Brushless motor electromagnetic noise suppression method and system based on harmonic current injection

Abstract

The present application relates to the technical fields of electromagnetic noise suppression, and relates to a brushless motor electromagnetic noise suppression method and system based on harmonic current injection, comprising: confirming a noise brushless motor and a motor monitoring device, obtaining motor data of the noise brushless motor, using the motor monitoring device to analyze the noise of the noise brushless motor, obtaining a motor noise signal, performing frequency spectrum feature analysis on the motor noise signal, obtaining noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, performing phase-sensitive detection on the motor noise signal based on the noise order, the electromagnetic characteristic frequency and the electric angle time signal, obtaining the motor relative phase, performing adaptive fine tuning on the preliminary harmonic current data set based on the motor monitoring device and the vector voltage time signal set, obtaining a target harmonic signal set, performing harmonic injection on the noise brushless motor based on the target harmonic signal set, obtaining a noise suppression motor, and completing electromagnetic noise suppression of the brushless motor. The present application can reduce the electromagnetic noise level of the brushless motor.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic noise suppression technology, and in particular to a method and system for suppressing electromagnetic noise in brushless motors based on harmonic current injection. Background Technology

[0002] With the widespread application of brushless motors in industrial equipment and precision drive systems, electromagnetic noise during operation has gradually become a significant factor affecting product performance and user experience. Therefore, the analysis and suppression of electromagnetic noise in brushless motors has become an important research direction in motor control.

[0003] Existing methods for suppressing electromagnetic noise in brushless motors mainly involve continuously trying various harmonic currents with different amplitudes and phases injected into the brushless motor to find the harmonic current that reduces electromagnetic noise the most, or by improving stator and rotor structural parameters, optimizing slot-pole ratios, or adjusting magnetic circuit design to reduce the excitation intensity of electromagnetic force waves and thus suppress electromagnetic noise.

[0004] However, in actual motor debugging, repeatedly trying various testing methods for injecting harmonic current into brushless motors is inefficient and imprecise, resulting in poor suppression of electromagnetic noise. Furthermore, some methods of injecting harmonic current directly affect the current control loop, easily disrupting the stability of the current closed loop in field-oriented control (FOC), and are limited by the current loop bandwidth, making it difficult to effectively modulate higher-order harmonics. Therefore, a control method that can accurately and efficiently suppress the electromagnetic noise of brushless motors is urgently needed. Summary of the Invention

[0005] This invention provides a method for suppressing electromagnetic noise in brushless motors based on harmonic current injection and a computer-readable storage medium, the main purpose of which is to reduce the electromagnetic noise level of brushless motors.

[0006] To achieve the above objectives, the present invention provides a method for suppressing electromagnetic noise in a brushless motor based on harmonic current injection, comprising: The noise-inhibiting brushless motor and motor monitoring device were identified. The motor monitoring device includes: a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noise-inhibiting brushless motor includes: an FOC microcontroller and a mechanical rotor. Obtain motor data for a noisy brushless motor, including: operating speed, number of pole pairs, and number of slots. The electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor are obtained based on the operating speed, and the vector voltage amplitude is obtained based on the vector voltage-time signal group. Noise analysis of a brushless motor is performed using a motor monitoring device to obtain the motor noise signal. Spectral characteristic analysis of the motor noise signal is then performed to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Phase-sensitive detection of motor noise signal is performed based on noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of sound and motor; Based on the pre-constructed harmonic current model, harmonic prediction is performed on noise order, electromagnetic noise amplitude, relative phase of sound equipment, motor data and vector voltage amplitude to obtain a preliminary harmonic current data set, which includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude and falling harmonic phase. Based on the motor monitoring device and the vector voltage time signal group, the preliminary harmonic current data group is adaptively fine-tuned to obtain the target harmonic signal group; By injecting harmonics into a noisy brushless motor based on a target harmonic signal group, a noise-suppressed motor is obtained, thus completing the electromagnetic noise suppression of the brushless motor.

[0007] Optionally, the step of acquiring the electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor based on the operating speed includes: Start the noisy brushless motor and set the speed of the started noisy brushless motor to the operating speed to obtain the running brushless motor; The mechanical rotation angle signal of the mechanical rotor in a running brushless motor is read using a pre-built position sensor; Calculate the electrical angle-time signal based on the mechanical rotation angle signal and the number of motor pole pairs; Read the first voltage signal and the second voltage signal from the FOC microcontroller that is running the brushless motor; The first voltage signal and the second voltage signal are combined to obtain the vector voltage time signal group.

[0008] Optionally, the step of using a motor monitoring device to perform noise analysis on the brushless motor to obtain a motor noise signal includes: The noise-reducing brushless motor is placed into a soundproof motor box to obtain a soundproof brushless motor; Start the soundproof brushless motor and set the speed of the started soundproof brushless motor to the working speed to obtain the test brushless motor; The recording microphone in the motor monitoring device is used to collect and test the motor noise signal of the brushless motor.

[0009] Optionally, the step of performing spectral characteristic analysis on the motor noise signal to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency includes: The motor noise signal is processed by FFT to obtain the noise signal spectrum; Multiple local spectral peak frequencies were identified based on the noise signal spectrum. For each of the multiple local spectral peak frequencies, perform the following operation: The order of candidates is calculated based on the local spectral peak frequency, operating speed, and number of motor pole pairs. By summing up the candidate orders, we obtain multiple candidate orders; The first test speed and the second test speed are determined based on the preset first multiplier value, the preset second multiplier value, and the working speed. The first test speed is the product of the first multiplier value and the working speed, and the second test speed is the product of the second multiplier value and the working speed. Multiple first spectral peak frequencies were identified based on the soundproof brushless motor and the first test speed, and multiple second spectral peak frequencies were identified based on the soundproof brushless motor and the second test speed. For each of the multiple candidate orders, perform the following operation: Multiply the local spectral peak frequency corresponding to the order to be selected by the first multiplier to obtain the first amplification frequency; A first frequency range is determined based on a preset frequency selection interval and a first amplification frequency. The minimum value of the first frequency range is the absolute difference between the first amplification frequency and the frequency selection interval, and the maximum value of the first frequency range is the sum of the first amplification frequency and the frequency selection interval. The second frequency range is determined based on the local spectral peak frequency corresponding to the candidate order, the second multiple, and the frequency selection interval. Determine whether there is a first spectral peak frequency within the first frequency range among multiple first spectral peak frequencies; If there is a first spectral peak frequency among the multiple first spectral peak frequencies that is located within the first frequency range, then determine whether there is a second spectral peak frequency among the multiple second spectral peak frequencies that is located within the second frequency range. If there is a second spectral peak frequency within the second frequency range among multiple second spectral peak frequencies, then the order to be selected is recorded as the selectable order; By summing the possible orders, multiple possible orders can be obtained; For each of the multiple optional orders, perform the following operation: Round the optional order to the nearest integer to obtain the integer order. The order difference is calculated based on the optional order and the rounding order, where the order difference is the absolute difference between the optional order and the rounding order. Summarize the order integer differences to obtain multiple order integer differences, and take the floor order corresponding to the smallest order integer difference among the multiple order integer differences as the noise order; The local spectral peak frequency corresponding to the noise order is taken as the electromagnetic characteristic frequency. The amplitude of electromagnetic noise is determined in the noise signal spectrum based on the electromagnetic characteristic frequency.

[0010] Optionally, the step of performing phase-sensitive detection on the motor noise signal based on the noise order, electromagnetic characteristic frequency, and electrical angle-time signal to obtain the relative phase of the motor and the sound source includes: The electromagnetic frequency range is determined based on the frequency selection interval and electromagnetic characteristic frequency. The motor noise signal is filtered based on the electromagnetic frequency range to obtain the filtered noise signal. The first reference signal and the second reference signal are constructed based on the noise order, the filtered noise signal, and the electrical angle-time signal. The first reference signal is sampled at equal intervals based on a preset sampling interval and a preset number of samples to obtain multiple first sampling points. The number of first sampling points among the multiple first sampling points is the number of samples. The first sampling point includes: a first sample value. Calculate the first moving average value based on multiple first sampling points; The second moving average value is obtained based on the sampling interval, the number of samples, and the second reference signal; The relative phase of the sound machine is calculated based on the first sliding average and the second sliding average.

[0011] Optionally, before obtaining the preliminary harmonic current data set by performing harmonic prediction on the noise order, electromagnetic noise amplitude, relative phase of the audio equipment, motor data, and vector voltage amplitude based on the pre-constructed harmonic current model, the method further includes: Multiple historical motor data and multiple historical harmonic control data are acquired. The historical motor data includes: historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude. The historical harmonic control data includes: historical rising harmonic amplitude, historical rising harmonic phase, historical falling harmonic amplitude, and historical falling harmonic phase. The historical motor data and the historical harmonic control data correspond one-to-one. The pre-built deep learning model was trained using multiple historical motor data and multiple historical harmonic regulation data to obtain the harmonic current model.

[0012] Optionally, the adaptive fine-tuning of the preliminary harmonic current data set based on the motor monitoring device and the vector voltage-time signal set to obtain the target harmonic signal set includes: Acquire the electrical data of the motor, including: motor angular velocity, motor stator resistance, and motor inductance; The electric angular velocity is calculated based on the motor angular velocity and the number of motor pole pairs, where the electric angular velocity is the product of the motor angular velocity and the number of motor pole pairs; The harmonic order of up-order and harmonic order of down-order are determined based on the noise order. Based on the harmonic order, the motor stator resistance, motor inductance, electric angular velocity, and the increased harmonic amplitude and phase in the preliminary harmonic current data set, a first and a second increased voltage signal are constructed. The first and second increased voltage signals are shown below: ; in, and These are the first and second raised-order voltage signals, respectively. For the amplitude of the higher harmonic, For the rising harmonic phase, , and These are the motor stator resistance, motor inductance, and electric angular velocity, respectively. For the order of harmonics, It is an electrical angle-time signal. Refers to the sine function. Cosine function The arctangent function; The first and second reduced-order voltage signals are obtained based on the reduced-order order of the harmonics, the stator resistance, inductance, and angular velocity of the motor in the electrical data of the motor, the amplitude and phase of the reduced-order harmonics in the preliminary harmonic current data set. The first injection voltage signal and the second injection voltage signal are constructed based on the first raised voltage signal, the second raised voltage signal, the first lowered voltage signal, the second lowered voltage signal, the first voltage signal, and the second voltage signal in the vector voltage time signal group; Based on the FOC microcontroller, the first injection voltage signal and the second injection voltage signal, the noise brushless motor is voltage controlled to obtain the initial control brushless motor; The target harmonic signal group is obtained by adaptively fine-tuning the initial control brushless motor using a motor monitoring device.

[0013] Optionally, the step of using a motor monitoring device to adaptively fine-tune the initial control brushless motor to obtain the target harmonic signal group includes: Based on the operating speed, the initial control brushless motor, and the soundproof motor box, the brushless motor was selected for evaluation. The recording microphone in the motor monitoring device is used to collect evaluation noise signals for the brushless motor. The evaluation noise amplitude is obtained based on the evaluation noise signal; The vibration sensor and the Hall sensor are both installed on the evaluated brushless motor to obtain a vibration sensor and a Hall sensor installed. The maximum amplitude of the brushless motor is obtained and evaluated based on the preset total acquisition time and the installed vibration sensor. The brushless motor is evaluated by acquiring multiple magnetic field strengths based on the total acquisition time, the preset acquisition time interval, and the installation of Hall sensors. The mean magnetic field strength is calculated based on multiple magnetic field strengths, where the mean magnetic field strength is the average of the multiple magnetic field strengths. The electromagnetic suppression index is calculated based on the evaluation noise amplitude, maximum amplitude, average magnetic field strength, and multiple magnetic field strengths. The amplitude of the raised harmonic is finely adjusted bidirectionally according to a preset amplitude percentage to obtain an increase in the raised amplitude and a decrease in the raised amplitude. The amplitude of the lower harmonic is increased and decreased based on the amplitude percentage and the lower harmonic amplitude. The raised harmonic phase is finely adjusted bidirectionally according to a preset fine-tuning angle to obtain an increase in the raised phase and a decrease in the raised phase. The decreased harmonic phase is obtained by adjusting the fine-tuning angle and the decreased harmonic phase. Based on increasing the amplitude of the order increase, increasing the amplitude of the order decrease, increasing the phase of the order increase and increasing the phase of the order decrease, the order of the order increase of the harmonics, the order of the order decrease of the harmonics, the motor stator resistance, the motor inductance, the electric angular velocity, the FOC microcontroller obtains the first update voltage signal and the second update voltage signal. Based on the first updated voltage signal, the second updated voltage signal, and the noise level of the brushless motor, an additional evaluation motor was identified. Based on motor monitoring devices and by adding evaluation motors to obtain electromagnetic indices; The electromagnetic index is reduced by reducing the amplitude of the rising order, reducing the amplitude of the falling order, reducing the phase of the rising order, reducing the phase of the falling order, the order of the rising harmonics, the order of the falling harmonics, the stator resistance of the motor, the inductance of the motor, the electric angular velocity, the FOC microcontroller, the noise brushless motor and the motor monitoring device. Compare the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index; If the electromagnetic index is increased to the maximum value among the electromagnetic suppression index, the electromagnetic index increase, and the electromagnetic index decrease, then the increased electromagnetic index is used as the electromagnetic suppression index, and the increased up-order amplitude, increased down-order amplitude, increased up-order phase, and increased down-order phase are used as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively. Then return to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic index is reduced to the maximum value among the electromagnetic suppression index, the electromagnetic index is increased, and the electromagnetic index is reduced, then the reduced electromagnetic index is taken as the electromagnetic suppression index, and the reduced up-order amplitude, reduced down-order amplitude, reduced up-order phase, and reduced down-order phase are taken as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively, and the process returns to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic suppression index is the maximum value among the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index, then the first update voltage signal and the second update voltage signal corresponding to the electromagnetic suppression index are respectively used as the target first voltage signal and the target second voltage signal. By combining the first voltage signal and the second voltage signal of the target, the target harmonic signal group is obtained.

[0014] Optionally, the formula for calculating the electromagnetic suppression index is as follows: ; in, Electromagnetic suppression index, The first of multiple magnetic field strengths One magnetic field strength, The mean magnetic field strength This refers to the number of magnetic field strengths among multiple magnetic field strengths. To evaluate the noise amplitude, For maximum amplitude, It is a natural constant.

[0015] To achieve the above objectives, the present invention also provides a brushless motor electromagnetic noise suppression system based on harmonic current injection, comprising: The brushless motor verification module is used to verify the noise of the brushless motor and the motor monitoring device. The motor monitoring device includes: a soundproof motor box, a recording microphone, a vibration sensor and a Hall sensor. The noise of the brushless motor includes: an FOC microcontroller and a mechanical rotor. The motor data acquisition module is used to acquire motor data of the noisy brushless motor. The motor data includes: operating speed, number of motor pole pairs and number of motor slots. Based on the operating speed, the module acquires the electrical angle time signal and vector voltage time signal group of the noisy brushless motor, and acquires the vector voltage amplitude based on the vector voltage time signal group. The motor noise analysis module is used to analyze the noise of a brushless motor using a motor monitoring device, obtain the motor noise signal, perform spectral characteristic analysis on the motor noise signal to obtain the noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, and perform phase-sensitive detection on the motor noise signal based on the noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of the motor. The motor noise suppression module is used to predict harmonics based on a pre-built harmonic current model, including noise order, electromagnetic noise amplitude, relative phase between the motor and the receiver, motor data, and vector voltage amplitude, to obtain a preliminary harmonic current data set. This preliminary harmonic current data set includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude, and falling harmonic phase. The module then adaptively fine-tunes the preliminary harmonic current data set based on the motor monitoring device and the vector voltage time signal set to obtain a target harmonic signal set. Based on the target harmonic signal set, harmonics are injected into the noisy brushless motor to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor.

[0016] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; The processor executes the instructions stored in the memory to implement the above-described method for suppressing electromagnetic noise in a brushless motor based on harmonic current injection.

[0017] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the above-described method for suppressing electromagnetic noise in a brushless motor based on harmonic current injection.

[0018] To address the problems described in the background section, this invention identifies a noisy brushless motor and a motor monitoring device. The motor monitoring device includes a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noisy brushless motor includes an FOC microcontroller and a mechanical rotor. This invention provides a complete equipment foundation for subsequent noise analysis by pre-identifying the noisy brushless motor and the motor monitoring device, thereby acquiring motor data, including operating speed, number of pole pairs, and number of slots. Based on the operating speed, the electrical angle-time signal and vector voltage-time signal set of the noisy brushless motor are obtained. The vector voltage amplitude is then obtained from the vector voltage-time signal set. This invention demonstrates that... By acquiring initial data of the brushless motor during operation, initial data references are provided for subsequent harmonic injection into the noisy brushless motor. Noise analysis is performed on the noisy brushless motor using a motor monitoring device to obtain the motor noise signal. Spectral feature analysis is then performed on the motor noise signal to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Based on the noise order, electromagnetic characteristic frequency, and electrical angle-time signal, phase-sensitive detection is performed on the motor noise signal to obtain the relative phase between the motor and the noise source. It is evident that this embodiment of the invention, through spectral decomposition of the noise signal, extracts the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency, achieving quantitative identification of the electromagnetic noise components in the motor noise signal and clearly defining the target harmonic order to be suppressed, thereby improving the accuracy of the control strategy. By calculating the relative phase of the sound equipment, phase cancellation can be achieved during harmonic injection, improving noise suppression. Based on a pre-constructed harmonic current model, harmonic prediction is performed on the noise order, electromagnetic noise amplitude, relative phase of the sound equipment, motor data, and vector voltage amplitude to obtain a preliminary harmonic current data set. This preliminary harmonic current data set includes: increased harmonic amplitude, increased harmonic phase, decreased harmonic amplitude, and decreased harmonic phase. The preliminary harmonic current data set is adaptively fine-tuned based on the motor monitoring device and the vector voltage time signal set to obtain the target harmonic signal set. Therefore, this embodiment of the invention, by introducing a pre-constructed harmonic current model, fuses and models the noise order, electromagnetic noise amplitude, relative phase of the sound equipment, motor data, and vector voltage amplitude, thereby improving noise suppression. The invention makes preliminary predictions of harmonic currents to suppress electromagnetic noise, improves the initial accuracy of harmonic current compensation, reduces the trial-and-error process, and improves control efficiency. Furthermore, it uses a motor monitoring device and a vector voltage-time signal group to adaptively fine-tune the preliminary harmonic current data group, further enhancing the suppression of electromagnetic noise. Based on the target harmonic signal group, harmonics are injected into the noisy brushless motor to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor. It can be seen that this embodiment of the invention achieves active cancellation of specific-order electromagnetic force waves by equating harmonic currents to voltage vector signals and injecting them at the front end of SVPWM. Without interfering with the FOC current closed-loop stability, it effectively reduces motor vibration and electromagnetic noise, achieving electromagnetic noise suppression of the brushless motor.Therefore, the present invention can reduce the electromagnetic noise level of brushless motors. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a brushless motor electromagnetic noise suppression method based on harmonic current injection, provided in an embodiment of the present invention. Figure 2 This is a functional block diagram of a brushless motor electromagnetic noise suppression system based on harmonic current injection, provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of an electronic device that implements the electromagnetic noise suppression method for brushless motors based on harmonic current injection, according to an embodiment of the present invention.

[0020] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0021] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0023] This application provides a method for suppressing electromagnetic noise in brushless motors based on harmonic current injection. The execution entity of this method includes, but is not limited to, at least one electronic device configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or server device, and the software may be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0024] Reference Figure 1 The diagram shown is a flowchart illustrating a brushless motor electromagnetic noise suppression method based on harmonic current injection according to an embodiment of the present invention. In this embodiment, the brushless motor electromagnetic noise suppression method based on harmonic current injection includes: S1. The noise-inhibiting brushless motor and motor monitoring device were identified. The motor monitoring device includes: a soundproof motor box, a recording microphone, a vibration sensor and a Hall sensor. The noise-inhibiting brushless motor includes: an FOC microcontroller and a mechanical rotor.

[0025] For example, the brushless motor inside a CNC machine tool in a factory frequently generates electromagnetic noise. It is now necessary to reduce the electromagnetic noise generated by the brushless motor through harmonic current injection. This brushless motor whose electromagnetic noise needs to be reduced is the noisy brushless motor. Specific methods of harmonic current injection are detailed in subsequent embodiments.

[0026] It should be explained that the aforementioned noisy brushless motor includes: an FOC microcontroller and a mechanical rotor. The mechanical rotor is the rotor in the brushless motor, and the FOC microcontroller is the microcontroller that performs Field Oriented Control (FOC) in the brushless motor. The field-oriented control process is as follows: the microcontroller acquires the three-phase stator current of the brushless motor: i a i b andi c The three-phase stator current in the three-phase stationary coordinate system is transformed to the two-phase stationary coordinate system (α-β coordinate system) by Clarke transformation, thus obtaining i α andi β The electrical angle of the brushless motor is obtained, and based on the electrical angle, the current i in the two-phase stationary coordinate system is transformed using Park transformation. α andi β Transform to a two-phase rotating coordinate system (dq coordinate system) that rotates synchronously with the magnetic field of the mechanical rotor to obtain the direct-axis current i. d and cross-axis current i q Then, the direct-axis current reference value and the quadrature-axis current reference value are confirmed respectively, and the direct-axis current reference value and i are calculated respectively. d Between and the quadrature axis current reference quantity and i q The current deviation between the two is calculated and adjusted by a proportional-integral (PI) controller, outputting a voltage reference value v in the dq coordinate system. d and v q Then, the voltage reference value v in the dq coordinate system is obtained through the inverse Park transformation. d and v q Inverse transformation back to the α-β coordinate system yields v α and v β Finally, through the Space Vector Pulse Width Modulation (SVPWM) algorithm, using v α and v β Six PWM drive signals are generated to control the on / off state of the power switching transistors, thereby applying three-phase voltage to the three-phase windings of the brushless motor and driving the brushless motor to operate. The above-mentioned field-oriented control process is a publicly available prior art, and will not be described in detail here. In this embodiment of the invention, the reduction of electromagnetic noise generated by the brushless motor through harmonic current injection refers to: using the space vector pulse width modulation (SVPWM) algorithm, utilizing v... α and vβ Before generating the six PWM drive signals, the voltage vector: v α and v β The correction process involves superimposing the calculated harmonic voltage components onto the initial voltage vector to obtain a corrected voltage vector: a target first voltage signal and a target second voltage signal. The corrected voltage vector is then input to SVPWM to generate a PWM drive signal to drive the brushless motor. For the specific application of the target first voltage signal and the target second voltage signal, please refer to the following embodiments.

[0027] It should be understood that, by performing harmonic correction on the voltage vector before space vector pulse width modulation, the embodiments of the present invention suppress the generation of electromagnetic force harmonics at the source of electromagnetic energy conversion, thereby fundamentally suppressing the electromagnetic noise caused by electromagnetic force in brushless motors.

[0028] It should be explained that the motor monitoring device is a device that integrates a soundproof motor box, a recording microphone, a vibration sensor, and a Hall sensor. The soundproof motor box is a type of soundproof box, the recording microphone is a microphone used to collect noise signals generated by the noisy brushless motor, the vibration sensor is a sensor used to measure the vibration amplitude of the noisy brushless motor, and the Hall sensor is a Hall effect sensor.

[0029] S2. Obtain motor data for the noisy brushless motor, including: operating speed, number of motor pole pairs, and number of motor slots.

[0030] For example, the brushless motor in a CNC machine tool in a factory is usually set to a fixed speed and runs continuously during operation. The speed set for the brushless motor during operation is the working speed.

[0031] It should be explained that the number of pole pairs and the number of slots refer to the number of pole pairs in a noisy brushless motor and the number of slots on the stator core of a noisy brushless motor for embedding coils, respectively.

[0032] S3. Obtain the electrical angle time signal and vector voltage time signal group of the noisy brushless motor based on the operating speed, and obtain the vector voltage amplitude based on the vector voltage time signal group.

[0033] Specifically, the method for acquiring the electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor based on its operating speed includes: Start the noisy brushless motor and set the speed of the started noisy brushless motor to the operating speed to obtain the running brushless motor; The mechanical rotation angle signal of the mechanical rotor in a running brushless motor is read using a pre-built position sensor; The electrical angle-time signal is calculated based on the mechanical rotation angle signal and the number of motor pole pairs. The calculation formula is as follows: ; in, It is an electrical angle-time signal. This is a mechanical rotation angle signal. This represents the number of pole pairs of the motor. Read the first voltage signal and the second voltage signal from the FOC microcontroller that is running the brushless motor; The first voltage signal and the second voltage signal are combined to obtain the vector voltage time signal group.

[0034] It should be explained that the position sensor is an angle sensor. Reading the mechanical rotation angle signal of the mechanical rotor in the brushless motor using a pre-built position sensor means: using the angle sensor to read the angle change of the mechanical rotor during rotation in real time, thereby obtaining the mapping relationship between the mechanical angle of the mechanical rotor during rotation and time. The mapping relationship between the mechanical angle and time is output as an electrical signal to obtain the mechanical rotation angle signal. This electrical angle-time signal characterizes the mapping relationship between the electrical angle and time of the mechanical rotor during rotation in the brushless motor. It should be noted that all signals in this embodiment are functions of physical quantities changing with time.

[0035] It is understood that reading the first voltage signal and the second voltage signal from the FOC microcontroller running the brushless motor means reading the voltage vector signal input to SVPWM from the FOC microcontroller running the brushless motor at this time. The voltage component of the voltage vector signal on the α axis in the two-phase stationary coordinate system (α-β coordinate system) is the first voltage signal, and the voltage component of the voltage vector signal on the β axis in the two-phase stationary coordinate system (α-β coordinate system) is the second voltage signal.

[0036] It should be explained that the vector voltage amplitude refers to the amplitude of the first voltage signal in the vector voltage time signal group.

[0037] S4. Use a motor monitoring device to perform noise analysis on the brushless motor to obtain the motor noise signal. Perform spectral characteristic analysis on the motor noise signal to obtain the noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency.

[0038] In detail, the method of using a motor monitoring device to perform noise analysis on the brushless motor and obtain the motor noise signal includes: The noise-reducing brushless motor is placed into a soundproof motor box to obtain a soundproof brushless motor; Start the soundproof brushless motor and set the speed of the started soundproof brushless motor to the working speed to obtain the test brushless motor; The recording microphone in the motor monitoring device is used to collect and test the motor noise signal of the brushless motor.

[0039] It should be explained that the use of the recording microphone in the motor monitoring device to collect the motor noise signal of the brushless motor means that the recording microphone is used to collect the sound signal generated by the brushless motor over a period of time. This sound signal is the motor noise signal. When the recording microphone collects the motor noise signal of the brushless motor, it is necessary to keep the recording microphone in close contact with the surface of the brushless motor housing.

[0040] In detail, the spectral characteristic analysis of the motor noise signal to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency includes: The motor noise signal is processed by FFT to obtain the noise signal spectrum; Multiple local spectral peak frequencies were identified based on the noise signal spectrum. For each of the multiple local spectral peak frequencies, perform the following operation: The candidate order is calculated based on the local spectral peak frequency, operating speed, and number of motor pole pairs, using the following formula: ; in, For the order to be selected, For local spectral peak frequencies, Operating speed; By summing up the candidate orders, we obtain multiple candidate orders; The first test speed and the second test speed are determined based on the preset first multiplier value, the preset second multiplier value, and the working speed. The first test speed is the product of the first multiplier value and the working speed, and the second test speed is the product of the second multiplier value and the working speed. Multiple first spectral peak frequencies were identified based on the soundproof brushless motor and the first test speed, and multiple second spectral peak frequencies were identified based on the soundproof brushless motor and the second test speed. For each of the multiple candidate orders, perform the following operation: Multiply the local spectral peak frequency corresponding to the order to be selected by the first multiplier to obtain the first amplification frequency; A first frequency range is determined based on a preset frequency selection interval and a first amplification frequency. The minimum value of the first frequency range is the absolute difference between the first amplification frequency and the frequency selection interval, and the maximum value of the first frequency range is the sum of the first amplification frequency and the frequency selection interval. The second frequency range is determined based on the local spectral peak frequency corresponding to the candidate order, the second multiple, and the frequency selection interval. Determine whether there is a first spectral peak frequency within the first frequency range among multiple first spectral peak frequencies; If there is a first spectral peak frequency among the multiple first spectral peak frequencies that is located within the first frequency range, then determine whether there is a second spectral peak frequency among the multiple second spectral peak frequencies that is located within the second frequency range. If there is a second spectral peak frequency within the second frequency range among multiple second spectral peak frequencies, then the order to be selected is recorded as the selectable order; By summing the possible orders, multiple possible orders can be obtained; For each of the multiple optional orders, perform the following operation: Round the optional order to the nearest integer to obtain the integer order. The order difference is calculated based on the optional order and the rounding order, where the order difference is the absolute difference between the optional order and the rounding order. Summarize the order integer differences to obtain multiple order integer differences, and take the floor order corresponding to the smallest order integer difference among the multiple order integer differences as the noise order; The local spectral peak frequency corresponding to the noise order is taken as the electromagnetic characteristic frequency. The amplitude of electromagnetic noise is determined in the noise signal spectrum based on the electromagnetic characteristic frequency.

[0041] It should be explained that the FFT processing of the motor noise signal refers to performing a Fast Fourier Transform on the motor noise signal. The identification of multiple local spectral peak frequencies based on the noise signal spectrum means that multiple spectral peaks in the noise signal spectrum are first identified, and the frequency corresponding to the highest point of each peak is the local spectral peak frequency. For example, if the discrete noise signal spectrum is considered as a continuous function, then the spectral peak appears at the position where the first derivative of the continuous function is zero and the second derivative is negative.

[0042] Understandably, the first and second multipliers are values ​​manually set by the technician controlling the brushless motor in the factory, used to adjust the speed of the soundproof brushless motor. Optionally, the first multiplier is 2 and the second multiplier is 3. The methods for determining multiple first spectral peak frequencies based on the soundproof brushless motor and the first test speed, and the methods for determining multiple second spectral peak frequencies based on the soundproof brushless motor and the second test speed, are the same as the methods for obtaining multiple local spectral peak frequencies using the soundproof brushless motor and the operating speed, and will not be repeated here. The frequency selection interval is a frequency manually set by the technician controlling the brushless motor in the factory; optionally, the frequency selection interval is 30 Hz. The method for determining the second frequency range based on the local spectral peak frequency corresponding to the candidate order, the second multiplier, and the frequency selection interval is the same as the method for obtaining the first frequency range using the local spectral peak frequency corresponding to the candidate order, the first multiplier, and the frequency selection interval, and will not be repeated here.

[0043] It should be explained that rounding the selectable order to the nearest integer means rounding the decimal part of the selectable order to the nearest integer. For example, if the selectable order is 6.1, then rounding the selectable order to the nearest integer will result in an integer order of 6. Determining the electromagnetic noise amplitude based on the electromagnetic characteristic frequency in the noise signal spectrum means using the electromagnetic characteristic frequency as the abscissa and recording the value of the ordinate of the corresponding point in the noise signal spectrum as the electromagnetic noise amplitude.

[0044] It should be understood that the embodiments of the present invention find the spectral peak frequency that changes proportionally with the rotational speed by changing the rotational speed. Since the frequency of electromagnetic noise is proportional to the electrical angular frequency, the spectral peak frequency that changes proportionally with the rotational speed can be determined as the main frequency of electromagnetic noise in the brushless motor. The electrical angular frequency is equal to the angular velocity of the rotor in the brushless motor multiplied by the number of pole pairs of the motor. The noise order characterizes the number of structural vibrations that cause electromagnetic noise when the rotor in the brushless motor completes one electrical angular rotation (the electrical angle of rotation reaches 2π). For example, if the noise order is 6, then after the rotor in the brushless motor completes one electrical angular rotation, the structure causing electromagnetic noise completes 6 periodic vibrations. It should be noted that the electromagnetic noise usually originates from the structural vibration caused by electromagnetic force fluctuations in the air gap of the brushless motor. The various orders of the electromagnetic force are not directly determined by a single order magnetic field, but are formed by the coupling between the fundamental magnetic field and the higher harmonic magnetic field. The fundamental magnetic field and the higher harmonic magnetic field are determined by the stator current in the brushless motor. Therefore, when there are harmonic components of a specific order in the current, corresponding magnetic field harmonics will be formed in the air gap, which will then generate force wave components of the corresponding order in the electromagnetic force, thereby further exciting the motor structure to generate vibration and noise. Specifically, when the noise order is k, the k-th order electromagnetic force component that generates the electromagnetic noise can usually be formed by the coupling effect between the fundamental magnetic field (order 1) and the adjacent order magnetic field components. The adjacent order is preferably k±1. Based on this coupling relationship, in subsequent embodiments, the voltage harmonic component of order k±1 is injected by the FOC microcontroller, which can modulate the corresponding magnetic field harmonic, thereby indirectly controlling or canceling the k-th order electromagnetic force component, thereby achieving effective suppression of electromagnetic noise. Therefore, in subsequent embodiments, the noise order is increased by one as the harmonic order increase and the noise order is decreased by one as the harmonic order decrease.

[0045] S5. Based on the noise order, electromagnetic characteristic frequency and electrical angle-time signal, perform phase-sensitive detection on the motor noise signal to obtain the relative phase of the motor and the sound.

[0046] In detail, the step of performing phase-sensitive detection on the motor noise signal based on the noise order, electromagnetic characteristic frequency, and electrical angle-time signal to obtain the relative phase of the motor and the sound source includes: The electromagnetic frequency range is determined based on the frequency selection interval and electromagnetic characteristic frequency. The motor noise signal is filtered based on the electromagnetic frequency range to obtain the filtered noise signal. A first reference signal and a second reference signal are constructed based on the noise order, the filtered noise signal, and the electrical angle-time signal, as shown below: ; in, As the first reference signal, As the second reference signal, To filter noise signals, Noise level, It is an electrical angle-time signal. Refers to the sine function. Refers to the cosine function; The first reference signal is sampled at equal intervals based on a preset sampling interval and a preset number of samples to obtain multiple first sampling points. The number of first sampling points among the multiple first sampling points is the number of samples. The first sampling point includes: a first sample value. The first moving average is calculated based on multiple first sampling points, and the calculation formula is as follows: ; in, The first moving average, The number of samples, For multiple first sampling points, the first The first sampled value of the first sampling point; The second moving average value is obtained based on the sampling interval, the number of samples, and the second reference signal; The relative phase of the audio equipment is calculated based on the first and second sliding average values, using the following formula: ; in, The relative phase of the audio equipment. and These are the first moving average and the second moving average, respectively. The preset value of pi. It is the arctangent function.

[0047] It should be explained that the method for determining the electromagnetic frequency range based on the frequency selection interval and electromagnetic characteristic frequency is the same as the method for determining the first frequency range based on the preset frequency selection interval and the first amplification frequency, and will not be repeated here. The filtering of the motor noise signal based on the electromagnetic frequency range to obtain the filtered noise signal refers to: performing bandpass filtering on the motor noise signal based on the electromagnetic frequency range, retaining the signals in the motor noise signal that are within the electromagnetic frequency range; this signal is the filtered noise signal.

[0048] For example, if the sampling interval is 0.1 milliseconds and the number of samples is 100, then the first reference signal is sampled every 0.1 milliseconds starting from the initial time, sequentially acquiring the first first sampling point (0.1 milliseconds, y1), the second first sampling point (0.2 milliseconds, y2), ..., the 100th first sampling point (10 milliseconds, y100), ultimately obtaining 100 first sampling points. Here, y1, y2, and y100 refer to the first sampled value of the first sampling point, the first sampled value of the second sampling point, and the first sampled value of the 100th sampling point, respectively, and y1, y2, and y100 specifically represent the first reference signal. The values ​​corresponding to t=0.1ms, t=0.2ms and t=10ms, where ms refers to milliseconds and t refers to time.

[0049] It should be explained that the method for obtaining the second moving average based on the sampling interval, the number of samples, and the second reference signal is the same as the method for obtaining the first moving average using the sampling interval, the number of samples, and the first reference signal, and will not be repeated here.

[0050] Understandably, since the electromagnetic noise of a brushless motor is caused by electromagnetic force fluctuations due to harmonic components in the electrical signal controlling the motor (e.g., the voltage vector signal input to SVPWM), the relative phase of the motor characterizes the phase difference between the filtered noise signal and the electrical signal that caused the filtered noise signal, reflecting their relative time delay.

[0051] S6. Based on the pre-constructed harmonic current model, harmonic prediction is performed on the noise order, electromagnetic noise amplitude, relative phase of the sound machine, motor data and vector voltage amplitude to obtain a preliminary harmonic current data set, which includes: the amplitude of the rising harmonic, the phase of the rising harmonic, the amplitude of the falling harmonic, and the phase of the falling harmonic.

[0052] In detail, before obtaining the preliminary harmonic current data set by performing harmonic prediction on the noise order, electromagnetic noise amplitude, relative phase of the audio equipment, motor data, and vector voltage amplitude based on the pre-constructed harmonic current model, the process also includes: Multiple historical motor data and multiple historical harmonic control data are acquired. The historical motor data includes: historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude. The historical harmonic control data includes: historical rising harmonic amplitude, historical rising harmonic phase, historical falling harmonic amplitude, and historical falling harmonic phase. The historical motor data and the historical harmonic control data correspond one-to-one. The pre-built deep learning model was trained using multiple historical motor data and multiple historical harmonic regulation data to obtain the harmonic current model.

[0053] For example, when the brushless motor in this factory historically exhibited electromagnetic noise, the noise level, amplitude, and relative phase of the motor at each historical point of electromagnetic noise generation were recorded to obtain historical noise level, amplitude, and relative phase. Additionally, the motor's operating speed, number of pole pairs, number of slots, and vector voltage amplitude were recorded to obtain historical operating speed, number of pole pairs, number of slots, and voltage amplitude. These historical data were then summarized to obtain historical motor data. If the noise order is 6, then the technicians in the factory, through manual testing (e.g., continuously trying various harmonic currents with different amplitudes and phases to inject, ultimately finding the harmonic current that reduces electromagnetic noise the most), found that the harmonic currents with the best electromagnetic noise reduction effect after injection are: the 5th order harmonic current and the 7th order harmonic current. The amplitude of the 7th order harmonic current is the historical amplitude of the rising harmonic, and the phase of the 7th order harmonic current is the historical phase of the rising harmonic. The amplitude of the 5th order harmonic current is the historical amplitude of the falling harmonic, and the phase of the 5th order harmonic current is the historical phase of the falling harmonic. For example, if the signal corresponding to the 7th order harmonic current is: ),in, The signal corresponding to the harmonic current. If the electrical angle-time signal corresponding to this brushless motor in history is given, then... This is the amplitude of the harmonic current. This refers to the phase of the harmonic current. Historical up-order harmonic amplitudes, phases, down-order harmonic amplitudes, and phases are summarized to obtain historical harmonic control data. Finally, historical motor data and historical harmonic control data corresponding to multiple brushless motors that generated electromagnetic noise are summarized and statistically analyzed to obtain multiple historical motor data and multiple historical harmonic control data. Since one brushless motor corresponds to one historical motor data and one historical harmonic control data, there is a one-to-one correspondence between the historical motor data and the historical harmonic control data.

[0054] It should be understood that the aforementioned harmonic current injection does not mean directly superimposing the harmonic current signal onto the direct-axis current reference and quadrature-axis current reference to control the brushless motor (if the harmonic current signal is superimposed onto the direct-axis current reference and quadrature-axis current reference, it will change the direct-axis current reference and quadrature-axis current reference from DC to AC, causing current loop instability). Instead, the harmonic current signal to be injected is first equivalently transformed into a voltage vector signal through field-oriented control (FOC) and then input into the SVPWM in the FOC microcontroller to generate a PWM drive signal to drive the brushless motor.

[0055] Optionally, the deep learning model is a multilayer perceptron.

[0056] Understandably, training the pre-built deep learning model using multiple historical motor data and multiple historical harmonic control data refers to the following: First, the historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical motor pole pair number, historical motor slot number, and historical voltage amplitude from the historical motor data are used as input data for training samples. The historical rising harmonic amplitude, historical rising harmonic phase, historical falling harmonic amplitude, and historical falling harmonic phase from the historical harmonic control data are used as output data for training samples. Since there is a one-to-one correspondence between historical motor data and historical harmonic control data, a single historical motor data point is combined with its corresponding historical harmonic control data to form a set of training samples. This process involves summarizing training samples to obtain a training sample set. Based on this training sample set, the deep learning model is iteratively trained. The model gradually adjusts the network parameters by optimizing the loss function (e.g., mean square error, weighted error, etc.) so that the model can learn the mapping relationship between (historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude) and (historical rising harmonic amplitude, historical rising harmonic phase, historical falling harmonic amplitude, and historical falling harmonic phase). The deep learning model after training is the harmonic current model. The training process of the above model is existing technology, and the embodiments of the present invention will not be described in detail here. After the model training is completed, when the noise order, electromagnetic noise amplitude, relative phase of the sound machine, operating speed in the motor data, number of motor pole pairs in the motor data, and vector voltage amplitude are respectively input into the harmonic current model as historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude, the harmonic current model can output the predicted rising harmonic amplitude (corresponding to historical rising harmonic amplitude), rising harmonic phase (corresponding to historical rising harmonic phase), falling harmonic amplitude (corresponding to historical falling harmonic amplitude), and falling harmonic phase (corresponding to historical falling harmonic phase).

[0057] It should be explained that the preliminary harmonic current data set obtained by predicting the noise order, electromagnetic noise amplitude, relative phase of the sound machine, motor data, and vector voltage amplitude based on the pre-constructed harmonic current model means that the noise order, electromagnetic noise amplitude, relative phase of the sound machine, operating speed in the motor data, number of motor pole pairs in the motor data, and vector voltage amplitude are respectively input into the harmonic current model as historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude. The harmonic current model can then output the predicted rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude, and falling harmonic phase, and summarize the rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude, and falling harmonic phase to obtain the preliminary harmonic current data set.

[0058] S7. Based on the motor monitoring device and the vector voltage time signal group, the preliminary harmonic current data group is adaptively fine-tuned to obtain the target harmonic signal group.

[0059] In detail, the adaptive fine-tuning of the preliminary harmonic current data set based on the motor monitoring device and the vector voltage-time signal set to obtain the target harmonic signal set includes: Acquire the electrical data of the motor, including: motor angular velocity, motor stator resistance, and motor inductance; The electric angular velocity is calculated based on the motor angular velocity and the number of motor pole pairs, where the electric angular velocity is the product of the motor angular velocity and the number of motor pole pairs; The harmonic order of up-order and harmonic order of down-order are determined based on the noise order. Based on the harmonic order, the motor stator resistance, motor inductance, electric angular velocity, and the increased harmonic amplitude and phase in the preliminary harmonic current data set, a first and a second increased voltage signal are constructed. The first and second increased voltage signals are shown below: ; in, and These are the first and second raised-order voltage signals, respectively. For the amplitude of the higher harmonic, For the rising harmonic phase, , and These are the motor stator resistance, motor inductance, and electric angular velocity, respectively. For the order of harmonics, It is an electrical angle-time signal. Refers to the sine function. Cosine function The arctangent function; The first and second reduced-order voltage signals are obtained based on the reduced-order order of the harmonics, the stator resistance, inductance, and angular velocity of the motor in the electrical data of the motor, the amplitude and phase of the reduced-order harmonics in the preliminary harmonic current data set. A first injection voltage signal and a second injection voltage signal are constructed based on the first raised-order voltage signal, the second raised-order voltage signal, the first lowered-order voltage signal, the second lowered-order voltage signal, and the first and second voltage signals in the vector voltage time signal group. The first injection voltage signal and the second injection voltage signal are as follows: ; in, and These are the first injection voltage signal and the second injection voltage signal, respectively. and These are the first voltage signal and the second voltage signal, respectively. and These are the first reduced-order voltage signal and the second reduced-order voltage signal, respectively; Based on the FOC microcontroller, the first injection voltage signal and the second injection voltage signal, the noise brushless motor is voltage controlled to obtain the initial control brushless motor; The target harmonic signal group is obtained by adaptively fine-tuning the initial control brushless motor using a motor monitoring device.

[0060] It should be explained that the motor angular velocity refers to the angular velocity of the rotor of the brushless motor when it rotates at the operating speed; the motor stator resistance refers to the resistance value of the stator winding of the brushless motor; and the motor inductance refers to the magnitude of the inductance generated by the rotor of the brushless motor when it rotates at the operating speed. Determining the harmonic order increase and decrease based on the noise order means: adding one to the noise order yields the harmonic order increase, and subtracting one from the noise order yields the harmonic order decrease.

[0061] It is understood that the method for obtaining the first and second reduced-order voltage signals based on the harmonic reduction order, the motor stator resistance, motor inductance, electric angular velocity, and the reduced-order harmonic amplitude and phase in the preliminary harmonic current data set is the same as the method for constructing the first and second increased-order voltage signals based on the harmonic increase order, the motor stator resistance, motor inductance, electric angular velocity, and the increased-order harmonic amplitude and phase in the preliminary harmonic current data set. Therefore, it will not be described in detail here.

[0062] It should be understood that the voltage control of the noisy brushless motor based on the FOC microcontroller, the first injected voltage signal, and the second injected voltage signal to obtain the initial control brushless motor means that the first injected voltage signal and the second injected voltage signal are used as voltage vector signals input to SVPWM in the FOC microcontroller to generate PWM drive signals to drive the brushless motor. The first injected voltage signal is the voltage component of the voltage vector signal on the α axis in the two-phase stationary coordinate system (α-β coordinate system), and the second injected voltage signal is the voltage component of the voltage vector signal on the β axis in the two-phase stationary coordinate system (α-β coordinate system). The noisy brushless motor that operates according to the first injected voltage signal and the second injected voltage signal is the initial control brushless motor.

[0063] In detail, the adaptive fine-tuning of the initial control brushless motor using a motor monitoring device to obtain the target harmonic signal set includes: Based on the operating speed, the initial control brushless motor, and the soundproof motor box, the brushless motor was selected for evaluation. The recording microphone in the motor monitoring device is used to collect evaluation noise signals for the brushless motor. The evaluation noise amplitude is obtained based on the evaluation noise signal; The vibration sensor and the Hall sensor are both installed on the evaluated brushless motor to obtain a vibration sensor and a Hall sensor installed. The maximum amplitude of the brushless motor is obtained and evaluated based on the preset total acquisition time and the installed vibration sensor. The brushless motor is evaluated by acquiring multiple magnetic field strengths based on the total acquisition time, the preset acquisition time interval, and the installation of Hall sensors. The mean magnetic field strength is calculated based on multiple magnetic field strengths, where the mean magnetic field strength is the average of the multiple magnetic field strengths. The electromagnetic suppression index is calculated based on the evaluation noise amplitude, maximum amplitude, average magnetic field strength, and multiple magnetic field strengths. The amplitude of the raised harmonic is finely adjusted bidirectionally according to a preset amplitude percentage to obtain an increase in the raised amplitude and a decrease in the raised amplitude. The amplitude of the lower harmonic is increased and decreased based on the amplitude percentage and the lower harmonic amplitude. The raised harmonic phase is finely adjusted bidirectionally according to a preset fine-tuning angle to obtain an increase in the raised phase and a decrease in the raised phase. The decreased harmonic phase is obtained by adjusting the fine-tuning angle and the decreased harmonic phase. Based on increasing the amplitude of the order increase, increasing the amplitude of the order decrease, increasing the phase of the order increase, increasing the phase of the order decrease, the order of the order increase of the harmonics, the order of the order decrease of the harmonics, the motor stator resistance, the motor inductance, the electric angular velocity, and the FOC microcontroller, the first update voltage signal and the second update voltage signal are obtained. Based on the first updated voltage signal, the second updated voltage signal, and the noise level of the brushless motor, an additional evaluation motor was identified. Based on motor monitoring devices and by adding evaluation motors to obtain electromagnetic indices; The electromagnetic index is reduced by reducing the amplitude of the rising order, reducing the amplitude of the falling order, reducing the phase of the rising order, reducing the phase of the falling order, the order of the rising harmonics, the order of the falling harmonics, the stator resistance of the motor, the inductance of the motor, the electric angular velocity, the FOC microcontroller, the noise brushless motor and the motor monitoring device. Compare the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index; If the electromagnetic index is increased to the maximum value among the electromagnetic suppression index, the electromagnetic index increase, and the electromagnetic index decrease, then the increased electromagnetic index is used as the electromagnetic suppression index, and the increased up-order amplitude, increased down-order amplitude, increased up-order phase, and increased down-order phase are used as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively. Then return to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic index is reduced to the maximum value among the electromagnetic suppression index, the electromagnetic index is increased, and the electromagnetic index is reduced, then the reduced electromagnetic index is taken as the electromagnetic suppression index, and the reduced up-order amplitude, reduced down-order amplitude, reduced up-order phase, and reduced down-order phase are taken as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively, and the process returns to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic suppression index is the maximum value among the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index, then the first update voltage signal and the second update voltage signal corresponding to the electromagnetic suppression index are respectively used as the target first voltage signal and the target second voltage signal. By combining the first voltage signal and the second voltage signal of the target, the target harmonic signal group is obtained.

[0064] It should be explained that the method for identifying the brushless motor for evaluation based on the operating speed, initial control brushless motor, and soundproof motor box is the same as the method for obtaining the test brushless motor using the operating speed, noise level of the brushless motor, and soundproof motor box. The method for collecting the evaluation noise signal of the brushless motor using the recording microphone in the motor monitoring device is the same as the method for collecting the motor noise signal of the test brushless motor using the recording microphone in the motor monitoring device. The method for obtaining the evaluation noise amplitude based on the evaluation noise signal is the same as the method for obtaining the electromagnetic noise amplitude using the motor noise signal. These will not be elaborated further here.

[0065] For example, if the total acquisition time is 5 seconds, the maximum amplitude recorded by the vibration sensor during operation of the brushless motor within those 5 seconds is taken as the maximum amplitude. If the acquisition interval is 0.1 seconds, the magnetic field strength at the brushless motor housing is read every 0.1 seconds using a Hall sensor until the total acquisition time reaches 5 seconds, resulting in 50 magnetic field strength readings. If the amplitude percentage is 10% and the increased harmonic amplitude is 0.2 amps, the increased harmonic amplitude is finely adjusted bidirectionally according to the preset amplitude percentage, resulting in an increase of 0.2 + 0.2 × 10% = 0.22 amps and a decrease of 0.2 - 0.2 × 10% = 0.18 amps. If the fine-tuning angle is 2 degrees, the increased harmonic phase is 30 degrees. The phase of the raised harmonic is then finely adjusted bidirectionally according to the preset fine-tuning angle, resulting in an increase of 30+2=32 degrees in the raised phase and a decrease of 30-2=28 degrees in the raised phase.

[0066] It is understood that the method for obtaining the increase and decrease of the reduced-order phase based on the fine-tuning angle and the phase of the reduced-order harmonic is the same as the method for bidirectionally fine-tuning the amplitude of the increased-order harmonic according to a preset amplitude percentage to obtain the increase and decrease of the increased-order amplitude. The method for obtaining the increase and decrease of the reduced-order phase based on the fine-tuning angle and the phase of the reduced-order harmonic is the same as the method for bidirectionally fine-tuning the phase of the increased-order harmonic according to a preset fine-tuning angle to obtain the increase and decrease of the increased-order phase. Amplitude, increasing the reduced-order amplitude, increasing the increased-order phase, increasing the reduced-order phase, harmonic order increase, harmonic order decrease, motor stator resistance, motor inductance, electric angular velocity, and the method of obtaining the first and second updated voltage signals using an FOC microcontroller, and utilizing the increased-order harmonic amplitude, reduced-order harmonic amplitude, increased-order harmonic phase, reduced-order harmonic phase, harmonic order increase, harmonic order decrease, motor stator resistance, motor inductance, electric angular velocity, and the method of obtaining the first and second injected voltage signals using an FOC microcontroller. The methods are the same. The method of confirming the addition of the evaluation motor based on the first update voltage signal, the second update voltage signal, and the noise brushless motor is the same as the method of obtaining the initial control brushless motor using the first injection voltage signal, the second injection voltage signal, and the noise brushless motor. The method of obtaining the increased electromagnetic index based on the motor monitoring device and the added evaluation motor is the same as the method of obtaining the electromagnetic suppression index using the motor monitoring device and the initial control brushless motor. The method of obtaining the reduced electromagnetic index based on reducing the increase amplitude, reducing the decrease amplitude, reducing the increase phase, reducing the decrease phase, harmonic increase order, harmonic decrease order, motor stator resistance, motor inductance, electric angular velocity, FOC microcontroller, noise brushless motor, and motor monitoring device is the same as the method of obtaining the increased electromagnetic index using increasing the increase amplitude, increasing the decrease amplitude, increasing the increase phase, increasing the decrease phase, harmonic increase order, harmonic decrease order, motor stator resistance, motor inductance, electric angular velocity, FOC microcontroller, noise brushless motor, and motor monitoring device. These methods will not be described in detail here.

[0067] It should be understood that, in this embodiment of the invention, the initial harmonic current data set that can initially suppress electromagnetic noise is first predicted by the harmonic current model, and then the initial harmonic current data set is adaptively fine-tuned to find the target harmonic signal set that is most ideal for suppressing electromagnetic noise. Compared with the conventional method of continuously trying to inject various harmonic currents with different amplitudes and phases to finally find the harmonic current that reduces electromagnetic noise the most, this embodiment of the invention has a higher efficiency in obtaining the target harmonic signal set and a better effect in suppressing electromagnetic noise.

[0068] In detail, the formula for calculating the electromagnetic suppression index is as follows: ; in, Electromagnetic suppression index, The first of multiple magnetic field strengths One magnetic field strength, The mean magnetic field strength This refers to the number of magnetic field strengths among multiple magnetic field strengths. To evaluate the noise amplitude, For maximum amplitude, It is a natural constant.

[0069] Understandably, the electromagnetic suppression index reflects the effect of suppressing electromagnetic noise caused by electromagnetic force fluctuations within the noisy brushless motor after voltage control is applied using the first and second injection voltage signals. A higher electromagnetic suppression index indicates better suppression of electromagnetic noise. It should be noted that when calculating the electromagnetic suppression index, multiple magnetic field strengths, evaluation noise amplitudes, and maximum amplitudes are only substituted with numerical values, without considering their dimensions.

[0070] S8. Based on the target harmonic signal group, harmonic injection is performed on the noisy brushless motor to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor.

[0071] It should be explained that the phrase "injecting harmonics into the noisy brushless motor based on the target harmonic signal group to obtain a noise-suppressed motor" refers to: using an FOC microcontroller, the target first voltage signal, and the target second voltage signal in the target harmonic signal group to perform voltage control on the noisy brushless motor to obtain a noise-suppressed motor. Furthermore, the method of using an FOC microcontroller, the target first voltage signal, and the target second voltage signal in the target harmonic signal group to perform voltage control on the noisy brushless motor to obtain a noise-suppressed motor is the same as the method of using an FOC microcontroller, the first injection voltage signal, and the second injection voltage signal to perform voltage control on the noisy brushless motor to obtain a primary control brushless motor, and will not be repeated here.

[0072] For example, after the factory re-controls the noisy brushless motor by using the modified voltage vector signal, namely the target first voltage signal and the target second voltage signal in the target harmonic signal group, it effectively reduces the electromagnetic noise caused by the electromagnetic force fluctuation inside the noisy brushless motor and completes the electromagnetic noise suppression of the brushless motor.

[0073] To address the problems described in the background section, this invention identifies a noisy brushless motor and a motor monitoring device. The motor monitoring device includes a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noisy brushless motor includes an FOC microcontroller and a mechanical rotor. This invention provides a complete equipment foundation for subsequent noise analysis by pre-identifying the noisy brushless motor and the motor monitoring device, thereby acquiring motor data, including operating speed, number of pole pairs, and number of slots. Based on the operating speed, the electrical angle-time signal and vector voltage-time signal set of the noisy brushless motor are obtained. The vector voltage amplitude is then obtained from the vector voltage-time signal set. This invention demonstrates that... By acquiring initial data of the brushless motor during operation, initial data references are provided for subsequent harmonic injection into the noisy brushless motor. Noise analysis is performed on the noisy brushless motor using a motor monitoring device to obtain the motor noise signal. Spectral feature analysis is then performed on the motor noise signal to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Based on the noise order, electromagnetic characteristic frequency, and electrical angle-time signal, phase-sensitive detection is performed on the motor noise signal to obtain the relative phase between the motor and the noise source. It is evident that this embodiment of the invention, through spectral decomposition of the noise signal, extracts the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency, achieving quantitative identification of the electromagnetic noise components in the motor noise signal and clearly defining the target harmonic order to be suppressed, thereby improving the accuracy of the control strategy. By calculating the relative phase of the sound equipment, phase cancellation can be achieved during harmonic injection, improving noise suppression. Based on a pre-constructed harmonic current model, harmonic prediction is performed on the noise order, electromagnetic noise amplitude, relative phase of the sound equipment, motor data, and vector voltage amplitude to obtain a preliminary harmonic current data set. This preliminary harmonic current data set includes: increased harmonic amplitude, increased harmonic phase, decreased harmonic amplitude, and decreased harmonic phase. The preliminary harmonic current data set is adaptively fine-tuned based on the motor monitoring device and the vector voltage time signal set to obtain the target harmonic signal set. Therefore, this embodiment of the invention, by introducing a pre-constructed harmonic current model, fuses and models the noise order, electromagnetic noise amplitude, relative phase of the sound equipment, motor data, and vector voltage amplitude, thereby improving noise suppression. The invention makes preliminary predictions of harmonic currents to suppress electromagnetic noise, improves the initial accuracy of harmonic current compensation, reduces the trial-and-error process, and improves control efficiency. Furthermore, it uses a motor monitoring device and a vector voltage-time signal group to adaptively fine-tune the preliminary harmonic current data group, further enhancing the suppression of electromagnetic noise. Based on the target harmonic signal group, harmonics are injected into the noisy brushless motor to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor. It can be seen that this embodiment of the invention achieves active cancellation of specific-order electromagnetic force waves by equating harmonic currents to voltage vector signals and injecting them at the front end of SVPWM. Without interfering with the FOC current closed-loop stability, it effectively reduces motor vibration and electromagnetic noise, achieving electromagnetic noise suppression of the brushless motor.Therefore, the present invention can reduce the electromagnetic noise level of brushless motors.

[0074] like Figure 2 The diagram shown is a functional block diagram of a brushless motor electromagnetic noise suppression system based on harmonic current injection provided in an embodiment of the present invention.

[0075] The harmonic current injection-based brushless motor electromagnetic noise suppression system 100 of this invention can be installed in electronic devices. Depending on the functions implemented, the harmonic current injection-based brushless motor electromagnetic noise suppression system 100 may include a brushless motor verification module 101, a motor data acquisition module 102, a motor noise analysis module 103, and a motor noise suppression module 104. The module described in this invention can also be called a unit, referring to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0076] The brushless motor confirmation module 101 is used to confirm the noisy brushless motor and the motor monitoring device. The motor monitoring device includes: a soundproof motor box, a recording microphone, a vibration sensor and a Hall sensor. The noisy brushless motor includes: an FOC microcontroller and a mechanical rotor. The motor data acquisition module 102 is used to acquire motor data of the noisy brushless motor. The motor data includes: operating speed, number of motor pole pairs and number of motor slots. Based on the operating speed, the module acquires the electrical angle time signal and vector voltage time signal group of the noisy brushless motor, and acquires the vector voltage amplitude based on the vector voltage time signal group. The motor noise analysis module 103 is used to perform noise analysis on the brushless motor using a motor monitoring device to obtain the motor noise signal, perform spectral feature analysis on the motor noise signal to obtain the noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, and perform phase-sensitive detection on the motor noise signal based on the noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of the motor. The motor noise suppression module 104 is used to predict the noise order, electromagnetic noise amplitude, relative phase between the motor and the sound source, motor data, and vector voltage amplitude based on a pre-constructed harmonic current model, and obtain a preliminary harmonic current data set. The preliminary harmonic current data set includes: the amplitude of the higher harmonic, the phase of the higher harmonic, the amplitude of the lower harmonic, and the phase of the lower harmonic. The preliminary harmonic current data set is adaptively fine-tuned based on the motor monitoring device and the vector voltage time signal set to obtain a target harmonic signal set. Harmonic injection is performed on the noisy brushless motor based on the target harmonic signal set to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor.

[0077] In detail, the modules in the brushless motor electromagnetic noise suppression system 100 based on harmonic current injection described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the electromagnetic noise suppression method for brushless motors based on harmonic current injection described above, and can produce the same technical effect, so it will not be repeated here.

[0078] like Figure 3 The diagram shown is a schematic representation of an electronic device that implements a method for suppressing electromagnetic noise in a brushless motor based on harmonic current injection, according to an embodiment of the present invention.

[0079] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a program for a method to suppress electromagnetic noise of a brushless motor based on harmonic current injection.

[0080] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a brushless motor electromagnetic noise suppression method based on harmonic current injection, but also to temporarily store data that has been output or will be output.

[0081] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a program for suppressing electromagnetic noise in a brushless motor based on harmonic current injection) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0082] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0083] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0084] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0085] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0086] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0087] The program for the brushless motor electromagnetic noise suppression method based on harmonic current injection, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: The noise-inhibiting brushless motor and motor monitoring device were identified. The motor monitoring device includes: a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noise-inhibiting brushless motor includes: an FOC microcontroller and a mechanical rotor. Obtain motor data for a noisy brushless motor, including: operating speed, number of pole pairs, and number of slots. The electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor are obtained based on the operating speed, and the vector voltage amplitude is obtained based on the vector voltage-time signal group. Noise analysis of a brushless motor is performed using a motor monitoring device to obtain the motor noise signal. Spectral characteristic analysis of the motor noise signal is then performed to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Phase-sensitive detection of motor noise signal is performed based on noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of sound and motor; Based on the pre-constructed harmonic current model, harmonic prediction is performed on noise order, electromagnetic noise amplitude, relative phase of sound equipment, motor data and vector voltage amplitude to obtain a preliminary harmonic current data set, which includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude and falling harmonic phase. Based on the motor monitoring device and the vector voltage time signal group, the preliminary harmonic current data group is adaptively fine-tuned to obtain the target harmonic signal group; By injecting harmonics into a noisy brushless motor based on a target harmonic signal group, a noise-suppressed motor is obtained, thus completing the electromagnetic noise suppression of the brushless motor.

[0088] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0089] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0090] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: The noise-inhibiting brushless motor and motor monitoring device were identified. The motor monitoring device includes: a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noise-inhibiting brushless motor includes: an FOC microcontroller and a mechanical rotor. Obtain motor data for a noisy brushless motor, including: operating speed, number of pole pairs, and number of slots. The electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor are obtained based on the operating speed, and the vector voltage amplitude is obtained based on the vector voltage-time signal group. Noise analysis of a brushless motor is performed using a motor monitoring device to obtain the motor noise signal. Spectral characteristic analysis of the motor noise signal is then performed to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Phase-sensitive detection of motor noise signal is performed based on noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of sound and motor; Based on the pre-constructed harmonic current model, harmonic prediction is performed on noise order, electromagnetic noise amplitude, relative phase of sound equipment, motor data and vector voltage amplitude to obtain a preliminary harmonic current data set, which includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude and falling harmonic phase. Based on the motor monitoring device and the vector voltage time signal group, the preliminary harmonic current data group is adaptively fine-tuned to obtain the target harmonic signal group; By injecting harmonics into a noisy brushless motor based on a target harmonic signal group, a noise-suppressed motor is obtained, thus completing the electromagnetic noise suppression of the brushless motor.

[0091] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0092] The modules described as separate components may or may not be physically separate. The components shown as modules 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 modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0094] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for suppressing electromagnetic noise in a brushless motor based on harmonic current injection, characterized in that, The method includes: The noise-inhibiting brushless motor and motor monitoring device were identified. The motor monitoring device includes: a soundproof motor housing, a recording microphone, a vibration sensor, and a Hall sensor. The noise-inhibiting brushless motor includes: an FOC microcontroller and a mechanical rotor. Obtain motor data for a noisy brushless motor, including: operating speed, number of pole pairs, and number of slots. The electrical angle-time signal and vector voltage-time signal group of the noisy brushless motor are obtained based on the operating speed, and the vector voltage amplitude is obtained based on the vector voltage-time signal group. Noise analysis of a brushless motor is performed using a motor monitoring device to obtain the motor noise signal. Spectral characteristic analysis of the motor noise signal is then performed to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency. Phase-sensitive detection of motor noise signal is performed based on noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of sound and motor; Based on the pre-constructed harmonic current model, harmonic prediction is performed on noise order, electromagnetic noise amplitude, relative phase of sound equipment, motor data and vector voltage amplitude to obtain a preliminary harmonic current data set, which includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude and falling harmonic phase. Based on the motor monitoring device and the vector voltage time signal group, the preliminary harmonic current data group is adaptively fine-tuned to obtain the target harmonic signal group; By injecting harmonics into a noisy brushless motor based on a target harmonic signal group, a noise-suppressed motor is obtained, thus completing the electromagnetic noise suppression of the brushless motor.

2. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 1, characterized in that, The electrical angle-time signal and vector voltage-time signal group for acquiring the noise-generating brushless motor based on its operating speed includes: Start the noisy brushless motor and set the speed of the started noisy brushless motor to the operating speed to obtain the running brushless motor; The mechanical rotation angle signal of the mechanical rotor in a running brushless motor is read using a pre-built position sensor; Calculate the electrical angle-time signal based on the mechanical rotation angle signal and the number of motor pole pairs; Read the first voltage signal and the second voltage signal from the FOC microcontroller that is running the brushless motor; The first voltage signal and the second voltage signal are combined to obtain the vector voltage time signal group.

3. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 2, characterized in that, The method of using a motor monitoring device to perform noise analysis on a brushless motor to obtain a motor noise signal includes: The noise-reducing brushless motor is placed into a soundproof motor box to obtain a soundproof brushless motor; Start the soundproof brushless motor and set the speed of the started soundproof brushless motor to the working speed to obtain the test brushless motor; The recording microphone in the motor monitoring device is used to collect and test the motor noise signal of the brushless motor.

4. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 3, characterized in that, The spectral characteristic analysis of the motor noise signal, to obtain the noise order, electromagnetic noise amplitude, and electromagnetic characteristic frequency, includes: The motor noise signal is processed by FFT to obtain the noise signal spectrum; Multiple local spectral peak frequencies were identified based on the noise signal spectrum. For each of the multiple local spectral peak frequencies, perform the following operation: The order of candidates is calculated based on the local spectral peak frequency, operating speed, and number of motor pole pairs. By summing up the candidate orders, we obtain multiple candidate orders; The first test speed and the second test speed are determined based on the preset first multiplier value, the preset second multiplier value, and the working speed. The first test speed is the product of the first multiplier value and the working speed, and the second test speed is the product of the second multiplier value and the working speed. Multiple first spectral peak frequencies were identified based on the soundproof brushless motor and the first test speed, and multiple second spectral peak frequencies were identified based on the soundproof brushless motor and the second test speed. For each of the multiple candidate orders, perform the following operation: Multiply the local spectral peak frequency corresponding to the order to be selected by the first multiplier to obtain the first amplification frequency; A first frequency range is determined based on a preset frequency selection interval and a first amplification frequency. The minimum value of the first frequency range is the absolute difference between the first amplification frequency and the frequency selection interval, and the maximum value of the first frequency range is the sum of the first amplification frequency and the frequency selection interval. The second frequency range is determined based on the local spectral peak frequency corresponding to the candidate order, the second multiple, and the frequency selection interval. Determine whether there is a first spectral peak frequency within the first frequency range among multiple first spectral peak frequencies; If there is a first spectral peak frequency among the multiple first spectral peak frequencies that is located within the first frequency range, then determine whether there is a second spectral peak frequency among the multiple second spectral peak frequencies that is located within the second frequency range. If there is a second spectral peak frequency within the second frequency range among multiple second spectral peak frequencies, then the order to be selected is recorded as the selectable order; By summing the possible orders, multiple possible orders can be obtained; For each of the multiple optional orders, perform the following operation: Round the optional order to the nearest integer to obtain the integer order. The order difference is calculated based on the optional order and the rounding order, where the order difference is the absolute difference between the optional order and the rounding order. Summarize the order integer differences to obtain multiple order integer differences, and take the floor order corresponding to the smallest order integer difference among the multiple order integer differences as the noise order; The local spectral peak frequency corresponding to the noise order is taken as the electromagnetic characteristic frequency. The amplitude of electromagnetic noise is determined in the noise signal spectrum based on the electromagnetic characteristic frequency.

5. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 4, characterized in that, The step of performing phase-sensitive detection on the motor noise signal based on noise order, electromagnetic characteristic frequency, and electrical angle-time signal to obtain the relative phase of the motor includes: The electromagnetic frequency range is determined based on the frequency selection interval and electromagnetic characteristic frequency. The motor noise signal is filtered based on the electromagnetic frequency range to obtain the filtered noise signal. The first reference signal and the second reference signal are constructed based on the noise order, the filtered noise signal, and the electrical angle-time signal. The first reference signal is sampled at equal intervals based on a preset sampling interval and a preset number of samples to obtain multiple first sampling points. The number of first sampling points among the multiple first sampling points is the number of samples. The first sampling point includes: a first sample value. Calculate the first moving average value based on multiple first sampling points; The second moving average value is obtained based on the sampling interval, the number of samples, and the second reference signal; The relative phase of the sound machine is calculated based on the first sliding average and the second sliding average.

6. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 5, characterized in that, Before obtaining the preliminary harmonic current data set by performing harmonic prediction on noise order, electromagnetic noise amplitude, relative phase of the audio equipment, motor data, and vector voltage amplitude based on the pre-constructed harmonic current model, the process also includes: Multiple historical motor data and multiple historical harmonic control data are acquired. The historical motor data includes: historical noise order, historical noise amplitude, historical relative phase, historical operating speed, historical number of motor pole pairs, historical number of motor slots, and historical voltage amplitude. The historical harmonic control data includes: historical rising harmonic amplitude, historical rising harmonic phase, historical falling harmonic amplitude, and historical falling harmonic phase. The historical motor data and the historical harmonic control data correspond one-to-one. The pre-built deep learning model was trained using multiple historical motor data and multiple historical harmonic regulation data to obtain the harmonic current model.

7. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 6, characterized in that, The adaptive fine-tuning of the preliminary harmonic current data set based on the motor monitoring device and vector voltage-time signal set to obtain the target harmonic signal set includes: Acquire the electrical data of the motor, including: motor angular velocity, motor stator resistance, and motor inductance; The electric angular velocity is calculated based on the motor angular velocity and the number of motor pole pairs, where the electric angular velocity is the product of the motor angular velocity and the number of motor pole pairs; The harmonic order of up-order and harmonic order of down-order are determined based on the noise order. Based on the harmonic order, the motor stator resistance, motor inductance, electric angular velocity, and the increased harmonic amplitude and phase in the preliminary harmonic current data set, a first and a second increased voltage signal are constructed. The first and second increased voltage signals are shown below: ； in, and These are the first and second raised-order voltage signals, respectively. For the amplitude of the higher harmonic, For the rising harmonic phase, , and These are the motor stator resistance, motor inductance, and electric angular velocity, respectively. For the order of harmonics, It is an electrical angle-time signal. Refers to the sine function. Cosine function The arctangent function; The first and second reduced-order voltage signals are obtained based on the reduced-order order of the harmonics, the stator resistance, inductance, and angular velocity of the motor in the electrical data of the motor, the amplitude and phase of the reduced-order harmonics in the preliminary harmonic current data set. The first injection voltage signal and the second injection voltage signal are constructed based on the first raised voltage signal, the second raised voltage signal, the first lowered voltage signal, the second lowered voltage signal, the first voltage signal, and the second voltage signal in the vector voltage time signal group; Based on the FOC microcontroller, the first injection voltage signal and the second injection voltage signal, the noise brushless motor is voltage controlled to obtain the initial control brushless motor; The target harmonic signal group is obtained by adaptively fine-tuning the initial control brushless motor using a motor monitoring device.

8. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 7, characterized in that, The method of using a motor monitoring device to adaptively fine-tune the initial control brushless motor to obtain the target harmonic signal group includes: Based on the operating speed, the initial control brushless motor, and the soundproof motor box, the brushless motor was selected for evaluation. The recording microphone in the motor monitoring device is used to collect evaluation noise signals for the brushless motor. The evaluation noise amplitude is obtained based on the evaluation noise signal; The vibration sensor and the Hall sensor are both installed on the evaluated brushless motor to obtain a vibration sensor and a Hall sensor installed. The maximum amplitude of the brushless motor is obtained and evaluated based on the preset total acquisition time and the installed vibration sensor. The brushless motor is evaluated by acquiring multiple magnetic field strengths based on the total acquisition time, the preset acquisition time interval, and the installation of Hall sensors. The mean magnetic field strength is calculated based on multiple magnetic field strengths, where the mean magnetic field strength is the average of the multiple magnetic field strengths. The electromagnetic suppression index is calculated based on the evaluation noise amplitude, maximum amplitude, average magnetic field strength, and multiple magnetic field strengths. The amplitude of the raised harmonic is finely adjusted bidirectionally according to a preset amplitude percentage to obtain an increase in the raised amplitude and a decrease in the raised amplitude. The amplitude of the lower harmonic is increased and decreased based on the amplitude percentage and the lower harmonic amplitude. The raised harmonic phase is finely adjusted bidirectionally according to a preset fine-tuning angle to obtain an increase in the raised phase and a decrease in the raised phase. The decreased harmonic phase is obtained by adjusting the fine-tuning angle and the decreased harmonic phase. Based on increasing the amplitude of the order increase, increasing the amplitude of the order decrease, increasing the phase of the order increase and increasing the phase of the order decrease, the order of the order increase of the harmonics, the order of the order decrease of the harmonics, the motor stator resistance, the motor inductance, the electric angular velocity, the FOC microcontroller obtains the first update voltage signal and the second update voltage signal. Based on the first updated voltage signal, the second updated voltage signal, and the noise level of the brushless motor, an additional evaluation motor was identified. Based on motor monitoring devices and by adding evaluation motors to obtain electromagnetic indices; The electromagnetic index is reduced by reducing the amplitude of the rising order, reducing the amplitude of the falling order, reducing the phase of the rising order, reducing the phase of the falling order, the order of the rising harmonics, the order of the falling harmonics, the stator resistance of the motor, the inductance of the motor, the electric angular velocity, the FOC microcontroller, the noise brushless motor and the motor monitoring device. Compare the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index; If the electromagnetic index is increased to the maximum value among the electromagnetic suppression index, the electromagnetic index increase, and the electromagnetic index decrease, then the increased electromagnetic index is used as the electromagnetic suppression index, and the increased up-order amplitude, increased down-order amplitude, increased up-order phase, and increased down-order phase are used as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively. Then return to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic index is reduced to the maximum value among the electromagnetic suppression index, the electromagnetic index is increased, and the electromagnetic index is reduced, then the reduced electromagnetic index is taken as the electromagnetic suppression index, and the reduced up-order amplitude, reduced down-order amplitude, reduced up-order phase, and reduced down-order phase are taken as the up-order harmonic amplitude, down-order harmonic amplitude, up-order harmonic phase, and down-order harmonic phase, respectively, and the process returns to the step of bidirectional fine-tuning the up-order harmonic amplitude according to the preset amplitude percentage. If the electromagnetic suppression index is the maximum value among the electromagnetic suppression index, increasing the electromagnetic index, and decreasing the electromagnetic index, then the first update voltage signal and the second update voltage signal corresponding to the electromagnetic suppression index are respectively used as the target first voltage signal and the target second voltage signal. By combining the first voltage signal and the second voltage signal of the target, the target harmonic signal group is obtained.

9. The method for suppressing electromagnetic noise of a brushless motor based on harmonic current injection as described in claim 8, characterized in that, The formula for calculating the electromagnetic suppression index is as follows: ； in, Electromagnetic suppression index, The first of multiple magnetic field strengths One magnetic field strength, The mean magnetic field strength This refers to the number of magnetic field strengths among multiple magnetic field strengths. To evaluate the noise amplitude, For maximum amplitude, It is a natural constant.

10. A brushless motor electromagnetic noise suppression system based on harmonic current injection, characterized in that, The system includes: The brushless motor verification module is used to verify the noise of the brushless motor and the motor monitoring device. The motor monitoring device includes: a soundproof motor box, a recording microphone, a vibration sensor and a Hall sensor. The noise of the brushless motor includes: an FOC microcontroller and a mechanical rotor. The motor data acquisition module is used to acquire motor data of the noisy brushless motor. The motor data includes: operating speed, number of motor pole pairs and number of motor slots. Based on the operating speed, the module acquires the electrical angle time signal and vector voltage time signal group of the noisy brushless motor, and acquires the vector voltage amplitude based on the vector voltage time signal group. The motor noise analysis module is used to analyze the noise of a brushless motor using a motor monitoring device, obtain the motor noise signal, perform spectral characteristic analysis on the motor noise signal to obtain the noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, and perform phase-sensitive detection on the motor noise signal based on the noise order, electromagnetic characteristic frequency and electrical angle-time signal to obtain the relative phase of the motor. The motor noise suppression module is used to predict harmonics based on a pre-built harmonic current model, including noise order, electromagnetic noise amplitude, relative phase between the motor and the receiver, motor data, and vector voltage amplitude, to obtain a preliminary harmonic current data set. This preliminary harmonic current data set includes: rising harmonic amplitude, rising harmonic phase, falling harmonic amplitude, and falling harmonic phase. The module then adaptively fine-tunes the preliminary harmonic current data set based on the motor monitoring device and the vector voltage time signal set to obtain a target harmonic signal set. Based on the target harmonic signal set, harmonics are injected into the noisy brushless motor to obtain a noise-suppressed motor, thus completing the electromagnetic noise suppression of the brushless motor.

Images