A variable frequency control and management system and method applied to a permanent magnet motor

Abstract

The present invention discloses a variable frequency control management system and method applied to a permanent magnet motor, relating to the technical field of permanent magnet motor control. It synchronizes the historical operation data collected by a data acquisition card; obtains the reading period of a controller and determines a fixed time step based on the reading period of the controller, and performs short-term prediction on the operation data of the fixed time step; calculates the matching degree between the synchronized real-time operation data and the input of a prediction model storing prediction results, and determines the predicted value of the real-time operation data based on the matching degree; the controller generates a control signal for an actuator based on the predicted value of the real-time operation data; controls the permanent magnet motor to match the operation data collected by the data acquisition card, and trains the model with the operation data at the same sampling time point to improve the prediction effect of the model; the controller obtains the operation data of the permanent magnet motor at the moment when the actuator acts, and generates a control signal according to the operation data to improve the real-time control ability of the control system.

Description

Technical Field

[0001] The present invention relates to the technical field of permanent magnet motor control, and specifically to a variable frequency control management system and method applied to a permanent magnet motor. Background Art

[0002] The excellent speed regulation performance and brushless operation characteristics of permanent magnet synchronous motors make them the first choice in the modern speed regulation field and the electrical drive field. After the motor is powered by an inverter, the design of the motor is more flexible, and many parameters are no longer restricted by the power grid, such as the number of phases, voltage, frequency, etc. of the motor. The speed of the motor can also be set arbitrarily according to requirements. Many functions originally completed by the motor body, such as starting characteristics, overload capacity, etc., can be jointly completed by the integrated system of the inverter and the motor. To fully utilize the advantages of high efficiency, energy saving, high reliability, and high power density of permanent magnet motors, a variable frequency control system must be well configured. The development and supporting application of the variable frequency control system for permanent magnet synchronous motors are of great significance. The acquisition and analysis of the operating parameters of the variable frequency control system is a complex process. To ensure that signals can be accurately acquired and reproduced, the sampling rate of the data acquisition card should be at least 10 times higher than the signal frequency. Since the signal frequencies of different operating parameters are not exactly the same and have different requirements for the sampling rate, the sampling rates of the data acquisition cards are not exactly the same, and it is impossible to ensure that the acquired operating data is the operating data at the same time point. Since the controller needs to generate control signals based on the operating data, the control effect of the controller is affected. Therefore, how to improve the control effect of the controller has become an urgent problem to be solved. Summary of the Invention

[0003] The purpose of the present invention is to provide a variable frequency control management system and method applied to a permanent magnet motor to solve the problems raised in the prior art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A variable frequency control management method applied to a permanent magnet motor, including:

[0005] S11, obtaining the historical operating data and sampling time data collected by each data acquisition card, synchronizing the historical operating data collected by the data acquisition card according to the sampling time of the data acquisition card, and training the prediction model of the operating data with the synchronized operating data;

[0006] S12, obtaining the reading cycle of the controller and determining a fixed time step based on the reading cycle of the controller, performing short-term prediction on the operating data of the fixed time step through the prediction model of the operating data, and storing the prediction result and the input of the prediction model;

[0007] S13. The data acquisition card obtains the real-time operation data of the permanent magnet motor. After synchronizing the real-time operation data according to the sampling time of the data acquisition card, it calculates the matching degree between the synchronized real-time operation data and the input of the prediction model storing the prediction result in step S12, and determines the predicted value of the real-time operation data based on the matching degree.

[0008] S14. The controller generates a control signal based on the predicted value of the real-time operation data for the actuator to control the permanent magnet motor.

[0009] In step S11, the synchronization of the historical operation data collected by the data acquisition card according to the sampling time of the data acquisition card further includes the following steps:

[0010] Let T i represent the sampling period of the i-th data acquisition card, and determine the maximum value T j of the sampling period. Let the j-th data acquisition card be the reference data acquisition card, and synchronize the historical operation data collected by other data acquisition cards according to the sampling period T j of the reference data acquisition card. Specifically, it includes the following steps:

[0011] S21. Obtain the number of times m i that the i-th data acquisition card has collected operation data and the number of times m j that the reference data acquisition card has collected operation data, and calculate the total sampling time m i ×T i of the i-th data acquisition card and the total sampling time m j ×T j of the reference data acquisition card;

[0012] S22. Determine the difference m i ×T i -m j ×T j between the total sampling time of the i-th data acquisition card and the total sampling time of the reference data acquisition card, and synchronize the operation data collected by the i-th data acquisition card according to the difference. Let x(m i ) represent the m i -th operation data collected by the i-th data acquisition card. If m i ×T i -m j ×T j is greater than zero, then the synchronized x(m i ) is tx(m i ), and tx(m i ) = x(m i ) - v × (m i ×T i -m j ×T j); if m i ×T i -m j ×T j is not greater than zero, then tx(m i ) = x(m i ) + v × (m j ×T j -m i ×T i ), where v is the transformation rate of the running data of the i-th data acquisition card, and v = [x(m i ) - x(m i-1 )] / T i .

[0013] In order to predict the running data, it is necessary to obtain the historical data of the data acquisition card. Since the sampling periods of the data acquisition cards are not exactly the same, the data used for prediction are not generated at the same time point, and there is a time difference in the data used to train the prediction model, and the time difference is not fixed, which will affect the effect of the prediction model. Therefore, the data collected by the data acquisition card is synchronized; after synchronization, a richer data set can be obtained. Before synchronization, for the i-th data acquisition card, the time difference of the collected running data is fixed at T i , and after synchronization, the difference m j ×T j -m i ×T i will change with time, and the running data with a time difference of m j ×T j -m i ×T i +k×T i can be obtained, and k can take any value.

[0014] In step S11, training the prediction model of the running data with the synchronized running data further includes the following steps:

[0015] S31. Obtain the running data collected by each data acquisition card after synchronization, and divide the running data into a training data set and a test data set. In the training data set, for the running data of the i-th data acquisition card, use the running data collected by each data acquisition card between the synchronized t moment and the t-p moment and the target time difference as the input, and the running data of the i-th data acquisition card that is not synchronized after the t moment as the output, and train the prediction model of the running data of the i-th data acquisition card. Here, p is the order of the prediction model, and the target time difference is the time difference between the t moment and the sampling node of the i-th data acquisition card after the t moment; in the test data set, verify the prediction model of the running data of the i-th data acquisition card obtained by training, and after verification, obtain the short-term prediction model of the running data of the i-th data acquisition card;

[0016] S32. Perform step S31 on the operation data of all data acquisition cards to obtain a prediction model for all operation data.

[0017] The sampling time points at times t, t - 1, …, t - p are the sampling time points of the reference data acquisition card and also the corresponding sampling time points of the operation data of all data acquisition cards after synchronization; p is the order of the prediction model, which can be determined by the grid search method, that is, under different orders p, train the prediction models for the operation data of the i-th data acquisition card respectively, and the order p corresponding to the prediction model with the best verification effect is the required order of the prediction model; the sampling time point at time t is the sampling time point of the reference data acquisition card and may not be the sampling node of the i-th data acquisition card. For the sampling nodes t1, t2, etc. of the i-th data acquisition card after time t, first calculate the error between t and t1, then use the operation data collected by the i-th data acquisition card at time t1 as the output, and use the operation data collected by each data acquisition card between time t and t - p and the target time difference t1 - t after synchronization as the input to obtain a set of training or test data; for the sampling node t2, only change the target time difference to t2 - t and use the operation data collected by the i-th data acquisition card at time t2 as the output to obtain another set of training or test data; the time difference between t1 and t is not fixed and will change with the increase in the sampling times of the i-th data acquisition card and the reference data acquisition card, so the data set for training the prediction model can be expanded.

[0018] In step S12, the determination of the fixed time step based on the reading cycle of the controller further includes the following steps:

[0019] S41. Let T c represent the reading cycle of the controller, m c represent the number of times the controller reads, T s represent the time required for the actuator to obtain the control signal of the controller, and T s is determined by measurement; calculate the total reading time m c ×T c ;

[0020] S43. Analyze the difference between the total reading time of the controller and the total sampling time of the i-th data acquisition card. Let k1 and k2 be 1, where k1 and k2 are test coefficients, representing the number of times the controller reads and the number of times the i-th data acquisition card collects operation data during testing;

[0021] S44. Calculate the difference k1×T c -k2×T i and record the data;

[0022] S45. Determine whether the difference is greater than 0. If it is greater than 0, increment the value of k2 by 1, and return to step S44. If it is less than 0, increment the value of k1 by 1, and return to step S44. If it is equal to 0, complete the test and proceed to step S46;

[0023] S46. Obtain the data of all records, and add T to the recorded data s , to obtain the fixed time step for prediction required by the i-th data acquisition card.

[0024] The difference between the total reading time of the controller and the total sampling time of the i-th data acquisition card changes periodically. For example, when the total reading time of the controller reaches the least common multiple of T c and T i , at this time, the i-th data acquisition card also just completes data acquisition, the difference is 0, and it continues to accumulate from 0 with time change; when the i-th data acquisition card acquires operation data at time T i , and the controller reads the data of the data acquisition card at time T c , the controller generates a control signal according to the operation data at time T c , and at time T i +T i , the actuator receives the control signal, that is, the actuator acts according to the operation data at time T s . In fact, the actuator needs to act according to the operation data at time T i +T i . Therefore, it is necessary to obtain operation data slightly in advance so that the action of the actuator matches the current operation data; for the time to be advanced, T s remains constant, while the difference between the total reading time of the controller and the total sampling time of the i-th data acquisition card changes periodically. The total reading time of the controller and the total sampling time of the i-th data acquisition card are calculated starting from zero when the permanent magnet motor starts, and are cleared after the permanent magnet motor completes braking. s

[0025] In step S12, the short-term prediction of the operation data for the fixed time step further includes the following steps:

[0026] S51. For the i-th data acquisition card, obtain the historical operation data collected by each data acquisition card after synchronization. Combine the consecutive p + 1 synchronized historical operation data of each data acquisition card with the fixed time step required for prediction by the i-th data acquisition card to obtain an input vector. Input the input vector into the prediction model of the operation data of the i-th data acquisition card to obtain the short-term prediction result of the operation data of the i-th data acquisition card for the fixed time step;

[0027] In S52, the moving window changes the selected consecutive p + 1 synchronized historical operation data, and repeats step S51 to obtain the short-term prediction results of the operation data of the i-th data acquisition card for a fixed time step under different operation data; store the input vector and the short-term prediction results of the operation data of the i-th data acquisition card for a fixed time step; perform the same steps for all data acquisition cards, and store the short-term prediction results and input vectors of all data acquisition cards.

[0028] By predicting the operation data after a fixed time step in advance, when the prediction results of the operation data are needed, only retrieve from the pre-computed data, without the need for complex on-site calculations, thus reducing the real-time computing requirements and accelerating the response speed; for the prediction of operation data, there are two factors affecting the prediction results. One is the current state of the permanent magnet motor, which is reflected by the consecutive p + 1 synchronized operation data, and the other is how long the operation data needs to be predicted, which is reflected by the fixed time step. For a set of consecutive p + 1 synchronized operation data, they are combined with different fixed time steps respectively and used for prediction to obtain the operation data at the required actuator action moment.

[0029] In step S13, the determination of the predicted value of the real-time operation data based on the matching degree further includes the following steps:

[0030] For the real-time operation data collected by the i-th data acquisition card, obtain the difference e between the total reading time of the controller and the total sampling time of the i-th data acquisition card, and add the time T required for the actuator to obtain the control signal of the controller s , from the short-term prediction results of the operation data of the i-th data acquisition card stored, filter out the short-term prediction results with the same fixed time step as e in the input vector, calculate the Euclidean distance between all real-time operation data and the filtered input vector. If the Euclidean distance is not greater than the preset threshold, then use the short-term prediction result of the input vector with the smallest Euclidean distance as the real-time prediction value of the operation data of the i-th data acquisition card; if the Euclidean distance is greater than the preset threshold, then the real-time operation data of the i-th data acquisition card remains unchanged, without prediction, and the controller directly reads the real-time operation data collected by the i-th data acquisition card; perform the same steps for all data acquisition cards to obtain the real-time prediction values of the operation data of all data acquisition cards.

[0031] Short-term prediction has been carried out in advance through historical operation data. For the generated real-time operation data, only need to find the input vector that matches the real-time operation data, then the short-term prediction result of the real-time operation data can be obtained according to the corresponding short-term prediction result of the input vector; for the short-term prediction results and input vectors of all stored data acquisition cards, use the method of regular update to ensure the availability of the stored data.

[0032] To achieve the above object, the present invention provides the following technical solution: A variable frequency control and management system applied to a permanent magnet motor, including a data acquisition module, a data storage module, a control module, and a data analysis module; the output end of the data acquisition module is connected to the input ends of the data storage module and the control module, and is used to obtain the operation data of the permanent magnet motor; the output end of the data storage module is connected to the input end of the data analysis module, and is used to store the historical operation data of the permanent magnet motor; the output end of the data analysis module is connected to the input end of the control module, and is used to synchronize the operation data collected by the data acquisition card, and use the synchronized operation data to train the short-term prediction model of the operation data to obtain the short-term prediction result of the operation data; the control module generates a control signal according to the read operation data to control the permanent magnet motor.

[0033] The data storage module obtains the operation data of the permanent magnet motor through a data acquisition card, transmits the operation data of the permanent magnet motor to the control module in real time, and stores the obtained operation data in the data storage module. The data analysis module further includes a first synchronization unit, an operation data prediction unit, and a data generation unit; the first synchronization unit is used to synchronize the operation data of each data acquisition card; the operation data prediction unit is used to train the short-term prediction model of the operation data of each data acquisition card; the data generation unit, according to the historical operation data of each data acquisition card and the time step to be predicted, obtains the short-term prediction result of the fixed time step under the historical operation data. The control module further includes a second synchronization unit, a matching unit, a controller, and an actuator; the second synchronization unit is used to synchronize the operation data of each received data acquisition card; the matching unit is used to store the operation data and short-term prediction results of each data acquisition card, and based on the matching degree between the synchronized operation data of each data acquisition card and the stored input vector, obtain the real-time prediction value of the operation data of each data acquisition card, and give the real-time prediction value of the operation data of each data acquisition card to the controller for reading. When there is no matching input vector, directly give the real-time operation data to the controller for reading; the controller generates a control signal based on the obtained operation data of the permanent magnet motor; the actuator generates a corresponding action according to the control signal to control the permanent magnet motor.

[0034] Compared with the prior art, the beneficial effect of the present invention is: Matching the operation data collected by the data acquisition card, training the model with the operation data at the same sampling time point, and improving the prediction effect of the model; the controller obtains the operation data of the permanent magnet motor at the moment when the actuator acts, and generates a control signal according to the operation data, improving the real-time control ability of the control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1Schematic structural diagram of a variable-frequency control and management system applied to a permanent magnet motor according to the present invention. Detailed implementation manners

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] Embodiment: As Figure 1 shown, the present invention provides a technical solution, a variable-frequency control and management system applied to a permanent magnet motor, including a data acquisition module, a data storage module, a control module, and a data analysis module; the output end of the data acquisition module is connected to the input ends of the data storage module and the control module, and is used to obtain the operation data of the permanent magnet motor; the output end of the data storage module is connected to the input end of the data analysis module, and is used to store the historical operation data of the permanent magnet motor; the output end of the data analysis module is connected to the input end of the control module, and is used to synchronize the operation data collected by the data acquisition card, and use the synchronized operation data to train the short-term prediction model of the operation data to obtain the short-term prediction result of the operation data; the control module generates a control signal to control the permanent magnet motor according to the read operation data.

[0038] The data storage module obtains the operation data of the permanent magnet motor through a data acquisition card, transmits the operation data of the permanent magnet motor to the control module in real time, and stores the obtained operation data in the data storage module. The data analysis module further includes a first synchronization unit, an operation data prediction unit, and a data generation unit; the first synchronization unit is used to synchronize the operation data of each data acquisition card; the operation data prediction unit is used to train a short-term prediction model for the operation data of each data acquisition card; the data generation unit obtains the short-term prediction results for a fixed time step under the historical operation data according to the historical operation data of each data acquisition card and the time step to be predicted. The control module further includes a second synchronization unit, a matching unit, a controller, and an actuator; the second synchronization unit is used to synchronize the operation data of each received data acquisition card; the matching unit is used to store the operation data and short-term prediction results of each data acquisition card, and based on the matching degree between the synchronized operation data of each data acquisition card and the stored input vector, obtains the real-time prediction value of the operation data of each data acquisition card, and gives the real-time prediction value of the operation data of each data acquisition card to the controller for reading. When there is no matching input vector, the real-time operation data is directly given to the controller for reading; the controller generates a control signal based on the obtained operation data of the permanent magnet motor; the actuator generates a corresponding action according to the control signal to control the permanent magnet motor.

[0039] Embodiment: The present invention provides a technical solution, a variable frequency control management method applied to a permanent magnet motor, including:

[0040] S11, obtaining the historical operation data and sampling time data collected by each data acquisition card, and synchronizing the historical operation data collected by the data acquisition card according to the sampling time of the data acquisition card:

[0041] Let T i represent the sampling period of the i-th data acquisition card, determine the maximum value T j of the sampling period, let the j-th data acquisition card be the reference data acquisition card, and synchronize the historical operation data collected by other data acquisition cards according to the sampling period T j of the reference data acquisition card, which specifically includes the following steps:

[0042] Obtain the number of times m i that the i-th data acquisition card has collected operation data and the number of times m j that the reference data acquisition card has collected operation data, calculate the total sampling time m i ×T i of the i-th data acquisition card, and the total sampling time m j ×T j of the reference data acquisition card;

[0043] Determine the difference m between the total sampling time of the i-th data acquisition card and the total sampling time of the reference data acquisition card i ×T i -m j ×T j , and synchronize the operation data collected by the i-th data acquisition card according to the difference. Let x(m i ) represent the m i -th operation data collected by the i-th data acquisition card. If m i ×T i -m j ×T j is greater than zero, then after synchronization, x(m i ) is tx(m i ), and tx(m i ) = x(m i ) - v × (m i ×T i -m j ×T j ); if m i ×T i -m j ×T j is not greater than zero, then tx(m i ) = x(m i ) + v × (m j ×T j -m i ×T i ), where v is the transformation rate of the operation data of the i-th data acquisition card, and v = [x(m i ) - x(m i-1 )] / T i .

[0044] Train the prediction model of the operation data with the synchronized operation data:

[0045] Obtain the operation data collected by each data acquisition card after synchronization, divide the operation data into a training data set and a test data set. In the training data set, for the operation data of the i-th data acquisition card, use the operation data collected by each data acquisition card between the synchronized t moment and the t - p moment and the target time difference as the input, and the operation data of the i-th data acquisition card that has not been synchronized after the t moment as the output to train the prediction model of the operation data of the i-th data acquisition card. Here, p is the order of the prediction model, and the target time difference is the time difference between the t moment and the sampling node of the i-th data acquisition card after the t moment; in the test data set, verify the prediction model of the operation data of the i-th data acquisition card obtained by training. After verification, obtain the short-term prediction model of the operation data of the i-th data acquisition card; perform the same operation on the operation data of all data acquisition cards to obtain the prediction model of all operation data.

[0046] For example, the electromagnetic torque of a permanent magnet motor is affected by factors such as the d-axis voltage, d-axis current, q-axis voltage, q-axis current, and angular velocity. When it is necessary to control the electromagnetic torque of the permanent magnet motor, the operating data collected by the data acquisition card includes the d-axis voltage, d-axis current, q-axis voltage, q-axis current, and angular velocity data, etc.; for the prediction model of the d-axis voltage, when the sampling period of the q-axis current is the largest, synchronize all the operating data collected by the data acquisition cards to the sampling time point of the d-axis voltage. When the times t, t-1, …, t-p are exactly the sampling time points of the d-axis voltage, use the d-axis voltage, d-axis current, q-axis voltage, q-axis current, angular velocity, and t1-t at the times t, t-1, …, t-p as inputs, and the d-axis voltage at the time t1 as the output to obtain a set of training data; then keep the d-axis voltage, d-axis current, q-axis voltage, q-axis current, and angular velocity at the times t, t-1, …, t-p unchanged, use t2-t as the input, and the d-axis voltage at the time t2 as the output to obtain another set of training data. t1 and t2 are the sampling time points of the d-axis voltage after the time t. By analogy, obtain the training data under the current t; then change the value of t to obtain the training data under other t values, and obtain the short-term prediction model of the d-axis voltage through the obtained training data; the short-term prediction models of the q-axis voltage, q-axis current, and angular velocity are obtained in a similar manner.

[0047] S12. Obtain the reading period of the controller and determine a fixed time step based on the reading period of the controller, including steps S41 to S46:

[0048] S41. Let T c represent the reading period of the controller, m c represent the number of times the controller reads, and T s represent the time required for the actuator to obtain the control signal of the controller, which is determined by measurement; calculate the total reading time m s ×T c ; c ;

[0049] S43. Analyze the difference between the total reading time of the controller and the total sampling time of the i-th data acquisition card. Let k1 and k2 be 1, and k1 and k2 be test coefficients, representing the number of times the controller reads and the number of times the i-th data acquisition card collects operating data during the test;

[0050] S44. Calculate the difference k1×T c -k2×T i and record the data;

[0051] S45. Determine whether the difference is greater than 0. If it is greater than 0, increment the value of k2 by 1 and return to step S44. If it is less than 0, increment the value of k1 by 1 and return to step S44. If it is equal to 0, complete the test and proceed to step S46;

[0052] S46. Obtain all the recorded data and add T to the recorded data s , to obtain the fixed time step for prediction required by the i-th data acquisition card.

[0053] Perform short-term prediction on the running data with the fixed time step by running the prediction model of the data:

[0054] S51. For the i-th data acquisition card, obtain the historical running data collected by each data acquisition card after synchronization. Combine the consecutive p + 1 synchronized historical running data of each data acquisition card with the fixed time step for prediction required by the i-th data acquisition card to obtain an input vector. Input the input vector into the prediction model of the running data of the i-th data acquisition card to obtain the short-term prediction result of the running data of the i-th data acquisition card for the fixed time step;

[0055] S52. Move the window to change the selected consecutive p + 1 synchronized historical running data, repeat step S51 to obtain the short-term prediction results of the running data of the i-th data acquisition card for the fixed time step under different running data; Store the input vector and the short-term prediction results of the running data of the i-th data acquisition card for the fixed time step; Perform the same steps for all data acquisition cards and store the short-term prediction results and input vectors of all data acquisition cards.

[0056] S13. The data acquisition card obtains the real-time running data of the permanent magnet motor. After synchronizing the real-time running data according to the sampling time of the data acquisition card, calculate the matching degree between the synchronized real-time running data and the input of the prediction model storing the prediction results in step S12, and determine the predicted value of the real-time running data based on the matching degree:

[0057] For the real-time running data collected by the i-th data acquisition card, obtain the difference e between the total reading time of the controller and the total sampling time of the i-th data acquisition card, and add the time T required for the actuator to obtain the control signal of the controller to the difference s, from the short-term prediction results of the operation data of the i-th data acquisition card stored, filter out the short-term prediction results in the input vector with a fixed time step equal to e, calculate the Euclidean distance between all real-time operation data and the filtered input vector. If the Euclidean distance is not greater than the preset threshold, then use the short-term prediction result of the input vector with the minimum Euclidean distance as the real-time prediction value of the operation data of the i-th data acquisition card; if the Euclidean distance is greater than the preset threshold, then the real-time operation data of the i-th data acquisition card remains unchanged, no prediction is performed, and the controller directly reads the real-time operation data collected by the i-th data acquisition card; perform the same steps for all data acquisition cards to obtain the real-time prediction values of the operation data of all data acquisition cards.

[0058] When the data acquisition card collects operation data, directly synchronize the operation data. When the latest d-axis voltage data is obtained, synchronize the d-axis voltage, and q synchronized d-axis voltage data before the current moment, obtain the q + 1 synchronized d-axis current, q-axis voltage, q-axis current, and angular velocity data at the current moment and before, and determine the difference e between the total reading time of the controller and the total sampling time of the d-axis voltage data acquisition card according to the number of times the d-axis voltage data acquisition card collects data and the number of times the controller reads data. From the short-term prediction results and input vectors of the d-axis voltage data acquisition card stored, find the input vector in the input vector with a fixed time step equal to e, and then calculate the Euclidean distance between the found input vector and the current operation data. The current operation data is the latest synchronized d-axis voltage data, q synchronized d-axis voltage data before the current moment, obtain the q + 1 synchronized d-axis current, q-axis voltage, q-axis current, and angular velocity data at the current moment and before; when the Euclidean distance is not greater than the set threshold, use the short-term prediction result corresponding to the matching input vector as the real-time prediction value of the d-axis voltage data; the real-time prediction values of the d-axis current, q-axis voltage, q-axis current, and angular velocity data are obtained in a similar manner;

[0059] When the controller reads the operation data, it can obtain the real-time prediction values of the d-axis voltage, d-axis current, q-axis voltage, q-axis current, and angular velocity data, that is, the operation data at the moment when the actuator acts, so that the actuator action matches the permanent magnet motor state.

[0060] S14, the controller generates a control signal based on the predicted value of the real-time operation data and gives it to the actuator to control the permanent magnet motor.

[0061] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A variable frequency control management method applied to a permanent magnet motor, characterized in that: The following steps are involved: S11, acquiring historical operation data and sampling time data collected by each data acquisition card, synchronizing the historical operation data collected by the data acquisition card according to the sampling time of the data acquisition card, and training a prediction model for the operation data with the synchronized operation data; Training the prediction model of the operation data with the synchronized operation data also includes the following steps S31 and S32: S31, obtaining the operation data collected by each data acquisition card after synchronization, dividing the operation data into a training data set and a test data set, in the training data set, for the operation data of the i-th data acquisition card, the operation data collected by each data acquisition card between time t and time tp after synchronization and the target time difference are used as input, and the operation data of the i-th data acquisition card that is not synchronized after time t is used as output, and a prediction model for the operation data of the i-th data acquisition card is trained, where p is the order of the prediction model, and the target time difference is the time difference between the sampling nodes of the i-th data acquisition card at time t and after time t; In the test data set, the prediction model of the operation data of the i-th data acquisition card obtained through training is verified, and after the verification is completed, a short-term prediction model of the operation data of the i-th data acquisition card is obtained; S32, executing step S31 on the operation data of all data acquisition cards to obtain a prediction model for all the operation data; S12, obtaining a reading cycle of the controller and determining a fixed time step based on the reading cycle of the controller, performing short-term prediction on the operation data of the fixed time step through a prediction model of the operation data, and storing the prediction result and the input of the prediction model; S13, the data acquisition card acquires the real-time operation data of the permanent magnet motor, synchronizes the real-time operation data according to the sampling time of the data acquisition card, calculates the matching degree between the synchronized real-time operation data and the prediction model input storing the prediction result in step S12, and determines the prediction value of the real-time operation data based on the matching degree; S14, the controller generates a control signal to the actuator based on the predicted value of the real-time operation data to control the permanent magnet motor.

2. The frequency conversion control management method applied to a permanent magnet motor according to claim 1, characterized in that: In step S11, the historical operation data collected by the data acquisition card is synchronized according to the sampling time of the data acquisition card, and the following steps are also included: T i Represents the sampling period of the i-th data acquisition card, and determines the maximum value of the sampling period T j , let the jth data acquisition card be the benchmark data acquisition card, and the historical operation data collected by other data acquisition cards are collected according to the sampling period T of the benchmark data acquisition card j Synchronization includes the following steps: S21, obtain the number of times m that the i-th data acquisition card has collected running data i The number of times the benchmark data acquisition card has collected running data m j , calculate the total sampling time m of the i-th data acquisition card i ×T i , the total sampling time of the benchmark data acquisition card is m j ×T j ; S22, determining the difference m between the total sampling time of the i-th data acquisition card and the total sampling time of the reference data acquisition card i ×T i -m j ×T j , and synchronize the running data collected by the i-th data acquisition card according to the difference, let x(m i ) represents the mth data collected by the i-th data acquisition card i running data, if m i ×T i -m j ×T j is greater than zero, then after synchronization x(m i ) is tx(m i ), tx(m i ) = x (m i )-v×(m i ×T i -m j ×T j ); if m i ×T i -m j ×T j is not greater than zero, then tx(m i ) = x (m i )+v×(m j ×T j -m i ×T i ), where v is the change rate of the running data of the ith data acquisition card, v=[x(m i )-x(m i-1 )] / T i .

3. The frequency conversion control management method applied to a permanent magnet motor according to claim 2, characterized in that: In step S12, the method of determining a fixed time step based on a reading cycle of the controller further includes the following steps: S41, let T c Indicates the controller's read cycle, m c Indicates the number of times the controller reads, T s It represents the time required for the actuator to obtain the control signal from the controller, T s Determined by measurement; calculate the total read time m of the controller c ×T c ; S43, analyzing the difference between the total reading time of the controller and the total sampling time of the i-th data acquisition card, setting k1 and k2 to 1, k1 and k2 are test coefficients, representing the number of times the controller reads and the number of times the i-th data acquisition card collects running data during the test; S44, calculate the difference k1×T c -k2×T i and record the data; S45, determine whether the difference is greater than 0. If it is greater than 0, add 1 to the value of k2 and return to step S44. If it is less than 0, add 1 to the value of k1 and return to step S44. If it is equal to 0, the test is completed and the process goes to step S46. S46, obtain all recorded data, add T to the recorded data s , get the fixed time step that the i-th data acquisition card needs to predict.

4. The frequency conversion control management method applied to a permanent magnet motor according to claim 3, characterized in that: In step S12, the short-term prediction of the operation data with a fixed time step also includes the following steps: S51, for the i-th data acquisition card, historical operation data collected by each data acquisition card after synchronization are obtained, the historical operation data of each data acquisition card after consecutive p+1 synchronizations are combined with the fixed time step that the i-th data acquisition card needs to predict to obtain an input vector, and the input vector is input into the prediction model of the operation data of the i-th data acquisition card to obtain a short-term prediction result of the operation data of the i-th data acquisition card for the fixed time step; S52, moving the window to change the selected continuous p+1 synchronized historical operating data, repeating step S51 to obtain the short-term prediction result of the operating data of the i-th data acquisition card for a fixed time step under different operating data; storing the input vector and the short-term prediction result of the operating data of the i-th data acquisition card for a fixed time step; executing the same steps for all data acquisition cards, storing the short-term prediction results and input vectors of all data acquisition cards.

5. The frequency conversion control management method applied to a permanent magnet motor according to claim 4, characterized in that: In step S13, determining the predicted value of the real-time operation data based on the matching degree further includes the following steps: For the real-time operation data collected by the i-th data acquisition card, obtain the difference e between the total reading time of the controller and the total sampling time of the i-th data acquisition card, and add the difference to the time T required for the actuator to obtain the control signal of the controller. s , from the stored short-term prediction results of the operation data of the i-th data acquisition card, the short-term prediction results with the same fixed time step as e in the input vector are screened out, and the Euclidean distance between all real-time operation data and the screened input vector is calculated. If the Euclidean distance is not greater than the preset threshold, the short-term prediction result of the input vector with the smallest Euclidean distance is used as the real-time prediction value of the operation data of the i-th data acquisition card; if the Euclidean distance is greater than the preset threshold, the real-time operation data of the i-th data acquisition card remains unchanged, no prediction is performed, and the controller directly reads the real-time operation data collected by the i-th data acquisition card; the same steps are performed on all data acquisition cards to obtain the real-time prediction values ​​of the operation data of all data acquisition cards.

6. A variable frequency control management system applied to a permanent magnet motor, using a variable frequency control management method applied to a permanent magnet motor as claimed in any one of claims 1 to 5, characterized in that: include: A data acquisition module, a data storage module, a control module and a data analysis module; the output end of the data acquisition module is connected to the input end of the data storage module and the control module, and is used to obtain the operation data of the permanent magnet motor; the output end of the data storage module is connected to the input end of the data analysis module, and is used to store the historical operation data of the permanent magnet motor; the output end of the data analysis module is connected to the input end of the control module, and is used to synchronize the operation data collected by the data acquisition card, and use the synchronized operation data to train the short-term prediction model of the operation data to obtain the short-term prediction result of the operation data; The control module generates a control signal to control the permanent magnet motor according to the read operation data.

7. The variable frequency control management system for permanent magnet motor according to claim 6, characterized in that: The data storage module acquires the operating data of the permanent magnet motor through the data acquisition card, transmits the operating data of the permanent magnet motor to the control module in real time, and stores the acquired operating data in the data storage module.

8. The variable frequency control management system for permanent magnet motor according to claim 7, characterized in that: The data analysis module also includes a first synchronization unit, an operation data prediction unit and a data generation unit; the first synchronization unit is used to synchronize the operation data of each data acquisition card; the operation data prediction unit is used to train the short-term prediction model of the operation data of each data acquisition card; the data generation unit obtains the short-term prediction results for a fixed time step under the historical operation data according to the historical operation data of each data acquisition card and the time step to be predicted.

9. The variable frequency control management system for permanent magnet motor according to claim 8, characterized in that: The control module also includes a second synchronization unit, a matching unit, a controller and an actuator; the second synchronization unit is used to synchronize the received operating data of each data acquisition card; the matching unit is used to store the operating data and short-term prediction results of each data acquisition card, and based on the matching degree between the operating data of each data acquisition card after synchronization and the stored input vector, obtain the real-time prediction value of the operating data of each data acquisition card, and send the real-time prediction value of the operating data of each data acquisition card to the controller for reading. When there is no matching input vector, the real-time operating data is directly sent to the controller for reading; the controller generates a control signal based on the acquired permanent magnet motor operating data; the actuator generates a corresponding action according to the control signal to control the permanent magnet motor.

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