Equipment control method and related device

Abstract

The invention discloses an equipment control method and a related device. The method comprises the following steps: acquiring a first rotating speed value and a first three-phase current measurement value of an induction motor; determining a first rotor flux linkage value according to the first three-phase current measurement value; determining a first rotating speed difference value between the preset rotating speed reference value and the first rotating speed value; determining a flux linkage reference value corresponding to the first rotating speed value; determining a first flux linkage difference between the flux linkage reference value and the first rotor flux linkage value; respectively inputting the first rotating speed difference value and the first flux linkage difference value into a first fuzzy PI controller and a second fuzzy PI controller to obtain an electromagnetic torque reference value and a flux linkage current reference value; determining a three-phase current reference value based on the electromagnetic torque reference value, the flux linkage current reference value and the first rotor flux linkage value; determining a control signal according to the first three-phase current measurement value and the three-phase current reference value; the control signal is used to suppress the fast falling of the rotating speed of the induction motor. According to the embodiment of the invention, the voltage sag endurance capability of the speed-adjustable driver is improved.

Description

Technical Field

[0001] The present application relates to the field of control technology, and in particular to a device control method and related apparatus. Background Art

[0002] At present, adjustable speed drives (ASD) usually adopt traditional vector control. However, vector control is suitable for ASD to control induction machines (IM) in steady-state operation, but ignores ASD's control over IM in transient operation when it suffers from voltage sag, which makes ASD's voltage sag tolerance poor, thus causing IM tripping, resulting in industrial shutdown and even safety accidents. Therefore, how to improve ASD's voltage sag tolerance needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide a device control method and related apparatus, which improve the voltage sag tolerance capability of the ASD.

[0004] In a first aspect, an embodiment of the present application provides a device control method, which is applied to an electronic device, wherein the electronic device includes an adjustable speed drive and an induction motor, and the method includes:

[0005] Acquire a first speed value and a first three-phase current measurement value of the induction motor;

[0006] Determining a first rotor flux value according to the first three-phase current measurement value;

[0007] Determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference;

[0008] Determining a flux reference value corresponding to the first speed value;

[0009] Determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference;

[0010] Inputting the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value;

[0011] Inputting the first flux difference into a second fuzzy PI controller to obtain a flux current reference value;

[0012] determining a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value;

[0013] Determine a control signal according to the first three-phase current measurement value and the three-phase current reference value;

[0014] The control signal is used to suppress a rapid drop in the rotation speed of the induction motor, so as to extend the voltage sag tolerance time of the induction motor.

[0015] In a second aspect, an embodiment of the present application provides a device control apparatus, which is applied to an electronic device, wherein the electronic device includes an adjustable speed drive and an induction motor, and the apparatus includes: an acquisition unit, a determination unit, and a control unit, wherein:

[0016] The acquisition unit is used to acquire a first speed value and a first three-phase current measurement value of the induction motor;

[0017] The determining unit is used to determine a first rotor flux value according to the first three-phase current measurement value; determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference; determine a flux reference value corresponding to the first speed value; determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference;

[0018] The control unit is used to input the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value; input the first flux difference into a second fuzzy PI controller to obtain a flux current reference value; determine a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value; determine a control signal according to the first three-phase current measurement value and the three-phase current reference value; and use the control signal to suppress a rapid drop in the speed of the induction motor to extend the voltage sag tolerance time of the induction motor.

[0019] In a third aspect, the present application provides an electronic device comprising: a processor and a memory, wherein the memory is used to store one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the present application.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the present application.

[0021] In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the present application. The computer program product may be a software installation package.

[0022] The implementation of this application has the following beneficial effects:

[0023] It can be seen that the equipment control method and related devices described in the present application respectively adjust the electromagnetic torque and the flux current through two fuzzy PI controllers, and generate control signals based on the adjustment results to control the adjustable speed drive, which can effectively suppress the rapid drop in the speed of the induction motor during a voltage sag, thereby improving the voltage sag tolerance capability of the adjustable speed drive. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0025] Figure 1 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0026] Figure 2 is a flow chart of a device control method provided by an embodiment of the present application;

[0027] Figure 3 is a structural diagram of a first fuzzy PI controller provided in an embodiment of the present application;

[0028] Figure 4 is a schematic diagram of a variable membership function provided in an embodiment of the present application;

[0029] Figure 5 is a system block diagram of a device control method provided in an embodiment of the present application;

[0030] Figure 6 It is a block diagram of the functional units of a device control device provided in an embodiment of the present application;

[0031] Figure 7 It is a schematic diagram of the structure of another electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] The following is an explanation of some professional terms involved in this application:

[0036] ASD: Adjustable speed drive is a device that can control the speed of a motor. It can flexibly adjust the speed of the motor according to different working requirements, thereby achieving energy saving, optimizing the production process, etc.

[0037] IM: Induction motor, also called asynchronous motor, is a common AC motor. It relies on the principle of electromagnetic induction to convert electrical energy into mechanical energy to achieve motor rotation.

[0038] Voltage sag tolerance: refers to the ability of electrical equipment (especially motors and their drive systems) to maintain normal operation or resume normal operation in a short time when the grid voltage temporarily sags.

[0039] Fuzzy PI controller: It is a controller that combines fuzzy control and proportional-integral (PI) control. It introduces fuzzy logic on the basis of PI controller, which can better handle nonlinearity, uncertainty and time-varying characteristics in the system.

[0040] ABC coordinates: In motor analysis, ABC coordinates are based on the natural coordinate system of the three-phase winding of the motor stator, where the a-phase, b-phase, and c-phase windings are 120° electrical degrees apart from each other in space and are fixed on the stator and stationary.

[0041] dq0 coordinates: a coordinate system that rotates at the synchronous rotation speed of the motor rotor, in which the d-axis is usually defined to be consistent with the direction of the rotor magnetic field, the q-axis is perpendicular to the d-axis and its direction is determined according to the right-hand rule, and the 0-axis is perpendicular to the plane formed by the d and q axes, representing the zero-sequence component.

[0042] Park transform: also known as Parker transform, is a mathematical transformation method widely used in the field of motor analysis and control. The basic idea of ​​Park transform is to transform the motor variables (such as current, voltage, magnetic flux, etc.) in a stationary coordinate system (for example, abc coordinate) into a coordinate system that rotates synchronously with the motor rotor (for example, dq0 coordinate), thereby simplifying the mathematical model of the motor.

[0043] See also Figure 1 , Figure 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application; Figure 1 It can be known that the electronic device may include an adjustable speed drive and an induction motor. The induction motor may include: a stator core, a stator winding, a rotor core, a rotor winding, etc., which are not limited here.

[0044] Among them, the induction motor in the electronic device is powered by an adjustable speed drive. The working principle of the induction motor is based on electromagnetic induction. When three-phase alternating current is passed through the stator winding, a rotating magnetic field is generated. The rotor winding induces electromotive force and current in the rotating magnetic field, and then generates electromagnetic torque to make the rotor rotate.

[0045] Among them, the adjustable speed drive can adjust the power frequency and voltage supplied to the induction motor. During the startup phase, the adjustable speed drive can gradually increase the voltage and frequency supplied to the motor according to the preset startup program, so that the motor starts smoothly and avoids excessive starting current shock. During operation, the adjustable speed drive adjusts the speed of the motor according to the working requirements of the equipment. For example, when the equipment needs to reduce the load, the adjustable speed drive reduces the power frequency supplied to the motor, and the motor speed decreases accordingly. In order to achieve precise control and optimized operation, the electronic device can adopt a device control method as provided in the embodiments of the present application to adjust the output of the adjustable speed drive by detecting the operating parameters of the motor (for example, speed, current). Specifically: a first speed value and a first three-phase current measurement value of the induction motor can be obtained; a first rotor flux value is determined according to the first three-phase current measurement value; a difference between the first speed value and a preset speed reference value is determined to obtain a first speed difference; a flux reference value corresponding to the first speed value is determined; a difference between the first rotor flux value and the flux reference value is determined to obtain a first flux difference; the first speed difference is input into a first fuzzy PI controller to obtain an electromagnetic torque reference value; the first flux difference is input into a second fuzzy PI controller to obtain a flux current reference value; a three-phase current reference value is determined based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value; a control signal is determined according to the first three-phase current measurement value and the three-phase current reference value; and the control signal is used to suppress the rapid drop in the speed of the induction motor to extend the voltage sag tolerance time of the induction motor.

[0046] See also Figure 2 , Figure 2 1 is a flow chart of a device control method provided in an embodiment of the present application. The method is applied to an electronic device, wherein the electronic device includes an adjustable speed drive and an induction motor. The method may include the following steps:

[0047] S201. Obtain a first rotation speed value and a first three-phase current measurement value of the induction motor.

[0048] In the embodiment of the present application, the induction motor may be a three-phase induction motor.

[0049] In a specific embodiment, a preset speed measurement method (for example, a Hall sensor method) can be used to measure the induction motor to obtain a first speed value. Then, a current sensor can be set on the induction motor to obtain a first three-phase current measurement value through detection by the current sensor. Specifically, for a three-phase induction motor, three current sensors can be installed on the three-phase input lines of the motor respectively, so that the input current of the motor can be directly measured, thereby obtaining the first three-phase current measurement value.

[0050] S202. Determine a first rotor flux value according to the first three-phase current measurement values.

[0051] In the embodiment of the present application, the first three-phase current measurement value may be analyzed and processed to obtain the first rotor flux value.

[0052] Optionally, step S202, determining the first rotor flux value according to the first three-phase current measurement value, may include the following steps:

[0053] S21, obtaining a first flux orientation angle corresponding to the induction motor at a first preset moment;

[0054] S22. Performing Park transformation on the first three-phase current measurement value based on the first flux orientation angle to obtain a first flux current and a first torque current;

[0055] S23. Determine the first rotor flux value according to the first flux current according to the following formula:

[0056]

[0057] Among them, ψ r represents the first rotor flux value, L m is the stator-rotor mutual inductance, R r is the rotor resistance, L r is the rotor inductance, s is the Lagrangian operator, i sd is the first flux current.

[0058] In the embodiment of the present application, the first preset moment may be preset in advance or defaulted. It should be explained that the first preset moment may be a moment before the target moment.

[0059] In a specific embodiment, a first flux orientation angle corresponding to the induction motor at a first preset moment can be obtained. Specifically, the electronic device can include a preset database, which is used to store working data of the electronic device. The first flux orientation angle at the first preset moment can be obtained by querying the preset database; then, the first three-phase current measurement value can be subjected to a Park transformation based on the first flux orientation angle, and the first three-phase current measurement value can be transformed from the abc coordinate to the dq0 coordinate to obtain the first flux current and the first torque current. Specifically, since Park transformation is a common technology, it is not limited here.

[0060] Next, the first rotor flux value can be determined according to the first flux current according to the following formula:

[0061]

[0062] It needs to be explained that the stator-rotor mutual inductance L m , rotor resistance R r , rotor inductance L r , Lagrangian operator s and other data can also be obtained from the preset database.

[0063] In this way, by obtaining the flux orientation angle and performing Park transformation, the three-phase current is decomposed into flux current and torque current components, thereby realizing decoupling control of the motor magnetic field and torque, that is, controlling the motor's flux and torque separately and independently, just like controlling two independent variables separately, greatly improving the flexibility and accuracy of control.

[0064] S203: Determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference.

[0065] In the embodiment of the present application, the first speed difference value can be obtained by subtracting the first speed value from the preset speed reference value.

[0066] S204: Determine a flux reference value corresponding to the first speed value.

[0067] In the embodiment of the present application, the first rotation speed value may be analyzed and processed to obtain a flux reference value.

[0068] Optionally, step S204, determining the flux reference value corresponding to the first speed value may include the following steps:

[0069] A1. Obtaining a preset adjustment coefficient;

[0070] A2. Calculate the first speed value according to the preset adjustment coefficient and the first rotor flux value using the following calculation formula to obtain the flux reference value:

[0071]

[0072] Among them, ψ red represents the flux reference value, k is the preset adjustment coefficient, ω r is the first speed value, ω ref is the flux reference value, ψ r is the first rotor flux value.

[0073] In the embodiment of the present application, a preset adjustment coefficient may be obtained first, and then the first speed value may be calculated according to the preset adjustment coefficient and the first rotor flux value to obtain a flux reference value (i.e., variable magnetization control). The specific calculation formula is as follows:

[0074]

[0075] It needs to be explained that according to vector control theory, the torque current i sq It can be expressed as:

[0076]

[0077] Among them, i sq is the torque current, i sd is the flux linkage current, i ABC is the three-phase current, is the rotor flux, L m is the stator-rotor mutual inductance. From this formula, it can be seen that when the rotor flux is actively reduced, the flux current will gradually decrease, and then the torque current will further increase. Therefore, actively reducing the rotor flux will increase the torque current.

[0078] In the case of voltage sag, the relationship between electromagnetic torque and speed change rate can be expressed as the following formula:

[0079]

[0080] Among them, T e Represents electromagnetic torque, T L Represents the load torque. According to the above formula, it can be deduced that the larger the electromagnetic torque increment, the faster the torque recovers to the load torque. Since the speed keeps decreasing during the period from torque drop to recovery, the faster the torque recovers, the less the speed drops.

[0081] In summary, when suffering from voltage sag, by actively reducing the rotor flux, the torque recovery can be improved, thereby suppressing the speed drop, thereby improving the voltage sag tolerance capability.

[0082] In this way, by presetting the adjustment coefficient, the relationship between the magnetic flux and the speed can be flexibly adjusted according to the specific application scenarios and working requirements of the motor. Different application scenarios may have different requirements for the speed and torque characteristics of the motor. By reasonably setting the value of the preset adjustment coefficient, the motor can achieve the best operating state under various working conditions, thereby improving the flexibility and applicability of the control method.

[0083] Optionally, step A1, obtaining a preset adjustment coefficient, may include the following steps:

[0084] B1. Obtaining an initial adjustment coefficient corresponding to the adjustable speed driver;

[0085] B2. Acquiring historical voltage data corresponding to the induction motor;

[0086] B3. Determine the voltage sag data in the historical voltage data to obtain a voltage sag data; a is a positive integer;

[0087] B4. Determine the voltage sag duration corresponding to each voltage sag data in the a voltage sag data to obtain a voltage sag durations;

[0088] B5. Determine the temporary dip duration that is greater than the preset duration among the a temporary dip durations, and obtain b temporary dip durations; b is a positive integer less than or equal to a;

[0089] B6. Determine the voltage sag data corresponding to the b sag durations in the a voltage sag data, and obtain b voltage sag data;

[0090] B7. Determine the maximum change value corresponding to each voltage sag data in the b voltage sag data to obtain b maximum change values;

[0091] B8. Adjust the initial adjustment coefficient according to the b temporary drop durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

[0092] In the embodiment of the present application, an initial adjustment coefficient corresponding to the adjustable speed driver can be obtained. Specifically, the target device model corresponding to the adjustable speed driver can be obtained first, and then the initial adjustment coefficient can be determined according to the target device model. For example, a mapping relationship between a preset device model and an adjustment coefficient can be pre-stored, and the initial adjustment coefficient corresponding to the target device model can be determined based on the mapping relationship; then, the historical voltage data corresponding to the induction motor can be obtained. Specifically, the historical time period can be determined first, for example, the past year, the past month, the past week, etc., and then, based on the historical time period, the corresponding voltage data can be extracted from a preset database to obtain the historical voltage data; further, the voltage sag data in the historical voltage data can be determined to obtain a voltage sag data. Specifically, a fixed voltage amplitude threshold can be set. When the voltage amplitude is lower than the threshold, it is determined that a voltage sag has occurred. For example, the threshold is set to 90% of the rated voltage. Once it is detected that the voltage amplitude in the historical voltage data is lower than this value, it is considered that a voltage sag event has occurred, and the voltage data corresponding to the voltage sag event is obtained, thereby obtaining a voltage sag data.

[0093] Next, the sag duration corresponding to each voltage sag data in a voltage sag data can be determined to obtain a sag durations. Specifically, the voltage sag data can include the occurrence time of each voltage data. The earliest and latest voltage occurrence times in the a voltage sag data can be obtained to obtain a earliest time and a latest time. The a sag durations can be obtained by subtracting the corresponding earliest time in the a earliest time from the a latest time. Then, the size relationship between the a sag durations and the preset duration can be compared to obtain b sag durations greater than the preset duration. Then, the b sag durations can be determined The voltage sag data corresponding to a voltage sag data is obtained to obtain b voltage sag data; then, the maximum change value corresponding to each voltage sag data in the b voltage sag data can be determined to obtain b maximum change values. Specifically, the voltage maximum value and the voltage minimum value of the b voltage sag data can be obtained to obtain b voltage maximum values ​​and b voltage minimum values. The corresponding voltage minimum value in the b voltage minimum values ​​is subtracted from the b voltage maximum values ​​to obtain the b maximum change values; finally, the initial adjustment coefficient can be adjusted according to the b sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

[0094] In this way, the two key factors of the duration of the voltage sag and the maximum change value are comprehensively considered, so that the adjusted preset adjustment coefficient can more accurately reflect the voltage sag situation faced by the equipment in actual operation. In subsequent operation, the adjustable speed drive can adjust its output more effectively according to the adjusted preset adjustment coefficient to better adapt to the changes in the grid voltage, ensure the stable operation of the induction motor, and reduce motor failures caused by voltage sags.

[0095] Optionally, step B8, adjusting the initial adjustment coefficient according to the b temporary drop durations and the b maximum change values ​​to obtain the preset adjustment coefficient, may include the following steps:

[0096] C1. Determine the duration difference between each adjacent temporary dip duration among the b temporary dip durations to obtain b-1 duration differences;

[0097] C2, fitting the b-1 duration differences and their starting times to obtain a first straight line;

[0098] C3. Determine the number of times the induction motor trips in the b voltage sag data to obtain a target tripping number;

[0099] C4. When the target tripping number is greater than the preset tripping number, predict the sag duration at the target time according to the first straight line to obtain a predicted sag duration;

[0100] C5. Determine the probability of the induction motor tripping according to the predicted temporary sag duration to obtain a first tripping probability;

[0101] C6. Determine b weights according to the b temporary drop durations; the longer the temporary drop duration, the greater the weight;

[0102] C7. Determine a target mean value according to the b weights and the b maximum change values;

[0103] C8. Determine the probability of the induction motor tripping according to the target mean value to obtain a second tripping probability;

[0104] C9. determining a target tripping probability according to the first tripping probability and the second tripping probability;

[0105] C10. Adjusting the initial adjustment coefficient according to the target tripping probability to obtain a first adjustment coefficient;

[0106] C11. When the first adjustment coefficient is less than or equal to a preset coefficient threshold, determining the preset adjustment coefficient according to the first adjustment coefficient;

[0107] C12. When the first adjustment coefficient is greater than the preset coefficient threshold, determine the preset adjustment coefficient according to the preset coefficient threshold.

[0108] In the embodiment of the present application, the preset number of tripping times and the preset coefficient threshold value can be preset in advance or defaulted.

[0109] In a specific embodiment, the duration difference between each adjacent temporary sag duration among b temporary sag durations can be calculated to obtain b-1 duration differences; then, the b-1 duration differences and their starting times can be fitted to obtain a first straight line, the abscissa of the first straight line is time, and the ordinate is the duration difference; the number of times the induction motor trips in the b voltage sag data is determined to obtain a target tripping number, specifically, the working status data of the induction motor corresponding to the b voltage sag data can be obtained from a preset database, and the target tripping number is determined based on the working status data.

[0110] When the target tripping number is greater than the preset tripping number, it can be considered that the induction motor has a tripping risk, and the temporary sag duration at the target moment can be predicted according to the first straight line to obtain the predicted temporary sag duration. Specifically, the linear equation of the first straight line can be obtained, and then the target moment is substituted into the linear equation to obtain the predicted temporary sag duration. Then, the probability of the induction motor tripping can be determined according to the predicted temporary sag duration to obtain the first tripping probability. Specifically, the mapping relationship between the preset temporary sag duration and the tripping probability can be pre-stored, and the first tripping probability corresponding to the predicted temporary sag duration can be determined based on the mapping relationship. Then, b weights can be determined according to b temporary sag durations. Specifically, , a mapping relationship between a preset temporary sag duration and a weight can be pre-stored, and b weights corresponding to b temporary sag durations are determined based on the mapping relationship, and each temporary sag duration corresponds to a weight. Then, a weighted operation can be performed according to the b weights and the b maximum change values ​​to obtain a target mean value; further, the probability of the induction motor tripping can be determined according to the target mean value to obtain a second tripping probability. For example, a mapping relationship between a preset mean value and the tripping probability can be pre-stored, and a second tripping probability corresponding to the target mean value can be determined based on the mapping relationship; then, the target tripping probability can be determined according to the first tripping probability and the second tripping probability. The specific calculation formula is as follows:

[0111] Target trip probability = 50%*first trip probability + 50%*second trip probability;

[0112] According to the above formula, the target tripping probability can be obtained. Then, the initial adjustment coefficient can be adjusted according to the target tripping probability. The specific calculation formula is as follows:

[0113] First adjustment coefficient = initial adjustment coefficient * (1 + target tripping probability * j);

[0114] Wherein, j is a preset probability coefficient, and the first adjustment coefficient can be obtained according to the above formula; when the first adjustment coefficient is less than or equal to the preset coefficient threshold, the first adjustment coefficient can be used as the preset adjustment coefficient;

[0115] When the first adjustment coefficient is greater than the preset coefficient threshold, the preset coefficient threshold may be used as the preset adjustment coefficient.

[0116] In this way, by adjusting the initial adjustment coefficient according to the target tripping probability, the adjustment coefficient can be closely related to the risk of motor tripping. When the target tripping probability is high, by appropriately adjusting the adjustment coefficient, the adjustable speed drive can adopt a more active adjustment strategy to better cope with voltage sag and reduce the possibility of motor tripping. Conversely, when the target tripping probability is low, the adjustment range of the adjustment coefficient can be relatively small to avoid the negative impact of over-adjustment on system performance.

[0117] S205 . Determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference.

[0118] In the embodiment of the present application, the first rotor flux value may be subtracted from the flux reference value to obtain the first flux difference value.

[0119] S206 , inputting the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value.

[0120] Optionally, in step S206, please refer to Figure 3 , Figure 3 is a structural diagram of a first fuzzy PI controller provided in an embodiment of the present application, wherein the first fuzzy PI controller comprises: a quantization factor pair (ie, K e and K ec ), a first fuzzy rule, a first fuzzy controller, a first PI controller, wherein, Figure 3 x in ref represents a preset speed reference value (or flux reference value), x represents a first speed value (or a first rotor flux value), and the step of inputting the first speed difference value into a first fuzzy controller to obtain an electromagnetic torque reference value may include the following steps:

[0121] D1. quantizing the first speed difference by using the quantization factor to obtain a first input value;

[0122] D2. Processing the first input quantity according to the first fuzzy rule by the first fuzzy controller to obtain a first output quantity;

[0123] D3, processing the first output quantity by a preset proportional factor to obtain a second input quantity;

[0124] D4. Processing the second input quantity through the first PI controller to obtain a second output quantity; the second output quantity includes the electromagnetic torque reference value.

[0125] In the embodiment of the present application, the quantization factor pair includes a first quantization factor K e and the second quantization factor K ec .

[0126] In a specific embodiment, the first speed difference can be quantized by a quantization factor to obtain a first input quantity. Specifically, assuming that the first speed difference is recorded as e, the first speed difference e can be derived to obtain an error change rate ec, and then the first quantization factor K can be used to obtain an error change rate ec. e The first speed difference e is converted into the domain range that the fuzzy controller can process to obtain input E1. The specific calculation formula can be shown as follows:

[0127] E1=K e *e;

[0128] Similarly, the second quantization factor K ec Convert the error change rate ec into the domain range that the fuzzy controller can handle, and get the input E2. The specific calculation formula can be shown as follows:

[0129] E2=K ec *ec;

[0130] According to the above formula, E1 and E2, that is, the first input quantity, can be obtained; then, the first fuzzy controller can process the first input quantity according to the first fuzzy rule to obtain the first output quantity. Specifically, the first fuzzy rule can be shown in Table 1:

[0131] Table 1

[0132]

[0133] It should be explained that for all input variables (e, ec) and control variables (ΔK (m＝P，I) ) all use triangular membership functions. Furthermore, a symmetric form is used, and the total membership value of each variable is always 1, so that the membership functions of adjacent fuzzy sets are complementary. The membership functions of each variable can be found in Figure 4 , Figure 4 is a schematic diagram of a variable membership function provided in an embodiment of the present application, wherein Figure 4 In the figure, Figure a is ΔK I The variable membership function of Figure b is ΔK P Figure 2 shows the variable membership function of Figure 3, Figure 3 shows the variable membership function of Figure 4, Figure 4 shows the variable membership function of Figure 5, Figure 5 shows the variable membership function of Figure 6, Figure 6 shows the variable membership function of Figure 7, Figure 7 shows the variable membership function of Figure 8, Figure 8 shows the variable membership function of Figure 9, Figure 9 shows the variable membership function of Figure 10, Figure 10 shows the variable membership function of Figure 11, Figure 11 shows the variable membership function of Figure 12, Figure 12 shows the variable membership function of Figure 13, Figure 13 shows the variable membership function of Figure 14, Figure 14 shows the variable membership function of Figure 15, Figure 15 shows the variable membership function of Figure 16, Figure 16 shows the variable membership function of Figure 17, Figure 17 shows the variable membership function of Figure 18, Figure 18 shows the variable membership function of Figure 19, Figure 19 shows the variable membership function of Figure 20,

[0134] Table 2

[0135]

[0136] Then, the first output quantity can be processed by a preset proportional factor, and the specific calculation formula can be as follows:

[0137] Second input quantity = first output quantity * preset proportional factor;

[0138] According to the above formula, the second input quantity can be obtained; finally, the second input quantity can be processed by the first PI controller to obtain the second output quantity; the second output quantity includes the electromagnetic torque reference value.

[0139] In this way, the quantization level can be reasonably selected according to the actual situation through the quantization process, so that the fuzzy controller can distinguish the size of the speed difference more finely. For example, selecting a higher quantization level can more accurately capture the slight changes in the speed difference, thereby providing a basis for subsequent precise control.

[0140] Optionally, in step D4, the quantization factor pair includes a first quantization factor and a second quantization factor, and the processing of the second input quantity by the first PI controller to obtain a second output quantity may include the following steps:

[0141] E1. Obtaining a value range pair corresponding to the quantization factor pair and the preset scale factor to obtain a plurality of value range pairs; each factor corresponds to a value range pair; each value range pair includes a normalized domain and an actual variation range;

[0142] E2. Calculate the quantization factor pair and the preset scale factor based on the corresponding value range pair among the multiple value range pairs; the specific calculation formula is as follows:

[0143]

[0144]

[0145]

[0146] Among them, K e is the first quantization factor, K ec is the second quantization factor, L (m) is the preset scaling factor, e min K e The corresponding minimum value of the actual variation range, e max K e The maximum value of the corresponding actual variation range, E min K e The corresponding minimum value of the normalized domain, E max K e The maximum value of the corresponding normalized domain; ec min K ec The minimum value of the corresponding actual variation range, ec max K ecThe maximum value of the actual variation range, EC min K ec The corresponding minimum value of the normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The corresponding minimum value of the normalized domain, △k (m)max For L (m) The maximum value of the corresponding normalized domain, △K (m)min For L (m) The corresponding minimum value of the actual variation range, △K (m)max For L (m) The maximum value of the corresponding actual variation range;

[0147] E3. Use the weighted tie fuzzy solution method to calculate and obtain the target control parameter variable, wherein the target control parameter variable includes the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) ; The calculation formula is as follows:

[0148]

[0149] Among them, ΔK (m) is the target control parameter variable, m is equal to P or I, i is the number of fuzzy rules in the first fuzzy rule; is the membership degree of the ith rule; C i It is the largest element in the membership degree;

[0150] E4. Calculate the control parameter of the first PI controller according to the target control parameter variable; the specific calculation formula is as follows:

[0151] K P =K P0 +ΔK P

[0152] K I =K I0 +ΔK I

[0153] Among them, K P , K I is the control parameter of the first PI controller, K P0 , K I0 are the initial control parameters of the first PI controller;

[0154] E5. Calculate the second output based on the control parameter. The specific calculation formula is as follows:

[0155]

[0156] Wherein, u(k) is the second output; e(k) is the input during the kth PI adjustment, that is, the second input; It is the cumulative error between the first PI adjustment and the kth PI adjustment.

[0157] In the embodiment of the present application, a value range pair corresponding to a quantization factor pair and a preset scale factor can be obtained to obtain multiple value range pairs. Specifically, a mapping relationship between a preset factor and a value range pair can be pre-stored, and multiple value range pairs corresponding to a quantization factor pair and a preset scale factor are determined based on the mapping relationship. Each factor corresponds to a value range pair. It is assumed that the multiple value range pairs are as shown in Table 3:

[0158] Table 3

[0159]

[0160] Next, the quantization factor pair and the preset scale factor may be calculated based on the corresponding value range pair in the multiple value range pairs; the specific calculation formula is as follows:

[0161]

[0162]

[0163]

[0164] Furthermore, a weighted average defuzzification method can be used to calculate and obtain the target control parameter variable, which includes the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) ; The calculation formula is as follows:

[0165]

[0166] Then, the control parameters of the first PI controller can be calculated according to the target control parameter variable; the specific calculation formula is as follows:

[0167] K P =K P0 +ΔK P

[0168] K I =K I0 +ΔK I

[0169] Finally, the second output can be calculated based on the control parameters. The specific calculation formula is as follows:

[0170]

[0171] According to the above formula, u(k), which is the second output, can be obtained.

[0172] In this way, based on a clear range of values ​​and calculation formulas, the controller can quickly calculate the appropriate control parameters, so that the device can respond quickly to a given signal. For example, during the motor start-up or acceleration process, the electromagnetic torque reference value can be quickly adjusted to enable the motor to quickly reach the desired speed, shorten the device's response time, and improve the device's dynamic performance.

[0173] S207 , inputting the first flux difference into a second fuzzy PI controller to obtain a flux current reference value.

[0174] In the embodiment of the present application, the structure of the second fuzzy PI controller may be the same as that of the first fuzzy PI controller.

[0175] In a specific embodiment, the first flux difference may be input as an input parameter into the second fuzzy PI controller to obtain a flux current reference value, and the specific implementation steps may be the same as the steps of obtaining the electromagnetic torque reference value in step S206.

[0176] S208. Determine a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value.

[0177] In the present application, please refer to Figure 5 , Figure 5 is a system block diagram of a device control method provided in an embodiment of the present application, wherein ω r is the speed measurement value, ω ref is the speed reference value, T e * is the electromagnetic torque reference value, n p is the number of motor pole pairs, ω s represents the synchronous angular velocity, ψ r is the rotor flux value, L m is the stator-rotor mutual inductance, L r is the rotor inductance, is the torque current reference value, i ABC-ref is the three-phase current reference value, i ABC is the three-phase current measurement value, pulse is the PWM pulse signal (i.e. control signal), ψ ref is the flux linkage reference value, is the reference value of flux current, i sd is the measured value of flux current, i sq is the torque current measurement value, R r is the rotor resistance, s is the Lagrangian operator, and θ is the flux orientation angle.

[0178] In a specific embodiment, the three-phase current reference value can be determined according to the electromagnetic torque reference value, the flux current reference value and the first rotor flux value. Specifically, the second flux orientation angle corresponding to the induction motor at the target time can be calculated according to the torque current measurement value and the rotor flux. The specific calculation formula is as follows:

[0179] θ=∫(n p ω r +ω s )dt

[0180] θ represents the second flux orientation angle. Then, the torque current reference value can be calculated according to the electromagnetic torque reference value and the first rotor flux value. The specific calculation formula is as follows:

[0181]

[0182] Finally, an inverse Park transformation may be performed based on the torque current reference value, the flux current reference value, and the second flux orientation angle to transform these reference values ​​from the dq0 coordinate to the abc coordinate, thereby obtaining the three-phase current reference value.

[0183] S209. Determine a control signal according to the first three-phase current measurement values ​​and the three-phase current reference values.

[0184] In the embodiment of the present application, the above-mentioned electronic device may include a PWM controller.

[0185] In a specific embodiment, the first three-phase current measurement value and the three-phase current reference value can be input into the PWM controller to obtain a PWM pulse signal, that is, a control signal. Specifically, the PWM controller can calculate the error signal between the first three-phase current measurement value and the three-phase current reference value, and generate a corresponding PWM pulse signal based on the error signal. This can be achieved by a comparator. For example, taking phase A as an example, the phase A signal in the error signal can be compared with a preset carrier signal (or a sawtooth carrier signal). When the phase A signal is greater than the preset carrier signal, the PWM controller outputs a high level (corresponding to the power switching device being turned on). When the phase A signal is less than the preset carrier signal, the PWM controller outputs a low level (corresponding to the power switching device being turned off). The comparison process similar to that of phase A is repeated for phases B and C to obtain a corresponding PWM pulse signal, that is, a control signal.

[0186] S210: Using the control signal to suppress a rapid drop in the rotation speed of the induction motor, so as to extend the voltage sag tolerance time of the induction motor.

[0187] In the embodiment of the present application, a control signal may be sent to the induction motor to suppress a rapid drop in the rotation speed of the induction motor, thereby extending the voltage sag tolerance time of the induction motor.

[0188] The implementation of this application has the following beneficial effects:

[0189] It can be seen that the device control method described in the present application adjusts the electromagnetic torque and the flux current respectively through two fuzzy PI controllers, and generates a control signal based on the adjustment results to control the adjustable speed drive, which can effectively suppress the rapid drop in the speed of the induction motor during a voltage sag, thereby improving the voltage sag tolerance capability of the adjustable speed drive.

[0190] See also Figure 6 , Figure 6 6 is a functional unit composition block diagram of a device control device 600 provided in an embodiment of the present application, which is applied to an electronic device, wherein the electronic device includes an adjustable speed drive and an induction motor, and the device control device 600 includes: an acquisition unit 601, a determination unit 602, and a control unit 603, wherein:

[0191] The acquisition unit 601 is used to acquire a first speed value and a first three-phase current measurement value of the induction motor;

[0192] The determining unit 602 is configured to determine a first rotor flux value according to the first three-phase current measurement value; determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference; determine a flux reference value corresponding to the first speed value; determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference;

[0193] The control unit 603 is used to input the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value; input the first flux difference into a second fuzzy PI controller to obtain a flux current reference value; determine a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value; determine a control signal according to the first three-phase current measurement value and the three-phase current reference value; and use the control signal to suppress a rapid drop in the speed of the induction motor to extend the voltage sag tolerance time of the induction motor.

[0194] Optionally, in determining the first rotor flux value according to the first three-phase current measurement values, the determining unit 602 is specifically configured to:

[0195] Acquire a first flux orientation angle corresponding to the induction motor at a first preset moment;

[0196] Performing Park transformation on the first three-phase current measurement value based on the first flux orientation angle to obtain a first flux current and a first torque current;

[0197] The first rotor flux value is determined according to the first flux current according to the following formula:

[0198]

[0199] Among them, ψ r represents the first rotor flux value, L m is the stator-rotor mutual inductance, R r is the rotor resistance, L r is the rotor inductance, s is the Lagrangian operator, i sd is the first flux current.

[0200] Optionally, in determining the flux reference value corresponding to the first speed value, the determining unit 602 is specifically configured to:

[0201] Get the preset adjustment coefficient;

[0202] The first speed value is calculated according to the preset adjustment coefficient and the first rotor flux value by using the following calculation formula to obtain the flux reference value:

[0203]

[0204] Among them, ψ ref represents the flux reference value, k is the preset adjustment coefficient, ω r is the first speed value, ω ref is the flux reference value, ψ r is the first rotor flux value.

[0205] Optionally, in terms of obtaining the preset adjustment coefficient, the determining unit 602 is specifically configured to:

[0206] Obtaining an initial adjustment coefficient corresponding to the adjustable speed driver;

[0207] Acquiring historical voltage data corresponding to the induction motor;

[0208] Determine the voltage sag data in the historical voltage data to obtain a voltage sag data; a is a positive integer;

[0209] Determine the voltage sag duration corresponding to each voltage sag data in the a voltage sag data to obtain a voltage sag durations;

[0210] Determine the temporary dip duration that is greater than the preset duration among the a temporary dip durations, and obtain b temporary dip durations; b is a positive integer less than or equal to a;

[0211] Determine the voltage sag data corresponding to the b sag durations in the a voltage sag data, to obtain b voltage sag data;

[0212] Determine a maximum change value corresponding to each voltage sag data among the b voltage sag data to obtain b maximum change values;

[0213] The initial adjustment coefficient is adjusted according to the b temporary sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

[0214] Optionally, in the aspect of adjusting the initial adjustment coefficient according to the b temporary drop durations and the b maximum change values ​​to obtain the preset adjustment coefficient, the determining unit 602 is specifically configured to:

[0215] Determine the duration difference between each adjacent temporary dip duration among the b temporary dip durations, and obtain b-1 duration differences;

[0216] Fitting the b-1 duration differences and their starting times to obtain a first straight line;

[0217] Determine the number of times the induction motor trips in the b voltage sag data to obtain a target number of trips;

[0218] When the target tripping number is greater than the preset tripping number, predicting the sag duration at the target time according to the first straight line to obtain a predicted sag duration;

[0219] Determining the probability of the induction motor tripping according to the predicted temporary sag duration to obtain a first tripping probability;

[0220] Determine b weights according to the b temporary drop durations; the longer the temporary drop duration, the greater the weight;

[0221] Determine a target mean value according to the b weights and the b maximum change values;

[0222] Determining the probability of the induction motor tripping according to the target mean value to obtain a second tripping probability;

[0223] Determining a target tripping probability according to the first tripping probability and the second tripping probability;

[0224] Adjusting the initial adjustment coefficient according to the target tripping probability to obtain a first adjustment coefficient;

[0225] When the first adjustment coefficient is less than or equal to a preset coefficient threshold, determining the preset adjustment coefficient according to the first adjustment coefficient;

[0226] When the first adjustment coefficient is greater than the preset coefficient threshold, the preset adjustment coefficient is determined according to the preset coefficient threshold.

[0227] Optionally, the first fuzzy PI controller includes: a quantization factor pair, a first fuzzy rule, a first fuzzy controller, and a first PI controller. In inputting the first speed difference into the first fuzzy controller to obtain the electromagnetic torque reference value, the control unit 603 is specifically used to:

[0228] The first speed difference is quantified by the quantization factor to obtain a first input quantity;

[0229] Processing the first input quantity according to the first fuzzy rule by the first fuzzy controller to obtain a first output quantity;

[0230] Processing the first output quantity by a preset proportional factor to obtain a second input quantity;

[0231] The second input quantity is processed by the first PI controller to obtain a second output quantity; the second output quantity includes the electromagnetic torque reference value.

[0232] Optionally, the quantization factor pair includes a first quantization factor and a second quantization factor, and in terms of obtaining a second output by processing the second input through the first PI controller, the control unit 603 is specifically configured to:

[0233] Obtaining a value range pair corresponding to the quantization factor pair and the preset scale factor to obtain a plurality of value range pairs; each factor corresponds to a value range pair; each value range pair includes a normalized domain and an actual variation range;

[0234] The quantization factor pair and the preset scale factor are calculated based on the corresponding value range pair in the multiple value range pairs; the specific calculation formula is as follows:

[0235]

[0236]

[0237]

[0238] Among them, K e is the first quantization factor, K ec is the second quantization factor, L (m) is the preset scaling factor, e min K e The corresponding minimum value of the actual variation range, e max K e The maximum value of the corresponding actual variation range, E min K e The corresponding minimum value of the normalized domain, E max Ke The maximum value of the corresponding normalized domain; ec min K ec The minimum value of the corresponding actual variation range, ec max K ec The maximum value of the actual variation range, EC min K ec The corresponding minimum value of the normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The corresponding minimum value of the normalized domain, △k (m)max For L (m) The maximum value of the corresponding normalized domain, △K (m)min For L (m) The corresponding minimum value of the actual variation range, △K (m)max For L (m) The maximum value of the corresponding actual variation range;

[0239] The weighted average defuzzification method is used to calculate and obtain the target control parameter variable, which includes the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) ; The calculation formula is as follows:

[0240]

[0241] Among them, ΔK (m) is the target control parameter variable, m is equal to P or I, i is the number of fuzzy rules in the first fuzzy rule; is the membership degree of the ith rule; C i It is the largest element in the membership degree;

[0242] The control parameters of the first PI controller are calculated according to the target control parameter variable; the specific calculation formula is as follows:

[0243] K P =K P0 +ΔK P

[0244] K I =K I0 +ΔK I

[0245] Among them, K P , K I is the control parameter of the first PI controller, K P0 , K I0 are the initial control parameters of the first PI controller;

[0246] The second output is calculated based on the control parameter, and the specific calculation formula is as follows:

[0247]

[0248] Wherein, u(k) is the second output; e(k) is the input during the kth PI adjustment, that is, the second input; It is the cumulative error between the first PI adjustment and the kth PI adjustment.

[0249] In a specific implementation, the device control apparatus 600 described in the embodiment of the present application may also execute other implementations described in the device control method provided in the above embodiment of the present application, which will not be described in detail here.

[0250] See also Figure 7 , Figure 7 It is a structural diagram of another electronic device provided in an embodiment of the present application, and the electronic device includes a processor, a memory, a communication interface and one or more programs. The processor, the memory and the communication interface are interconnected through a bus. The one or more programs are stored in the memory and are configured to be executed by the processor. The one or more programs include instructions for executing other implementations described in the device control method provided in the embodiment of the present application, which are not repeated here.

[0251] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer may include an electronic device.

[0252] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer may include an electronic device.

[0253] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0254] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0255] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0256] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0257] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0258] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0259] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A device control method, characterized in that: Applied to an electronic device, the electronic device includes an adjustable speed drive and an induction motor, the method includes: Acquire a first speed value and a first three-phase current measurement value of the induction motor; Determining a first rotor flux value according to the first three-phase current measurement value; Determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference; Determining a flux reference value corresponding to the first speed value; Determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference; Inputting the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value; Inputting the first flux difference into a second fuzzy PI controller to obtain a flux current reference value; determining a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value; Determine a control signal according to the first three-phase current measurement value and the three-phase current reference value; The control signal is used to suppress a rapid drop in the rotation speed of the induction motor, so as to extend the voltage sag tolerance time of the induction motor.

2. The method according to claim 1, characterized in that The determining the first rotor flux value according to the first three-phase current measurement value comprises: Acquire a first flux orientation angle corresponding to the induction motor at a first preset moment; Performing Park transformation on the first three-phase current measurement value based on the first flux orientation angle to obtain a first flux current and a first torque current; The first rotor flux value is determined according to the first flux current according to the following formula: Among them, ψ r represents the first rotor flux value, L m is the stator-rotor mutual inductance, R r is the rotor resistance, L r is the rotor inductance, s is the Lagrangian operator, i sd is the first flux current.

3. The method according to claim 2, characterized in that The determining of the flux reference value corresponding to the first speed value includes: Get the preset adjustment coefficient; The first speed value is calculated according to the preset adjustment coefficient and the first rotor flux value by using the following calculation formula to obtain the flux reference value: Among them, ψ ref represents the flux reference value, k is the preset adjustment coefficient, ω r is the first speed value, ω ref is the flux reference value, ψ r is the first rotor flux value.

4. The method according to claim 3, characterized in that The obtaining of the preset adjustment coefficient includes: Obtaining an initial adjustment coefficient corresponding to the adjustable speed driver; Acquiring historical voltage data corresponding to the induction motor; Determine the voltage sag data in the historical voltage data to obtain a voltage sag data; a is a positive integer; Determine the voltage sag duration corresponding to each voltage sag data in the a voltage sag data to obtain a voltage sag durations; Determine the temporary dip duration that is greater than the preset duration among the a temporary dip durations, and obtain b temporary dip durations; b is a positive integer less than or equal to a; Determine the voltage sag data corresponding to the b sag durations in the a voltage sag data, to obtain b voltage sag data; Determine a maximum change value corresponding to each voltage sag data among the b voltage sag data to obtain b maximum change values; The initial adjustment coefficient is adjusted according to the b temporary sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

5. The method according to claim 4, characterized in that The step of adjusting the initial adjustment coefficient according to the b temporary drop durations and the b maximum change values ​​to obtain the preset adjustment coefficient includes: Determine the duration difference between each adjacent temporary dip duration among the b temporary dip durations, and obtain b-1 duration differences; Fitting the b-1 duration differences and their starting times to obtain a first straight line; Determine the number of times the induction motor trips in the b voltage sag data to obtain a target number of trips; When the target tripping number is greater than the preset tripping number, predicting the sag duration at the target time according to the first straight line to obtain a predicted sag duration; Determining the probability of the induction motor tripping according to the predicted temporary sag duration to obtain a first tripping probability; Determine b weights according to the b temporary drop durations; the longer the temporary drop duration, the greater the weight; Determine a target mean value according to the b weights and the b maximum change values; Determining the probability of the induction motor tripping according to the target mean value to obtain a second tripping probability; Determining a target tripping probability according to the first tripping probability and the second tripping probability; Adjusting the initial adjustment coefficient according to the target tripping probability to obtain a first adjustment coefficient; When the first adjustment coefficient is less than or equal to a preset coefficient threshold, determining the preset adjustment coefficient according to the first adjustment coefficient; When the first adjustment coefficient is greater than the preset coefficient threshold, the preset adjustment coefficient is determined according to the preset coefficient threshold.

6. The method according to any one of claims 1 to 5, characterized in that: The first fuzzy PI controller includes: a quantization factor pair, a first fuzzy rule, a first fuzzy controller, and a first PI controller. The first speed difference is input into the first fuzzy controller to obtain an electromagnetic torque reference value, including: The first speed difference is quantified by the quantization factor to obtain a first input quantity; Processing the first input quantity according to the first fuzzy rule by the first fuzzy controller to obtain a first output quantity; Processing the first output quantity by a preset proportional factor to obtain a second input quantity; The second input quantity is processed by the first PI controller to obtain a second output quantity; the second output quantity includes the electromagnetic torque reference value.

7. The method according to claim 6, characterized in that The quantization factor pair includes a first quantization factor and a second quantization factor, and the second input quantity is processed by the first PI controller to obtain a second output quantity, including: Obtaining a value range pair corresponding to the quantization factor pair and the preset scale factor to obtain a plurality of value range pairs; each factor corresponds to a value range pair; each value range pair includes a normalized domain and an actual variation range; The quantization factor pair and the preset scale factor are calculated based on the corresponding value range pair in the multiple value range pairs; the specific calculation formula is as follows: Among them, K e is the first quantization factor, K ec is the second quantization factor, L (m) is the preset scaling factor, e min K e The corresponding minimum value of the actual variation range, e max K e The maximum value of the corresponding actual variation range, E min K e The corresponding minimum value of the normalized domain, E max K e The maximum value of the corresponding normalized domain; ec min K ec The minimum value of the corresponding actual variation range, ec max K ec The maximum value of the actual variation range, EC min K ec The corresponding minimum value of the normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The corresponding minimum value of the normalized domain, △k (m)max For L (m) The corresponding maximum value of the normalized domain, △K (m)min For L (m) The corresponding minimum value of the actual variation range, △K (m)max For L (m) The maximum value of the corresponding actual variation range; The weighted average defuzzification method is used to calculate and obtain the target control parameter variable, which includes the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) ; The calculation formula is as follows: Among them, ΔK (m) is the target control parameter variable, m is equal to P or I, i is the number of fuzzy rules in the first fuzzy rule; μ CI is the membership degree of the ith rule; C i It is the largest element in the membership degree; The control parameters of the first PI controller are calculated according to the target control parameter variable; the specific calculation formula is as follows: K P =K P0 +ΔK P K I =K I0 +ΔK I Among them, K P , K I is the control parameter of the first PI controller, K P0 , K I0 are the initial control parameters of the first PI controller; The second output is calculated based on the control parameter, and the specific calculation formula is as follows: Wherein, u(k) is the second output; e(k) is the input during the kth PI adjustment, that is, the second input; It is the cumulative error between the first PI adjustment and the kth PI adjustment.

8. A device control device, characterized in that: Applied to electronic equipment, the electronic equipment includes an adjustable speed drive and an induction motor, the device includes: an acquisition unit, a determination unit, and a control unit, wherein: The acquisition unit is used to acquire a first speed value and a first three-phase current measurement value of the induction motor; The determining unit is used to determine a first rotor flux value according to the first three-phase current measurement value; determine a difference between a preset speed reference value and the first speed value to obtain a first speed difference; determine a flux reference value corresponding to the first speed value; determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference; The control unit is used to input the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value; input the first flux difference into a second fuzzy PI controller to obtain a flux current reference value; determine a three-phase current reference value based on the electromagnetic torque reference value, the flux current reference value and the first rotor flux value; determine a control signal according to the first three-phase current measurement value and the three-phase current reference value; and use the control signal to suppress a rapid drop in the speed of the induction motor to extend the voltage sag tolerance time of the induction motor.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the program includes instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 7.

Images