Device control method and related apparatus

Abstract

The application discloses a device control method and related device, and 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 a 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 value between the flux linkage reference value and the first rotor flux linkage value; inputting the first rotating speed difference value and the first flux linkage difference value into a first and a second fuzzy PI controller respectively 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; and suppressing the rapid drop of the rotating speed of the induction motor by using the control signal. By adopting the embodiment of the application, the voltage sag tolerance of the adjustable speed driver is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of control, and particularly relates to a device control method and related apparatus. BACKGROUND

[0002] At present, an adjustable speed drive (ASD) usually adopts traditional vector control. However, the vector control is suitable for the control of an ASD on an induction machine (IM) in a steady state, and ignores the control of the ASD on the IM in a transient state when the ASD suffers from voltage sag, so that the voltage sag tolerance of the ASD is poor, thereby causing the IM to trip, resulting in industrial production stop or even safety accidents. Therefore, how to improve the voltage sag tolerance of the ASD is an urgent problem to be solved. SUMMARY

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

[0004] In a first aspect, the embodiments of the present application provide a device control method, applied to an electronic device, the electronic device comprising an adjustable speed drive and an induction machine, and the method comprises:

[0005] obtaining a first rotational speed value and a first three-phase current measurement value of the induction machine;

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

[0007] determining a first rotational speed difference value between a preset rotational speed reference value and the first rotational speed value;

[0008] determining a flux linkage reference value corresponding to the first rotational speed value;

[0009] determining a first flux linkage difference value between the flux linkage reference value and the first rotor flux linkage value;

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

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

[0012] 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;

[0013] determining 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 acquiring unit is configured to acquire a first speed value and a first three-phase current measurement value of the induction motor;

[0017] The determining unit is configured to determine a first rotor flux value based on 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; and 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 configured 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 based on the first three-phase current measurement value and the three-phase current reference value; and utilize the control signal to suppress a rapid drop in the speed of the induction motor, thereby extending 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 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 some 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, wherein the computer program is operable to cause a computer to perform 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 this application respectively adjust the electromagnetic torque and 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 voltage sag, thereby improving the voltage sag tolerance 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 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0026] Figure 2 This 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 Schematic diagram of a variable membership function provided in an embodiment of the present application;

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

[0030] Figure 6 This 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 structural diagram 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 present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, 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", and the like in the description and in the claims of the present application and above-described drawings are used to distinguish different objects, not to describe a particular sequential order. Moreover, the terms "comprises", "comprising", and the like are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that comprises a list of steps or units is not limited to the listed steps or units, but can optionally further comprise additional steps or units not listed, or can optionally further comprise other steps or units inherent to such processes, methods, products, or apparatus.

[0034] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive or alternative embodiments. It is expressly understood that the embodiments described herein can be combined with each other in their various permutations and combinations.

[0035] Some professional terms involved in the present application will be explained below:

[0036] ASD: Adjustable Speed Drive, is a device that can control the speed of the motor. It can flexibly adjust the running speed of the motor according to different work requirements, so as to achieve the purpose of energy saving, optimizing production process, etc.

[0037] IM: Induction Motor, also known as Asynchronous Motor, is a common AC motor. It relies on electromagnetic induction principle to convert electrical energy into mechanical energy to realize the rotation of the motor.

[0038] Voltage sag tolerance: refers to the ability of electrical equipment (especially motor and its driving system) to maintain normal operation or recover normal operation within a short time when the voltage of the power grid appears sag phenomenon.

[0039] Fuzzy PI controller: 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 the nonlinearity, uncertainty and time-varying characteristics in the system.

[0040] abc coordinates: In motor analysis, abc coordinates are the natural coordinate system based on the three-phase winding of the motor stator. Among them, the a-phase, b-phase and c-phase windings are 120° apart in space and fixed on the stator.

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

[0042] Park transformation: also known as Park transformation, is a kind of mathematical transformation method widely used in the field of motor analysis and control, the basic idea of Park transformation is to transform the motor variables (such as current, voltage, flux linkage, etc.) in the stationary coordinate system (for example, abc coordinates) to a coordinate system (for example, dq0 coordinates) rotating synchronously with the motor rotor, so as to simplify the mathematical model of the motor.

[0043] Please refer to Figure 1 , Figure 1 is a structural schematic diagram of an electronic device provided by an embodiment of the present application; by Figure 1 It can be known that the electronic device can include a variable speed driver and an induction motor, the induction motor can 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 the variable speed driver. The working principle of the induction motor is based on electromagnetic induction. The stator winding is connected to a three-phase alternating current to generate a rotating magnetic field. The rotor winding induces an electromotive force and current in the rotating magnetic field, and then generates an electromagnetic torque to rotate the rotor.

[0045] Among them, the variable speed driver can adjust the frequency and voltage of the power supply to the induction motor. In the starting stage, the variable speed driver can gradually increase the voltage and frequency of the power supply to the motor according to the preset starting program, so that the motor starts smoothly and avoids excessive starting current impact. In the running process, the variable speed driver adjusts the speed of the motor according to the working requirements of the device. For example, when the device needs to run at a lower load, the variable speed driver reduces the power frequency supplied to the motor, and the motor speed decreases accordingly. In order to realize accurate control and optimize operation, the electronic device can use the device control method provided in the embodiments of the present application to adjust the output of the variable speed driver by detecting the running parameters (such as speed, current) of the motor. Specifically: the first speed value and the first three-phase current measurement value of the induction motor can be obtained; the first rotor flux linkage value is determined according to the first three-phase current measurement value; the difference between the first speed value and the preset speed reference value is determined to obtain the first speed difference value; the flux linkage reference value corresponding to the first speed value is determined; the difference between the first rotor flux linkage value and the flux linkage reference value is determined to obtain the first flux linkage difference value; the first speed difference value is input into the first fuzzy PI controller to obtain the electromagnetic torque reference value; the first flux linkage difference value is input into the second fuzzy PI controller to obtain the flux linkage current reference value; the three-phase current reference value is determined based on the electromagnetic torque reference value, the flux linkage current reference value and the first rotor flux linkage value; the control signal is determined according to the first three-phase current measurement value and the three-phase current reference value; the control signal is used to suppress the rapid drop of the speed of the induction motor, so as to prolong the voltage sag tolerance time of the induction motor.

[0046] Please refer to Figure 2 , Figure 2 is a flowchart of a device control method provided by an embodiment of the present application. The method is applied to an electronic device, which includes an adjustable-speed driver and an induction motor. The method can include the following steps:

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

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

[0049] In a specific embodiment, the induction motor can be measured by using a preset rotational speed measurement method (for example, a Hall sensor method) to obtain the first rotational speed value. Then, a current sensor can be arranged on the induction motor to obtain the 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, 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 value.

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

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

[0053] S21: Obtain a first flux orientation angle of the induction motor corresponding to a first preset time;

[0054] S22: Perform 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] wherein 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 Laplace operator, and 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 may 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, a Park transformation can be performed on the first three-phase current measurement value 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] Then, 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, the flux and torque of the motor are controlled separately and independently, just like controlling two independent variables separately, which greatly improves 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 can be obtained by subtracting the first speed value from the preset speed reference value.

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

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

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

[0069] A1. Obtain the 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 linkage 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. Then, the first speed value may be calculated based on 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 follows:

[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, we can see that when the rotor flux is actively reduced, the flux current gradually decreases, further increasing the torque current. 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, 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. Obtaining historical voltage data corresponding to the induction motor;

[0086] B3. Determine 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 dip durations that are greater than the preset duration among the a dip durations, to obtain b dip durations; where 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, to 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 sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

[0092] In an embodiment of the present application, an initial adjustment coefficient corresponding to the adjustable speed drive can be obtained. Specifically, a target device model corresponding to the adjustable speed drive can be obtained first, and then the initial adjustment coefficient can be determined based on 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. Next, historical voltage data corresponding to the induction motor can be obtained. Specifically, a 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, corresponding voltage data can be extracted from a preset database to obtain historical voltage data. Further, 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 a voltage amplitude is lower than this value in the historical voltage data, it is considered that a voltage sag event has occurred, and 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 the a voltage sag data can be determined to obtain a sag durations. Specifically, the voltage sag data may 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 earliest time in the a earliest time is subtracted from the latest time to obtain a sag duration. Then, the a sag duration can be compared with a preset duration to obtain b sag durations that are greater than the preset duration. Then, the b sag durations can be determined. The corresponding voltage sag data in the a voltage sag data can be used 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 maximum voltage value and the minimum voltage value of the b voltage sag data can be obtained to obtain b maximum voltage values ​​and b minimum voltage values. The corresponding minimum voltage value in the b minimum voltage values ​​can be subtracted from the b maximum voltage 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 a preset adjustment coefficient.

[0094] In this way, the two key factors, 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 conditions faced by the equipment in actual operation. In subsequent operation, the adjustable speed drive can more effectively adjust its output according to the adjusted preset adjustment coefficient to better adapt to 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 sag 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 dip duration among the b dip durations to obtain b-1 duration differences;

[0097] C2. Fit 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, predicting the sag duration at the target time according to the first straight line to obtain a predicted sag duration;

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

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

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

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

[0104] C9. Determine a target trip probability according to the first trip probability and the second trip probability;

[0105] C10. Adjusting the initial adjustment coefficient according to the target trip 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 sag duration among b sag durations can be calculated to obtain b-1 duration differences; then, these b-1 duration differences and their starting times can be fitted to obtain a first straight line, where 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. The sag duration at the target moment can be predicted based on the first straight line to obtain the predicted 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 sag duration. Then, the probability of the induction motor tripping can be determined based on the predicted sag duration to obtain a first tripping probability. Specifically, a mapping relationship between a preset sag duration and the tripping probability can be pre-stored, and the first tripping probability corresponding to the predicted sag duration can be determined based on the mapping relationship. Then, b weights can be determined based on b sag durations. Specifically, , a mapping relationship between a preset sag duration and a weight can be pre-stored, and b weights corresponding to b sag durations are determined based on the mapping relationship, with each sag duration corresponding to one weight. Then, a weighted operation can be performed based on the b weights and the b maximum change values ​​to obtain a target mean. Further, the probability of the induction motor tripping can be determined based on the target mean to obtain a second tripping probability. For example, a mapping relationship between a preset mean and the tripping probability can be pre-stored, and the second tripping probability corresponding to the target mean can be determined based on the mapping relationship. Then, the target tripping probability can be determined based on 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] The target tripping probability can be obtained according to the above formula. 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 trip 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 : Input the first speed difference into a first fuzzy PI controller to obtain an electromagnetic torque reference value.

[0120] Optional, step S206, see Figure 3 , Figure 3 This is a structural diagram of a first fuzzy PI controller provided by an embodiment of the present application. The first fuzzy PI controller includes: 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 inputting the first speed difference into the first fuzzy controller to obtain the electromagnetic torque reference value may include the following steps:

[0121] D1. quantizing the first speed difference 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 firstly 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 the 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 to obtain 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, i.e., 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 symmetrical form is used, where the total membership value of each variable is always 1, so that the membership functions of adjacent fuzzy sets are complementary. For the membership functions of each variable, please refer to Figure 4 , Figure 4 is a schematic diagram of a variable membership function provided by an embodiment of the present application, wherein Figure 4 In Figure a, ΔK I The variable membership function, Figure b is ΔK P Figure c is the variable membership function of e, and Figure d is the variable membership function of ec. The horizontal axis of the variable membership function represents the value of the variable, and the vertical axis represents the membership of the variable. In addition, the membership function labels are shown in Table 2:

[0134] Table 2

[0135]

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

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

[0138] According to the above formula, a second input quantity can be obtained; finally, the second input quantity can be processed by the first PI controller to obtain a second output quantity; the second output quantity includes an 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 by the first PI controller to obtain a second output may include the following steps:

[0141] E1. Obtaining value range pairs 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 scaling factor based on corresponding value range pairs 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 minimum value of the corresponding 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 corresponding actual variation range, EC min K ec The minimum value of the corresponding normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The minimum value of the corresponding normalized domain, △k (m)max For L (m) The maximum value of the corresponding normalized domain, △K (m)min For L (m) The minimum value of the corresponding actual variation range, △K (m)max For L (m) The maximum value of the corresponding actual variation range;

[0147] E3. Use the weighted average defuzzification method 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:

[0148]

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

[0150] E4. Calculate the control parameters 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 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, i.e., the second input; It is the cumulative error between the first PI adjustment and the kth PI adjustment.

[0157] In an 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. Based on the mapping relationship, multiple value range pairs corresponding to the quantization factor pair and the preset scale factor are determined. Each factor corresponds to a value range pair. Assume that the multiple value range pairs are as shown in Table 3:

[0158] Table 3

[0159]

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

[0161]

[0162]

[0163]

[0164] Furthermore, the weighted average defuzzification method can be used to calculate and obtain the target control parameter variables, which include 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 appropriate control parameters, enabling the device to respond quickly to given signals. For example, during motor startup or acceleration, the electromagnetic torque reference value can be quickly adjusted to quickly achieve the desired motor speed, shortening the device's response time and improving its dynamic performance.

[0173] S207 : Input 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. 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 embodiments of this application, please refer to Figure 5 , Figure 5 is a system block diagram of a device control method provided by 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 pole pairs of the motor, 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 based on 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 based on 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 value and the three-phase current reference value.

[0184] In the embodiment of the present application, the 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 through 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 the corresponding PWM pulse signal, that is, the control signal.

[0186] S210 , using the control signal to suppress a rapid drop in the rotational speed of the induction motor, so as to extend a 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 rotational speed of the induction motor, thereby extending the voltage sag tolerance time of the induction motor.

[0188] The application is implemented to have the following beneficial effects:

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

[0190] Please refer to Figure 6 , Figure 6 is a functional unit composition block diagram of a device control apparatus 600 provided by an embodiment of the application, applied to an electronic device, the electronic device comprising an adjustable speed driver and an induction motor, the device control apparatus 600 comprising: an acquisition unit 601, a determination unit 602, and a control unit 603, wherein:

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

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

[0193] The control unit 603 is configured to input the first speed difference value into a first fuzzy PI controller to obtain an electromagnetic torque reference value, input the first flux difference value 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 the rapid drop of the speed of the induction motor to prolong the voltage sag tolerance time of the induction motor.

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

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

[0196] perform 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] determine the first rotor flux value 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 linkage 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 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 linkage 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 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 dip durations that are greater than the preset duration among the a dip durations, to obtain b 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 in the b voltage sag data to obtain b maximum change values;

[0213] The initial adjustment coefficient is adjusted according to the b 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 dip 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 dip duration among the b dip durations to obtain b-1 duration differences;

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

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

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

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

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

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

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

[0223] determining a target trip probability according to the first trip probability and the second trip probability;

[0224] Adjusting the initial adjustment coefficient according to the target trip 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 configured to:

[0228] Quantizing the first rotation speed difference by using 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. In terms of processing the second input quantity by the first PI controller to obtain the second output quantity, 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 corresponding value range pairs among 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 minimum value of the corresponding 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 corresponding actual variation range, EC min K ec The minimum value of the corresponding normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The minimum value of the corresponding normalized domain, △k (m)max For L (m) The maximum value of the corresponding normalized domain, △K (m)min For L (m) The minimum value of the corresponding 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 variables, which include the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) The calculation formula is as follows:

[0240]

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

[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 parameters, 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, i.e., 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 This is a structural diagram of another electronic device provided in an embodiment of the present application. The electronic device includes a processor, a memory, a communication interface and one or more programs. The processor, memory and communication interface are interconnected through a bus. The above one or more programs are stored in the above memory and are configured to be executed by the above processor. The one or more programs include instructions for executing other implementation methods described in the device control method provided in the above embodiment of the present application, which will not be 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, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer may include an electronic device.

[0252] The present application also provides a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may comprise 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 this application is not limited by the order of the actions described, because according to this 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 this application.

[0254] In the above embodiments, the description of each embodiment has its own focus. 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 this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, 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 separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0257] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or 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, 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, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0259] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein 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 those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods 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 comprising: Obtaining 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; determining a difference between a preset speed reference value and the first speed value to obtain a first speed difference; determining a flux linkage reference value corresponding to the first speed value; determining a difference between the flux linkage reference value and the first rotor flux linkage value to obtain a first flux linkage 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; determining a control signal according to the first three-phase current measurement value and the three-phase current reference value; Using the control signal to suppress a rapid drop in the rotational speed of the induction motor, so as to extend the voltage sag tolerance time of the induction motor; The determining of the flux linkage 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 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 preset speed reference value, ψ r is the first rotor flux value; The step of obtaining a 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 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 dip durations that are greater than the preset duration among the a dip durations, to obtain b 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 in the b voltage sag data to obtain b maximum change values; The initial adjustment coefficient is adjusted according to the b sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

2. The method according to claim 1, wherein Determining a first rotor flux value according to the first three-phase current measurement value includes: Obtaining a first flux orientation angle corresponding to the induction motor at a first preset moment; Performing a 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 1, wherein The adjusting the initial adjustment coefficient according to the b sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient includes: Determine the duration difference between each adjacent dip duration among the b dip durations to obtain b-1 duration differences; Fit the b-1 duration differences and their starting times to obtain a first straight line; Determining the number of times the induction motor trips in the b voltage sag data to obtain a target tripping number; When the target tripping number is greater than the preset tripping number, predicting the sag duration at the target moment according to the first straight line to obtain a predicted sag duration; Determining a probability of the induction motor tripping according to the predicted sag duration to obtain a first tripping probability; Determine b weights according to the b dip durations; the longer the dip duration, the greater the weight; Determining a target mean value according to the b weights and the b maximum change values; Determining a probability of the induction motor tripping according to the target mean value to obtain a second tripping probability; determining a target trip probability according to the first trip probability and the second trip probability; Adjusting the initial adjustment coefficient according to the target trip 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.

4. The method according to any one of claims 1 to 3, wherein The first fuzzy PI controller includes: a quantization factor pair, a first fuzzy rule, a first fuzzy controller, and a first PI controller. Inputting the first speed difference into the first fuzzy controller to obtain an electromagnetic torque reference value includes: Quantizing the first rotation speed difference by using 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.

5. The method according to claim 4, wherein The quantization factor pair includes a first quantization factor and a second quantization factor, and the processing of the second input by the first PI controller to obtain a second output includes: 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 corresponding value range pairs among 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 minimum value of the corresponding 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 corresponding actual variation range, EC min K ec The minimum value of the corresponding normalized domain, EC max K ec The maximum value of the corresponding normalized domain; △k (m)min For L (m) The minimum value of the corresponding normalized domain, △k (m)max For L (m) The maximum value of the corresponding normalized domain, △K (m)min For L (m) The minimum value of the corresponding 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 variables, which include the first control parameter variable ΔK (P) and the second control parameter variable ΔK (I) The calculation formula is as follows: Where ΔK (m) is the target control parameter variable, m is equal to P or I, and i is the number of fuzzy rules in the first fuzzy rule; is the membership degree of the i-th 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 parameters, 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, i.e., the second input; It is the cumulative error between the first PI adjustment and the kth PI adjustment.

6. 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 acquiring unit is configured to acquire a first speed value and a first three-phase current measurement value of the induction motor; The determining unit is configured to determine a first rotor flux value based on 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; and determine a difference between the flux reference value and the first rotor flux value to obtain a first flux difference; The control unit is configured to input the first speed difference value into a first fuzzy PI controller to obtain an electromagnetic torque reference value; input the first flux difference value 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 based on the first three-phase current measurement value and the three-phase current reference value; and utilize the control signal to suppress a rapid drop in the speed of the induction motor, thereby extending a voltage sag tolerance time of the induction motor; In the aspect of determining the flux linkage reference value corresponding to the first speed value, the determining unit is specifically configured to: Get the preset adjustment coefficient; The first speed value is calculated according to the preset adjustment coefficient and the first rotor flux value 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 preset speed reference value, ψ r is the first rotor flux value; In terms of obtaining the preset adjustment coefficient, the determining unit is specifically configured to: Obtaining an initial adjustment coefficient corresponding to the adjustable speed driver; Acquiring historical voltage data corresponding to the induction motor; Determine 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 dip durations that are greater than the preset duration among the a dip durations, to obtain b 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 in the b voltage sag data to obtain b maximum change values; The initial adjustment coefficient is adjusted according to the b sag durations and the b maximum change values ​​to obtain the preset adjustment coefficient.

7. 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 programs include instructions for executing the steps of the method according to any one of claims 1 to 5.

8. 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 5.

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