A method and system for reducing the heat loss of a permanent magnet synchronous motor

Abstract

The application relates to the technical field of permanent magnet synchronous motor control, in particular to a permanent magnet synchronous motor control method and system for reducing heat loss, which comprises the following steps: collecting real-time data of currents of each phase of a stator in a permanent magnet synchronous motor and vibration data of a bearing seat; obtaining variation coefficients of each phase, three-phase unbalance degrees and current variation characteristic values in each period; obtaining abnormal vibration characteristic values in each period by the fluctuation degree and pulse characteristics of the vibration data in each period; comprehensively obtaining comprehensive variation values of the permanent magnet synchronous motor in each period by comprehensively combining the current variation characteristic values and the abnormal vibration characteristic values; obtaining difference coefficients in each period; and controlling the rotating speed of the permanent magnet synchronous motor to reduce the heat loss of the permanent magnet synchronous motor, wherein the prediction step parameter of model predictive control is adjusted by the difference coefficients. The application aims to reduce the heat loss of the permanent magnet synchronous motor in time.

Description

Technical Field

[0001] This application relates to the field of permanent magnet synchronous motor control technology, specifically to a permanent magnet synchronous motor control method and system for reducing heat loss. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in AC drive applications due to their advantages such as simple structure, low energy consumption, and rapid dynamic response. However, various losses generated during the operation of PMSMs are converted into heat energy, leading to increased motor temperature. Specifically, when the stator winding current in a PMSM is large and contains numerous harmonics, the main magnetic field waveform is distorted, generating a large number of harmonics. These harmonics induce a large number of eddy currents in the rotor permanent magnets, resulting in eddy current losses and a significant increase in rotor permanent magnet temperature. Furthermore, mechanical losses such as bearing friction and rotor-air friction further exacerbate motor heating.

[0003] Existing technologies generally use model predictive control to regulate the speed of permanent magnet synchronous motors (PMSMs) in order to reduce heat loss. The prediction step size parameter in model predictive control is determined based on the heat loss of the PMSM. However, under complex operating conditions such as variable speed and variable load, it is difficult to accurately assess the heat loss of the PMSM, which makes it impossible to effectively adjust the prediction step size parameter in model predictive control, thus making it difficult to reduce the heat loss of the motor in a timely manner. Summary of the Invention

[0004] In view of the above, it is necessary to provide a control method and system for permanent magnet synchronous motors that reduces heat loss. Compared with traditional control methods for permanent magnet synchronous motors that reduce heat loss, this method can effectively reduce the heat loss of the permanent magnet synchronous motor.

[0005] In a first aspect, embodiments of this application provide a control method for a permanent magnet synchronous motor that reduces heat loss, the method comprising the following steps:

[0006] Real-time acquisition of stator current data for each phase in a permanent magnet synchronous motor, as well as vibration data of the bearing housing;

[0007] By analyzing the harmonic distortion and changes of the current data of each phase in each time period, the change coefficient of each phase in each time period is obtained. Combined with the analysis of the symmetrical components of the three-phase current data in each time period, the three-phase unbalance in each time period is obtained, and the characteristic value of the current change in each time period is obtained.

[0008] By analyzing the fluctuations and pulse characteristics of vibration data within each time period, abnormal vibration characteristic values ​​for each time period can be obtained.

[0009] The current change characteristic value and the abnormal vibration characteristic value are integrated to obtain a comprehensive change value of the permanent magnet synchronous motor in each period.

[0010] A prediction value of the comprehensive change value of the plurality of adjacent periods in each period is obtained, and a difference coefficient in each period is obtained by comparing the comprehensive change value of the plurality of adjacent periods in each period with the prediction value.

[0011] The rotational speed of the permanent magnet synchronous motor is regulated by model predictive control, thereby reducing the heat loss of the permanent magnet synchronous motor, wherein the prediction step parameter of the model predictive control is adjusted by the difference coefficient.

[0012] In one embodiment, the process of the change coefficient is as follows:

[0013] A frequency spectrum of the current data of each phase in each period is obtained, the ratio of the amplitude of each odd harmonic frequency to the amplitude of the fundamental frequency in the frequency spectrum is denoted as an amplitude ratio, and a sum value of all the amplitude ratios in the frequency spectrum is calculated.

[0014] A fitting curve of the current data of each phase in each period is obtained, and a first derivative of the fitting curve at each time in each period is obtained, and a dispersion of all the first derivatives of the fitting curve in each period is denoted as a change dispersion.

[0015] The change coefficient is positively correlated with the sum value and the change dispersion, respectively.

[0016] In one embodiment, the process of obtaining the three-phase imbalance degree is as follows:

[0017] The positive sequence component, the negative sequence component, and the zero sequence component of the three-phase current data in each period are obtained.

[0018] The ratio of the modulus of the negative sequence component to the modulus of the positive sequence component is denoted as a negative sequence ratio.

[0019] The ratio of the modulus of the zero sequence component to the modulus of the positive sequence component is denoted as a zero sequence ratio.

[0020] The three-phase imbalance degree is positively correlated with the negative sequence ratio and the zero sequence ratio, respectively.

[0021] In one embodiment, the three-phase imbalance degree is the average of the negative sequence ratio and the zero sequence ratio.

[0022] In one embodiment, the current change characteristic value is the product of the average of the change coefficients of all phases in each period and the three-phase imbalance degree.

[0023] In one embodiment, the process of obtaining the abnormal vibration characteristic value is as follows:

[0024] obtaining each peak value of the vibration data in time sequence in each period, and recording the dispersion of all peak values in the vibration data in each period as a peak dispersion;

[0025] obtaining a margin index of the vibration data in each period;

[0026] The abnormal vibration characteristic value is positively correlated with the peak dispersion and the margin index.

[0027] In one embodiment, the comprehensive change value is a weighted sum of a normalized value of the current change characteristic value and a normalized value of the abnormal vibration characteristic value.

[0028] In one embodiment, the difference coefficient is obtained by:

[0029] calculating a difference value between the prediction value and the comprehensive change value of each period;

[0030] The difference coefficient is a mean value of the difference values of each period and a plurality of adjacent periods before the each period.

[0031] In one embodiment, the adjustment method of the prediction step parameter is:

[0032] adjusting an adjustment interval of a prediction step parameter of a model predictive control, wherein the adjustment interval includes a plurality of periods;

[0033] multiplying a normalized value of the difference coefficient in a first period in each adjustment interval by a preset value to obtain a prediction step parameter of a next adjustment interval of the model predictive control.

[0034] In a second aspect, the embodiments of the present application also provide a permanent magnet synchronous motor control system for reducing heat loss, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the permanent magnet synchronous motor control method for reducing heat loss.

[0035] The present application has at least the following beneficial effects:

[0036] The present application can accurately reflect the harmonic problems and the abnormal degree of the waveform in each phase current by calculating the change coefficient, comprehensively considering the harmonic distortion and change of the current, and considering the unbalanced characteristics between the three-phase currents by calculating the three-phase unbalance degree; and then the current change characteristic value obtained by combining the change coefficient and the three-phase unbalance degree can accurately evaluate the eddy current loss intensity caused by the current quality problem in each period.

[0037] Further, by analyzing the fluctuation degree and pulse characteristics of the vibration data, abnormal vibration characteristic values are obtained, which can accurately reflect the wear and tear caused by mechanical reasons in each period;

[0038] Further, by combining the current change characteristic value with the abnormal vibration characteristic value, a comprehensive change value is obtained, which can more comprehensively and accurately evaluate the heat loss of the permanent magnet synchronous motor under complex operating conditions, and provide more comprehensive reference for subsequent optimization control;

[0039] Further, considering the delay effect of heat transfer, by obtaining the predicted value of the comprehensive change value and comparing it with the actual value, the delay effect of heat transfer can be considered in advance, so that the speed of the permanent magnet synchronous motor can be accurately regulated according to the real-time heating state of the permanent magnet synchronous motor, thereby reducing the heat loss of the permanent magnet synchronous motor in time. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0041] Figure 1 A step flow chart of a permanent magnet synchronous motor control method for reducing heat loss provided by an embodiment of the present application;

[0042] Figure 2 A schematic diagram of the acquisition process of the comprehensive change value;

[0043] Figure 3 A schematic diagram of the acquisition process of the difference coefficient. DETAILED DESCRIPTION

[0044] In the description of the embodiments of the present application, the words "exemplary", "or", "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplary", "or", "for example" are intended to present the relevant concept in a specific manner.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art to which the present application belongs. The terms used in the present application are only for the purpose of describing the specific embodiments and are not intended to limit the present application. It should be understood that, in the present application, unless otherwise specified, " / " means or.

[0046] In addition, it should be noted that the terms "first", "second" in the present application are used to distinguish similar objects, not to describe a specific order or sequence.

[0047] The specific scheme of the permanent magnet synchronous motor control method and system for reducing heat loss provided by the present application will be specifically described below in combination with the drawings.

[0048] Please refer to Figure 1 , which shows the step flow chart of a permanent magnet synchronous motor control method for reducing heat loss provided by an embodiment of the present application, which comprises the following steps:

[0049] Step 1, real-time acquisition of the current data of each phase of the stator in the permanent magnet synchronous motor and the vibration data of the bearing seat.

[0050] The heat loss generated by the permanent magnet synchronous motor in operation mainly comes from the winding loss, eddy current loss and mechanical loss. Among them, the winding loss is mainly determined by the relevant parameters of the motor equipment, such as the wire cross-sectional area or the size of the slot space, which is difficult to reduce the loss by control adjustment; the eddy current loss is caused by a large amount of eddy current induced by the harmonic components of current and voltage in the permanent magnet; and the mechanical loss is mainly caused by the friction generated by the rotation of the bearing or the additional friction caused by the imbalance of the rotor. In order to monitor the eddy current loss and mechanical loss state of the permanent magnet synchronous motor in real time during operation, high-precision current sensors are used to collect the current data of each phase of the stator in the permanent magnet synchronous motor in real time, and vibration sensors are used to collect the vibration data of the bearing seat in real time.

[0051] In this embodiment, the collection frequency of current data and vibration data is set to 2kHz, and the collection frequency of current data and vibration data is set by human being, and the implementer can set it according to the actual situation, and the present application does not make special limitation.

[0052] Step 2, analyze the current data and vibration data in each period respectively, obtain the change coefficient of each phase in each period, and obtain the current change characteristic value in each period, and then obtain the comprehensive change value of the permanent magnet synchronous motor in each period.

[0053] When the permanent magnet synchronous motor operates at high frequency or high speed, the magnetic field change rate increases, which will cause the induced eddy current in the core and permanent magnet to increase, in addition, in the process of load mutation or dynamic adjustment, the bearing friction or rotor eccentricity problem will also cause the mechanical loss to increase significantly. The above factors jointly act on the permanent magnet synchronous motor, which will cause the permanent magnet synchronous motor to appear significant heat abnormality under complex working conditions. Therefore, it is necessary to analyze the running state of the permanent magnet synchronous motor.

[0054] Step 2.1, obtain the change coefficient of each phase in each time period through the harmonic distortion and change of the current data of each phase in each time period, and obtain the current change characteristic value in each time period by combining the three-phase unbalance degree in each time period obtained by analyzing the symmetrical components of the three-phase current data in each time period.

[0055] When the eddy current loss of the permanent magnet synchronous motor increases, it indicates that there are a large number of harmonic magnetic fields in the permanent magnet synchronous motor, which are generated by non-sinusoidal current excitation, and the ideal current is a standard sine wave. The non-sinusoidal current excitation is that the current contains obvious harmonic components, that is, in addition to the fundamental frequency, there are rich harmonic components of each order, in addition, the more serious the distortion of the current waveform is, the more obvious the local abnormal jitter characteristics in the waveform are, and the more obvious the unbalance characteristics between the currents of each phase are. Therefore, by analyzing the abnormal characteristics of the stator current waveform, the eddy current loss state of the permanent magnet synchronous motor can be reflected.

[0056] Based on the above analysis, a fixed length time period is set to analyze the state of the permanent magnet synchronous motor in a short time. The change coefficient of each phase in each time period is obtained through the harmonic distortion and change of the current data of each phase in each time period, and the specific process is as follows:

[0057] Obtain the frequency spectrum of the current data of each phase in each time period; the ratio of the amplitude of each odd harmonic frequency to the amplitude of the fundamental frequency in each frequency spectrum is denoted as the amplitude ratio; and the sum of all the amplitude ratios in the frequency spectrum is calculated.

[0058] Obtain the fitting curve of the current data of each phase in each time period, and obtain the first derivative of the fitting curve at each time in each time period; the dispersion of all the first derivatives of the fitting curve in each time period is denoted as the change dispersion.

[0059] The change coefficient of each phase in each time period is positively correlated with the sum and the change dispersion, respectively. The calculation of the derivative is a known technology, and will not be described herein. It should be noted that when calculating the amplitude ratio, if the amplitude of the fundamental frequency is 0, in order to avoid the case that the denominator is 0 and cannot be calculated, the cumulative sum of the amplitude of the fundamental frequency and 0.01A is calculated first, and then the ratio of the amplitude of the odd harmonic frequency to the cumulative sum is taken as the amplitude ratio, wherein 0.01A is only an embodiment of the present application, and the implementer can set it according to the actual situation, and the present application does not make special limitations.

[0060] It should be noted that the dispersion refers to the unevenness of data distribution, which can be realized by calculating the standard deviation, variance, coefficient of variation, etc., and the present application does not make special limitations.

[0061] It should be noted that: positive correlation refers to the same change direction of variables, one variable increases, the other variable also increases, one variable decreases, the other variable also decreases.

[0062] In this embodiment, the length of the time period is 1s, and the length of the time period is artificially preset. The implementer can set it according to the actual situation, and the application does not make special restrictions.

[0063] In this embodiment, the fast discrete Fourier transform technique is used to obtain the frequency spectrum diagram of the current data, wherein the fast discrete Fourier transform technique is a known technique, and the application will not be repeated. As other embodiments, on the basis of being able to realize obtaining the frequency spectrum diagram of the current data, the implementer can adopt other existing feasible techniques, and the application does not make special restrictions.

[0064] In this embodiment, the fundamental frequency is 50HZ.

[0065] In this embodiment, in the process of calculating the change coefficient, the odd harmonic frequency involved is N times the fundamental frequency, wherein N is an odd number in the interval [3, 11] to balance the calculation complexity and accuracy. The value of N is artificially preset, and the implementer can set it according to the actual situation, and the application does not make special restrictions.

[0066] In this embodiment, the least square method is used to obtain the fitting curve of the current data, wherein the least square method is a known technique, and the application will not be repeated. As other embodiments, on the basis of being able to realize obtaining the fitting curve of the current data, the implementer can adopt other existing techniques, such as local weighted regression, K-neighborhood regression, etc., and the application does not make special restrictions.

[0067] In this embodiment, the dispersion of the first derivative is the coefficient of variation.

[0068] In this embodiment, the expression of the change coefficient of each phase in each time period is:

[0069] In the formula, indicates the change coefficient of the i-th phase in the t-th time period; indicates a positive number obtained by mapping the change dispersion of the i-th phase in the t-th time period; represents the sum value of the i-th phase in the t-th time period. The purpose of mapping the change dispersion to a positive number is to avoid the situation that the calculation result of the change coefficient is forced to be 0 when the change dispersion is 0. There are many ways to map data to a positive number, which can be achieved by calculating the sum of data and a preset value greater than 0, or taking data as the index of an exponential function with a natural constant as the base, etc. In this application, unless otherwise specified, the purpose of mapping data to a positive number is achieved by calculating the sum of data and a preset value greater than 0. The value of the preset value greater than 0 is set by human, and the implementer can set its specific value according to the actual situation. In this embodiment, the specific value of the preset value greater than 0 is 0.01.

[0070] In another embodiment, the expression of the change coefficient of each phase in each time period is:

[0071] In the formula, represents the change coefficient of the i-th phase in the t-th time period; represents the change dispersion of the i-th phase in the t-th time period; represents the sum value of the i-th phase in the t-th time period.

[0072] It should be noted that the more obvious the local abnormal jitter characteristics in the current waveform are, the greater the change amplitude of the first derivative is, and the greater the change dispersion calculated is. The odd harmonic frequency energy is extracted from the frequency spectrum of the current data, and the change coefficient is calculated by combining the change amplitude of the first derivative of the waveform at each time, which is used to reflect the harmonic distortion and abnormal waveform characteristics of the three-phase current in each time period. The greater the change coefficient calculated is, the greater the energy proportion of the harmonic component contained in the three-phase current in each time period is, and the more obvious the local abnormal jitter characteristics in the waveform are.

[0073] Further, the more obvious the unbalance characteristics between the three-phase currents are, the more serious the eddy current loss of the permanent magnet synchronous motor exists. Based on the above analysis, the three-phase unbalance degree in each time period is obtained by analyzing the symmetrical components of the three-phase current data in each time period, and the specific process is:

[0074] The positive sequence component, the negative sequence component and the zero sequence component of the three-phase current data in each time period are obtained. Under the balanced state of the three-phase circuit, the negative sequence component and the zero sequence component are small. The higher the modulus of the obtained negative sequence component or zero sequence component is, the more significant the unbalance characteristics in each time period are.

[0075] The ratio of the modulus of the negative sequence component to the modulus of the positive sequence component in each period is denoted as the negative sequence ratio; the ratio of the modulus of the zero sequence component to the modulus of the positive sequence component in each period is denoted as the zero sequence ratio; the average of the negative sequence ratio and the zero sequence ratio in each period is taken as the three-phase unbalance degree in each period. It should be noted that when calculating the negative sequence ratio and the zero sequence ratio, if the modulus of the positive sequence component is 0, in order to avoid the case that the denominator is 0 and the calculation is impossible, the cumulative sum of the modulus of the positive sequence component and 0.01A is calculated first, and then the ratio of the modulus of the negative sequence component and the modulus of the zero sequence component to the cumulative sum is taken as the negative sequence ratio and the zero sequence ratio respectively; wherein 0.01A is only an embodiment of the present application, and the implementer can set it according to the actual situation, and the present application does not make special limitation.

[0076] In the embodiment, the Fortescue transformation is used to obtain the positive sequence component, the negative sequence component and the zero sequence component of the three-phase current data in each period, wherein the Fortescue transformation is a known technology and will not be described herein.

[0077] It should be noted that the three-phase unbalance degree is used to reflect the three-phase current unbalance characteristics of the stator in the permanent magnet synchronous motor in each period; the greater the calculated three-phase unbalance degree, the more significant the three-phase unbalance characteristics.

[0078] Since abnormal response of the current during load mutation or dynamic adjustment is easy to cause eddy current loss, the variation coefficient of each phase in each period and the three-phase unbalance degree in each period are comprehensively analyzed to obtain the current variation characteristic value in each period, which is specifically:

[0079] The average of the variation coefficients of all phases in each period is calculated, and the product of the average in each period and the three-phase unbalance degree is taken as the current variation characteristic value in each period.

[0080] It should be noted that the current variation characteristic value is used to reflect the eddy current loss intensity caused by deterioration of the current quality in each period; the greater the calculated current variation characteristic value, the greater the eddy current loss intensity caused by deterioration of the current quality in each period.

[0081] Step 2.2, the abnormal vibration characteristic value in each period is obtained through the fluctuation degree and the pulse characteristics of the vibration data in each period.

[0082] Further, the rotor eccentricity of the permanent magnet synchronous motor is one of the key reasons for abnormal heating under complex working conditions. When the rotor is eccentric, the air gap is no longer uniform, causing periodic fluctuations in the saturation of the magnetic circuit at the stator slot opening, which not only increases the eddy current loss to some extent, but also induces severe mechanical vibration and noise, thereby exacerbating local temperature rise. The more obvious the abnormal vibration characteristics, the more serious the bearing friction, and the greater the mechanical loss. The abnormal vibration characteristics of the bearing seat are irregular and severe fluctuations and pulses. Based on this, the abnormal vibration characteristic values in each period are obtained through the fluctuation degree and pulse characteristics of the vibration data in each period, and the specific process is as follows:

[0083] Obtain the peak value of the vibration data in each period in time sequence; under the influence of irregular severe fluctuations, the fluctuation amplitude of the peak value is more random, the dispersion of all peak values in the vibration data in each period is recorded as the peak value dispersion; the peak value dispersion is used to reflect the severe fluctuation degree of the vibration data in each period;

[0084] Obtain the margin index of the vibration data in each period; the margin index is used to reflect the strength of the pulse component in the vibration data of the bearing seat in the permanent magnet synchronous motor in each period;

[0085] The abnormal vibration characteristic values in each period are positively correlated with the peak value dispersion and the margin index. The calculation of the margin index is a known technology, and will not be described here.

[0086] In this embodiment, the Automatic Multiscale-based Peak Detection (AMPD) algorithm is used to obtain the peak value of the vibration data in time sequence. The AMPD algorithm is a known technology and will not be described here. As other embodiments, as long as the peak value of the vibration data in time sequence can be obtained, other existing technologies such as peak and valley detection algorithm, extreme point detection algorithm, etc. can be used, and the application does not make special restrictions.

[0087] In this embodiment, the dispersion of the peak value is the standard deviation.

[0088] In this embodiment, the peak value dispersion is mapped to a positive number, and the product of the mapped positive number and the margin index is taken as the abnormal vibration characteristic value in each period. The purpose of mapping the peak value dispersion to a positive number is to avoid the situation that the calculation result of the abnormal vibration characteristic value is forced to be 0 when the peak value dispersion is 0.

[0089] In another embodiment, the sum of the peak value dispersion and the margin index is taken as the abnormal vibration characteristic value in each period.

[0090] It should be noted that the abnormal vibration characteristic value is used to reflect the abnormal vibration characteristics of the bearing seat in the permanent magnet synchronous motor in each period; the greater the calculated abnormal vibration characteristic value, the more obvious the abnormal vibration characteristics, and at this time, the mechanical loss intensity of the permanent magnet synchronous motor is greater.

[0091] Step 2.3, the current change characteristic value and the abnormal vibration characteristic value are integrated to obtain the comprehensive change value of the permanent magnet synchronous motor in each period.

[0092] Under the complex operating conditions of variable speed or variable load, the permanent magnet synchronous motor is more likely to have eddy current loss and mechanical loss, which will cause the permanent magnet synchronous motor to heat significantly. Since the current change characteristic value reflects the eddy current loss intensity of the permanent magnet synchronous motor, and the abnormal vibration characteristic value reflects the mechanical loss intensity of the permanent magnet synchronous motor, the current change characteristic value and the abnormal vibration characteristic value in each period are integrated to obtain the comprehensive change value of the permanent magnet synchronous motor in each period, which is used to reflect the influence degree characteristic of the complex operating conditions on the heating loss of the permanent magnet synchronous motor in each period, and the expression is:

[0093] In the formula, comprehensive change value of the permanent magnet synchronous motor in the tthperiod; , are both preset constants greater than 0; normalized value of the current change characteristic value in the tthperiod; normalized value of the abnormal vibration characteristic value in the tthperiod.

[0094] In this embodiment, , the values of and are 0.55 and 0.45 respectively, , the values of and are obtained from experimental data.

[0095] In this embodiment, the Min-Max normalization method is used to obtain the normalized values of the current change characteristic value and the abnormal vibration characteristic value, wherein the Min-Max normalization method is a known technology, and will not be described herein.

[0096] It should be noted that by comprehensively considering the eddy current loss intensity and the mechanical loss degree of the permanent magnet synchronous motor under complex operating conditions, the heating influence characteristics of the permanent magnet synchronous motor are analyzed to obtain the comprehensive change value; the greater the calculated comprehensive change value, the more obvious the influence degree characteristic of the complex operating conditions on the heating loss of the permanent magnet synchronous motor in each period. The flowchart for obtaining the comprehensive change value is shown in Figure 2 .

[0097] Step 3, obtaining the predicted value of the comprehensive change value of the plurality of adjacent time periods of each time period, and obtaining the difference coefficient in each time period by comparing the comprehensive change value of the plurality of adjacent time periods of each time period with the predicted value.

[0098] Further, no matter the eddy current loss or the mechanical loss, there is a certain delay in the heat generated in the permanent magnet synchronous motor being transferred to the shell, resulting in a lagging effect of the temperature data collected through the shell. Therefore, by predicting and analyzing the influence characteristics of the heat generation loss, compared with directly relying on the shell temperature data of the permanent magnet synchronous motor, the overheat risk of the permanent magnet synchronous motor can be identified earlier and more actively.

[0099] Based on the above analysis, the predicted value of the comprehensive change value of each time period and a plurality of adjacent time periods before the time period is obtained, and the difference coefficient in each time period is obtained by comparing the comprehensive change value of each time period and a plurality of adjacent time periods before the time period with the predicted value, which is used to reflect the dynamic change of the heat generation loss of the permanent magnet synchronous motor in the running process. The specific process is as follows:

[0100] The difference between the predicted value and the comprehensive change value of each time period is calculated; and the average value of the difference of each time period and a plurality of adjacent time periods before the time period is taken as the difference coefficient in each time period. The flowchart of obtaining the difference coefficient is shown in Figure 3 .

[0101] In this embodiment, in order to avoid too many adjacent time periods and increase the calculation complexity, and to avoid too few adjacent time periods and not enough historical information, the number of adjacent time periods of each time period is 20, and the number of adjacent time periods is artificially preset. When the number of adjacent time periods is an integer in the interval [20, 25], the implementer can set the number of adjacent time periods, and the present application does not make special limitation.

[0102] In this embodiment, the first-order exponential smoothing algorithm is used to obtain the predicted value of the comprehensive change value, wherein the first-order exponential smoothing algorithm is a known technology, and the present application will not be described again. As other embodiments, on the basis of obtaining the predicted value of the comprehensive change value, the implementer can use other existing technologies such as Kalman filter, and the present application does not make special limitation.

[0103] Step 4, using model predictive control to regulate the speed of the permanent magnet synchronous motor, so as to reduce the heat generation loss of the permanent magnet synchronous motor, wherein the prediction step parameter of the model predictive control is adjusted through the difference coefficient.

[0104] The application analyzes the abnormal change characteristics of the stator current and the bearing seat vibration during the operation of the permanent magnet synchronous motor, extracts the eddy current loss intensity and mechanical loss degree of the permanent magnet synchronous motor under complex operating conditions, and considers the delay characteristics of heat transfer, and analyzes the heating state characteristics of the permanent magnet synchronous motor. Based on this, the model predictive control is used to adjust the speed of the permanent magnet synchronous motor to reduce the heating loss, wherein the difference coefficient in each period is used to adjust the prediction step parameter of the model predictive control, specifically:

[0105] When the difference coefficient is larger, the temperature rise characteristics are more obvious, and at this time, a larger prediction step parameter is set to better suppress the load disturbance and further reduce the heating loss of the permanent magnet synchronous motor; on the contrary, the smaller the difference coefficient is, the smaller the heating loss is, and at this time, a smaller prediction step parameter is set to improve the dynamic response of the control system.

[0106] Based on the above analysis, first, in order to reduce the calculation delay interference, the adjustment interval of the prediction step parameter of the model predictive control is preset, wherein the adjustment interval contains multiple periods; the product of the normalized value of the difference coefficient in the first period in each adjustment interval and the preset value is used as the prediction step parameter of the model predictive control in the next adjustment interval of each adjustment interval. At the same time, in order to avoid the problem that the prediction step parameter is too small, resulting in weak anti-disturbance ability, the lower limit of the prediction step parameter is set to 10.

[0107] In this embodiment, the length of the adjustment interval is 1 min, and the length of the adjustment interval is artificially preset. The implementer can set it according to the actual situation, and the application does not make special restrictions.

[0108] In this embodiment, the process of obtaining the normalized value of the difference coefficient is: using the Min-Max normalization method to map the difference coefficient to the interval [-3, 3] to ensure that the input value of the sigmoid function falls in its linear sensitive region, preventing the output of the sigmoid function from being always 1 or 0, wherein the sigmoid function is a known technology, and the application will not be repeated.

[0109] In this embodiment, the value of the preset value is 30, and the value of the preset value is obtained by historical experiment verification. The implementer can set it according to the actual situation, and the application does not make special restrictions.

[0110] Further, the actual speed data of the first period in each adjustment interval is input into the model predictive control, and the inverter duty cycle signal is output, which is used to adjust the speed of the next adjustment interval of each adjustment interval, so as to reduce the heating loss of the permanent magnet synchronous motor in time.

[0111] Based on the same inventive concept as the above method, the embodiment of the present application also provides a permanent magnet synchronous motor control system for reducing heat loss, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any one of the above methods for reducing heat loss of a permanent magnet synchronous motor.

[0112] In summary, the present application calculates the variation coefficient, comprehensively considers the harmonic distortion and variation of the current, and can accurately reflect the harmonic problems and the abnormal degree of the waveform in the current of each phase. The three-phase unbalance degree is calculated, and the imbalance characteristics between the three-phase currents are considered. Then, the current variation characteristic value is obtained by combining the variation coefficient and the three-phase unbalance degree, and the eddy current loss intensity caused by the current quality problem in each period can be accurately evaluated.

[0113] Further, by analyzing the fluctuation degree and pulse characteristics of the vibration data, the abnormal vibration characteristic value is obtained, which can accurately reflect the loss caused by mechanical reasons in each period.

[0114] Further, the current variation characteristic value and the abnormal vibration characteristic value are combined to obtain a comprehensive variation value, which can more comprehensively and accurately evaluate the heat loss of the synchronous permanent magnet motor under complex operating conditions, and provide a more comprehensive reference for subsequent optimization control.

[0115] Further, considering the delay effect of heat transfer, by obtaining the predicted value of the comprehensive variation value and comparing it with the actual value, the delay effect of heat transfer can be considered in advance, so that the speed of the permanent magnet synchronous motor can be accurately controlled according to the real-time heat state of the permanent magnet synchronous motor, thereby reducing the heat loss of the permanent magnet synchronous motor in time.

[0116] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0117] It is apparent that a person skilled in the art can make a variety of modifications to the application described above without departing from the spirit and scope of the application. Therefore, the above-described embodiments of the application are to be considered exemplary and not restrictive, and the application is not limited to the details given herein but can be implemented in other specific forms without departing from the basic characteristics thereof.

Claims

1. A method of controlling a permanent magnet synchronous motor to reduce heat generation loss, characterized by, The method comprises the following steps: Real-time acquisition of stator phase current data and bearing seat vibration data in the permanent magnet synchronous motor; Obtaining the change coefficient of each phase in each period through the harmonic distortion and change of the current data of each phase in each period, and obtaining the three-phase unbalance degree in each period through the analysis of the symmetrical components of the three-phase current data in each period, to obtain the current change characteristic value in each period; Obtaining the abnormal vibration characteristic value in each period through the fluctuation degree and pulse characteristics of the vibration data in each period; Obtaining the comprehensive change value of the permanent magnet synchronous motor in each period by comprehensively considering the current change characteristic value and the abnormal vibration characteristic value; Obtaining the prediction value of the comprehensive change value of the plurality of adjacent periods of each period, and obtaining the difference coefficient in each period by comparing the comprehensive change value of the plurality of adjacent periods of each period with the prediction value; Using model predictive control to regulate the speed of the permanent magnet synchronous motor, thereby reducing the heat loss of the permanent magnet synchronous motor, wherein the prediction step parameter of the model predictive control is adjusted through the difference coefficient.

2. The control method of the permanent magnet synchronous motor for reducing the heat generation loss according to claim 1, wherein, The process of the change coefficient is as follows: Obtaining the frequency spectrum of the current data of each phase in each period; the ratio of the amplitude of each odd harmonic frequency to the amplitude of the fundamental frequency in the frequency spectrum is denoted as the amplitude ratio; Calculating the sum of all amplitude ratios in the frequency spectrum; Obtaining the fitting curve of the current data of each phase in each period, and obtaining the first derivative of the fitting curve at each time in each period; the dispersion of all first derivatives of the fitting curve in each period is denoted as the change dispersion; The change coefficient is positively correlated with the sum and the change dispersion.

3. The control method of a permanent magnet synchronous motor for reducing heat generation loss according to claim 1, characterized in that, The process of obtaining the three-phase unbalance degree is as follows: Obtaining the positive sequence component, negative sequence component and zero sequence component of the three-phase current data in each period; The ratio of the modulus of the negative sequence component to the modulus of the positive sequence component is denoted as the negative sequence ratio; The ratio of the modulus of the zero sequence component to the modulus of the positive sequence component is denoted as the zero sequence ratio; The three-phase unbalance degree is positively correlated with the negative sequence ratio and the zero sequence ratio.

4. The control method of a permanent magnet synchronous motor for reducing heat generation loss according to claim 3, characterized in that, The three-phase unbalance degree is the average of the negative sequence ratio and the zero sequence ratio.

5. The control method of a permanent magnet synchronous motor for reducing heat generation loss according to claim 1, wherein The current change characteristic value is the product of the average of the change coefficients of all phases in each period and the three-phase unbalance degree.

6. The control method of a permanent magnet synchronous motor for reducing heat generation loss according to claim 1, wherein The process of obtaining the abnormal vibration characteristic value is as follows: Obtaining each peak value of the vibration data in each period in time sequence, and denoting the dispersion of all peak values in the vibration data in each period as the peak value dispersion; Obtaining the margin index of the vibration data in each period; The abnormal vibration characteristic value is positively correlated with the peak value dispersion and the margin index.

7. The control method of a permanent magnet synchronous motor reducing heat generation loss according to claim 1, wherein, The comprehensive change value is the weighted sum of the normalized value of the current change characteristic value and the normalized value of the abnormal vibration characteristic value.

8. The control method of a permanent magnet synchronous motor for reducing heat generation loss according to claim 1, wherein, The process of obtaining the difference coefficient is as follows: Calculating the difference between the prediction value and the comprehensive change value of each period; The difference coefficient is the average of the difference values of each period and the plurality of adjacent periods before each period.

9. The control method of a permanent magnet synchronous motor reducing heat generation loss according to claim 1, wherein, The adjustment method of the prediction step parameter is as follows: Pre-setting the adjustment interval of the prediction step parameter of the model predictive control, wherein the adjustment interval contains a plurality of periods; The product of the normalized value of the difference coefficient in the first time period in each adjustment interval and a preset value is taken as a prediction step parameter of the model predictive control in the next adjustment interval of each adjustment interval.

10. A permanent magnet synchronous motor control system for reducing heat loss, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, The processor implements the steps of the permanent magnet synchronous motor control method for reducing heat loss according to any one of claims 1-9 when executing the computer program.

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