A brushless motor starting control method and system based on high-frequency signal injection

Abstract

The present invention relates to the field of brushless motor starting technology, and includes a brushless motor starting control method and system based on high-frequency signal injection, comprising: identifying a target brushless motor and a signal generator, acquiring environmental parameters, generating an initial high-frequency signal, acquiring a historical current signal sequence of a stator winding, acquiring high-frequency signal parameters, injecting the high-frequency signal into the stator winding to obtain a high-frequency current response signal, estimating an initial rotor position, optimizing the high-frequency signal parameters to obtain optimized high-frequency parameters, obtaining a precise rotor position, obtaining a brushless motor starting mode, calculating the rapid starting efficiency and progressive starting efficiency of the target brushless motor, obtaining the optimal starting efficiency, obtaining a normally started brushless motor, and completing brushless motor starting control based on the normally started brushless motor. The present invention can improve the accuracy and reliability of rotor position detection.

Description

Technical Field

[0001] The present invention relates to the technical field of brushless motor starting control, and in particular to a brushless motor starting control method and system based on high-frequency signal injection. Background Art

[0002] A high-frequency signal is an electrical signal with a relatively high frequency, typically well above the frequency range of conventional signals. A brushless motor is a motor that does not use mechanical brushes. Its rotor typically incorporates permanent magnets, and the stator windings use an electronic commutator to control the flow and direction of current, thereby achieving motor rotation. Starting control refers to the control and management of the motor's transition from a stationary state to normal operation.

[0003] Traditional brushless motor starting control methods rely primarily on position sensors to obtain rotor position information, enabling precise electronic commutation and control. The use of position sensors increases the cost and complexity of motor systems. Furthermore, position sensors are prone to failure in harsh environments (such as high temperature, high humidity, and strong vibration), which can affect the proper operation of the motor. Therefore, improving the accuracy and reliability of rotor position detection is an urgent technical challenge. Summary of the Invention

[0004] The present invention provides a brushless motor starting control method based on high-frequency signal injection and a computer-readable storage medium, the main purpose of which is to improve the accuracy and reliability of rotor position detection.

[0005] To achieve the above objectives, the present invention provides a brushless motor starting control method based on high-frequency signal injection, comprising:

[0006] Identify a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environment sensing unit;

[0007] Acquiring environmental parameters using an environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity;

[0008] Generate an initial high-frequency signal according to environmental parameters and a signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters according to the historical current signal sequence, set an initial high-frequency signal according to the high-frequency signal parameters, and obtain a high-frequency signal;

[0009] receiving a high-frequency signal injection instruction, injecting a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtaining a high-frequency current response signal, and extracting a rotor position feature from the high-frequency current response signal;

[0010] Obtain inductance model parameters, estimate the initial rotor position based on the rotor position characteristics and the inductance model parameters, optimize the high-frequency signal parameters based on the initial rotor position, and obtain optimized high-frequency parameters;

[0011] Obtaining precise rotor position based on optimized high-frequency parameters, and obtaining a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting mode includes: a fast starting mode and a gradual starting mode;

[0012] Calculate the rapid start efficiency and the gradual start efficiency of the target brushless motor according to the rapid start mode and the gradual start mode;

[0013] Obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, and obtain the normal starting of the brushless motor based on the optimal starting mode;

[0014] The brushless motor starting control based on high frequency signal injection is completed based on the normal starting of the brushless motor.

[0015] Optionally, obtaining high-frequency signal parameters according to a historical current signal sequence includes:

[0016] Performing high-pass filtering on the historical current signal sequence to obtain an initial filtered signal sequence, and performing band-pass filtering on the initial filtered signal sequence to obtain a filtered signal sequence;

[0017] Segmenting the filtered signal sequence to obtain a filtered signal segment set, wherein the filtered signal segment set includes: a plurality of filtered signal segments, and each filtered signal segment includes a plurality of filtered current values;

[0018] Extract filtered signal segments from the filtered signal segment set in sequence, and perform the following operations on each of the extracted filtered signal segments:

[0019] Obtaining a window function signal segment based on the filtered signal segment, obtaining a signal spectrum according to the window function signal segment, and extracting a signal amplitude spectrum from the signal spectrum, wherein the horizontal axis of the signal amplitude spectrum is frequency and the vertical axis of the amplitude spectrum is amplitude;

[0020] Obtaining an amplitude set according to the signal amplitude spectrum, extracting amplitudes from the amplitude set in sequence, and comparing the amplitudes with the preset high-frequency signal amplitudes;

[0021] If the amplitude is greater than the preset high-frequency signal amplitude, the amplitude is regarded as the abnormal amplitude, and the frequency corresponding to the amplitude is regarded as the abnormal frequency;

[0022] Abnormal amplitudes and abnormal frequencies are summarized separately to obtain abnormal amplitude groups and abnormal frequency groups, and abnormal amplitude groups and abnormal frequency groups are summarized separately to obtain abnormal amplitude group sets and abnormal frequency group sets;

[0023] The abnormal amplitude interval and the abnormal frequency interval are obtained according to the abnormal amplitude group set and the abnormal frequency group set, and the high-frequency signal parameters are confirmed according to the abnormal amplitude interval and the abnormal frequency interval.

[0024] Optionally, obtaining the window function signal segment based on the filtered signal segment includes:

[0025] Multiple window functions are identified, window functions are extracted from the multiple window functions in sequence, and the following operations are performed on each of the extracted window functions:

[0026] Obtaining a signal length of a filtered signal segment, obtaining a window function length according to the signal length, and generating a plurality of filtered current indexes according to a plurality of filtered current values ​​in the filtered signal segment, wherein the filtered current values ​​correspond to the filtered current indexes one-to-one;

[0027] Extracting filtered current values ​​from the filtered signal segments in sequence, calculating an initial window function value of the filtered current value using a window function, identifying a target filtered current index from a plurality of filtered current indexes according to the filtered current value, and calculating a window function value according to the filtered current value, the window function length, the target filtered current index, and the initial window function value;

[0028] Summarize the window function values ​​to obtain a window function value set corresponding to the filtered signal segment, and visualize the window function value set and the filtered signal segment to obtain a window function waveform graph and a filtered signal waveform graph;

[0029] Performing a first-order derivative on each window function value on the window function waveform to obtain a plurality of first derivative values, and performing a first-order derivative on each filtered current value on the filtered signal waveform to obtain a plurality of second derivative values, wherein a first derivative value in the plurality of first derivative values ​​corresponds one-to-one to a second derivative value in the plurality of second derivative values;

[0030] Extract first derivative values ​​from the multiple first derivative values ​​in sequence, and perform the following operations on each of the extracted first derivative values:

[0031] determining a target second derivative value from a plurality of second derivative values ​​according to the first derivative value, and comparing the first derivative value with the target second derivative value;

[0032] If it is confirmed that the first derivative value is greater than or equal to the target second derivative value, the first derivative value is used as an abnormal derivative value, the abnormal derivative values ​​are summarized to obtain an abnormal derivative value set, and the number of abnormal derivative values ​​in the abnormal derivative value set is confirmed. If it is confirmed that the number of abnormal derivative values ​​is greater than a preset number of normal abnormal derivative values, the window function is used as an unqualified window function, the unqualified window function is eliminated from the multiple window functions to obtain multiple updated window functions, the multiple updated window functions are used as multiple window functions, and the process returns to the step of sequentially extracting window functions from the multiple window functions until all the multiple window functions are extracted;

[0033] If the first derivative value is less than the target second derivative value, return to the step of extracting the first derivative value from the multiple first derivative values ​​in sequence until all the multiple first derivative values ​​are extracted, and use the window function value set corresponding to the window function waveform graph corresponding to the first derivative value as the window function signal segment.

[0034] Optionally, extracting the rotor position feature from the high-frequency current response signal includes:

[0035] Performing signal conversion on the high-frequency current response signal to obtain high-frequency response current data, and performing denoising on the high-frequency response current data to obtain denoised current data, wherein the denoised current data includes a plurality of denoised current values;

[0036] Confirm the static state of the target brushless motor, obtain the static current value according to the static state, and use the static current value as the zero offset value;

[0037] Each denoised current value in the denoised current data is calibrated using the zero offset value to obtain calibrated current data;

[0038] Setting initial phase-locked loop parameters, and inputting calibration current data into a pre-built phase comparator according to the initial phase-locked loop parameters to obtain imported current data;

[0039] Obtain the phase difference between the imported current data and the calibration current data, and determine whether the phase difference is equal to zero;

[0040] If the phase difference is not equal to zero, the initial parameters of the phase-locked loop are adjusted to obtain optimized phase-locked loop parameters, the optimized phase-locked loop parameters are used as the initial phase-locked loop parameters, and the process returns to the step of inputting the calibration current data into the pre-built phase comparator according to the initial phase-locked loop parameters until the phase difference is equal to zero, thereby obtaining output current data;

[0041] The current phase is determined based on the output current data and is used as the rotor position feature.

[0042] Optionally, obtaining the inductance model parameters includes:

[0043] Obtaining a motor rotor position set of a target brushless motor, wherein the motor rotor position set includes a plurality of motor rotor positions, and each motor rotor position is different;

[0044] Obtain a historical detection time period, collect high-frequency current data for each motor rotor position in the motor rotor position set using the historical detection time period to obtain a historical high-frequency current value set, and obtain a historical current phase set based on the historical high-frequency current value set, wherein the motor rotor position corresponds to the historical high-frequency current value in a one-to-one manner;

[0045] Calculating a historical inductance value set according to the historical current phase set, wherein the historical current phases in the historical current phase set correspond one-to-one to the historical inductance values ​​in the historical inductance value set;

[0046] The phase inductance equation is constructed based on the historical current phase set and the historical inductance value set. The phase inductance equation is as follows:

[0047]

[0048] in, represents the phase inductance equation, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, represents the average inductance, represents the second harmonic component of inductance, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the number of motor rotor positions in the motor rotor position set;

[0049] The phase inductance equation is solved using a pre-built least squares method to obtain the optimized average inductance and the optimized second harmonic component of the inductance, which are then used as inductance model parameters.

[0050] Optionally, optimizing the high-frequency signal parameters according to the initial rotor position to obtain optimized high-frequency parameters includes:

[0051] Determine the target amplitude and target frequency according to the initial rotor position, use the target amplitude and target frequency as relay high-frequency signal parameters, and use the relay high-frequency signal parameters to obtain the relay current response signal;

[0052] Obtaining a relay current abnormal amplitude interval and a relay current abnormal frequency interval according to the relay current response signal;

[0053] Obtain an abnormal current amplitude interval based on the abnormal relay current amplitude interval and the abnormal amplitude interval, and obtain an abnormal current frequency interval based on the abnormal relay current frequency interval and the abnormal frequency interval;

[0054] The maximum current amplitude and the maximum current frequency are obtained according to the abnormal current amplitude interval and the abnormal current frequency interval, and the high-frequency signal parameters are updated using the maximum current amplitude and the maximum current frequency to obtain optimized high-frequency parameters.

[0055] Optionally, the calculating of the rapid starting efficiency and the progressive starting efficiency of the target brushless motor according to the rapid starting mode and the progressive starting mode includes:

[0056] The target brushless motor is started using the fast start mode, and the target brushless motor is monitored in real time after startup to obtain the initial rated voltage;

[0057] The time when the target brushless motor is started using the fast start mode is used as the starting point, and the time is recorded in real time to obtain the motor running time;

[0058] When the initial rated voltage reaches the preset operating rated voltage, the actual output torque, actual speed and operating time of the target brushless motor are recorded;

[0059] Acquire response time according to motor operation time and operation time, acquire temperature difference according to the ambient temperature and preset standard ambient temperature, and acquire humidity difference according to the ambient humidity and preset standard ambient humidity;

[0060] Calculate the quick start efficiency based on the actual output torque, actual speed, response time, temperature difference and humidity difference;

[0061] The progressive starting efficiency of the target brushless motor is calculated based on the progressive starting mode.

[0062] Optionally, the calculation formula for the rapid start efficiency is as follows:

[0063]

[0064] in, Indicates the quick start efficiency, Indicates the actual output torque, Indicates the preset maximum theoretical torque of the motor. Indicates the response time, Indicates the preset temperature influence coefficient, Indicates the temperature difference, Indicates the preset humidity influence coefficient, Represents the humidity difference, Indicates the preset desired speed, Indicates the actual speed, Indicates the preset time constant, represents the natural exponential function.

[0065] Optionally,

[0066] The method of obtaining a normal starting state of the brushless motor based on the optimal starting mode includes:

[0067] The target brushless motor is powered on using the optimal starting mode, and the target brushless motor is monitored in real time to obtain motor starting parameters, wherein the motor starting parameters include: current value, speed and vibration value;

[0068] If the current value is equal to a preset normal current value, the speed is equal to a preset normal speed, and the vibration value is equal to a preset normal vibration value, the optimal starting mode is switched to a pre-established normal motor operation mode to obtain a normal starting brushless motor;

[0069] If the current value is not equal to the preset normal current value, the speed is not equal to the preset normal speed, or the vibration value is not equal to the preset normal vibration value, the motor starting parameters are adjusted until the current value is equal to the preset normal current value, the speed is equal to the preset normal speed, and the vibration value is equal to the preset normal vibration value, and the calibration parameters are obtained. The target brushless motor is operated using the calibration parameters to obtain a normally started brushless motor.

[0070] To achieve the above object, the present invention further provides a brushless motor starting control system based on high-frequency signal injection, comprising:

[0071] a high-frequency signal generation module, configured to identify a target brushless motor and a signal generator, wherein the target brushless motor includes a stator winding, wherein the signal generator includes an environment sensing unit, utilizing the environment sensing unit to obtain environmental parameters, wherein the environmental parameters include ambient temperature and ambient humidity, generating an initial high-frequency signal based on the environmental parameters and the signal generator, obtaining a historical current signal sequence of the stator winding, obtaining high-frequency signal parameters based on the historical current signal sequence, setting an initial high-frequency signal based on the high-frequency signal parameters, and obtaining a high-frequency signal;

[0072] a rotor position detection module, configured to receive a high-frequency signal injection instruction, inject a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtain a high-frequency current response signal, extract rotor position characteristics from the high-frequency current response signal, obtain inductance model parameters, estimate an initial rotor position according to the rotor position characteristics and the inductance model parameters, and optimize the high-frequency signal parameters according to the initial rotor position to obtain optimized high-frequency parameters;

[0073] a starting mode selection module, configured to obtain a precise rotor position based on optimized high-frequency parameters, and to obtain a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting modes include a rapid starting mode and a gradual starting mode, and to calculate a rapid starting efficiency and a gradual starting efficiency of a target brushless motor based on the rapid starting mode and the gradual starting mode;

[0074] The brushless motor normal starting module is used to obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, obtain the normal starting of the brushless motor based on the optimal starting mode, and complete the brushless motor starting control based on the high-frequency signal injection based on the normal starting of the brushless motor.

[0075] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0076] a memory storing at least one instruction;

[0077] The processor executes the instructions stored in the memory to implement the above-mentioned brushless motor starting control method based on high-frequency signal injection.

[0078] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned brushless motor starting control method based on high-frequency signal injection.

[0079] The present invention solves the problem described in the background technology. The present invention identifies a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environmental sensing unit, and the signal generator of the present invention serves as the source of high-frequency signals. Its characteristics and functions directly affect the quality and stability of high-frequency signals. The environmental parameters are obtained by using the environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity. The present invention considers the influence of environmental factors and can more accurately simulate the actual operating state of the motor, thereby improving the accuracy of high-frequency signal injection control and reducing errors and uncertainties caused by environmental changes. An initial high-frequency signal is generated according to the environmental parameters and the signal generator, and a historical current signal sequence of the stator winding is obtained. The high-frequency signal parameters are obtained according to the historical current signal sequence, and the initial high-frequency signal is set according to the high-frequency signal parameters to obtain a high-frequency signal. The present invention generates the initial high-frequency signal in combination with the environmental parameters, which can make the high-frequency signal better adapt to the actual operating environment of the motor.Under different ambient temperatures and humidities, the electrical characteristics of the motor will change. Adjusting the high-frequency signal according to the environmental parameters can ensure that the high-frequency signal can effectively excite the motor and improve the effect of signal injection. The historical current signal sequence of the stator winding is obtained and the high-frequency signal parameters are determined accordingly. The historical operation information of the motor can be fully utilized. A high-frequency signal injection instruction is received and the high-frequency signal is injected into the stator winding according to the high-frequency signal injection instruction to obtain a high-frequency current response signal. The rotor position characteristics are extracted from the high-frequency current response signal. The present invention can effectively filter out noise and interference by extracting the rotor position characteristics from the high-frequency current response signal, and extract useful information related to the rotor position, which helps to improve the accuracy and reliability of rotor position detection and provide accurate data support for subsequent position estimation and control. The inductance model parameters are obtained, and the initial rotor position is estimated based on the rotor position characteristics and the inductance model parameters. The high-frequency signal parameters are optimized based on the initial rotor position to obtain optimized high-frequency parameters. The present invention optimizes the high-frequency signal parameters based on the initial rotor position, which can further improve the injection effect of the high-frequency signal. The optimized high-frequency signal can better adapt to the actual operating state of the motor, improve the accuracy and stability of rotor position detection, and obtain accurate information based on the optimized high-frequency parameters. Quasi-rotor position, obtain the brushless motor starting mode according to the precise rotor position, wherein the brushless motor starting mode includes: fast starting mode and progressive starting mode. The present invention determines the starting mode of the brushless motor according to the precise rotor position, and can select the most appropriate starting mode according to the actual operation requirements and working conditions of the motor, reduce torque fluctuation and energy loss, and calculate the fast starting efficiency and progressive starting efficiency of the target brushless motor according to the fast starting mode and progressive starting mode. The present invention reflects the energy conversion efficiency of the motor during the starting process through the efficiency index. By comparing the efficiencies of the two starting modes, we can understand their performance under different working conditions. The advantages and disadvantages of the two modes provide a basis for selecting the optimal starting mode. The optimal starting efficiency is obtained based on the rapid starting efficiency and the gradual starting efficiency. The optimal starting mode is determined based on the optimal starting efficiency. The brushless motor is normally started based on the optimal starting mode. By selecting the optimal starting mode based on the rapid starting efficiency and the gradual starting efficiency, the present invention can achieve optimal energy utilization and optimal performance while meeting the motor starting requirements. Normally starting the brushless motor based on the optimal starting mode ensures the stability and reliability of the motor during the starting process. Based on the normal starting of the brushless motor, the brushless motor starting control based on high-frequency signal injection is completed. Therefore, the present invention can improve the accuracy and reliability of rotor position detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 A schematic flow chart of a brushless motor starting control method based on high-frequency signal injection provided by one embodiment of the present invention;

[0081] Figure 2A functional module diagram of a brushless motor starting control system based on high-frequency signal injection provided by one embodiment of the present invention;

[0082] Figure 3 A schematic structural diagram of an electronic device for implementing the brushless motor starting control method based on high-frequency signal injection provided by an embodiment of the present invention.

[0083] Description of reference numerals:

[0084] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0085] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0086] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0087] An embodiment of the present application provides a brushless motor starting control method based on high-frequency signal injection. The execution subject of the brushless motor starting control method based on high-frequency signal injection includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the brushless motor starting control method based on high-frequency signal injection can be executed by software or hardware installed on a terminal device or a server device, and the software can 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, etc.

[0088] Reference Figure 1 FIG. 1 is a flow chart of a brushless motor starting control method based on high-frequency signal injection according to an embodiment of the present invention. In this embodiment, the brushless motor starting control method based on high-frequency signal injection includes:

[0089] S1. Identify a target brushless motor and a signal generator, wherein the target brushless motor includes a stator winding, and the signal generator includes an environment sensing unit.

[0090] It should be explained that the target brushless motor refers to the brushless motor to be controlled. A brushless motor refers to a motor without brushes, which controls the operation of the motor through an electronic commutator rather than a mechanical commutator. This motor is generally characterized by high efficiency, high reliability and low maintenance costs. A signal generator refers to a device that can generate a signal of a specific frequency and amplitude. The signal generator described in the embodiment of the present invention is used to generate a high-frequency signal and inject the high-frequency signal into the stator winding of the target brushless motor to detect the rotor position. The stator winding refers to the coil winding of the stator part of the brushless motor, which is used to generate a magnetic field to drive the rotor to rotate. The stator part of the brushless motor refers to the fixed part of the brushless motor. The environmental sensing unit refers to a unit that can monitor and sense the surrounding environmental parameters in real time, wherein the environmental sensing unit includes: a temperature sensor and a humidity sensor.

[0091] S2. Utilize the environment sensing unit to obtain environmental parameters, wherein the environmental parameters include: ambient temperature and ambient humidity.

[0092] It should be explained that the step of obtaining environmental parameters using the environmental sensing unit comprises: activating the temperature sensor and humidity sensor in the environmental sensing unit, using the activated temperature sensor and humidity sensor and a preset acquisition frequency to collect the temperature and humidity of the current environment of the target brushless motor, obtaining temperature data and humidity data, calculating the average temperature and average humidity of the temperature data and humidity data, respectively, and using the average temperature and average humidity as the ambient temperature and ambient humidity. The acquisition frequency refers to a preset frequency for collecting the temperature and humidity of the current environment of the target brushless motor.

[0093] S3. Generate an initial high-frequency signal according to the environmental parameters and the signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters according to the historical current signal sequence, set the initial high-frequency signal according to the high-frequency signal parameters, and obtain a high-frequency signal.

[0094] It should be explained that the generation of the initial high-frequency signal according to the environmental parameters and the signal generator refers to increasing or decreasing the high-frequency signal according to the temperature and humidity in the environment. For example, if it is in a winter environment, the amplitude of the high-frequency signal is increased by a preset increase amplitude coefficient; if it is in a summer environment, the amplitude of the high-frequency signal is reduced by a preset decrease amplitude coefficient; if it is in a rainy environment, the frequency of the high-frequency signal is reduced by a preset decrease frequency coefficient; if it is in a dry environment, the frequency of the high-frequency signal is increased by a preset decrease frequency coefficient. The increase amplitude coefficient, decrease amplitude coefficient, decrease frequency coefficient and decrease frequency coefficient all refer to coefficients set in advance by humans. The high-frequency signal refers to an electrical signal generated by a signal generator in the start-up control of a brushless motor that is higher than the normal motor starting frequency.

[0095] In detail, obtaining high-frequency signal parameters according to the historical current signal sequence includes:

[0096] Performing high-pass filtering on the historical current signal sequence to obtain an initial filtered signal sequence, and performing band-pass filtering on the initial filtered signal sequence to obtain a filtered signal sequence;

[0097] Segmenting the filtered signal sequence to obtain a filtered signal segment set, wherein the filtered signal segment set includes: a plurality of filtered signal segments, and each filtered signal segment includes a plurality of filtered current values;

[0098] Extract filtered signal segments from the filtered signal segment set in sequence, and perform the following operations on each of the extracted filtered signal segments:

[0099] Obtaining a window function signal segment based on the filtered signal segment, obtaining a signal spectrum according to the window function signal segment, and extracting a signal amplitude spectrum from the signal spectrum, wherein the horizontal axis of the signal amplitude spectrum is frequency and the vertical axis of the amplitude spectrum is amplitude;

[0100] Obtaining an amplitude set according to the signal amplitude spectrum, extracting amplitudes from the amplitude set in sequence, and comparing the amplitudes with the preset high-frequency signal amplitudes;

[0101] If the amplitude is greater than the preset high-frequency signal amplitude, the amplitude is regarded as the abnormal amplitude, and the frequency corresponding to the amplitude is regarded as the abnormal frequency;

[0102] Abnormal amplitudes and abnormal frequencies are summarized separately to obtain abnormal amplitude groups and abnormal frequency groups, and abnormal amplitude groups and abnormal frequency groups are summarized separately to obtain abnormal amplitude group sets and abnormal frequency group sets;

[0103] The abnormal amplitude interval and the abnormal frequency interval are obtained according to the abnormal amplitude group set and the abnormal frequency group set, and the high-frequency signal parameters are confirmed according to the abnormal amplitude interval and the abnormal frequency interval.

[0104] It should be explained that the high-pass filtering of the historical current signal sequence refers to high-pass filtering the historical current signal sequence using a high-pass filter. For example, the high-pass filter is a Butterworth filter, a Chebyshev filter, etc. The purpose of high-pass filtering is to remove DC components and low-frequency noise. The initial filtered signal sequence refers to the current signal sequence after high-pass filtering. The band-pass filtering of the initial filtered signal sequence refers to band-pass filtering the initial filtered signal sequence using a band-pass filter. For example, the band-pass filter is an RC band-pass filter or an RLC band-pass filter. The purpose of band-pass filtering is to retain signals within a specific frequency range in the historical current signal and remove signals of other frequencies. Segmenting the filtered signal sequence refers to segmenting the filtered signal sequence using a preset signal segment length. The signal segment length refers to the pre-set length used to segment the filtered signal sequence. The filtered current value refers to the current value of each sample point in the filtered signal sequence. Acquiring the signal spectrum based on the window function signal segment refers to obtaining the signal spectrum after performing a fast Fourier transform on the window function signal segment. The signal spectrum refers to the representation of the signal in the frequency domain.

[0105] It should be explained that the signal amplitude spectrum refers to the amplitude portion of the signal spectrum, representing the amplitude corresponding to each frequency. The amplitude set refers to the set of all amplitude values ​​extracted from the signal amplitude spectrum. The high-frequency signal amplitude refers to a pre-set amplitude threshold for the high-frequency signal, which is used to determine anomalies in historical current signals. The abnormal amplitude is the amplitude value in the signal amplitude spectrum that is greater than the high-frequency signal amplitude. The abnormal frequency refers to the frequency corresponding to the abnormal amplitude. The abnormal amplitude group refers to the set of all abnormal amplitudes. The abnormal frequency group refers to the set of all abnormal frequencies. The abnormal amplitude group set refers to the set of all abnormal amplitude groups. The abnormal frequency group set refers to the set of all abnormal frequency groups. Determining abnormal amplitude intervals and abnormal frequency intervals based on the abnormal amplitude group set and abnormal frequency group set refers to extracting the maximum abnormal amplitude, minimum abnormal amplitude, maximum abnormal frequency, and minimum abnormal frequency from the abnormal amplitude group set and abnormal frequency group set, respectively, forming an abnormal amplitude interval based on the maximum abnormal amplitude and minimum abnormal amplitude, and forming an abnormal frequency interval based on the maximum abnormal frequency and minimum abnormal frequency. The determining of the high-frequency signal parameters according to the abnormal amplitude interval and the abnormal frequency interval refers to taking the maximum abnormal amplitude and the maximum frequency in the abnormal amplitude interval and the abnormal frequency interval as the high-frequency signal parameters.

[0106] In detail, obtaining the window function signal segment based on the filtered signal segment includes:

[0107] Multiple window functions are identified, window functions are extracted from the multiple window functions in sequence, and the following operations are performed on each of the extracted window functions:

[0108] Obtaining a signal length of a filtered signal segment, obtaining a window function length according to the signal length, and generating a plurality of filtered current indexes according to a plurality of filtered current values ​​in the filtered signal segment, wherein the filtered current values ​​correspond to the filtered current indexes one-to-one;

[0109] Extracting filtered current values ​​from the filtered signal segments in sequence, calculating an initial window function value of the filtered current value using a window function, identifying a target filtered current index from a plurality of filtered current indexes according to the filtered current value, and calculating a window function value according to the filtered current value, the window function length, the target filtered current index, and the initial window function value;

[0110] Summarize the window function values ​​to obtain a window function value set corresponding to the filtered signal segment, and visualize the window function value set and the filtered signal segment to obtain a window function waveform graph and a filtered signal waveform graph;

[0111] Performing a first-order derivative on each window function value on the window function waveform to obtain a plurality of first derivative values, and performing a first-order derivative on each filtered current value on the filtered signal waveform to obtain a plurality of second derivative values, wherein a first derivative value in the plurality of first derivative values ​​corresponds one-to-one to a second derivative value in the plurality of second derivative values;

[0112] Extract first derivative values ​​from the multiple first derivative values ​​in sequence, and perform the following operations on each of the extracted first derivative values:

[0113] determining a target second derivative value from a plurality of second derivative values ​​according to the first derivative value; and comparing the first derivative value with the target second derivative value;

[0114] If it is confirmed that the first derivative value is greater than or equal to the target second derivative value, the first derivative value is used as an abnormal derivative value, the abnormal derivative values ​​are summarized to obtain an abnormal derivative value set, and the number of abnormal derivative values ​​in the abnormal derivative value set is confirmed. If it is confirmed that the number of abnormal derivative values ​​is greater than a preset number of normal abnormal derivative values, the window function is used as an unqualified window function, the unqualified window function is eliminated from the multiple window functions to obtain multiple updated window functions, the multiple updated window functions are used as multiple window functions, and the process returns to the step of sequentially extracting window functions from the multiple window functions until all the multiple window functions are extracted;

[0115] If the first derivative value is less than the target second derivative value, return to the step of extracting the first derivative value from the multiple first derivative values ​​in sequence until all the multiple first derivative values ​​are extracted, and use the window function value set corresponding to the window function waveform graph corresponding to the first derivative value as the window function signal segment.

[0116] It should be explained that a window function is a function used to reduce spectral leakage in signal processing. For example, a window function includes a Hanning window, a Hamming window, a Blackman window, etc. The signal length refers to the number of filtered current values ​​contained in a filtered signal segment. The window function length refers to the length of the window function containing the number of filtered current values. In the embodiments of the present invention, the window function length is the same as the signal length. The filtered current index refers to the index of each filtered current value in the filtered signal segment. The initial window function value refers to the value obtained by calculating the filtered current value using the window function. The target filtered current index refers to the index position corresponding to the filtered current value when calculating the window function value. Calculating the window function value based on the filtered current value, the target filtered current index, and the initial window function value refers to multiplying the filtered current value corresponding to the target filtered current index by the initial window function value to obtain the window function value. The window function value set refers to the set of window function values ​​corresponding to all filtered current values ​​after the window function is applied. Visualizing the window function value set and the filtered signal segment separately refers to visualizing the window function value set and the filtered signal segment separately using a drawing tool. For example, a drawing tool such as Matplotlib or Seaborn can be used. The window function waveform and the filtered signal waveform refer to the waveform of a window function value set and the waveform of a filtered signal segment, respectively. The first-order derivative of each window function value on the window function waveform and the first-order derivative of each filtered current value on the filtered signal waveform are both derived using numerical differentiation methods. A first derivative value refers to the first-order derivative value of a window function value on the window function waveform. A second derivative value refers to the first-order derivative value of a filtered current value on the filtered signal waveform. A larger derivative value indicates greater waveform fluctuation. An unqualified window function refers to a window function whose first derivative value is greater than or equal to its second derivative value. An updated window function refers to the window function remaining after eliminating unqualified window functions. A target second derivative value refers to the second derivative value corresponding to a first derivative value extracted from a plurality of first derivative values. An abnormal derivative value refers to a first derivative value greater than or equal to the target second derivative value. An abnormal derivative value set refers to the set of all abnormal derivative values. The number of abnormal derivative values ​​refers to the number of abnormal derivative values ​​in the abnormal derivative value set. The number of normal abnormal derivative values ​​refers to a pre-set number of abnormal derivative values.

[0117] S4. Receive a high-frequency signal injection instruction, inject a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtain a high-frequency current response signal, and extract a rotor position feature from the high-frequency current response signal.

[0118] It should be noted that the high-frequency signal injection command is used to trigger the signal generator to inject the high-frequency signal into the stator winding of the brushless motor. The high-frequency current response signal refers to the current response generated within the brushless motor after the high-frequency signal is injected into the stator winding of the brushless motor.

[0119] In detail, extracting the rotor position feature from the high-frequency current response signal includes:

[0120] Performing signal conversion on the high-frequency current response signal to obtain high-frequency response current data, and performing denoising on the high-frequency response current data to obtain denoised current data, wherein the denoised current data includes a plurality of denoised current values;

[0121] Confirm the static state of the target brushless motor, obtain the static current value according to the static state, and use the static current value as the zero offset value;

[0122] Each denoised current value in the denoised current data is calibrated using the zero offset value to obtain calibrated current data;

[0123] Setting initial phase-locked loop parameters, and inputting calibration current data into a pre-built phase comparator according to the initial phase-locked loop parameters to obtain imported current data;

[0124] Obtain the phase difference between the imported current data and the calibration current data, and determine whether the phase difference is equal to zero;

[0125] If the phase difference is not equal to zero, the initial parameters of the phase-locked loop are adjusted to obtain optimized phase-locked loop parameters, the optimized phase-locked loop parameters are used as the initial phase-locked loop parameters, and the process returns to the step of inputting the calibration current data into the pre-built phase comparator according to the initial phase-locked loop parameters until the phase difference is equal to zero, thereby obtaining output current data;

[0126] The current phase is determined based on the output current data and is used as the rotor position feature.

[0127] It should be explained that the signal conversion of the high-frequency current response signal to obtain high-frequency response current data refers to converting the high-frequency current response signal from analog form to digital form using an analog-to-digital converter to obtain the high-frequency response current data. The denoising of the high-frequency response current data refers to denoising the high-frequency response current data using a low-pass filter. The denoised current data refers to the current data obtained after denoising the high-frequency response current data. The stationary state refers to the state when the rotor is not rotating. The stationary current value refers to the current value measured when the motor is stationary. The zero-point offset value refers to the current value measured when the motor is stationary and is used to calibrate subsequent current data. The calibrating each denoised current value in the denoised current data using the zero-point offset value to obtain the calibrated current data refers to subtracting the zero-point offset value from each denoised current value in the denoised current data to obtain the calibrated current data. The initial phase-locked loop parameters refer to the initial setting parameters of the phase-locked loop when it starts operating, including loop bandwidth, phase comparator gain, etc. The phase comparator refers to a component in the phase-locked loop that is used to compare the phase difference between the calibrated current data and the imported current data. Importing current data refers to the current data input to the phase comparator of the phase-locked loop (PLL). Optimizing PLL parameters involves adjusting the PLL parameters based on the output of the phase comparator to achieve better performance. For example, if the phase difference is not zero and is greater than the preset standard phase difference, the loop bandwidth is increased.

[0128] S5. Obtain inductance model parameters, estimate the initial rotor position according to the rotor position characteristics and the inductance model parameters, optimize the high-frequency signal parameters according to the initial rotor position, and obtain optimized high-frequency parameters.

[0129] In detail, the obtaining of the inductance model parameters includes:

[0130] Obtaining a motor rotor position set of a target brushless motor, wherein the motor rotor position set includes a plurality of motor rotor positions, and each motor rotor position is different;

[0131] Obtain a historical detection time period, collect high-frequency current data for each motor rotor position in the motor rotor position set using the historical detection time period to obtain a historical high-frequency current value set, and obtain a historical current phase set based on the historical high-frequency current value set, wherein the motor rotor position corresponds to the historical high-frequency current value in a one-to-one manner;

[0132] Calculating a historical inductance value set according to the historical current phase set, wherein the historical current phases in the historical current phase set correspond one-to-one to the historical inductance values ​​in the historical inductance value set;

[0133] The phase inductance equation is constructed based on the historical current phase set and the historical inductance value set. The phase inductance equation is as follows:

[0134]

[0135] in, represents the phase inductance equation, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, represents the average inductance, represents the second harmonic component of inductance, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the number of motor rotor positions in the motor rotor position set;

[0136] The phase inductance equation is solved using a pre-built least squares method to obtain the optimized average inductance and the optimized second harmonic component of the inductance, which are then used as inductance model parameters.

[0137] It should be explained that the motor rotor position refers to the specific position of the rotor in the motor, expressed in degrees. The historical detection time period refers to the time period in the past period of time used to collect the motor rotor position and high-frequency current data. The historical high-frequency current value set refers to the set of all high-frequency current values ​​collected in the historical detection time period. The historical high-frequency current value set reflects the high-frequency current response of the target brushless motor under different rotor positions. The method of obtaining the historical current phase set based on the historical high-frequency current value set is the same as the method of extracting the rotor position characteristics from the high-frequency current response signal, and will not be repeated here. The steps of calculating the historical inductance value set based on the historical current phase set are: extracting the historical current phase from the historical current phase set in sequence, obtaining the simulated rotor position based on the historical current phase, calculating the historical inductance value based on the simulated rotor position, summarizing the historical inductance values, and obtaining the historical inductance value set. The steps of obtaining the simulated rotor position based on the historical current phase are: simulated rotor position = historical current phase / 2. The calculation formula for calculating the historical inductance value based on the simulated rotor position is as follows:

[0138]

[0139] in, represents the historical inductance value, Represents the historical current phase. Average inductance refers to the portion of the inductance model that does not vary with rotor position. It reflects the average inductance of the motor when there is no magnetic saturation. The second harmonic component of inductance refers to the portion of the inductance model that varies with rotor position. The optimized average inductance and optimized second harmonic component of inductance are the average inductance and second harmonic component of inductance, respectively, obtained by solving the phase inductance equation using the least squares method.

[0140] In detail, the optimizing of the high-frequency signal parameters according to the initial rotor position to obtain the optimized high-frequency parameters includes:

[0141] Determine the target amplitude and target frequency according to the initial rotor position, use the target amplitude and target frequency as relay high-frequency signal parameters, and use the relay high-frequency signal parameters to obtain the relay current response signal;

[0142] Obtaining a relay current abnormal amplitude interval and a relay current abnormal frequency interval according to the relay current response signal;

[0143] Obtain an abnormal current amplitude interval based on the abnormal relay current amplitude interval and the abnormal amplitude interval, and obtain an abnormal current frequency interval based on the abnormal relay current frequency interval and the abnormal frequency interval;

[0144] The maximum current amplitude and the maximum current frequency are obtained according to the abnormal current amplitude interval and the abnormal current frequency interval, and the high-frequency signal parameters are updated using the maximum current amplitude and the maximum current frequency to obtain optimized high-frequency parameters.

[0145] It should be explained that the target amplitude refers to the amplitude corresponding to the initial rotor position. The target frequency refers to the frequency corresponding to the initial rotor position. The relay high-frequency signal parameter refers to the temporary high-frequency signal parameter determined according to the initial rotor position during the optimization process. The method of obtaining the relay current response signal using the relay high-frequency signal parameter is the same as the method of injecting the high-frequency signal into the stator winding according to the high-frequency signal injection instruction to obtain the high-frequency current response signal, and will not be repeated here. The relay current response signal refers to the current response signal generated by the motor after the relay high-frequency signal is injected into the stator winding. The method of obtaining the relay current abnormal amplitude interval and the relay current abnormal frequency interval based on the relay current response signal is the same as the method of obtaining the abnormal amplitude interval and the abnormal frequency interval based on the historical current signal sequence, and will not be repeated here. Obtaining the abnormal current amplitude interval based on the abnormal relay current amplitude interval and the abnormal amplitude interval refers to extracting the maximum and minimum abnormal relay current amplitudes from the abnormal relay current amplitude interval, extracting the maximum and minimum abnormal amplitudes from the abnormal amplitude interval, obtaining the maximum and minimum abnormal amplitude values ​​from the maximum and minimum abnormal relay current amplitudes, and forming the abnormal current amplitude interval based on the maximum and minimum abnormal amplitude values. The method for obtaining the abnormal current frequency interval based on the abnormal relay current frequency interval and the abnormal frequency interval is the same as the method for obtaining the abnormal current amplitude interval based on the abnormal relay current amplitude interval and the abnormal amplitude interval, and will not be repeated here. The maximum current amplitude refers to the maximum current amplitude. The maximum current frequency refers to the maximum current frequency. Updating the high-frequency signal parameters using the maximum current amplitude and the maximum current frequency refers to comparing the maximum current amplitude and the maximum current frequency with the amplitude and frequency in the high-frequency signal parameters, and using the maximum amplitude and the maximum frequency as the high-frequency signal parameters. Optimizing the high-frequency parameters refers to the high-frequency parameters obtained after the above optimization. The optimized high-frequency parameters can improve the starting performance and operating efficiency of the motor.

[0146] S6. Obtain a precise rotor position according to the optimized high-frequency parameters, and obtain a brushless motor starting mode according to the precise rotor position, wherein the brushless motor starting mode includes: a fast starting mode and a gradual starting mode.

[0147] It should be explained that precise rotor position refers to the actual position of the motor rotor, precisely determined by optimizing high-frequency signal parameters. This precise rotor position is more accurate than the initial rotor position. Precise rotor position is used to achieve precise motor control, helping to optimize motor performance, reduce energy consumption, and improve efficiency. Rapid start mode allows the motor to quickly reach rated speed within a preset timeframe. Progressive start mode increases the motor speed over multiple time periods until the rated speed is reached.

[0148] S7. Calculate the rapid starting efficiency and the gradual starting efficiency of the target brushless motor according to the rapid starting mode and the gradual starting mode.

[0149] In detail, the calculation of the rapid starting efficiency and the gradual starting efficiency of the target brushless motor according to the rapid starting mode and the gradual starting mode includes:

[0150] The target brushless motor is started using the fast start mode, and the target brushless motor is monitored in real time after startup to obtain the initial rated voltage;

[0151] The time when the target brushless motor is started using the fast start mode is used as the starting point, and the time is recorded in real time to obtain the motor running time;

[0152] When the initial rated voltage reaches the preset operating rated voltage, the actual output torque, actual speed and operating time of the target brushless motor are recorded;

[0153] Acquire response time according to motor operation time and operation time, acquire temperature difference according to the ambient temperature and preset standard ambient temperature, and acquire humidity difference according to the ambient humidity and preset standard ambient humidity;

[0154] Calculate the quick start efficiency based on the actual output torque, actual speed, response time, temperature difference and humidity difference;

[0155] The progressive starting efficiency of the target brushless motor is calculated based on the progressive starting mode.

[0156] It should be explained that the initial rated voltage refers to the initial voltage applied when the motor starts in fast start mode. The motor operating time refers to the time from the start of the motor's operation to the point where it reaches a specific state (such as a preset operating rated voltage). The operating rated voltage refers to the preset voltage value that the motor should reach during normal operation. The operating time refers to the time corresponding to the motor reaching the rated operating voltage. Obtaining the response time based on the motor operating time and the operating time refers to subtracting the time corresponding to the motor operating time from the operating time. The temperature difference refers to the difference between the current ambient temperature and the preset standard ambient temperature. The humidity difference refers to the difference between the current ambient humidity and the preset standard ambient humidity. The standard ambient temperature and standard ambient humidity refer to the ambient temperature and ambient humidity that are preset by humans. The actual output torque refers to the torque value actually output by the motor during operation. The actual speed refers to the speed value actually reached by the motor during operation.

[0157] Importantly, the step of calculating the progressive starting efficiency of the target brushless motor based on the progressive starting mode is: obtaining a plurality of progressive times and a plurality of rated voltages, wherein the progressive times correspond to the rated voltages in a one-to-one manner;

[0158] Extracting the rated voltage from the multiple rated voltages in sequence, determining the target progressive time according to the rated voltage, starting the target brushless motor using the progressive starting mode and the rated voltage, and monitoring the target brushless motor in real time to obtain the initial progressive time;

[0159] When the initial progressive time reaches the target progressive time, the progressive output torque and progressive actual speed of the target brushless motor are recorded, the initial progressive starting efficiency is calculated based on the progressive output torque, progressive actual speed, target progressive time, temperature difference, and humidity difference, and the step of sequentially extracting the rated voltage from the multiple rated voltages is returned to until the multiple rated voltages are extracted.

[0160] The initial progressive starting efficiencies are summarized to obtain an initial progressive starting efficiency set, and the progressive starting efficiency is calculated based on the initial progressive starting efficiency set.

[0161] It should also be explained that the ramp-up time refers to the time required for the motor to gradually increase its speed from a stationary state to the rated speed in the ramp-up mode. The rated voltage refers to the voltage value that the motor should reach when the ramp-up time is reached. The initial ramp-up time refers to the time it takes for the motor to start running from a stationary state and reach a specific state (such as a rated voltage) in the ramp-up mode. The target ramp-up time refers to the ramp-up time corresponding to a rated voltage extracted from multiple rated voltages. The progressive output torque refers to the torque value actually output by the motor at a rated voltage among the multiple rated voltages. The progressive actual speed refers to the speed actually achieved by the motor at a rated voltage among the multiple rated voltages. The initial progressive starting efficiency set refers to the set of all initial progressive starting efficiencies. Calculating the progressive starting efficiency based on the initial progressive starting efficiency set refers to the value obtained by adding up each initial progressive starting efficiency in the initial progressive starting efficiency set. The formula for calculating the initial progressive starting efficiency based on the progressive output torque, progressive actual speed, target progressive time, temperature difference and humidity difference is the same as the formula for calculating the rapid starting efficiency based on the actual output torque, actual speed, response time, temperature difference and humidity difference, and will not be repeated here.

[0162] In detail, the calculation formula of the rapid start efficiency is as follows:

[0163]

[0164] in, Indicates the quick start efficiency, Indicates the actual output torque, Indicates the preset maximum theoretical torque of the motor. Indicates the response time, Indicates the preset temperature influence coefficient, Indicates the temperature difference, Indicates the preset humidity influence coefficient, Represents the humidity difference, Indicates the preset desired speed, Indicates the actual speed, Indicates the preset time constant, represents the natural exponential function.

[0165] It should be explained that the temperature impact coefficient refers to a pre-set coefficient used to quantify the impact of ambient temperature on rapid start efficiency. The larger the temperature impact coefficient, the greater the impact on rapid start efficiency. The humidity impact coefficient refers to a pre-set coefficient used to quantify the impact of ambient humidity on rapid start efficiency. The larger the humidity impact coefficient, the greater the impact on rapid start efficiency. The expected speed refers to the pre-set speed corresponding to normal operation. The time constant refers to the time constant used to adjust the impact of response time, temperature difference, and humidity difference on rapid start efficiency. The larger the time constant, the smaller the impact of response time, temperature difference, and humidity difference on starting efficiency.

[0166] S8. Obtain an optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine an optimal starting mode based on the optimal starting efficiency, and obtain a normal starting mode for the brushless motor based on the optimal starting mode.

[0167] It should be explained that obtaining the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency means taking the maximum efficiency between the rapid starting efficiency and the progressive starting efficiency as the optimal starting efficiency. The optimal starting mode refers to the mode corresponding to the optimal starting efficiency.

[0168] In detail, the method of obtaining a normal starting state of the brushless motor based on the optimal starting mode includes:

[0169] The target brushless motor is powered on using the optimal starting mode, and the target brushless motor is monitored in real time to obtain motor starting parameters, wherein the motor starting parameters include: current value, speed and vibration value;

[0170] If the current value is equal to a preset normal current value, the speed is equal to a preset normal speed, and the vibration value is equal to a preset normal vibration value, the optimal starting mode is switched to a pre-established normal motor operation mode to obtain a normal starting brushless motor;

[0171] If the current value is not equal to the preset normal current value, the speed is not equal to the preset normal speed, or the vibration value is not equal to the preset normal vibration value, the motor starting parameters are adjusted until the current value is equal to the preset normal current value, the speed is equal to the preset normal speed, and the vibration value is equal to the preset normal vibration value, and the calibration parameters are obtained. The target brushless motor is operated using the calibration parameters to obtain a normally started brushless motor.

[0172] It should be explained that the current value refers to the current value flowing through the stator winding of the motor during the starting process. The speed refers to the rotation speed of the motor rotor. The vibration value refers to the vibration value measured by the vibration sensor during the operation of the motor. The normal current value, normal speed and normal vibration value all refer to the pre-set current value, speed and vibration value. The normal operating mode of the motor refers to the mode in which the motor operates under normal working conditions. The adjustment of the motor starting parameters means that if the current value is greater than the normal current value, the power supply voltage of the target brushless motor is reduced; if the speed is less than the normal speed, the power supply voltage of the target brushless motor is increased; if the vibration value is greater than the normal vibration value, the power supply voltage of the target brushless motor is increased.

[0173] S9. Based on the normal starting of the brushless motor, the brushless motor starting control based on the high-frequency signal injection is completed.

[0174] It should be explained that the normally started brushless motor refers to a target brushless motor that is successfully started and enters a normal operating mode under an optimal starting mode.

[0175] The present invention solves the problem described in the background technology. The present invention identifies a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environmental sensing unit, and the signal generator of the present invention serves as the source of high-frequency signals. Its characteristics and functions directly affect the quality and stability of high-frequency signals. The environmental parameters are obtained by using the environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity. The present invention considers the influence of environmental factors and can more accurately simulate the actual operating state of the motor, thereby improving the accuracy of high-frequency signal injection control and reducing errors and uncertainties caused by environmental changes. An initial high-frequency signal is generated according to the environmental parameters and the signal generator, and a historical current signal sequence of the stator winding is obtained. The high-frequency signal parameters are obtained according to the historical current signal sequence, and the initial high-frequency signal is set according to the high-frequency signal parameters to obtain a high-frequency signal. The present invention generates the initial high-frequency signal in combination with the environmental parameters, which can make the high-frequency signal better adapt to the actual operating environment of the motor.Under different ambient temperatures and humidities, the electrical characteristics of the motor will change. Adjusting the high-frequency signal according to the environmental parameters can ensure that the high-frequency signal can effectively excite the motor and improve the effect of signal injection. The historical current signal sequence of the stator winding is obtained and the high-frequency signal parameters are determined accordingly. The historical operation information of the motor can be fully utilized. A high-frequency signal injection instruction is received and the high-frequency signal is injected into the stator winding according to the high-frequency signal injection instruction to obtain a high-frequency current response signal. The rotor position characteristics are extracted from the high-frequency current response signal. The present invention can effectively filter out noise and interference by extracting the rotor position characteristics from the high-frequency current response signal, and extract useful information related to the rotor position, which helps to improve the accuracy and reliability of rotor position detection and provide accurate data support for subsequent position estimation and control. The inductance model parameters are obtained, and the initial rotor position is estimated based on the rotor position characteristics and the inductance model parameters. The high-frequency signal parameters are optimized based on the initial rotor position to obtain optimized high-frequency parameters. The present invention optimizes the high-frequency signal parameters based on the initial rotor position, which can further improve the injection effect of the high-frequency signal. The optimized high-frequency signal can better adapt to the actual operating state of the motor, improve the accuracy and stability of rotor position detection, and obtain accurate information based on the optimized high-frequency parameters. Quasi-rotor position, obtain the brushless motor starting mode according to the precise rotor position, wherein the brushless motor starting mode includes: fast starting mode and progressive starting mode. The present invention determines the starting mode of the brushless motor according to the precise rotor position, and can select the most appropriate starting mode according to the actual operation requirements and working conditions of the motor, reduce torque fluctuation and energy loss, and calculate the fast starting efficiency and progressive starting efficiency of the target brushless motor according to the fast starting mode and progressive starting mode. The present invention reflects the energy conversion efficiency of the motor during the starting process through the efficiency index. By comparing the efficiencies of the two starting modes, we can understand their performance under different working conditions. The advantages and disadvantages of the two modes provide a basis for selecting the optimal starting mode. The optimal starting efficiency is obtained based on the rapid starting efficiency and the gradual starting efficiency. The optimal starting mode is determined based on the optimal starting efficiency. The brushless motor is normally started based on the optimal starting mode. By selecting the optimal starting mode based on the rapid starting efficiency and the gradual starting efficiency, the present invention can achieve optimal energy utilization and optimal performance while meeting the motor starting requirements. Normally starting the brushless motor based on the optimal starting mode ensures the stability and reliability of the motor during the starting process. Based on the normal starting of the brushless motor, the brushless motor starting control based on high-frequency signal injection is completed. Therefore, the present invention can improve the accuracy and reliability of rotor position detection.

[0176] like Figure 2 , which is a functional module diagram of a brushless motor starting control system based on high-frequency signal injection provided by an embodiment of the present invention.

[0177] The brushless motor starting control system 100 based on high-frequency signal injection described in the present invention can be installed in an electronic device. Depending on the functionality to be implemented, the brushless motor starting control system 100 based on high-frequency signal injection can include a high-frequency signal generation module 101, a rotor position detection module 102, a starting mode selection module 103, and a brushless motor normal starting module 104. The modules described in the present invention, also referred to as units, refer to a series of computer program segments that can be executed by an electronic device processor and can perform fixed functions, and are stored in the memory of the electronic device.

[0178] The high-frequency signal generating module 101 is configured to identify a target brushless motor and a signal generator, wherein the target brushless motor includes a stator winding, wherein the signal generator includes an environment sensing unit, and utilizes the environment sensing unit to obtain environmental parameters, wherein the environmental parameters include ambient temperature and ambient humidity, and to generate an initial high-frequency signal based on the environmental parameters and the signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters based on the historical current signal sequence, and set an initial high-frequency signal based on the high-frequency signal parameters to obtain a high-frequency signal;

[0179] The rotor position detection module 102 is configured to receive a high-frequency signal injection instruction, inject a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtain a high-frequency current response signal, extract rotor position characteristics from the high-frequency current response signal, obtain inductance model parameters, estimate an initial rotor position based on the rotor position characteristics and the inductance model parameters, and optimize the high-frequency signal parameters based on the initial rotor position to obtain optimized high-frequency parameters;

[0180] The starting mode selection module 103 is configured to obtain a precise rotor position based on the optimized high-frequency parameters, and to obtain a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting mode includes a rapid starting mode and a gradual starting mode, and to calculate a rapid starting efficiency and a gradual starting efficiency of the target brushless motor based on the rapid starting mode and the gradual starting mode;

[0181] The brushless motor normal starting module 104 is used to obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, obtain the normal starting of the brushless motor based on the optimal starting mode, and complete the brushless motor starting control based on the high-frequency signal injection based on the normal starting of the brushless motor.

[0182] In detail, each module in the brushless motor starting control system 100 based on high frequency signal injection in the embodiment of the present invention adopts the same method as above when in use. Figure 1 The brushless motor starting control method based on high-frequency signal injection described in the previous section has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0183] like Figure 3 1 is a schematic structural diagram of an electronic device for implementing a brushless motor starting control method based on high-frequency signal injection according to an embodiment of the present invention.

[0184] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may further include a computer program stored in the memory 11 and executable on the processor 10, such as a brushless motor starting control method program based on high-frequency signal injection.

[0185] The memory 11 includes at least one type of readable storage medium, including flash memory, a removable hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in removable hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 11 includes both internal storage units of the electronic device 1 and external storage devices. The memory 11 can be used not only to store application software installed in the electronic device 1 and various data, such as the code of a brushless motor starting control method program based on high-frequency signal injection, but also to temporarily store data that has been output or is about to be output.

[0186] In some embodiments, the processor 10 may be comprised of an integrated circuit, such as a single packaged integrated circuit or a combination of multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (control unit) of the electronic device, connecting the various components of the electronic device using various interfaces and circuits. It executes programs or modules stored in the memory 11 (e.g., a program for a brushless motor starting control method based on high-frequency signal injection) and accesses data stored in the memory 11 to perform various functions and process data.

[0187] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0188] Figure 3 Only the electronic device with components is shown, and it can 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 in the figure, or combine certain components, or arrange the components differently.

[0189] For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) to power various components. Preferably, the power supply may be logically connected to the at least one processor 10 via a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management through the power management device. The power supply may further include any components such as one or more DC or AC power supplies, a recharging device, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not further described here.

[0190] 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 generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0191] Optionally, the electronic device 1 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be 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. The display may also be appropriately referred to as a display screen or a display unit, and is used to display information processed by the electronic device 1 and to display a visual user interface.

[0192] The program of the brushless motor starting control method based on high-frequency signal injection stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve the following:

[0193] Identify a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environment sensing unit;

[0194] Acquiring environmental parameters using an environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity;

[0195] Generate an initial high-frequency signal according to environmental parameters and a signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters according to the historical current signal sequence, set an initial high-frequency signal according to the high-frequency signal parameters, and obtain a high-frequency signal;

[0196] receiving a high-frequency signal injection instruction, injecting a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtaining a high-frequency current response signal, and extracting a rotor position feature from the high-frequency current response signal;

[0197] Obtain inductance model parameters, estimate the initial rotor position based on the rotor position characteristics and the inductance model parameters, optimize the high-frequency signal parameters based on the initial rotor position, and obtain optimized high-frequency parameters;

[0198] Obtaining precise rotor position based on optimized high-frequency parameters, and obtaining a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting mode includes: a fast starting mode and a gradual starting mode;

[0199] Calculate the rapid start efficiency and the gradual start efficiency of the target brushless motor according to the rapid start mode and the gradual start mode;

[0200] Obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, and obtain the normal starting of the brushless motor based on the optimal starting mode;

[0201] The brushless motor starting control based on high frequency signal injection is completed based on the normal starting of the brushless motor.

[0202] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0203] Furthermore, if the modules / units integrated into the electronic device 1 are implemented as software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. The computer-readable storage medium may 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 mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0204] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0205] Identify a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environment sensing unit;

[0206] Acquiring environmental parameters using an environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity;

[0207] Generate an initial high-frequency signal according to environmental parameters and a signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters according to the historical current signal sequence, set an initial high-frequency signal according to the high-frequency signal parameters, and obtain a high-frequency signal;

[0208] receiving a high-frequency signal injection instruction, injecting a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtaining a high-frequency current response signal, and extracting a rotor position feature from the high-frequency current response signal;

[0209] Obtain inductance model parameters, estimate the initial rotor position based on the rotor position characteristics and the inductance model parameters, optimize the high-frequency signal parameters based on the initial rotor position, and obtain optimized high-frequency parameters;

[0210] Obtaining precise rotor position based on optimized high-frequency parameters, and obtaining a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting mode includes: a fast starting mode and a gradual starting mode;

[0211] Calculate the rapid start efficiency and the gradual start efficiency of the target brushless motor according to the rapid start mode and the gradual start mode;

[0212] Obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, and obtain the normal starting of the brushless motor based on the optimal starting mode;

[0213] The brushless motor starting control based on high frequency signal injection is completed based on the normal starting of the brushless motor.

[0214] In the several embodiments provided by the present 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 only exemplary, and actual implementations may have other division methods.

[0215] The modules described as separate components may or may not be physically separate, and 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 elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0216] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0217] 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.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A brushless motor starting control method based on high-frequency signal injection, characterized in that: The method comprises: Identify a target brushless motor and a signal generator, wherein the target brushless motor includes: a stator winding, wherein the signal generator includes: an environment sensing unit; Acquiring environmental parameters using an environmental sensing unit, wherein the environmental parameters include: ambient temperature and ambient humidity; Generate an initial high-frequency signal according to environmental parameters and a signal generator, obtain a historical current signal sequence of the stator winding, obtain high-frequency signal parameters according to the historical current signal sequence, set an initial high-frequency signal according to the high-frequency signal parameters, and obtain a high-frequency signal; receiving a high-frequency signal injection instruction, injecting a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtaining a high-frequency current response signal, and extracting a rotor position feature from the high-frequency current response signal; Obtain inductance model parameters, estimate the initial rotor position based on the rotor position characteristics and the inductance model parameters, optimize the high-frequency signal parameters based on the initial rotor position, and obtain optimized high-frequency parameters; Obtaining precise rotor position based on optimized high-frequency parameters, and obtaining a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting mode includes: a fast starting mode and a gradual starting mode; Calculate the rapid start efficiency and the gradual start efficiency of the target brushless motor according to the rapid start mode and the gradual start mode; Obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, and obtain the normal starting of the brushless motor based on the optimal starting mode; The brushless motor starting control based on high frequency signal injection is completed based on the normal starting of the brushless motor.

2. The brushless motor starting control method based on high-frequency signal injection according to claim 1, characterized in that: The obtaining of high-frequency signal parameters according to the historical current signal sequence includes: Performing high-pass filtering on the historical current signal sequence to obtain an initial filtered signal sequence, and performing band-pass filtering on the initial filtered signal sequence to obtain a filtered signal sequence; Segmenting the filtered signal sequence to obtain a filtered signal segment set, wherein the filtered signal segment set includes: a plurality of filtered signal segments, and each filtered signal segment includes a plurality of filtered current values; Extract filtered signal segments from the filtered signal segment set in sequence, and perform the following operations on each of the extracted filtered signal segments: Obtaining a window function signal segment based on the filtered signal segment, obtaining a signal spectrum according to the window function signal segment, and extracting a signal amplitude spectrum from the signal spectrum, wherein the horizontal axis of the signal amplitude spectrum is frequency and the vertical axis of the amplitude spectrum is amplitude; Obtaining an amplitude set according to the signal amplitude spectrum, extracting amplitudes from the amplitude set in sequence, and comparing the amplitudes with the preset high-frequency signal amplitudes; If the amplitude is greater than the preset high-frequency signal amplitude, the amplitude is regarded as the abnormal amplitude, and the frequency corresponding to the amplitude is regarded as the abnormal frequency; Abnormal amplitudes and abnormal frequencies are summarized separately to obtain abnormal amplitude groups and abnormal frequency groups, and abnormal amplitude groups and abnormal frequency groups are summarized separately to obtain abnormal amplitude group sets and abnormal frequency group sets; The abnormal amplitude interval and the abnormal frequency interval are obtained according to the abnormal amplitude group set and the abnormal frequency group set, and the high-frequency signal parameters are confirmed according to the abnormal amplitude interval and the abnormal frequency interval.

3. The brushless motor starting control method based on high-frequency signal injection according to claim 2, characterized in that: The step of obtaining a window function signal segment based on the filtered signal segment includes: Multiple window functions are identified, window functions are extracted from the multiple window functions in sequence, and the following operations are performed on each of the extracted window functions: Obtaining a signal length of a filtered signal segment, obtaining a window function length according to the signal length, and generating a plurality of filtered current indexes according to a plurality of filtered current values ​​in the filtered signal segment, wherein the filtered current values ​​correspond to the filtered current indexes one-to-one; Extracting filtered current values ​​from the filtered signal segments in sequence, calculating an initial window function value of the filtered current value using a window function, identifying a target filtered current index from a plurality of filtered current indexes according to the filtered current value, and calculating a window function value according to the filtered current value, the window function length, the target filtered current index, and the initial window function value; Summarize the window function values ​​to obtain a window function value set corresponding to the filtered signal segment, and visualize the window function value set and the filtered signal segment to obtain a window function waveform graph and a filtered signal waveform graph; Performing a first-order derivative on each window function value on the window function waveform to obtain a plurality of first derivative values, and performing a first-order derivative on each filtered current value on the filtered signal waveform to obtain a plurality of second derivative values, wherein a first derivative value in the plurality of first derivative values ​​corresponds one-to-one to a second derivative value in the plurality of second derivative values; Extract first derivative values ​​from the multiple first derivative values ​​in sequence, and perform the following operations on each of the extracted first derivative values: determining a target second derivative value from a plurality of second derivative values ​​according to the first derivative value, and comparing the first derivative value with the target second derivative value; If it is confirmed that the first derivative value is greater than or equal to the target second derivative value, the first derivative value is used as an abnormal derivative value, the abnormal derivative values ​​are summarized to obtain an abnormal derivative value set, and the number of abnormal derivative values ​​in the abnormal derivative value set is confirmed. If it is confirmed that the number of abnormal derivative values ​​is greater than a preset number of normal abnormal derivative values, the window function is used as an unqualified window function, the unqualified window function is eliminated from the multiple window functions to obtain multiple updated window functions, the multiple updated window functions are used as multiple window functions, and the process returns to the step of sequentially extracting window functions from the multiple window functions until all the multiple window functions are extracted; If the first derivative value is less than the target second derivative value, return to the step of extracting the first derivative value from the multiple first derivative values ​​in sequence until all the multiple first derivative values ​​are extracted, and use the window function value set corresponding to the window function waveform graph corresponding to the first derivative value as the window function signal segment.

4. The brushless motor starting control method based on high-frequency signal injection according to claim 3, characterized in that: The step of extracting the rotor position feature from the high-frequency current response signal comprises: Performing signal conversion on the high-frequency current response signal to obtain high-frequency response current data, and performing denoising on the high-frequency response current data to obtain denoised current data, wherein the denoised current data includes a plurality of denoised current values; Confirm the static state of the target brushless motor, obtain the static current value according to the static state, and use the static current value as the zero offset value; Each denoised current value in the denoised current data is calibrated using the zero offset value to obtain calibrated current data; Setting initial phase-locked loop parameters, and inputting calibration current data into a pre-built phase comparator according to the initial phase-locked loop parameters to obtain imported current data; Obtain the phase difference between the imported current data and the calibration current data, and determine whether the phase difference is equal to zero; If the phase difference is not equal to zero, the initial parameters of the phase-locked loop are adjusted to obtain optimized phase-locked loop parameters, the optimized phase-locked loop parameters are used as the initial phase-locked loop parameters, and the process returns to the step of inputting the calibration current data into the pre-built phase comparator according to the initial phase-locked loop parameters until the phase difference is equal to zero, thereby obtaining output current data; The current phase is determined based on the output current data and is used as the rotor position feature.

5. The brushless motor starting control method based on high-frequency signal injection according to claim 4, characterized in that: The obtaining of the inductance model parameters includes: Obtaining a motor rotor position set of a target brushless motor, wherein the motor rotor position set includes a plurality of motor rotor positions, and each motor rotor position is different; Obtain a historical detection time period, collect high-frequency current data for each motor rotor position in the motor rotor position set using the historical detection time period to obtain a historical high-frequency current value set, and obtain a historical current phase set based on the historical high-frequency current value set, wherein the motor rotor position corresponds to the historical high-frequency current value in a one-to-one manner; Calculating a historical inductance value set according to the historical current phase set, wherein the historical current phases in the historical current phase set correspond one-to-one to the historical inductance values ​​in the historical inductance value set; The phase inductance equation is constructed based on the historical current phase set and the historical inductance value set. The phase inductance equation is as follows: in, represents the phase inductance equation, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, represents the average inductance, represents the second harmonic component of inductance, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the historical current phase concentration The historical inductance value corresponding to the historical current phase, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the motor rotor position concentration The motor rotor position, Indicates the number of motor rotor positions in the motor rotor position set; The phase inductance equation is solved using a pre-built least squares method to obtain the optimized average inductance and the optimized second harmonic component of the inductance, which are then used as inductance model parameters.

6. The brushless motor starting control method based on high-frequency signal injection according to claim 5, characterized in that: The step of optimizing the high-frequency signal parameters according to the initial rotor position to obtain optimized high-frequency parameters includes: Determine the target amplitude and target frequency according to the initial rotor position, use the target amplitude and target frequency as relay high-frequency signal parameters, and use the relay high-frequency signal parameters to obtain the relay current response signal; Obtaining a relay current abnormal amplitude interval and a relay current abnormal frequency interval according to the relay current response signal; Obtain an abnormal current amplitude interval based on the abnormal relay current amplitude interval and the abnormal amplitude interval, and obtain an abnormal current frequency interval based on the abnormal relay current frequency interval and the abnormal frequency interval; The maximum current amplitude and the maximum current frequency are obtained according to the abnormal current amplitude interval and the abnormal current frequency interval, and the high-frequency signal parameters are updated using the maximum current amplitude and the maximum current frequency to obtain optimized high-frequency parameters.

7. The brushless motor starting control method based on high-frequency signal injection according to claim 6, characterized in that: The calculating of the rapid starting efficiency and the gradual starting efficiency of the target brushless motor according to the rapid starting mode and the gradual starting mode includes: The target brushless motor is started using the fast start mode, and the target brushless motor is monitored in real time after startup to obtain the initial rated voltage; The time when the target brushless motor is started using the fast start mode is used as the starting point, and the time is recorded in real time to obtain the motor running time; When the initial rated voltage reaches the preset operating rated voltage, the actual output torque, actual speed and operating time of the target brushless motor are recorded; Acquire response time according to motor operation time and operation time, acquire temperature difference according to the ambient temperature and preset standard ambient temperature, and acquire humidity difference according to the ambient humidity and preset standard ambient humidity; Calculate the quick start efficiency based on the actual output torque, actual speed, response time, temperature difference and humidity difference; The progressive starting efficiency of the target brushless motor is calculated based on the progressive starting mode.

8. The brushless motor starting control method based on high-frequency signal injection according to claim 7, characterized in that: The calculation formula of the rapid start efficiency is as follows: in, Indicates the quick start efficiency, Indicates the actual output torque, Indicates the preset maximum theoretical torque of the motor. Indicates the response time, Indicates the preset temperature influence coefficient, Indicates the temperature difference, Indicates the preset humidity influence coefficient, Represents the humidity difference, Indicates the preset desired speed, Indicates the actual speed. Indicates the preset time constant, represents the natural exponential function.

9. The brushless motor starting control method based on high-frequency signal injection according to claim 8, characterized in that: The method of obtaining a normal starting state of the brushless motor based on the optimal starting mode includes: The target brushless motor is powered on using the optimal starting mode, and the target brushless motor is monitored in real time to obtain motor starting parameters, wherein the motor starting parameters include: current value, speed and vibration value; If the current value is equal to a preset normal current value, the speed is equal to a preset normal speed, and the vibration value is equal to a preset normal vibration value, the optimal starting mode is switched to a pre-established normal motor operation mode to obtain a normal starting brushless motor; If the current value is not equal to the preset normal current value, the speed is not equal to the preset normal speed, or the vibration value is not equal to the preset normal vibration value, the motor starting parameters are adjusted until the current value is equal to the preset normal current value, the speed is equal to the preset normal speed, and the vibration value is equal to the preset normal vibration value, and the calibration parameters are obtained. The target brushless motor is operated using the calibration parameters to obtain a normally started brushless motor.

10. A brushless motor starting control system based on high-frequency signal injection, characterized in that: The system comprises: a high-frequency signal generation module, configured to identify a target brushless motor and a signal generator, wherein the target brushless motor includes a stator winding, wherein the signal generator includes an environment sensing unit, utilizing the environment sensing unit to obtain environmental parameters, wherein the environmental parameters include ambient temperature and ambient humidity, generating an initial high-frequency signal based on the environmental parameters and the signal generator, obtaining a historical current signal sequence of the stator winding, obtaining high-frequency signal parameters based on the historical current signal sequence, setting an initial high-frequency signal based on the high-frequency signal parameters, and obtaining a high-frequency signal; a rotor position detection module, configured to receive a high-frequency signal injection instruction, inject a high-frequency signal into the stator winding according to the high-frequency signal injection instruction, obtain a high-frequency current response signal, extract rotor position characteristics from the high-frequency current response signal, obtain inductance model parameters, estimate an initial rotor position according to the rotor position characteristics and the inductance model parameters, and optimize the high-frequency signal parameters according to the initial rotor position to obtain optimized high-frequency parameters; a starting mode selection module, configured to obtain a precise rotor position based on optimized high-frequency parameters, and to obtain a brushless motor starting mode based on the precise rotor position, wherein the brushless motor starting modes include a rapid starting mode and a gradual starting mode, and to calculate a rapid starting efficiency and a gradual starting efficiency of a target brushless motor based on the rapid starting mode and the gradual starting mode; The brushless motor normal starting module is used to obtain the optimal starting efficiency based on the rapid starting efficiency and the progressive starting efficiency, determine the optimal starting mode based on the optimal starting efficiency, obtain the normal starting of the brushless motor based on the optimal starting mode, and complete the brushless motor starting control based on the high-frequency signal injection based on the normal starting of the brushless motor.

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