A method for NVH testing of an automotive electric machine

Abstract

The application provides a kind of NVH test method for automobile motor, comprising: the automobile motor is placed into the quiet room of NVH detection equipment and is fixed;Start automobile motor and execute the speed condition of automobile motor according to the set program, NVH detection equipment controls microphone to collect the noise signal in quiet room in real time, simultaneously control acceleration sensor to collect the vibration signal of automobile motor in real time;Comprehensive analysis obtains multiple algorithm index data of automobile motor when running, including order, time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data and sound pressure level data index, simultaneously judge whether these index data of the automobile motor meet the standard, save data result and output display.The beneficial effects of the application: the root cause of abnormal sound generated by automobile motor during operation can be found through NVH test, so that corresponding measures can be taken to optimize automobile motor parts and process, improve and eliminate abnormal sound.

Description

Technical Field

[0001] This invention relates to the field of automotive NVH technology, and more particularly to an NVH testing method for automotive motors. Background Technology

[0002] An automobile is a powered vehicle with four or more wheels that travels on land without relying on tracks or overhead wires. The main functions of an automobile include: carrying people and goods, towing vehicles carrying people and / or goods, and completing specific transportation or operational tasks. Due to its versatility, the automobile has become an indispensable part of modern society. Its design not only considers basic driving performance but also incorporates various safety and comfort features. Automobiles are classified in various ways, mainly into passenger cars and freight cars, as well as special-purpose vehicles designed to complete specific tasks. These special-purpose vehicles may include fire trucks, ambulances, police cars, etc.

[0003] In the automotive industry, NVH (Noise, Vibration, Harshness) refers to noise, vibration, and acoustic roughness, a comprehensive issue for measuring automotive manufacturing quality. The generation of automotive vibration and noise is not independent but closely related; noise originates from vibration, and vibration, noise, and comfort are closely interrelated. In the automotive production process, the automotive motor is a device that converts and transmits electrical energy, primarily serving as the power source for electric vehicles. The automotive motor plays a crucial role in modern automobiles, especially in electric vehicles. It is not only responsible for converting electrical energy into mechanical energy to propel the vehicle forward but also involves energy management and distribution. With the development of electric vehicle technology, the performance requirements for automotive motors are constantly increasing to meet demands for higher energy efficiency, faster response times, and longer driving ranges.

[0004] In the production process of automotive motors, functional testing of various aspects of the motor is crucial. Motors that fail the tests cannot be qualified products and can leave the factory. However, current automotive motor functional testing generally focuses on whether the motor operates normally and performs power conversion, often neglecting its performance in terms of noise and vibration. Instead, it is often a simple test. Sometimes, the noise and vibration performance of automotive motors can affect the user experience, resulting in some products providing a less than ideal user experience. Summary of the Invention

[0005] To address the problems in existing technologies, this invention provides an NVH testing method for automotive motors. This method can identify the root cause of abnormal noises generated by automotive motors during operation through NVH testing, thereby taking corresponding measures to optimize automotive motor components and processes, improve and eliminate abnormal noises, significantly enhance the user's driving experience, and solve the problem that existing technologies do not focus on noise and vibration aspects during pre-shipment testing of automotive motors.

[0006] The present invention provides an NVH testing method for automotive motors, comprising the following steps:

[0007] Step 1: Preparation before NVH testing. The robotic arm places the car motor into the quilted chamber of the NVH testing equipment and fixes it in place. The power supply is connected to the car motor. The NVH testing equipment automatically checks whether the microphone used to collect noise signals in the quilted chamber and the accelerometer used to collect vibration signals of the car motor are functioning properly.

[0008] Step 2: NVH testing and data acquisition. Start the car motor and execute the car motor speed operation according to the set program. The NVH testing equipment controls the microphone to collect the noise signal in the quiet room in real time, and at the same time controls the acceleration sensor to collect the vibration signal of the car motor in real time. Save the noise signal and vibration signal according to the timestamp of the collected data.

[0009] Step 3: Data Analysis and Result Output. The control center of the NVH testing equipment uses order analysis, full-spectrum algorithm, and K-value algorithm to analyze the collected noise and vibration signals. It uses envelope spectrum algorithm to demodulate and analyze the low-frequency impact signals in the noise and vibration signals. At the same time, it calculates the linear summation relationship between noise frequency, vibration frequency, and vehicle motor speed. Finally, it comprehensively analyzes and obtains multiple algorithm index data of the vehicle motor during operation, including order, time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data, and sound pressure level data. It also determines whether these index data of the vehicle motor meet the standards, saves the data results, and outputs and displays them.

[0010] The present invention is further improved in that, in step 3, the order analysis method is used to analyze the relationship between the operating speed and vibration displacement of the automotive motor bearing and the operating speed and vibration displacement of the overall automotive motor structure in the vibration data, and to generate an order analysis curve; it is also used to analyze the noise generated by the automotive motor bearing during operation and the noise generated by the overall automotive motor structure during operation in the noise data, and to generate an order analysis curve.

[0011] The present invention is further improved in that, in step 3, the full spectrum algorithm is used to analyze abnormal noise and abnormal vibration in the noise signal and vibration signal according to the set limit, and generate a car motor noise curve and a car motor vibration curve that are easy to identify.

[0012] The present invention is further improved in that, in step 3, the K-value algorithm is used to analyze the variation amplitude in the noise signal and vibration signal, and to generate time-varying automotive motor noise variation curves and automotive motor vibration variation curves that are easy to identify as anomalies.

[0013] In a further improvement to this invention, in step 3, the envelope spectrum algorithm is used to demodulate and extract the low-frequency impact signal from the noise signal and the vibration signal.

[0014] The present invention is further improved in that, in step 3, the linear summation is used to establish a relationship between the noise frequency and the speed of the car motor, and between the vibration frequency and the speed of the car motor, and to generate linear summation curves of the car motor noise frequency and the car motor speed and the car motor vibration frequency and the car motor speed as they change over time.

[0015] In a further improvement to this invention, in step 1, when the NVH testing equipment automatically detects that the microphone used to collect noise signals in the soundproof room and the accelerometer used to collect vibration signals from the car motor are not functioning properly, the NVH testing equipment automatically notifies the management personnel to handle the issue.

[0016] The present invention is further improved in that, in step 2, the noise data includes the decibel level and frequency of the sound generated when the car motor is running.

[0017] The present invention is further improved in that, in step 2, the vibration data includes the vibration amplitude and vibration frequency generated when the car motor is running.

[0018] The beneficial effects of this invention are as follows: This invention provides an NVH testing method for automotive motors, which comprehensively analyzes and obtains time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data, and sound pressure level data indicators of the automotive motor during operation. At the same time, it determines whether these indicators of the automotive motor meet the standards. It can identify the root cause of abnormal noise generated by the automotive motor during operation through NVH testing, thereby taking corresponding measures to optimize the automotive motor components and processes, improve and eliminate abnormal noise, significantly improve the user's driving experience, and solve the problem that the existing technology does not pay attention to noise and vibration aspects during the pre-shipment testing of automotive motors. Attached Figure Description

[0019] Figure 1 This is a flowchart of an NVH testing method for automotive motors according to the present invention. Detailed Implementation

[0020] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0021] Please see Figure 1The present invention provides an NVH testing method for automotive motors, comprising the following steps:

[0022] Step 1: Preparation before NVH testing. The robotic arm places and secures the car motor in the vegetative chamber of the NVH testing equipment. Power is then supplied to the car motor. The NVH testing equipment automatically checks whether the microphone used to collect noise signals in the vegetative chamber and the accelerometer used to collect vibration signals from the car motor are functioning properly. If either the microphone or the accelerometer fails to function properly, the NVH testing equipment automatically notifies the management personnel for handling.

[0023] Step 2: NVH testing and data acquisition. Start the car motor and execute the motor speed operation according to the set program. The NVH testing equipment controls the microphone to collect noise signals in the soundproof room in real time, and simultaneously controls the acceleration sensor to collect vibration signals of the car motor in real time. Save the noise and vibration signals according to the timestamp of the collected data. Among them, the noise data includes the decibel level and frequency of the sound generated when the car motor is running; the vibration data includes the vibration amplitude and frequency generated when the car motor is running.

[0024] Step 3: Data Analysis and Result Output. The control center of the NVH testing equipment uses order analysis, full-spectrum algorithm, and K-value algorithm to analyze the collected noise and vibration signals. Envelope spectrum algorithm is used for demodulation analysis to extract low-frequency impact signals from the noise and vibration signals. Simultaneously, the linear summation relationship between noise frequency, vibration frequency, and vehicle motor speed is calculated. Finally, a comprehensive analysis yields multiple algorithmic index data for the vehicle motor during operation, including order, time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data, and sound pressure level data. The system also determines whether these index data of the vehicle motor meet the standards, saves the data results, and outputs them for display. The order analysis method can identify the cursor position on the color energy map, automatically identify the order position, and generate order analysis curves. In this embodiment, the order analysis method is used to analyze the relationship between the operating speed and vibration displacement of the vehicle motor bearing and the relationship between the operating speed and vibration displacement of the overall vehicle motor structure in the vibration data, generating order analysis curves. It is also used to analyze the noise generated by the vehicle motor bearing and the overall vehicle motor structure during operation in the noise data, generating order analysis curves. The full-spectrum algorithm divides the color energy map into N grids and synthesizes a curve by taking the maximum / average energy value within each block. This curve can be effectively differentiated by setting limits. In this embodiment, the full-spectrum algorithm is used to analyze abnormal noise and vibration signals according to set limits, generating easily identifiable abnormal automotive motor noise and vibration curves. The K-value (kurtosis) is a numerical statistic reflecting the distribution characteristics of a random variable; it is a fourth-order cumulant and is typically used to reflect the steepness of a waveform. When K=3, it indicates normal kurtosis. In the K-value curve, the x-axis represents time, and the y-axis represents the K-value, showing how the K-value changes over time. In this embodiment, the K-value algorithm is used to analyze the amplitude of changes in noise and vibration signals, generating easily identifiable time-varying automotive motor noise and vibration curves. Among them, the envelope spectrum algorithm is a demodulation method. In some automotive motor bearing failures (such as periodic gear collisions), the bearing will generate periodic impact signals during operation. These signals are modulated by high-frequency natural vibrations. Envelope spectrum analysis can effectively demodulate and extract such low-frequency impact signals. In this embodiment, the envelope spectrum algorithm is used to demodulate and extract low-frequency impact signals from noise signals and vibration signals.Linear summation is a spectral analysis method that links signal frequency with rotational speed. Order refers to the number of rotations or cycles occurring per unit time. Linear summation displays the frequency components of the signal as they change over time, as well as the relationship between these frequencies and the system's rotational speed. The linear summation curve shows the distribution of energy at different orders during the rotation of the car motor. In this embodiment, linear summation is used to establish a relationship between noise frequency and car motor speed, and between vibration frequency and car motor speed, and to generate linear summation curves of car motor noise frequency and car motor speed as they change over time, as well as linear summation curves of car motor vibration frequency and car motor speed.

[0025] In this embodiment, time-varying loudness data is represented by a time-varying loudness curve, showing how the loudness of the audio signal in the noise data changes over time. By analyzing the fluctuations of the curve, the intensity changes of the audio signal at different time points can be understood, thereby determining whether the car motor generates abnormal audio signals, such as noise or howling, during operation. Noise data is represented by a noise curve, reflecting the magnitude and distribution of noise in the audio signal of the noise data. By observing the fluctuations and peaks of the curve, the noise level generated by the device during operation can be assessed, thereby determining whether the car motor needs noise reduction processing or optimization. Steady-state loudness data is represented by a steady-state loudness curve, which is usually a relatively smooth curve. It represents the loudness level of the audio signal in the noise data under a stable state. By observing the smoothness and magnitude of the curve, the audio signal quality of the car motor during stable operation can be determined. Sharpness spectrum data is represented by a sharpness spectrum curve, showing the sharpness distribution of the audio signal at different frequencies in the noise data. By observing the shape and peak positions of the curve, the clarity and detail of the audio signal at different frequencies can be understood, thereby determining the performance of the car motor in audio processing. Sound pressure level data is represented by a sound pressure level curve, which indicates the sound pressure level of the audio signal in the noise data under steady-state conditions. By observing the value and stability of the curve, the strength and stability of the audio signal generated by the car motor during operation can be evaluated, thereby judging the product's performance in terms of audio output. The invented NVH testing method for automotive motors can identify the root causes of noise generated during motor operation, such as electromagnetic and mechanical noise. This allows for the implementation of corresponding measures to optimize motor components and processes, reducing in-vehicle noise levels and improving ride comfort. It can also reduce vibration by detecting motor vibration and preventing its transmission to the vehicle body and other components, thus preventing structural resonance and reducing wear and fatigue, extending the lifespan of automotive parts. Furthermore, it enhances the driving experience by optimizing the NVH performance of motors, resulting in smoother and quieter vehicle operation and a more comfortable driving environment for drivers and passengers, improving vehicle quality and user satisfaction. Finally, it meets regulations and standards; the automotive industry has relevant NVH standards and regulations, and NVH testing ensures that motors comply with these requirements, enabling vehicles to pass certification and be marketed smoothly. Finally, it supports product development; during the motor development phase, NVH testing provides engineers with data to help improve designs and optimize motor structure, materials, and control strategies to enhance overall product performance.

[0026] As can be seen from the above, the beneficial effects of the present invention are as follows: The present invention provides an NVH testing method for automotive motors, which comprehensively analyzes and obtains time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data, and sound pressure level data indicators of the automotive motor during operation. At the same time, it determines whether these indicators of the automotive motor meet the standards. It can discover the root cause of abnormal noise generated by the automotive motor during operation through NVH testing, thereby taking corresponding measures to optimize the automotive motor components and processes, improve and eliminate abnormal noise, significantly improve the user's driving experience, and solve the problem that the existing technology does not pay attention to noise and vibration aspects during the pre-shipment testing of automotive motors.

[0027] The specific embodiments described above are preferred embodiments of the present invention and are not intended to limit the specific scope of the present invention. The scope of the present invention includes, but is not limited to, these specific embodiments. All equivalent changes made in accordance with the present invention are within the protection scope of the present invention.

Claims

1. An NVH testing method for automotive motors, characterized in that, Includes the following steps, Step 1: Preparation before NVH testing. The robotic arm places the car motor into the quilted chamber of the NVH testing equipment and fixes it in place. The power supply is connected to the car motor. The NVH testing equipment automatically checks whether the microphone used to collect noise signals in the quilted chamber and the accelerometer used to collect vibration signals of the car motor are functioning properly. Step 2: NVH testing and data acquisition. Start the car motor and execute the car motor speed operation according to the set program. The NVH testing equipment controls the microphone to collect the noise signal in the quiet room in real time, and at the same time controls the acceleration sensor to collect the vibration signal of the car motor in real time. Save the noise signal and vibration signal according to the timestamp of the collected data. Step 3: Data Analysis and Result Output. The control center of the NVH testing equipment uses order analysis, full-spectrum algorithm, and K-value algorithm to analyze the collected noise and vibration signals. Envelope spectrum algorithm is used for demodulation analysis to extract low-frequency impact signals from the noise and vibration signals. Simultaneously, the linear summation relationship between noise frequency, vibration frequency, and vehicle motor speed is calculated. Finally, a comprehensive analysis yields multiple algorithmic index data for the vehicle motor during operation, including order, time-varying loudness data, noise data, steady-state loudness data, sharpness spectrum data, and sound pressure level data. The system also determines whether these index data of the vehicle motor meet the standards, saves the data results, and outputs them for display. Specifically, order analysis is used to analyze the relationship between the vehicle motor bearing operating speed and vibration displacement, and the relationship between the overall operating speed and vibration displacement of the vehicle motor structure, generating order analysis curves. It is also used to analyze noise data... The algorithm analyzes the noise generated by the bearings of the automotive motor during operation and the noise generated by the overall structure of the automotive motor during operation, generating order analysis curves. A full-spectrum algorithm is used to analyze abnormal noise and vibration signals according to set limits, generating automotive motor noise and vibration curves that facilitate anomaly identification. A K-value algorithm is used to analyze the amplitude changes in noise and vibration signals, generating time-varying automotive motor noise and vibration change curves that facilitate anomaly identification. An envelope spectrum algorithm is used to demodulate and extract low-frequency impact signals from noise and vibration signals. Linear summation is used to establish a relationship between noise frequency and automotive motor speed, and between vibration frequency and automotive motor speed, generating time-varying linear summation curves for automotive motor noise frequency and automotive motor speed, and automotive motor vibration frequency and automotive motor speed.

2. The NVH testing method for automotive motors as described in claim 1, characterized in that: In step 3, when the NVH testing equipment automatically detects that the microphone used to collect noise signals in the soundproof room and the accelerometer used to collect vibration signals from the car motor are not functioning properly in step 1, the NVH testing equipment automatically notifies the management personnel to handle the issue.

3. The NVH testing method for automotive motors as described in claim 2, characterized in that: In step 2, the noise data includes the decibel level and frequency of the sound generated when the car motor is running.

4. The NVH testing method for automotive motors as described in claim 3, characterized in that: In step 2, the vibration data includes the vibration amplitude and frequency generated when the car motor is running.

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