Offline identification and online optimization method of control parameters of brushless double-fed variable frequency speed regulation system

Abstract

The present invention relates to the technical field of AC motors, and specifically provides a method for offline identification and online optimization of control parameters applicable to a brushless double-fed variable frequency speed regulation system, which aims to assist in realizing the requirements of the existing brushless double-fed variable frequency speed regulation system control algorithm design, optimize the identification method of brushless double-fed motor parameters, and improve the reliability of the brushless double-fed variable frequency speed regulation system. The method can calculate the control parameters of the motor based on conventional operating conditions, and perform online correction of the parameters according to the actual operating conditions of the system, thereby helping to improve the reliability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of AC motors, and in particular to an off-line identification and on-line optimization method for control parameters of a brushless double-fed variable frequency speed regulation system. Background Art

[0002] At present, in the process of building a new power system, in order to promote green development, save resources, and improve the efficiency of motor drive systems, it is of great significance to promote high-voltage variable frequency drive systems. At present, the high-voltage variable frequency drive system mainly includes asynchronous motors, permanent magnet motors and double-fed motors. Asynchronous motors and permanent magnet motors are required to be equipped with full-power high-voltage inverters, while double-fed motors only need to use partial-power low-voltage inverters to meet the requirements. Compared with conventional brushed double-fed motors, brushless double-fed motors have similar operating characteristics, but the characteristics of their stator excitation make the system more reliable.

[0003] At present, most of the parameter identification methods for brushless doubly-fed motors are offline identification, and the unit needs to be controlled to operate under multiple different working conditions, which makes the operation process complicated. During the operation of the brushless doubly-fed motor, the resistance and inductance parameters will change due to the factors of motor temperature rise or magnetic field saturation, and the existing parameter identification scheme cannot achieve the organic combination of offline identification and online optimization. In addition, the variable frequency drive system mostly adopts speed sensorless control, and parameter changes will lead to inaccurate rotor position identification. It is necessary to propose a relatively simple parameter identification method to estimate the parameters of the brushless doubly-fed motor and be able to correct it online. Summary of the invention

[0004] The present invention provides a joint health monitoring and evaluation system and method in smart medical care to solve the above-mentioned background technology problems.

[0005] In a first aspect, the present invention proposes a method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system, comprising:

[0006] Step 1: Start the target scalar control and switch the brushless doubly-fed motor to the doubly-fed mode;

[0007] Step 2: In the double-fed mode, receiving the stator control side adjustment instruction, changing the current amplitude of the motor stator control side, and recording multiple sets of stator control side data; wherein the stator control side data includes recorded current data and recorded voltage data;

[0008] Step 3: performing fitting calculation on the recorded current data and the recorded voltage data and then performing comparison verification. When the verification result is within a preset verification threshold, determining the first target current data and the first target voltage data;

[0009] Step 4: Repeat step 2 and step 3 to obtain second target current data and second target voltage data, and compare the second target current data and the second target voltage data with the control parameters of the current brushless double-fed motor;

[0010] Step 5: When the deviation comparison exceeds the preset deviation threshold, the control parameters of the current brushless doubly-fed motor are optimized online.

[0011] In combination with the first aspect, the stator control side data is determined by performing park transformation on the three-phase voltage and current on the stator power side through the stator power side voltage orientation angle;

[0012] The recorded current data is the dp component u of the stator power side voltage dp 、u pq ; Among them, u dp It represents the d-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented, u pq It represents the q-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented;

[0013] The recorded voltage data is the dp component i of the stator power side current pd 、i pq ; where i pd It represents the d-axis component obtained by park transformation of the stator power side current after the stator power side voltage is oriented, i pq The q-axis component is obtained by park transforming the stator power side current after the stator power side voltage is oriented.

[0014] In combination with the first aspect, the recorded current data and the recorded voltage data are fitted and calculated as follows:

[0015]

[0016] Among them, k 1 represents the current correlation coefficient, k 2 represents the voltage correlation coefficient; ic represents the current amplitude on the stator control side.

[0017] In combination with the first aspect, the comparison check is shown as follows:

[0018]

[0019] Where e represents the offline calculation error of the correlation coefficient; Indicates the offline calculated value of the current correlation coefficient; Indicates the offline calculated value of voltage correlation coefficient.

[0020] In combination with the first aspect, when the verification result is within the preset verification threshold, it meets the following formula:

[0021]

[0022] Among them, icd represents the d-axis component obtained by park transforming the stator control side current after the stator power side voltage is oriented; icq represents the q-axis component obtained by park transforming the stator control side current after the stator power side voltage is oriented.

[0023] In combination with the first aspect, the control parameters of the online optimization conform to the following formula:

[0024]

[0025] Among them, e 01 Indicates the online correction error of the current correlation coefficient; e 02 Indicates the online correction error of the current correlation coefficient; Indicates the online correction value of the voltage correlation coefficient; Indicates the online correction value of the current correlation coefficient.

[0026] In combination with the first aspect, the online optimization further includes:

[0027] According to the online optimized control parameters, judging whether the control parameters are within the preset control parameter range;

[0028] When the control parameter is within a preset control parameter range, the real-time control parameter of the current brushless double-fed motor is replaced by the control parameter;

[0029] When the control parameter is not within the preset control parameter range, step 2 is performed again until the control parameter is within the preset control parameter range.

[0030] In combination with the first aspect, when the brushless doubly-fed motor is switched to the doubly-fed mode, the method further includes:

[0031] Determining the real-time operating curve of a brushless doubly-fed machine under scalar control

[0032] According to the real-time operation curve, fitting calculation is performed to determine the optimal frequency adjustment point, abnormal frequency adjustment point and reference frequency adjustment point on the real-time operation curve; wherein, the optimal frequency adjustment point indicates that the brushless doubly-fed motor is at the optimal speed at this time; the abnormal frequency adjustment point indicates that the brushless doubly-fed motor is not working / lower than the standard speed at this time; the reference frequency adjustment point indicates that the brushless doubly-fed motor is at the standard speed state at this time.

[0033] In combination with the first aspect, the target scalar control further includes:

[0034] Step 101: presetting a time period for offline identification;

[0035] Step 102: within a time period, starting the brushless double-fed motor by using the first variable voltage / first scalar frequency respectively, and obtaining a control curve within the time period;

[0036] Step 103: Calculate the stable operation mean value of the brushless double-fed inverter according to the control curve;

[0037] Step 104: Calculate the control curve of the second variable voltage / second scalar frequency in the next time period, and determine the mean deviation of stable operation;

[0038] Step 105: Repeat the iteration of step 104. When the mean deviation remains unchanged, determine the scalar control parameter at the corresponding moment and use it as the target scalar control parameter.

[0039] In combination with the first aspect, the online optimization further includes:

[0040] Set the current target scalar control parameters and receive the real-time efficiency value of the brushless doubly-fed motor;

[0041] When the real-time efficiency value decreases, the target scalar control parameter is adjusted.

[0042] The beneficial effects of the present invention are:

[0043] (1) The control parameter offline identification method for the brushless double-fed variable frequency speed regulation system provided by the present invention is simple and easy to implement. In actual use, the operating conditions corresponding to the offline identification method can be realized by using a conventional V / F or I / F open-loop control method. By collecting the operating data of the motor under different control side current amplitudes and fitting the control parameters, the precise parameters required for identifying the rotor position and operating control can be obtained without calculating detailed parameters such as the resistance and inductance of the motor.

[0044] (2) The control parameter online optimization method for the brushless double-fed variable frequency speed regulation system provided by the present invention corrects the control parameters based on offline identification and the actual operating conditions of the motor. It can effectively solve the influence of parameter changes on the control system caused by factors such as unit heating and magnetic field saturation during operation. By rolling optimizing the control parameters, the identification accuracy of the rotor position in the speed sensorless control mode is improved, and the stability of the system is enhanced.

[0045] (3) The control parameter offline identification and online optimization method of the brushless double-fed variable frequency speed regulation system for phase-adjusting operation provided by the present invention has a small amount of calculation in both the offline identification and online optimization stages. In addition, the calculation process of offline identification and online optimization is substantially the same, and the codes of the calculation process can be reused mutually, which is suitable for implantation into the control algorithm. Only a small amount of calculation time is added to effectively improve the control effect of the system.

[0046] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0047] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0049] Figure 1 A method flow chart of an offline identification and online optimization method of control parameters of a brushless double-fed variable frequency speed regulation system in an embodiment of the present invention;

[0050] Figure 2 This is a flow chart of off-line identification of control parameters applicable to a brushless double-fed variable frequency speed regulation system in an embodiment of the present invention;

[0051] Figure 3 The figure is a flow chart of online optimization of control parameters applicable to a brushless double-fed variable frequency speed regulation system in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0053] like Figure 1 As shown, in the first aspect, the present invention proposes a method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system, comprising:

[0054] Step 1: Start the target scalar control and switch the brushless doubly-fed motor to the doubly-fed mode;

[0055] Step 2: In the double-fed mode, receiving the stator control side adjustment instruction, changing the current amplitude of the motor stator control side, and recording multiple sets of stator control side data; wherein the stator control side data includes recorded current data and recorded voltage data;

[0056] Step 3: performing fitting calculation on the recorded current data and the recorded voltage data and then performing comparison verification. When the verification result is within a preset verification threshold, determining the first target current data and the first target voltage data;

[0057] Step 4: Repeat step 2 and step 3 to obtain second target current data and second target voltage data, and compare the second target current data and the second target voltage data with the control parameters of the current brushless double-fed motor;

[0058] Step 5: When the deviation comparison exceeds the preset deviation threshold, the control parameters of the current brushless doubly-fed motor are optimized online.

[0059] The principle of the above technical solution is:

[0060] like Figure 2 and Figure 3 The specific process of the present invention is as follows:

[0061] S1: Use the stator power side voltage orientation angle to perform park transformation on the three-phase voltage and current on the stator power side to obtain the dq component u of the stator power side voltage dp 、u pq , the dq component i of the stator power side current pd 、i pq ;

[0062] S2: Offline identification stage, scalar control is used to control the brushless doubly fed motor to operate in doubly fed mode, the current amplitude of the motor stator control side is changed, and 4 sets of data are recorded, corresponding to different control side current amplitudes. Each set of data contains u pd 、i pd 、i pq 、i c . Where i c Represents the current amplitude of the stator control side;

[0063] S3: Combine the four sets of recorded data and use the following formula to calculate the parameter k 1 , k 2 Fitting is performed and the calculation is obtained (k 1 k 2 )';

[0064]

[0065] S4: Due to k 1 , k 2 All are positive numbers, take the calculated result The square root of k is obtained. 1 ', k 2 ';

[0066] S5: Use formula (2) to calculate k 1 ', k 2 'with(k 1 k 2)' for comparison and verification, if the calculation result of e is within 1.0%, it is considered that k 1 ', k 2 'With the actual k 1 , k 2 Consistency;

[0067]

[0068] S6: Offline identified parameter k 1 , k 2 The following formula can be used to identify the rotor position of the brushless double-fed variable frequency speed regulation system and design the control system;

[0069]

[0070] S7: During the actual operation, four sets of data are recorded under different stable operating conditions, corresponding to different control side current amplitudes or load torques. Each set of data contains u pq 、i pd 、i pq 、i c .

[0071] S8: Repeat the process from S3 to S5 to calculate the new k 1 , k 2 (respectively denoted as k 10 , k 20 ), use the following formula to convert k 10 , k 20 Compared with the k used in the current control algorithm 1 , k 2 For comparison, if e 01 or 02 If the calculated result is greater than 5.0%, k 10 , k 20 Replace the k used in the current control algorithm 1 , k 2 , perform rolling online optimization of control parameters.

[0072]

[0073] The beneficial effects of the present invention are:

[0074] (1) The control parameter offline identification method for the brushless double-fed variable frequency speed regulation system provided by the present invention is simple and easy to implement. In actual use, the operating conditions corresponding to the offline identification method can be realized by using a conventional V / F or I / F open-loop control method. By collecting the operating data of the motor under different control side current amplitudes and fitting the control parameters, the precise parameters required for identifying the rotor position and operating control can be obtained without calculating detailed parameters such as the resistance and inductance of the motor.

[0075] (2) The control parameter online optimization method for the brushless double-fed variable frequency speed regulation system provided by the present invention corrects the control parameters based on offline identification and the actual operating conditions of the motor. It can effectively solve the influence of parameter changes on the control system caused by factors such as unit heating and magnetic field saturation during operation. By rolling optimizing the control parameters, the identification accuracy of the rotor position in the speed sensorless control mode is improved, and the stability of the system is enhanced.

[0076] (3) The control parameter offline identification and online optimization method of the brushless double-fed variable frequency speed regulation system for phase-adjusting operation provided by the present invention has a small amount of calculation in both the offline identification and online optimization stages. In addition, the calculation process of offline identification and online optimization is substantially the same, and the codes of the calculation process can be reused mutually, which is suitable for implantation into the control algorithm. Only a small amount of calculation time is added to effectively improve the control effect of the system.

[0077] As an embodiment of the present invention: the stator control side data is determined by performing park transformation on the three-phase voltage and current of the stator power side through the stator power side voltage orientation angle;

[0078] The recorded current data is the dp component u of the stator power side voltage dp 、u pq ; Among them, u dp It represents the d-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented, u pq It represents the q-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented;

[0079] The recorded voltage data is the dp component i of the stator power side current pd 、i pq ; where i pd It represents the d-axis component obtained by park transformation of the stator power side current after the stator power side voltage is oriented, i pq The q-axis component is obtained by park transforming the stator power side current after the stator power side voltage is oriented.

[0080] The present invention mainly obtains required data through Park transformation of voltage and current on the stator power side, and then processes and analyzes the data, thereby optimizing system control parameters.

[0081] First, the brushless double-fed variable frequency speed regulation system performs Park transformation on the three-phase voltage and current on the stator power side through the voltage orientation angle on the stator power side to obtain the corresponding dp component and u dp 、u pq Among them, u dpIt represents the d-axis component obtained by Park transformation of the stator power side voltage after the stator power side voltage is oriented, u pq It represents the q-axis component obtained by Park transformation of the stator power side voltage after the stator power side voltage is oriented, i pd It represents the d-axis component obtained by Park transformation of the stator power side current after the stator power side voltage is oriented, i pq The q-axis component is obtained by performing Park transformation on the stator power side current after the stator power side current is oriented.

[0082] Secondly, the system will record and analyze this data. For example, it can calculate the mean and variance of voltage and current and other statistical information to determine the operating status of the system. In addition, it can also set thresholds according to actual needs to determine whether the data exceeds the normal range. If it exceeds the normal range, it may mean that there is a problem with the motor system and it needs to be adjusted in time.

[0083] The beneficial effects of the above technical solution are:

[0084] The present invention optimizes the control parameters according to the results of data analysis. This can be achieved by modifying the angle of Park transformation or increasing or decreasing certain parameters. These modifications may affect the performance of the system in the short term, but in the long term, the best control effect can be achieved.

[0085] In combination with the first aspect, the recorded current data and the recorded voltage data are fitted and calculated as follows:

[0086]

[0087] Among them, k 1 represents the current correlation coefficient, k 2 represents the voltage correlation coefficient; i c Represents the current amplitude on the stator control side.

[0088] In the above technical solution:

[0089] The present invention can perform correlation analysis on current data and voltage data, establish a mathematical model between the two, and estimate the relationship between current and voltage by fitting the model. It represents the sum of the square of the current and the square of the voltage, reflecting a certain degree of correlation between current and voltage. and 2k 1 k 2 i pd u pd The representations represent the product of the square of voltage and the square of current with the d-axis component of the voltage, respectively, reflecting the specific relationship between the square of voltage and current.

[0090] The beneficial effects of the above technical solution are:

[0091] The present invention can obtain more accurate control parameters, and can also discover potential problems between current and voltage and make targeted improvements.

[0092] As an embodiment of the present invention: the comparison check is shown as follows:

[0093]

[0094] Where e represents the offline calculation error of the correlation coefficient; Indicates the offline calculated value of the current correlation coefficient; Indicates the offline calculated value of voltage correlation coefficient.

[0095] In the above technical solution:

[0096] In order to ensure the correctness and reliability of control parameters, the present invention introduces an evaluation index of the offline calculation error of the correlation coefficient. The evaluation index can be used to measure the accuracy of the offline calculation result and the consistency between the offline calculation result and the actual system operation.

[0097] Specifically, after the current and voltage data have been collected and Park transformed, the offline calculation value of the correlation coefficient can be calculated by the above formula, and then compared with the actual correlation coefficient. If the difference between the absolute values ​​of the two is less than the set threshold, it means that the accuracy of the offline calculation result is high, and the offline calculation result is consistent with the actual system operation. On the contrary, if the difference between the absolute values ​​of the two is large, it means that the accuracy of the offline calculation result is low, and the offline calculation result is inconsistent with the actual system operation.

[0098] The beneficial effects of the above technical solution are:

[0099] The present invention can comprehensively evaluate the accuracy and consistency of offline calculation results by calculating the offline calculation error of the correlation coefficient, and timely discover and correct errors to ensure stable and safe operation of the motor.

[0100] As an embodiment of the present invention: when the verification result is within the preset verification threshold, it meets the following formula:

[0101]

[0102] Among them, i cd It represents the d-axis component obtained by park transformation of the stator control side current after the stator power side voltage is oriented; i cq It represents the q-axis component obtained by park transforming the stator control side current after the stator power side voltage is oriented.

[0103] In the above technical solution:

[0104] In the process of optimizing the control parameters of the present invention: when the verification result is within the preset threshold, it means that the accuracy of the offline calculation result is high, and the offline calculation result is consistent with the actual system operation. At this time, it can be considered that the angle setting of the Park transformation is reasonable and does not need to be adjusted too much. When the verification result is outside the preset threshold, it means that the accuracy of the offline calculation result is low, and the offline calculation result is inconsistent with the actual system operation. At this time, it is necessary to adjust the angle of the Park transformation to improve the accuracy of the offline calculation result. The specific adjustment method can be to increase or decrease the angle of the Park transformation, or to adjust the time constant of the Park transformation. At the same time, when it is found that there is a large difference between the offline calculation result and the actual system operation, it may be caused by some assumptions in the offline calculation process not being established. At this time, it is necessary to review these assumptions and make corrections according to the actual situation.

[0105] The beneficial effects of the above technical solution are:

[0106] The present invention can effectively improve the control parameter setting of the brushless double-fed variable frequency speed regulation system, so that it can better adapt to different working conditions and load changes, improve the stability and efficiency of the system, reduce operating costs, and extend the life of the equipment.

[0107] As an embodiment of the present invention: the control parameters of the online optimization conform to the following formula:

[0108]

[0109] Among them, e 01 Indicates the online correction error of the current correlation coefficient; e 02 Indicates the online correction error of the current correlation coefficient; Indicates the online correction value of the voltage correlation coefficient; Indicates the online correction value of the current correlation coefficient.

[0110] In the above technical solution:

[0111] The present invention obtains the control parameter k of the brushless double-fed variable frequency speed regulation system 1 and k 2 , and identify it offline. According to the actual operation data, k 1 and k 2 Perform online optimization. 01 Indicates the online correction error of the current correlation coefficient, which is calculated based on the actual operation data; e 02 Indicates the online correction error of the current correlation coefficient, which is calculated based on the actual operating data; Indicates the online correction value of the voltage correlation coefficient, which is obtained by 2 Results obtained after online optimization; Indicates the online correction value of the current correlation coefficient, which is obtained by 1 The results obtained after online optimization.

[0112] The beneficial effects of the above technical solution are:

[0113] The present invention can realize effective management and optimization of control parameters of the brushless double-fed variable frequency speed regulation system, thereby improving the operating efficiency and stability of the system and reducing energy consumption.

[0114] As an embodiment of the present invention: the online optimization further includes:

[0115] According to the online optimized control parameters, judging whether the control parameters are within the preset control parameter range;

[0116] When the control parameter is within a preset control parameter range, the real-time control parameter of the current brushless double-fed motor is replaced by the control parameter;

[0117] When the control parameter is not within the preset control parameter range, step 2 is performed again until the control parameter is within the preset control parameter range.

[0118] In the above technical solution:

[0119] In the specific implementation of the present invention, first, the control parameters of the brushless double-fed variable frequency speed regulation system are obtained and stored, and these parameters generally include switching frequency, voltage, current, etc. Next, these control parameters are identified offline, that is, the value range and law of the control parameters are analyzed, so as to obtain an offline control parameter model. Then, these offline control parameter models are compared with the actual operation conditions to determine whether the control parameters are within the preset control parameter range. If not, online optimization is performed according to certain rules and algorithms until the control parameters are within the preset control parameter range.

[0120] The beneficial effects of the above technical solution are:

[0121] The present invention replaces the real-time control parameters of the current brushless double-fed motor through control parameters to achieve effective control of the system state.

[0122] As an embodiment of the present invention: when the brushless doubly-fed motor is switched to the doubly-fed mode, it also includes:

[0123] Determining the real-time operating curve of a brushless doubly-fed machine under scalar control

[0124] According to the real-time operation curve, fitting calculation is performed to determine the optimal frequency adjustment point, abnormal frequency adjustment point and reference frequency adjustment point on the real-time operation curve; wherein, the optimal frequency adjustment point indicates that the brushless doubly-fed motor is at the optimal speed at this time; the abnormal frequency adjustment point indicates that the brushless doubly-fed motor is not working / lower than the standard speed at this time; the reference frequency adjustment point indicates that the brushless doubly-fed motor is at the standard speed state at this time.

[0125] In the above technical solution:

[0126] In another embodiment of the present invention, the control parameter offline identification and online optimization method also includes processing when the brushless doubly-fed motor is switched to the doubly-fed mode. Specifically, after the brushless doubly-fed motor is switched to the doubly-fed mode, it is necessary to perform real-time frequency control on it to ensure its stable operation under various working conditions. In order to achieve this purpose, the following control strategy can be adopted: First, it is necessary to obtain the real-time operation data of the brushless doubly-fed motor, including current, voltage, speed, etc. According to these real-time operation data, the real-time operation curve of the brushless doubly-fed motor can be calculated. This curve can reflect the speed change of the brushless doubly-fed motor at different frequencies. Next, a fitting calculation can be performed on the real-time operation curve to determine the optimal frequency adjustment point, the abnormal frequency adjustment point and the reference frequency adjustment point. The selection of these points can help better control the speed of the brushless doubly-fed motor so that it always runs in the best state. For example, the abnormal frequency adjustment point can be set to a state where the brushless doubly-fed motor is not working or is lower than the standard speed, so that in the event of a fault or the need to reduce the speed, timely measures can be taken to avoid unnecessary losses. The optimal frequency adjustment point represents the maximum speed that the brushless double-fed motor can achieve under ideal conditions, which is the goal that needs to be pursued. As for the reference frequency adjustment point, it represents the speed of the brushless double-fed motor under standard working conditions, which is the main reference point for frequency control.

[0127] As an embodiment of the present invention: the target scalar control further includes:

[0128] Step 101: presetting a time period for offline identification;

[0129] Step 102: within a time period, starting the brushless double-fed motor by using the first variable voltage / first scalar frequency respectively, and obtaining a control curve within the time period;

[0130] Step 103: Calculate the stable operation mean value of the brushless double-fed inverter according to the control curve;

[0131] Step 104: Calculate the control curve of the second variable voltage / second scalar frequency in the next time period, and determine the mean deviation of stable operation;

[0132] Step 105: Repeat the iteration of step 104. When the mean deviation remains unchanged, determine the scalar control parameter at the corresponding moment and use it as the target scalar control parameter.

[0133] In the above technical solution:

[0134] For step 101: pre-set the time period for offline identification, and set the length of the time period so as to regularly perform offline identification of control parameters. For step 102: within the set time period, start the brushless doubly-fed motor by the first variable voltage / first scalar frequency respectively, and record the operating status of the motor at each time point after starting. For step 103: calculate the stable operation mean of the brushless doubly-fed motor according to the recorded control curve. The calculation of the mean can consider some statistical methods such as mean value and median. For step 104: calculate the control curve of the second variable voltage / second scalar frequency in the next time period, and determine the mean deviation of stable operation. The calculation of the deviation can be based on the previous mean result. For step 105: repeat the iteration step 104. When the mean deviation remains unchanged, determine the scalar control parameter at the corresponding moment and use it as the target scalar control parameter. Step 105 here is the process of optimizing and adjusting the control parameters obtained by offline identification.

[0135] Through the above method: the control parameters of the brushless doubly-fed motor can be effectively tracked and corrected to improve its operating efficiency and performance.

[0136] As an embodiment of the present invention: the online optimization further includes:

[0137] Set the current target scalar control parameters and receive the real-time efficiency value of the brushless doubly-fed motor;

[0138] When the real-time efficiency value decreases, the target scalar control parameter is adjusted.

[0139] In the above technical solution:

[0140] The present invention dynamically adjusts the target scalar control parameter by real-time monitoring of the efficiency value of the brushless double-fed motor. Specifically, this method can set a current target scalar control parameter, and then continuously receive the real-time efficiency value of the brushless double-fed motor. If the real-time efficiency value decreases, it means that there may be a problem with the current target scalar control parameter. At this time, it is necessary to adjust the target scalar control parameter in the hope of improving the efficiency value of the brushless double-fed motor.

[0141] The beneficial effects of the above technical solution are:

[0142] The present invention can adjust the control parameters in real time according to the operation status of the motor to achieve the best operation effect, while also avoiding the static error caused by offline identification. However, this also brings challenges, that is, how to quickly and accurately obtain the real-time efficiency value of the brushless double-fed motor, and how to quickly and accurately adjust the control parameters. Both of these are problems that need to be solved in practical applications.

[0143] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system, characterized in that: include: Step 1: Start the target scalar control and switch the brushless doubly-fed motor to the doubly-fed mode; Step 2: In the double-fed mode, receiving the stator control side adjustment instruction, changing the current amplitude of the motor stator control side, and recording multiple sets of stator control side data; wherein the stator control side data includes recorded current data and recorded voltage data; Step 3: After fitting the recorded current data and the recorded voltage data, a comparative check is performed. When the check result is within a preset check threshold, the first target current data and the first target voltage data are determined; wherein, the fitting calculation of the recorded current data and the recorded voltage data is as follows: Where k1 represents the current correlation coefficient, k2 represents the voltage correlation coefficient; i c Represents the current amplitude of the stator control side; the comparison check is shown in the following formula: Where e represents the offline calculation error of the correlation coefficient; Indicates the offline calculated value of the current correlation coefficient; Indicates the offline calculated value of voltage correlation coefficient; When the verification result is within the preset verification threshold, it meets the following formula: Among them, i cd It represents the d-axis component obtained by park transformation of the stator control side current after the stator power side voltage is oriented; i cq It represents the q-axis component obtained by park transformation of the stator control side current after the stator power side voltage is oriented; Step 4: Repeat steps 2 and 3 to obtain second target current data and second target voltage data, and compare the second target current data and second target voltage data with the control parameters of the current brushless double-fed motor; Step 5: When the deviation comparison exceeds the preset deviation threshold, the control parameters of the current brushless doubly-fed motor are optimized online.

2. A method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system as claimed in claim 1, characterized in that: The stator control side data is determined by performing park transformation on the three-phase voltage and current on the stator power side through the stator power side voltage orientation angle; The recorded current data is the dp component u of the stator power side voltage dp 、u pq ; Among them, u dp It represents the d-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented, u pq It represents the q-axis component obtained by park transformation of the stator power side voltage after the stator power side voltage is oriented; The recorded voltage data is the dp component i of the stator power side current pd 、i pq ; where i pd It represents the d-axis component obtained by park transformation of the stator power side current after the stator power side voltage is oriented, i pq The q-axis component is obtained by park transforming the stator power side current after the stator power side voltage is oriented.

3. The method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system according to claim 1, characterized in that: The control parameters of the online optimization conform to the following formula: Among them, e 01 Indicates the online correction error of the current correlation coefficient; e 02 Indicates the online correction error of the current correlation coefficient; Indicates the online correction value of the voltage correlation coefficient; Indicates the online correction value of the current correlation coefficient.

4. A method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system as claimed in claim 3, characterized in that: The online optimization also includes: According to the online optimized control parameters, judging whether the control parameters are within the preset control parameter range; When the control parameter is within a preset control parameter range, the real-time control parameter of the current brushless double-fed motor is replaced by the control parameter; When the control parameter is not within the preset control parameter range, step 2 is performed again until the control parameter is within the preset control parameter range.

5. The method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system as claimed in claim 1, characterized in that: When the brushless double-fed motor is switched to the double-fed mode, the method further includes: Determining the real-time operating curve of a brushless doubly-fed machine under scalar control According to the real-time operation curve, fitting calculation is performed to determine the optimal frequency adjustment point, abnormal frequency adjustment point and reference frequency adjustment point on the real-time operation curve; wherein, the optimal frequency adjustment point indicates that the brushless doubly fed motor is at the optimal speed at this time; the abnormal frequency adjustment point indicates that the brushless doubly fed motor is not working or is lower than the standard speed at this time; the reference frequency adjustment point indicates that the brushless doubly fed motor is at the standard speed state at this time.

6. A method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system as claimed in claim 1, characterized in that: The target scalar control further includes: Step 101: presetting a time period for offline identification; Step 102: within a time period, starting the brushless double-fed motor by using a first variable voltage or a first scalar frequency respectively, and obtaining a control curve within the time period; Step 103: Calculate the stable operation mean value of the brushless double-fed inverter according to the control curve; Step 104: Calculate the control curve of the second variable voltage or the second scalar frequency in the next time period, and determine the mean deviation of stable operation; Step 105: Repeat the iteration of step 104. When the mean deviation remains unchanged, determine the scalar control parameter at the corresponding moment and use it as the target scalar control parameter.

7. A method for offline identification and online optimization of control parameters of a brushless double-fed variable frequency speed regulation system as claimed in claim 6, characterized in that: The online optimization also includes: Set the current target scalar control parameters and receive the real-time efficiency value of the brushless doubly-fed motor; When the real-time efficiency value decreases, the target scalar control parameter is adjusted.

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