vibration force, determine the sound pressure level of the in-vehicle compressor noise at different frequencies.

[0034] In this embodiment, by acquiring compressor vibration force and noise data of the electric compressor at different frequencies, and combining this with the natural frequency and system attenuation coefficient of the vibration isolation system, a predictive model based on actual test data is constructed. This model can predict the sound pressure level of the in-vehicle compressor noise in advance during the development stage of electric vehicles, thereby avoiding design modifications and cost increases due to noise issues later on. Furthermore, by predicting the in-vehicle compressor noise, the performance of different electric compressor models and vibration isolation components can be quickly evaluated based on different vibration isolation component parameters and system design goals. This allows for the selection of the most suitable electric compressor model and vibration isolation components during the design phase, ensuring that their noise performance in actual applications meets expectations, and thus optimizing the overall NVH performance of the vehicle.

[0035] Optionally, the vibration force and noise data of the electric compressor under test at different frequencies are acquired, including: in an anechoic laboratory environment, controlling the electric compressor under test to rotate at different frequencies, acquiring the excitation force of multiple mounting points of the electric compressor under test at different frequencies, and the noise data of the compressor at a preset distance from the electric compressor under test; wherein the electric compressor under test is rigidly connected to multiple force sensors through multiple mounting points; based on the excitation force of multiple mounting points at different frequencies, the resultant force of multiple excitation forces in the x, y, and z directions is determined to obtain the vibration force of the compressor at different frequencies.

[0036] In this embodiment, an electric compressor was selected for bench testing. By precisely controlling the compressor's rotational speed and acquiring vibration and noise data at different frequencies, the accuracy and reliability of the test data were ensured, providing high-quality foundational data for subsequent noise prediction and analysis. Force sensors were placed at multiple mounting points and rigidly connected to the electric compressor, allowing the acquisition of excitation forces at each point at different frequencies. Furthermore, by calculating the resultant force of these excitation forces in the x, y, and z directions, the compressor vibration force at different frequencies was obtained, comprehensively reflecting the vibration characteristics of the electric compressor in actual operation and avoiding errors and incompleteness caused by single-point measurements. Microphones were placed at a predetermined distance from the electric compressor to accurately measure its noise data at different frequencies, effectively eliminating interference from other noise sources and ensuring that the collected noise data truly reflects the noise characteristics of the electric compressor.

[0037] Optionally, the preset distance is 30cm.

[0038] Optionally, the method for predicting in-vehicle compressor noise further includes filtering out data with frequencies higher than a preset frequency from the compressor noise data after obtaining the compressor noise data.

[0039] In this embodiment, by filtering noise data above a preset frequency, noise components that do not belong to the main operating frequency band of the electric compressor can be removed, which helps to reduce interference from irrelevant noise and allows subsequent analysis to focus more on the actual noise characteristics generated by the electric compressor, thereby improving the purity of the data and the accuracy of the analysis.

[0040] Optionally, the preset frequency is 100Hz.

[0041] Optionally, the natural frequency of the vibration isolation system is determined as follows: the physical inertia of the electric compressor under test is obtained, and the mass matrix is ​​determined based on the physical inertia and total mass of the electric compressor under test; the system stiffness matrix is ​​determined based on the parallel stiffness, torsional stiffness, and co-stiffness in the parameters of the vibration isolation element; and the natural frequency of the vibration isolation system is determined based on the mass matrix and the system stiffness matrix.

[0042] In this embodiment, a torsional pendulum test is used to obtain the physical inertia and total mass of the electric compressor under test. Combined with the stiffness parameters of the vibration isolation components, the natural frequency of the vibration isolation system can be accurately calculated. Based on the physical model and actual parameters, the accuracy and reliability of the calculation results are ensured. The calculation of the natural frequency provides a clear theoretical basis for the design of the vibration isolation system. Based on the calculated natural frequency, the parameters of the vibration isolation components can be optimized, thereby designing a more effective vibration isolation system. The natural frequency is a key parameter of the dynamic behavior of the vibration isolation system. By accurately calculating the natural frequency, the accuracy of in-vehicle noise prediction can be improved, and the response characteristics of the vibration isolation system at different frequencies can be more accurately reflected, thus predicting the in-vehicle noise level more reliably.

[0043] Alternatively, the natural frequency of the vibration isolation system can be calculated in a Python program using a function definition.

[0044] Optionally, the system response force of the vibration isolation system at different frequencies is determined based on the compressor vibration force and the natural frequency of the vibration isolation system, including: determining the amplitude response coefficient of the vibration isolation system at different frequencies based on the vibration frequency and natural frequency of the vibration isolation system; and determining the system response force of the vibration isolation system at different frequencies based on the compressor vibration force and the amplitude response coefficient.

[0045] In this embodiment, the vibration isolation system composed of a compressor and a rubber elastic element is analyzed and simplified as a single-degree-of-freedom vibration isolation system with the compressor as a rigid body and the rubber vibration isolation element as a spring. By calculating the amplitude response coefficient of the vibration isolation system and combining it with the compressor's vibration force, the dynamic response of the vibration isolation system at different frequencies can be accurately evaluated. The amplitude response coefficient is calculated based on the ratio of the vibration frequency of the vibration isolation system to its natural frequency. The amplitude response coefficient provides a clear understanding of the dynamic behavior of the vibration isolation system at different frequencies. For example, the system may exhibit resonance near its natural frequency, while it shows better vibration isolation performance further away from its natural frequency. This analysis helps optimize the design of the vibration isolation system and avoid the adverse effects of resonance. By determining the system response force, the performance of the vibration isolation system under actual operating conditions can be evaluated more intuitively, helping to optimize the parameters of the vibration isolation element to achieve better vibration isolation. For example, by adjusting the stiffness of the vibration isolation element, the natural frequency of the system can be moved away from the main excitation frequency of the electric compressor, thereby reducing the amplitude of vibration transmitted to the vehicle body.

[0046] Alternatively, the amplitude response coefficient can be determined according to the following formula:

[0047] Among them, T M ζ is the amplitude response coefficient, λ is the ratio of the vibration frequency to the natural frequency of the vibration isolation system, and ζ is the system damping ratio.

[0048] Optionally, the system damping ratio ζ can be in the range of [0.05, 0.1].

[0049] In this embodiment, the amplitude response coefficient clearly reveals the dynamic behavior of the system near and far from the resonant frequency. When λ approaches 1, the system is close to resonance, and the amplitude response coefficient increases significantly, indicating high vibration transmission efficiency. Conversely, the amplitude response coefficient decreases when far from the resonant frequency, indicating good vibration isolation. By calculating the amplitude response coefficient, the vibration isolation performance of the system at different frequencies can be evaluated. Furthermore, a higher damping ratio can effectively suppress the amplitude of the resonance peak, thereby improving vibration isolation performance. By adjusting the damping ratio, the design of the vibration isolation system can be optimized, resulting in better performance in practical applications.

[0050] Optionally, the system attenuation coefficient of the vibration isolation system can be determined as follows: determine the vibration isolation amount at different frequencies; and determine the system attenuation coefficient of the vibration isolation system at different frequencies based on the vibration isolation amount.

[0051] In this embodiment, by determining the vibration isolation amount at different frequencies, the vibration isolation effect of the vibration isolation system at various frequencies can be quantified. The vibration isolation amount can intuitively reflect the degree of attenuation of vibration energy when passing through the vibration isolation system. Based on the vibration isolation amount, the system attenuation coefficient of the vibration isolation system at different frequencies can be further calculated, which directly reflects the vibration isolation system's ability to attenuate vibration energy.

[0052] Alternatively, the sound pressure level of the in-vehicle compressor noise can be determined according to the following formula:

[0053] Among them, y k The sound pressure level (NTF) of the in-vehicle compressor noise. ik For structural acoustic transfer function, NTF jk Let F be the airborne sound transfer function. Ri For vehicle body vibration force, P j Here are the compressor noise data, where n is the number of structural sound transmission paths and m is the number of airborne sound transmission paths.

[0054] This embodiment integrates both structural sound and airborne sound transmission paths, enabling a comprehensive assessment of the sound pressure level of the in-vehicle compressor noise. In vehicle NVH analysis, the structural sound transfer function (NTF) is... ik This describes the path of noise transmitted from the vehicle body structure to the interior, where n is the number of structural sound transmission paths. For example, it may include vibration transmission paths in different directions (e.g., x, y, z directions) or at different locations (e.g., different mounting points); the airborne sound transfer function (NTF) is also included. jk This describes the path from the compressor noise source through the air to the vehicle interior, where m is the number of airborne sound transmission paths. For example, this might include the number of noise sources at different frequencies or at different locations. By traversing all relevant transmission paths, the calculated sound pressure level y of the in-vehicle compressor noise is ensured. k It can comprehensively reflect all possible noise transmission contributions.

[0055] The method for predicting in-vehicle compressor noise provided by this disclosure will be described below with a specific embodiment.

[0056] Combination Figure 2 As shown, in one specific embodiment, this disclosure provides another method for predicting in-vehicle compressor noise, including: S201. A compressor bench test is conducted in an anechoic laboratory environment. The electric compressor under test is controlled to rotate at different frequencies to obtain the excitation force at multiple mounting points of the electric compressor under test at different frequencies, as well as the compressor noise data at a preset distance from the electric compressor under test.

[0057] S202, based on the excitation forces at multiple installation points at different frequencies, determines the resultant force of multiple excitation forces in the x, y, and z directions respectively, so as to obtain the compressor vibration force at different frequencies.

[0058] S203. Conduct a torsional pendulum test to obtain the physical inertia of the electric compressor under test, and determine the mass matrix based on the physical inertia and total mass of the electric compressor under test.

[0059] S204. Determine the system stiffness matrix based on the parallel stiffness, torsional stiffness, and co-stiffness in the vibration isolation element parameters.

[0060] S205. Determine the natural frequency of the vibration isolation system based on the mass matrix and the system stiffness matrix.

[0061] S206. Based on the vibration frequency and natural frequency of the vibration isolation system, determine the amplitude response coefficient of the vibration isolation system at different frequencies, and based on the compressor vibration force and amplitude response coefficient, determine the system response force of the vibration isolation system at different frequencies.

[0062] S207, determine the vibration isolation amount at different frequencies, and determine the system attenuation coefficient of the vibration isolation system at different frequencies based on the vibration isolation amount, and determine the body vibration force transmitted to the vehicle body at different frequencies based on the system attenuation coefficient and system response force of the vibration isolation system.

[0063] S208 determines the sound pressure level of the in-vehicle compressor noise at different frequencies based on compressor noise data and vehicle body vibration force.

[0064] Combination Figure 3 As shown, during the compressor bench test, taking an electric compressor with three mounting points as an example, the electric compressor was placed in an anechoic chamber. The three mounting points were rigidly connected to three force sensors via designed fixtures, with the other end of the sensors fixed to the bench. A microphone sensor was placed parallel to the compressor's center of mass and 30cm away. All sensors and the compressor speed signal were connected to the data acquisition system. Outside the anechoic chamber, the compressor was started and stabilized at 600rpm. The data acquisition device was then activated, and the compressor speed was gradually increased from 600rpm to 6000rpm. During this period, the data acquisition device was set to collect one sample every 60rpm for later frequency conversion. Several sets of samples were collected, and the set closest to the average value was selected. This set of data was then frequency-domain converted, i.e., f=n / 60, where f is the frequency and n is the rotational speed. This yields the excitation force F at each frequency for the three mounting points. Ti Compressor noise data P at 30cm T .

[0065] Since the force sensor test data is the amplitude of force in three directions, it is necessary to calculate the resultant force in each direction, i.e.:

[0066]

[0067]

[0068] Among them, F Txi Let F be the magnitude of the force at the i-th mounting point in the x-direction. Tyi Let F be the magnitude of the force at the i-th mounting point in the y-direction. Tzi Let be the magnitude of the force at the i-th mounting point in the z-direction.

[0069] This allows for the calculation of the amplitude of the resultant force in the three directions at various frequencies (10Hz to 100Hz). Simultaneously, the compressor noise data is post-processed, using the LMS system's filtering function to remove frequency components above 100Hz, retaining only the amplitude variation of compressor noise data with frequency below 100Hz.

[0070] When an electric compressor is independently installed on an electric vehicle, it requires a rubber bushing as a vibration isolation element. This creates an elastic system with inherent modes, the physical inertia of the compressor of which needs to be measured to calculate these modes. The torsional pendulum method can be used to test the rotational inertia of a rigid body, allowing the compressor's physical parameters to be obtained experimentally. In the inherent mode calculation, the compressor is treated as a rigid body, the rubber bushing as a linear spring, and the effect of damping is ignored. Therefore, the formula for calculating the natural frequency can be derived from the formula for calculating the inherent modes of an undamped elastic system.

[0071] Optionally, the formula for calculating the natural modes of an undamped elastic system is:

[0072] Therefore, we can deduce that:

[0073] Where, ω n Let be the natural frequency, K be the system stiffness matrix, and M be the mass matrix.

[0074] Alternatively, the formula for calculating the mass matrix is:

[0075] Where m is the total mass of the electric compressor, J xx J yy J zz J xy J yx J xz J zx J yz Jzy These are the compressor inertial parameters obtained through the torsional pendulum method test.

[0076] Optionally, the formula for calculating the system stiffness matrix is:

[0077] Among them, K xx K yy K zz K represents the sum of the stiffnesses in the three parallel directions of the rubber vibration isolation element. αα K ββ K γγ The sum of the stiffnesses in the three torsional directions of the rubber vibration isolation element is given, and the remaining stiffnesses are considered as co-stiffnesses.

[0078] Using the above formula, the natural mode values ​​can be calculated in a Python program through function definition, and it has 6 natural modes. Since the compressor's main excitation is caused by the rotation of the drive motor driving the rotor and turntable, the natural modes around the compressor motor drive shaft, i.e., the Roll direction modes, are mainly considered as the natural frequencies of the vibration isolation system.

[0079] In electric vehicles, the electric compressor is typically mounted on a vibration isolation element composed of rubber bushings. This results in a certain proportional difference between the system response force supported by the vibration isolation element and the compressor vibration force measured on a test bench. Based on the amplitude response coefficient T of the vibration isolation system... M The system response force F of the vibration isolation system at different frequencies can be calculated. M For: F M =F Ti ×T M Thus, we obtain the following: Figure 4 The diagram shows the vibration force response spectrum as the vibration force amplitude changes with frequency.

[0080] Among them, F Ti For F Tx F Ty F Tz Therefore, the system response force of vibration in three directions at various frequencies can be calculated:

[0081]

[0082]

[0083] The system response force of the electric compressor is attenuated by the vibration isolation system before being transmitted to the vehicle body. The force attenuation coefficient is related to the amount of vibration isolation. In automotive design, the amount of vibration isolation is related to the stiffness of the rubber bushings and the stiffness of the brackets connecting the elastic elements. During the research and development phase, it is generally designed as a value that varies with frequency. In this embodiment, the amount of vibration isolation at each frequency is taken as 30dB.

[0084] The formula for calculating vibration isolation is:

[0085] Where F is the input force, F b TR represents the attenuated output force, and TR represents the vibration isolation amount.

[0086] Therefore, the system attenuation coefficient T can be calculated when the vibration isolation is 30dB. r for:

[0087] At this moment, the body vibration force F is transmitted to the body in three directions. Rx F Ry F Rz They are respectively:

[0088]

[0089]

[0090] During the electric vehicle R&D phase, it is necessary to set targets for structural sound and airborne sound transfer functions. The structural sound transfer function describes the linear relationship between the input force of the vehicle body system and the output noise inside the vehicle in the frequency domain. In engineering, it is generally obtained through experiments using a force hammer or vibrator, microphone, and data acquisition system, or it can be calculated using CAE boundary element method or acoustic finite element method. The airborne sound transfer function describes the sound pressure level transfer relationship from one sound source location to another receiving point location in an acoustic environment. In engineering, it is generally measured by placing a volumetric sound source outside the vehicle to test the sound attenuation inside the vehicle. In this embodiment, the structural sound transfer function (NTF) of the vehicle body is... ik The target for sound attenuation along the air path is 55 dB / N across all frequencies (10 Hz to 100 Hz), and the target for sound attenuation along the air path is 25 dB across all frequencies (10 Hz to 100 Hz), corresponding to a target airborne sound transfer function (P). T -25) / P T .

[0091] According to the formula for calculating the sound pressure level of the in-vehicle compressor noise:

[0092] The total sound pressure level y of the in-vehicle compressor noise in this embodiment can be obtained.com for:

[0093] The sound pressure level y of the in-vehicle compressor noise at various frequencies can be predicted using the above formula. com Thus, we obtain the following: Figure 5 The diagram shows the sound pressure level of the in-vehicle compressor noise as a function of frequency, representing the in-vehicle noise spectrum.

[0094] In different embodiments, different vibration isolation targets and transfer function targets can be set for different NVH performance positioning requirements to predict the level of in-vehicle noise. Simultaneously, different vibration isolation component parameters can also be set to predict the in-vehicle noise level. Furthermore, based on the predicted in-vehicle noise level, noise reduction schemes can be designed, providing a rapid and efficient basis for electric compressor selection, vibration isolation component parameter and vibration isolation amount design, and vehicle body transfer function setting, thereby significantly shortening the electric vehicle development cycle and reducing R&D costs.

[0095] Combination Figure 6 As shown, this disclosure provides an apparatus 600 for predicting in-vehicle compressor noise, including a processor 601 and a memory 602. Optionally, the apparatus may further include a communication interface 603 and a bus 604. The processor 601, communication interface 603, and memory 602 can communicate with each other via the bus 604. The communication interface 603 can be used for information transmission. The processor 601 can call logical instructions in the memory 602 to execute the method for predicting in-vehicle compressor noise described in the above embodiment.

[0096] Furthermore, the logic instructions in the aforementioned memory 602 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0097] The memory 602, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 601 executes functional applications and data processing by running the program instructions / modules stored in the memory 602, that is, it implements the method for predicting in-vehicle compressor noise in the above embodiments.

[0098] The memory 602 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 602 may include high-speed random access memory and may also include non-volatile memory.

[0099] This disclosure provides an electronic device, including: an electronic device body, and the aforementioned device for predicting in-vehicle compressor noise. The device for predicting in-vehicle compressor noise is mounted on the electronic device body. The mounting relationship described herein is not limited to placement inside the electronic device, but also includes mounting connections with other components of the electronic device, including but not limited to physical connections, electrical connections, or signal transmission connections. Those skilled in the art will understand that the device for predicting in-vehicle compressor noise can be adapted to feasible product bodies to achieve other feasible embodiments.

[0100] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described method for predicting in-vehicle compressor noise.

[0101] This disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions that, when executed by a computer, cause the computer to perform the above-described method for predicting in-vehicle compressor noise.

[0102] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0103] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0104] The foregoing description and accompanying drawings fully illustrate embodiments of the present disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included or substituted for parts and features of other embodiments. The scope of the embodiments of this disclosure includes the entire scope of the claims and all available equivalents of the claims. While the terms “first,” “second,” etc., may be used in this application to describe elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, a first element may be called a second element without changing the meaning of the description, and similarly, a second element may be called a first element, provided that all occurrences of “first element” are consistently renamed and all occurrences of “second element” are consistently renamed. First and second elements are both elements, but may not be the same element. Moreover, the terminology used in this application is only for describing embodiments and is not intended to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” are intended to also include the plural forms. Similarly, the term “and / or” as used herein means including one or more of the associated listed any and all possible combinations. Additionally, when used herein, the terms “comprise” and its variations “comprises” and / or “comprising” refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase “comprising an…” does not exclude the presence of additional identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0105] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0106] The methods and products disclosed in the embodiments herein (including but not limited to devices and equipment) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0107] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for predicting in-vehicle compressor noise, characterized in that, include: Acquire data on compressor vibration force and compressor noise of the electric compressor under test at different frequencies; Based on the compressor vibration force and the natural frequency of the vibration isolation system, the system response force of the vibration isolation system at different frequencies is determined; wherein, the vibration isolation system is constructed based on the electric compressor under test and the preset vibration isolation element parameters; Based on the system attenuation coefficient and system response force of the vibration isolation system, determine the body vibration force transmitted to the vehicle body at different frequencies; Based on compressor noise data and vehicle body vibration, the sound pressure level of the in-vehicle compressor noise at different frequencies was determined.

2. The method according to claim 1, characterized in that, Acquire compressor vibration force and compressor noise data of the electric compressor under test at different frequencies, including: In an anechoic laboratory environment, the electric compressor under test is controlled to rotate at different frequencies to obtain the excitation force at multiple mounting points of the electric compressor under test at different frequencies, as well as the compressor noise data at a preset distance from the electric compressor under test; wherein, the electric compressor under test is rigidly connected to multiple force sensors through multiple mounting points respectively. Based on the excitation forces at multiple installation points at different frequencies, the resultant force of the multiple excitation forces in the x, y, and z directions is determined to obtain the compressor vibration force at different frequencies.

3. The method according to claim 2, characterized in that, Also includes: After obtaining the compressor noise data, the data with frequencies higher than the preset frequency are filtered out.

4. The method according to claim 1, characterized in that, The natural frequency of the vibration isolation system shall be determined as follows: Obtain the physical inertia of the electric compressor under test, and determine the mass matrix based on the physical inertia and total mass of the electric compressor under test; The system stiffness matrix is ​​determined based on the parallel stiffness, torsional stiffness, and co-stiffness in the parameters of the vibration isolation element. The natural frequencies of the vibration isolation system are determined based on the mass matrix and the system stiffness matrix.

5. The method according to claim 1, characterized in that, Based on the compressor vibration force and the natural frequency of the vibration isolation system, determine the system response force of the vibration isolation system at different frequencies, including: Based on the vibration frequency and natural frequency of the vibration isolation system, determine the amplitude response coefficients of the vibration isolation system at different frequencies; Based on the compressor vibration force and amplitude response coefficient, the system response force of the vibration isolation system at different frequencies is determined.

6. The method according to claim 5, characterized in that, The amplitude response coefficient is determined using the following formula: Among them, T M ζ is the amplitude response coefficient, λ is the ratio of the vibration frequency to the natural frequency of the vibration isolation system, and ζ is the system damping ratio.

7. The method according to claim 1, characterized in that, The system attenuation coefficient of the vibration isolation system shall be determined as follows: Determine the vibration isolation amount at different frequencies; The system attenuation coefficient of the vibration isolation system at different frequencies is determined based on the amount of vibration isolation.

8. The method according to any one of claims 1 to 7, characterized in that, The sound pressure level of the in-vehicle compressor noise is determined using the following formula: Among them, y k The sound pressure level (NTF) of the in-vehicle compressor noise. ik For structural acoustic transfer function, NTF jk Let F be the airborne sound transfer function. Ri For vehicle body vibration force, P j Here are the compressor noise data, where n is the number of structural sound transmission paths and m is the number of airborne sound transmission paths.

9. A device for predicting in-vehicle compressor noise, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to, when executing the program instructions, perform the method for predicting in-vehicle compressor noise as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: The electronic device itself; The device for predicting in-vehicle compressor noise as described in claim 9 is mounted on the electronic device body.

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