ASD voltage tolerance improvement method based on improved control strategy

Abstract

The present invention is a method and device for improving the voltage tolerance of an ASD based on an improved control strategy, which belongs to the field of control strategies. In view of the problem that installing additional energy storage devices to improve tolerance is not conducive to actual production, the technical solution adopted is as follows: A method for improving the voltage tolerance of an adjustable speed drive based on an improved control strategy, comprising: using an anti-disturbance model to obtain a reference electromagnetic torque of an induction motor; calculating an expected value of the flux linkage of the induction motor; calculating a voltage switch vector through a switch vector table according to the reference electromagnetic torque, the reference value of the flux linkage and the expected value of the flux linkage; obtaining a voltage switch vector according to the state of the voltage switch vector; and controlling the motor speed to be close to the speed reference value. Increasing the torque current of the induction motor forces the speed to be close to the speed reference value, and reducing the flux linkage to improve the voltage sag tolerance of the adjustable speed drive, while overcoming the problem of increased cost due to the addition of external energy storage devices, which is conducive to actual production.

Description

Technical Field

[0001] This invention belongs to the field of control strategies, and specifically relates to a method for improving ASD voltage tolerance based on an improved control strategy. Background Technology

[0002] Adjustable speed drives (ASDs) convert voltages of fixed amplitude and frequency into voltages that vary according to industrial production needs, and are commonly used to control the speed of rotating equipment. ASDs are often part of an overall industrial system, operating alongside other electrical equipment and typically driving critical system loads. However, ASDs are highly sensitive to voltage sags. Voltage sags and short-term interruptions in the supply voltage will affect the normal operation of the adjustable speed drive. Since voltage sags are usually short-lived, and the tolerance time of current adjustable speed drives (i.e., the time they can withstand voltage sags without tripping the equipment or maintaining normal production) is typically only tens to thirty milliseconds, it is insufficient to withstand most voltage sag events. In continuous industrial processes, voltage sags and ASD failures (or malfunctions) can lead to production interruptions, equipment damage, serious economic losses, and even safety issues.

[0003] The basic structure of ASD is as follows: Figure 1 As shown, the system can be divided into five main parts: rectifier module, DC circuit module, inverter module, induction motor, and controller. The functions of each module are described below:

[0004] Rectifier module: Its main function is to rectify the power frequency current input from the grid, so that the rectified DC voltage is stabilized at a certain value. Depending on the power requirements, uncontrollable or fully controlled rectifier modules are used.

[0005] DC circuit module: A capacitor with a large capacitance value is used to stabilize the output voltage of the rectifier module within a certain range to ensure voltage stability; when a sag occurs, the voltage amplitude at the input terminal decreases, and the voltage of the DC capacitor also decreases. The capacitor can be used as a very small energy storage unit as a power source for the control circuit.

[0006] Inverter module: Under the action of the gate trigger signal, the DC voltage output by the rectifier module is transformed into multiple square wave signals with different duty cycles by the inverter module, which can realize the variable frequency speed regulation of the induction motor. When the input voltage decreases to the threshold, the inverter module will not work properly, which will affect the normal operation of the induction motor. This is the main reason why the adjustable speed driver does not work properly due to voltage drop.

[0007] The controller: By detecting current signals, speed signals, electromagnetic torque signals, DC circuit module voltage signals, and using built-in control algorithms and reference values, it generates the gate drive signals required by the inverter module and protects the entire inverter module and induction motor through a protection module; existing ASDs generally use vector controllers, whose structure Figure 2 As shown. However, the vector controller has the following problems:

[0008] (1) Vector control is based on a steady-state mathematical model and focuses on the control performance under steady-state and dynamic (sudden changes in load or other small disturbances). The calculation model is heavily dependent on the parameters of the motor. The changes in the stator and rotor resistance values ​​and the changes in the stator and rotor mutual inductance will have a great impact on the control performance. In the case of sag, not only will the resistance and inductance values ​​change, but the orientation angle of the flux linkage will also deviate, which will cause the control performance to decline.

[0009] (2) In vector controllers, PI controllers or PID controllers are widely used. The speed and flux reference values ​​are preset. The control parameters of the controller are fixed. The design is based on the driver and performance requirements under steady-state and dynamic conditions. Under voltage sag, the controller parameters cannot be adjusted online in time. The response speed and response amount of the torque and speed output by the driver are insufficient, resulting in insufficient voltage tolerance of the adjustable speed driver.

[0010] Therefore, existing technologies employ external energy storage devices to address voltage dips:

[0011] (a) Uninterruptible power supply (UPS): The structure of an UPS is similar to that of a storage battery. Its characteristic is that it maintains a stable output DC voltage. When the controller detects a voltage drop at the control grid terminal, it can quickly switch the UPS to the DC circuit, so that the voltage value of the DC capacitor is still maintained at a stable value. This eliminates the disturbance to the speed and torque of the driver caused by insufficient or abnormal power supply. However, the performance of the UPS gradually deteriorates with the increase of service life. It is also expensive, has low reliability, occupies a large area, and requires regular inspection.

[0012] (b) Dynamic Voltage Restorer: By connecting a DVR in series between the sensitive device and the power grid, the DVR does not work under normal operating conditions. The controller uses precise sensors and algorithms to detect voltage dips. When the DVR activates, it injects more energy to raise the voltage at the device to the normal value, thereby improving the device's voltage dip tolerance. However, when the system's power supply voltage drops to a certain limit or the power supply is completely interrupted, the DVR cannot provide energy compensation. It also has a short operating time, is expensive, and has a large footprint.

[0013] (c) Solid-state switching: Solid-state switching is composed of electronic components SCR; when a voltage drop occurs on one side of the power grid, the power supply circuit will be quickly switched under the control of the controller. Its action time is short, and the voltage change has little or no impact on the load; however, it is only used when the adjustable speed drive is powered by two independent power inputs, and its actual application is rare.

[0014] (d) DC-BANK: It adopts DC support technology, with a Boost or Buck-Boost boost chopper connected in parallel across the rectifier bridge of the adjustable speed driver; the output of the boost chopper is connected in parallel across the DC capacitor of the adjustable speed driver to maintain the stability of the capacitor voltage. By ensuring the stability of the DC voltage, the normal operation of the driver is guaranteed. However, this not only increases the equipment cost, but also increases the complexity of control. The switching devices inside the DC-BANK also need to be inspected regularly, so the total cost is high.

[0015] Existing methods for upgrading adjustable speed drives involve installing additional energy storage devices, but these methods typically involve significant investment and maintenance costs, resulting in poor economic efficiency and difficulties in practical application. Summary of the Invention

[0016] To address the issue of poor economic efficiency in using additional energy storage devices to enhance the performance of adjustable speed drives, this invention provides an adjustable speed drive that employs an improved control strategy to enhance voltage tolerance. This eliminates the need for external energy storage devices, avoiding increased costs and facilitating production applications.

[0017] The technical solution adopted in this invention is as follows: A method for improving the voltage tolerance of an adjustable speed driver based on an improved control strategy, comprising:

[0018] Step 1, based on the reference value w of the induction motor speed ref (t) and rotational speed w r (t), the reference electromagnetic torque T of the induction motor is obtained through the active disturbance rejection controller model. e* To adjust the induction motor speed w under different voltage operating conditions r (t) Maintain the set speed reference value w ref (t);

[0019] Step 2, based on the current signal i in the two-phase rotating coordinate system d,q Voltage signal V d,q and magnetic flux reference value ψ ref The expected value ψ(k+2) of the flux linkage of the induction motor is calculated by using a discrete model and cost function, so as to keep the current of the induction motor at an appropriate level.

[0020] Step 3, based on the reference electromagnetic torque Te* The magnetic flux reference value ψ ref The voltage switching vector state is calculated using the expected value ψ(k+2) of the magnetic flux through the switching vector table to obtain the voltage switching vector state that the ASD controller needs to output, ensuring that the actual operation of the induction motor is close to each reference value and the expected value.

[0021] Step 4: Obtain the voltage switching vector based on the voltage switching vector state;

[0022] Step 5: Based on the voltage switch vector control, the motor speed is brought close to the speed reference value w. ref (t) is used to improve the tolerance of ASD voltage sag.

[0023] By controlling the speed and flux linkage to increase the torque current of the induction motor when a voltage sag occurs, the speed is forced to approach the speed reference value, and the flux linkage is reduced, thereby improving the voltage sag tolerance of the adjustable speed driver. At the same time, it overcomes the problem of increased costs caused by adding external energy storage devices, which is beneficial to actual production.

[0024] Furthermore, the specific steps of step 1 are as follows:

[0025] Step 1.1, using the aforementioned speed reference value w ref (t) Obtain its differential signal v1;

[0026] Step 1.2, according to the rotational speed w r (t) and the actual electromagnetic torque T of the induction motor e The torque tracking signal z1 and the uncertain disturbance signal z2 based on the torque tracking signal z1 are obtained. The torque tracking signal z1 tracks the differential signal v1 to obtain the error signal e1.

[0027] Step 1.3: Obtain the initial control variable u0 of the controller for the induction motor based on the error signal e1;

[0028] Step 1.4: Control the uncertain disturbance signal z2 to track the initial control variable u0. By introducing a proportional factor 1 / b and a compensation factor a, obtain the controller's output control signal u(t) to calculate the reference electromagnetic torque T of the induction motor. e* .

[0029] Furthermore, step 1 involves the following formula:

[0030] The equation of motion for an induction motor is:

[0031]

[0032] In the formula, J is the moment of inertia of the induction motor; n pp is the number of pole pairs of the induction motor; D is the damping coefficient; K is the torsional elastic torque coefficient; T L is the load magnitude; w is the rotational speed of the induction motor (the same as w r (t) above); θ is the angle of rotation of the rotor of the induction motor; is the differential of the rotational speed of the induction motor;

[0033] Combined with the motion equation of the induction motor, the rotational speed w r (t) of the induction motor can be obtained as follows:

[0034]

[0035] where a is the compensation factor, and z2 is estimated by the following formula:

[0036]

[0037] In the formula, c1 and c2 are non-linear factors, and the adjustment rule for their values is 0 < c2 < c1 < 1; δ is the filtering factor; α0 and α1 are adjustable parameters; and are the differentials of z1 and z2 respectively.

[0038] fbl(e1, c, δ) is a non-linear function, and its specific expression is as follows:

[0039]

[0040]

[0041] c is a non-linear factor. By replacing c1 and c2 with c respectively, fbl(e1, c1, δ) and fbl(e1, c2, δ) can be obtained; α is an adjustable parameter;

[0042] Calculate the reference electromagnetic torque T e* according to the output control signal u(t):

[0043]

[0044] In the scope of the present invention, since the active disturbance rejection controller is designed according to the rotational speed control, K = 1 is considered.

[0045] Furthermore, the specific process of step 2 is as follows:

[0046] Step 2.1, transform the three-phase current, voltage, and magnetic flux into the current, voltage, and magnetic flux in the two-phase rotating coordinate system through coordinate transformation; based on the discretized expression of the current, according to the current change rate at time k, obtain the current prediction value i d，q (k + 1);

[0047] Step 2.2: Using a cost function, based on the magnetic flux reference value ψ ref Current prediction value i d，q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q By obtaining the expected flux linkage value ψ(k+2), the flux linkage value at the next moment under the current operating conditions is obtained, so that the induction motor operates near the reference value at the next moment.

[0048] In traditional model predictive control, the current control speed can be affected by parameter changes. To eliminate the impact of parameter changes on control performance, the output state is fed back into the current prediction model to obtain the current value at time k+1 corresponding to the flux linkage model. This current is then used as the input for flux linkage predictive control, making the predicted flux linkage change at time k+2 obtained by multiplying the flux linkage differential approximation with the changing resistance and inductance parameters relatively smooth, and the switching vector output more stable, thereby enhancing steady-state control performance.

[0049] In step 2.1, the switching state corresponding to the optimal cost function is selected as the output by discretizing the current state equation. The discretized expression of the current is:

[0050]

[0051] For current i d,q The differential, i d,q (k) represents the current i at time k. d,q The magnitude of T is the time period for the controller signal acquisition.

[0052] By transforming the motor voltage equation into a discrete current model, and further obtaining the discrete state equation of the flux linkage based on the relationship between current and flux linkage, the following equation is derived:

[0053]

[0054]

[0055] In the formula, ψ d (k+2), ψ q (k+2) represent the expected flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k+2; ψ d (k+1), ψ q (k+1) represent the expected flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k+1, respectively, ω s ψ is the synchronous speed of the motor rotation. d (k), ψ q (k) represents the flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k, where R is the stator resistance of the motor, and T is the flux linkage component along the d-axis and q-axis. si is the stator time constant of the motor. d (k), i q (k) represents the current components along the d-axis and q-axis in the two-phase rotating coordinate system at time k, respectively. d (k+1),i q (k+1) represent the current components along the d-axis and q-axis in the two-phase rotating coordinate system at time k+1, respectively. d (k), V q (k) represents the voltage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k.

[0056] Step 2.2: Substitute the predicted values ​​from the current model into the state equation above for calculation, and then select the cost function C as:

[0057]

[0058] In the formula, ψ d * ψ q * α1 and α2 are the components of the flux linkage reference values ​​on the d-axis and q-axis in a two-phase rotating coordinate system; α1 and α2 are flux linkage adjustment coefficients. Based on the control degree of model predictive control, the two coefficients are adjusted to optimize the cost function and achieve the best control performance.

[0059] To enhance the flexibility of the cost function under different voltage sag depths, adjustment coefficients α1 and α2 are introduced to improve the flexibility of adjusting the two flux linkage components. Step 2 also includes step 2.3, where the adjustment coefficients satisfy the following rules:

[0060] α1+α2=2

[0061] When the voltage sag amplitude U sag At 0.85pu sag When α<1.0pu, α1=α2=1;

[0062] When the voltage sag amplitude U sag When the value is less than 0.85 pu, increase α1 and make α2 > 0.

[0063] When the voltage sag amplitude U sag At 0.85pu sag When the voltage sag is less than 1.0 pu, most ASDs can tolerate this depth of voltage dip. To reduce controller computation, α1 = α2 = 1 is maintained; when the voltage dip amplitude U sag ​​When the voltage drop is less than 0.85 pu, the ASD (Automatic Speed ​​Driver) malfunctions or even shuts down due to voltage sags. Increasing α1 can adjust the flux linkage component of the d-axis, reducing the current in the flux linkage component and increasing the current in the q-axis, thus maintaining normal motor operation and improving the overall voltage tolerance of the variable speed drive. In summary, based on the control requirements of model predictive control and the average voltage sag experienced by the equipment, adjusting the coefficients α1 and α2 optimizes the cost function and achieves the best control performance.

[0064] The desired output state can be obtained by calculating the flux linkage modulus difference in the cost function C. By introducing a flux linkage adjustment coefficient to control the calculation of the cost function, the inverter state under the minimum cost function is obtained, maximizing the control effect and achieving optimal control performance for the current torque component i under voltage sag. q Further increase the size to improve the voltage sag tolerance of the adjustable speed drive.

[0065] The apparatus used to implement the above method includes:

[0066] Active disturbance rejection controller, based on the speed reference value w of the induction motor. ref (t) and rotational speed w r (t), the reference electromagnetic torque T of the induction motor is obtained through the active disturbance rejection controller model. e* To adjust the induction motor speed w under different voltage operating conditions r (t) Maintain the set speed reference value w ref (t);

[0067] The model predictive controller is based on the current signal i in a two-phase rotating coordinate system. d,q Voltage signal V d,q and magnetic flux reference value ψ ref The expected value ψ(k+2) of the flux linkage of the induction motor is calculated by using a discrete model and cost function, so as to keep the current of the induction motor at an appropriate level.

[0068] Cost function calculator, based on the reference electromagnetic torque T e* The magnetic flux reference value ψ ref The voltage switching vector is calculated using the expected value ψ(k+2) of the magnetic flux through the switching vector table to obtain the voltage switching vector state that the ASD controller needs to output, ensuring that the actual operation of the induction motor is close to each reference value and the expected value.

[0069] A voltage switch vector calculator obtains the voltage switch vector based on the voltage switch vector state.

[0070] The inverter, based on the voltage switch vector control, enables the motor speed to approach the speed reference value w. ref (t) is used to improve the tolerance of ASD voltage sag.

[0071] By setting an active disturbance rejection controller to control the speed, the robustness of the system parameters to change is improved. By setting a model predictive controller to control the flux linkage, the combination of the two can increase the torque current of the induction motor when a voltage sag occurs, forcing the speed to approach the speed reference value and reducing the flux linkage, thereby improving the voltage sag tolerance of the adjustable speed driver. Since no external energy storage device is added, there is no increase in cost, which is beneficial to actual production.

[0072] Furthermore, the active disturbance rejection controller includes:

[0073] The state tracker uses the rotational speed reference value w ref (t) Obtain its differential signal v1;

[0074] Extended state observer, based on the rotational speed w r (t) and the actual electromagnetic torque T of the induction motor e The torque tracking signal z1 and the uncertain disturbance signal z2 based on the torque tracking signal z1 are obtained. The torque tracking signal z1 tracks the differential signal v1 to obtain the error signal e1, which is used as the output signal to determine whether the torque tracking signal z1 is tracking normally.

[0075] An error controller obtains the initial control variable u0 for the induction motor based on the error signal e1.

[0076] An extended state observer controls the uncertain disturbance signal z2 to track the initial control variable u0. By introducing a scaling factor 1 / b and a compensation factor a, the controller's output control signal u(t) is obtained to calculate the reference electromagnetic torque T of the induction motor. e* The purpose is to control the speed of the induction motor to remain at the set reference speed value w. ref (t) near.

[0077] The active disturbance rejection controller first calculates the error between the motor speed and the set reference speed by collecting the motor output speed and torque. The error controller keeps the speed close to the set reference speed, thereby improving the robustness of the system parameters. Combined with the uncertain disturbance signal z2 estimated in real time by the extended state observer, the control quantity output by the speed controller is finally obtained by introducing the proportional factor 1 / b and the compensation factor a.

[0078] Furthermore, the model predictive controller is connected to the induction motor via a coordinate transformer and a flux linkage observer. The coordinate transformer converts the current signal i of the induction motor into... s and voltage signal V s Transformed into a current signal i in a two-phase rotating coordinate system d,q and voltage signal V d,qThe value is input to the flux linkage observer, and the actual flux linkage value ψ(k) of the motor is obtained through the calculation of the flux linkage observer.

[0079] Furthermore, the model predictive controller includes a current predictive controller and a flux prediction controller, wherein the current predictive controller is based on the current i at time k. d,q Magnitude and rate of change of current at time k Calculate and obtain the predicted current value i d，q (k+1), the flux linkage prediction controller is based on the flux linkage reference value ψ ref and the predicted current value i d,q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q Obtain the expected value of magnetic flux linkage ψ(k+2).

[0080] The beneficial effects of this invention are: by controlling the rotational speed and flux linkage to increase the torque current of the induction motor when a voltage sag occurs, the rotational speed is forced to approach the reference value, and the flux linkage is reduced, thereby improving the voltage sag tolerance of the adjustable speed driver. At the same time, it overcomes the problem of increased costs caused by adding external energy storage devices, which is beneficial to actual production. Attached Figure Description

[0081] Figure 1 This is a basic structural diagram of the existing ASD;

[0082] Figure 2 Here is a diagram of the controller structure for an existing vector control strategy;

[0083] Figure 3 This is a schematic diagram of the adjustable speed drive of this application;

[0084] Figure 4 This is a schematic diagram of the active disturbance rejection controller.

[0085] Figure 5 This is a schematic diagram of the model predictive controller.

[0086] Figure 6 The speed response curve under the transient descent condition is shown in the example diagram;

[0087] Figure 7 The tolerance curves are for the embodiments and existing methods. Detailed Implementation

[0088] The technical solutions of the embodiments of the present invention will be explained and described below with reference to the accompanying drawings. However, the following embodiments are only preferred embodiments of the present invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments in the implementation methods without creative effort are all within the protection scope of the present invention.

[0089] Example 1

[0090] This embodiment presents a method for improving the voltage tolerance of an adjustable speed driver based on an improved control strategy, such as... Figure 3 As shown, it includes:

[0091] Step 1, as follows Figure 4 As shown, the reference value w of the induction motor speed is... ref (t) and rotational speed w r (t), the reference electromagnetic torque T of the induction motor is obtained by using an active disturbance rejection controller. e* To adjust the induction motor speed w under different voltage operating conditions r (t) Maintain the set speed reference value w ref (t):

[0092] Step 1.1, using the aforementioned speed reference value w ref (t) Obtain its differential signal v1;

[0093] Step 1.2, according to the rotational speed w r (t) and the actual electromagnetic torque T of the induction motor e The torque tracking signal z1 and the uncertain disturbance signal z2 based on the torque tracking signal z1 are obtained. The torque tracking signal z1 tracks the differential signal v1 to obtain the error signal e1.

[0094] Step 1.3: Obtain the initial control variable u0 of the controller for the induction motor based on the error signal e1;

[0095] Step 1.4: Control the uncertain disturbance signal z2 to track the initial control variable u0. By introducing a proportional factor 1 / b and a compensation factor a, obtain the controller's output control signal u(t) to calculate the reference electromagnetic torque T of the induction motor. e* ;

[0096] Step 1 involves the following formulas:

[0097] The equation of motion for an induction motor is:

[0098]

[0099] In the formula, J is the moment of inertia of the induction motor; n p D is the number of pole pairs of the induction motor; K is the damping coefficient; T is the torsional elastic torque coefficient; L θ represents the load size; w represents the induction motor speed; θ represents the angle of rotation of the induction motor rotor. This is the derivative of the induction motor's rotational speed;

[0100] By combining the equations of motion of the induction motor, the rotational speed w of the induction motor can be obtained. r (t) is:

[0101]

[0102] Among them, a is a compensation factor, and z2 is estimated by the following formula:

[0103]

[0104] In the above formula, c1 and c2 are non-linear factors, and the adjustment rule of their values is 0 < c2 < c1 < 1; δ is a filtering factor; α0 and α1 are adjustable parameters; and are the differentials of z1 and z2 respectively.

[0105] fbl(e1, c, δ) is a non-linear function, and its specific expression is as follows:

[0106]

[0107]

[0108] c is a non-linear factor. By replacing c1 and c2 with c respectively, fbl(e1, c1, δ) and fbl(e1, c2, δ) can be obtained; α is an adjustable parameter.

[0109] Calculate the reference electromagnetic torque T according to the output control signal u(t) e* :

[0110]

[0111] In the scope of the present invention, since the auto-disturbance rejection controller is designed according to the speed control, consider K = 1;

[0112] Step 2, according to the current signal i d,q 、voltage signal V d,q and the magnetic flux reference value ψ ref , calculate the expected value ψ(k + 2) of the magnetic flux of the induction motor through the discrete model and the cost function, and keep the current of the induction motor at an appropriate level:

[0113] Step 2.1, convert the three-phase current, voltage, and magnetic flux into the current, voltage, and magnetic flux in the two-phase rotating coordinate system through coordinate transformation; based on the discretized expression of the current, according to the current change rate at time k the predicted current value i d，q (k + 1) can be obtained; select the switching state corresponding to the optimal cost function as the output through the discretized current state equation, and the discretized expression of the current is:

[0114]

[0115] For current i d,q The differential, i d,q (k) represents the current i at time k. d,q The magnitude of T is the time period for the controller signal acquisition.

[0116] By transforming the motor voltage equation into a discrete current model, and further obtaining the discrete state equation of the flux linkage based on the relationship between current and flux linkage, the following equation is derived:

[0117]

[0118]

[0119] In the formula, ψ d (k+1), ψ q (k+1) represent the expected flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k+1, respectively, ω s ψ is the synchronous speed of the motor rotation. d (k), ψ q (k) represents the flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k, where R is the stator resistance of the motor, and T is the flux linkage component along the d-axis and q-axis. s i is the stator time constant of the motor. d (k), i q (k) represents the current components along the d-axis and q-axis in the two-phase rotating coordinate system at time k, respectively. d (k), V q (k) represents the voltage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k;

[0120] Step 2.2: Using a cost function, based on the magnetic flux reference value ψ ref Current prediction value i d，q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q By obtaining the expected flux linkage value ψ(k+2), we can determine the flux linkage value at the next moment under the current operating conditions, ensuring that the induction motor operates near the reference value at the next moment.

[0121] Substituting the current model predictions into the state equation above for calculation, and then selecting the cost function as:

[0122]

[0123] In the formula, ψ d (k+2), ψ q (k+2) represent the expected flux linkage components along the d-axis and q-axis in the two-phase rotating coordinate system at time k+2; ψ d * ψ q* α1 and α2 are the components of the flux linkage reference values ​​on the d-axis and q-axis in a two-phase rotating coordinate system; α1 and α2 are the flux linkage adjustment coefficients. Based on the control degree of the model predictive control, the two coefficients are adjusted to optimize the cost function and achieve the best control performance.

[0124] Step 2.3: To enhance the flexibility of the cost function under different voltage sag depths, adjustment coefficients α1 and α2 are introduced to improve the flexibility of adjusting the two flux linkage components. The adjustment coefficients satisfy the following rules:

[0125] α1+α2=2

[0126] When the voltage sag amplitude U sag At 0.85pu sag When α<1.0pu, α1=α2=1;

[0127] When the voltage sag amplitude U sag When the value is less than 0.85 pu, increase α1.

[0128] When the voltage sag amplitude U sag At 0.85pu sag When the voltage sag is less than 1.0 pu, most ASDs can tolerate this depth of voltage dip. To reduce controller computation, α1 = α2 = 1 is maintained; when the voltage dip amplitude U sag When the voltage drop is less than 0.85 pu, the ASD (Automatic Speed ​​Driver) malfunctions or even shuts down due to voltage sags. Increasing α1 can adjust the flux linkage component of the d-axis, reducing the current in the flux linkage component and increasing the current in the q-axis, thus maintaining normal motor operation and improving the overall voltage tolerance of the variable speed drive. In summary, based on the control requirements of model predictive control and the average voltage sag experienced by the equipment, adjusting the coefficients α1 and α2 optimizes the cost function and achieves the best control performance.

[0129] The desired output state can be obtained by calculating the flux linkage modulus difference in the cost function C. By introducing a flux linkage adjustment coefficient to control the calculation of the cost function, the inverter state under the minimum cost function is obtained, maximizing the control effect and achieving optimal control performance for the current torque component i under voltage sag. q Further increase the voltage sag tolerance of the adjustable speed drive;

[0130] ​​In traditional model predictive control, the current control speed is affected by parameter changes. To eliminate the impact of parameter variations on control performance, the output state is fed back into the current prediction model to obtain the current value at time k+1 corresponding to the flux linkage model. This current is then used as the input for flux linkage predictive control, resulting in a smoother predicted flux linkage change at time k+2 obtained by multiplying the flux linkage differential approximation with the changing inductance parameters. This leads to a more stable switching vector output and enhances steady-state control performance. The overall control block diagram is shown below. Figure 3 As shown, the detailed schematic diagram of the model predictive controller is as follows: Figure 5 As shown;

[0131] Step 3, based on the reference electromagnetic torque T e* The magnetic flux reference value ψ ref The voltage switching vector state is calculated using the expected value ψ(k+2) of the magnetic flux to obtain the voltage switching vector state that the ASD controller needs to output, ensuring that the actual operation of the induction motor is close to each reference value and the expected value.

[0132] Step 4: Obtain the voltage switching vector based on the voltage switching vector state;

[0133] Step 5: Based on the voltage switch vector control, the motor speed is brought close to the speed reference value w. ref (t) is used to improve the tolerance of ASD voltage sag.

[0134] A simulation model of an adjustable speed driver was built in the MATLAB / Simulink environment. Vector control and model predictive control-based vector control were applied to the adjustable speed driver. The motor parameters in ASD were set as follows: P n =15kW; U n =400V; n N =1460rpm; L m =0.06419H; R s =0.2417; L s =0.00991H; R r =0.2206; L r =0.00991H; J=0.102kg·m^2.

[0135] The adjustable speed drive starts from no load, applies rated load at 0.15s, and transitions to a three-phase balanced transition. The transition time t is... sag =0.5s. Considering that the duration of most temporary sags does not exceed 1s (due to the fault disappearing due to automatic reclosing, etc.), the end time of the temporary sag is t. s ′ ag =1.5s.

[0136] Figure 6The ASD speed response under two control modes is presented at a sag of 0.76 pu (0.72 times the rated voltage). Figure 6 It can be seen that vector control based on model predictive control has better voltage sag tolerance. For voltage sag events above 0.72 pu (accounting for approximately 95% of sag events), the inverter can operate normally regardless of the duration of the sag (the area below the curve represents the abnormal or production interruption region; the area above the curve represents the normal operation region). In contrast, vector control inverters can only tolerate voltage sag events with an amplitude above 0.86 pu (accounting for approximately 50% of sag events). Therefore, this invention significantly improves the voltage sag tolerance of the inverter. Furthermore, the additional cost of this invention is minimal, only requiring the addition of some control commands to the controller, greatly saving costs compared to installing external equipment.

[0137] Figure 7 The voltage sag tolerance curves of the frequency converter under two control modes are given (the horizontal axis is the duration of the sag; the vertical axis is the sag amplitude, and pu represents the rated voltage amplitude). Figure 7 It can be seen that the present invention has better voltage sag tolerance than ordinary frequency converters under the same sag conditions.

[0138] Example 2

[0139] Devices that improve ASD voltage withstand capability based on improved control strategies include:

[0140] Active disturbance rejection controller, based on the speed reference value w of the induction motor. ref (t) and rotational speed w r (t), the reference electromagnetic torque T of the induction motor is obtained using the active disturbance rejection model. e* Under different operating conditions, the induction motor speed w r (t) Maintain the set speed reference value w ref (t);

[0141] The model predictive controller is based on the current signal i in a two-phase rotating coordinate system. d,q Voltage signal V d,q and magnetic flux reference value ψ ref The expected value ψ(k+2) of the flux linkage of the induction motor is calculated by using a discrete model and cost function, so as to keep the current of the induction motor at an appropriate level.

[0142] Cost function calculator, based on the reference electromagnetic torque T e* The magnetic flux reference value ψ refThe voltage switching vector is calculated using the expected value ψ(k+2) of the magnetic flux through the switching vector table to obtain the voltage switching vector state that the ASD controller needs to output, ensuring that the actual operation of the induction motor is close to each reference value and the expected value.

[0143] A voltage switch vector calculator obtains the voltage switch vector based on the voltage switch vector state.

[0144] The inverter, based on the voltage switch vector control, enables the motor speed to approach the speed reference value w. ref (t) is used to improve the tolerance of ASD voltage sag.

[0145] By setting an active disturbance rejection controller to control the speed, the robustness of the system parameters to change is improved. By setting a model predictive controller to control the flux linkage, the combination of the two can increase the torque current of the induction motor when a voltage sag occurs, forcing the speed to approach the speed reference value and reducing the flux linkage, thereby improving the voltage sag tolerance of the adjustable speed driver. Since no external energy storage device is added, there is no increase in cost, which is beneficial to actual production.

[0146] The active disturbance rejection controller includes:

[0147] The state tracker uses the rotational speed reference value w ref (t) Obtain its differential signal v1;

[0148] Extended state observer, based on the rotational speed w r (t) and the actual electromagnetic torque T of the induction motor e The torque tracking signal z1 and the uncertain disturbance signal z2 based on the torque tracking signal z1 are obtained. The torque tracking signal z1 tracks the differential signal v1 to obtain an error signal e1, which serves as the output signal for determining whether the torque tracking signal z1 is tracking normally.

[0149] An error controller obtains the initial control variable u0 for the induction motor based on the error signal e1.

[0150] An extended state observer controls the uncertain disturbance signal z2 to track the initial control variable u0. By introducing a scaling factor 1 / b and a compensation factor a, the controller's output control signal u(t) is obtained to calculate the reference electromagnetic torque T of the induction motor. e* The purpose is to control the speed of the induction motor to remain at the set reference speed value w. ref (t) near.

[0151] The active disturbance rejection controller first calculates the error between the motor speed and the set reference speed by collecting the motor output speed and torque. The error controller keeps the speed close to the set reference speed, thereby improving the robustness of the system parameters. Combined with the uncertain disturbance signal z2 estimated in real time by the extended state observer, the control quantity output by the speed controller is finally obtained by introducing the proportional factor 1 / b and the compensation factor a.

[0152] The model predictive controller is connected to the induction motor via a coordinate transformer and a flux linkage observer. The coordinate transformer converts the induction motor's current signal i... s and voltage signal V s Transformed into a current signal i in a two-phase rotating coordinate system d,q and voltage signal V d,q The value is input to the flux linkage observer, and the actual flux linkage value ψ(k) of the motor is obtained through the calculation of the flux linkage observer.

[0153] The model predictive controller includes a current predictive controller and a flux prediction controller. The current predictive controller is based on the current i at time k. d,q Magnitude and rate of change of current at time k Calculate and obtain the predicted current value i d，q (k+1), the flux linkage prediction controller is based on the flux linkage reference value ψ ref and the predicted current value i d,q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q Obtain the expected value of magnetic flux linkage ψ(k+2).

[0154] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art should understand that the present invention includes, but is not limited to, the contents described in the accompanying drawings and the specific embodiments above. Any modifications that do not depart from the functional and structural principles of the present invention will be included within the scope of the claims.

Claims

1. A method for improving ASD voltage tolerance based on improved control strategy, characterized in that: include: Step 1, based on the speed reference value w of the induction motor ref (t) and speed w r (t), the reference electromagnetic torque T of the induction motor is obtained through the ADRC model e* , under different voltage conditions, the speed of the induction motor is w r (t) Maintain the speed reference value w ref (t); Step 2: According to the current signal i in the two-phase rotating coordinate system d,q , voltage signal V d,q , the expected value of the magnetic flux of the induction motor ψ(k+2) is calculated by the discrete model; the specific process is: Step 2.1, transform the three-phase current, voltage, and flux into the current, voltage, and flux in the two-phase rotating coordinate system through coordinate transformation; based on the discrete model, according to the current change rate at time k Get the current prediction value i d，q (k+1); the discretized expression of current is: is the current i d,q The differential of d,q (k) is the current i at time k d,q The size of is, T is the time period of controller signal acquisition; By converting the motor voltage equation into a discrete model of current, the discrete state equation of magnetic flux is further obtained according to the relationship between current and magnetic flux, as shown in the following formula: In the formula, ψ d (k+2),ψ q (k+2) are the expected value components of the flux linkage of the d-axis and q-axis in the two-phase rotating coordinate system at time k+2; ψ d (k+1),ψ q (k+1) are the expected value components of the flux linkage of the d-axis and q-axis in the two-phase rotating coordinate system at time k+1, ω s is the synchronous speed of the motor, ψ d (k),ψ q (k) are the flux linkage components of the d-axis and q-axis in the two-phase rotating coordinate system at time k, R is the stator resistance of the motor, T s is the motor stator time constant, i d (k), i q (k) are the current components of the d-axis and q-axis in the two-phase rotating coordinate system at time k, i d (k+1), i q (k+1) are the current components of the d-axis and q-axis in the two-phase rotating coordinate system at time k+1, V d (k), V q (k) are the voltage components of the d-axis and q-axis in the two-phase rotating coordinate system at time k; Te is the actual electromagnetic torque; Step 2.2, according to the current prediction value i d，q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q Obtain the expected value of flux ψ(k+2), and obtain the flux value at the next moment under the current operation condition, so that the induction motor runs near the reference value at the next moment; bring the current model prediction value into the discrete state equation for calculation, and then select the cost function C as: In the formula, ψ d * , q * are the components of the flux reference values ​​of the d-axis and q-axis in the two-phase rotating coordinate system; α1 and α2 are the flux adjustment coefficients; Step 2.3, the adjustment coefficient satisfies the following rules: α1+α2＝2 When the voltage sag amplitude U sag At 0.85pu sag When <1.0pu, α1=α2=1;​ When the voltage sag amplitude U sag When it is less than 0.85pu, increase α1 and make α2>0; Step 3: Based on the cost function, according to the reference electromagnetic torque T e* , the flux reference value ψ ref and the expected value ψ(k+2) of the flux linkage to calculate the voltage switch vector state, and obtain the voltage switch vector state that the ASD controller needs to output, so as to ensure that the actual operation of the induction motor is close to the reference values ​​and the expected values; Step 4, obtaining a voltage switching vector according to the voltage switching vector state; Step 5: Based on the voltage switch vector control, the motor speed is close to the speed reference value w ref (t) to improve the ASD’s ability to withstand voltage sags.

2. The method for improving ASD voltage tolerance based on improved control strategy according to claim 1, characterized in that: The specific steps of step 1 are: Step 1.1, by the speed reference value w ref (t) obtaining its differential signal v1; Step 1.2, according to the rotation speed w r (t) and the actual electromagnetic torque T of the induction motor e , obtaining a torque tracking signal z1 and a torque disturbance signal z2 based on the torque tracking signal z1, wherein the torque tracking signal z1 tracks the differential signal v1 to obtain an error signal e1; Step 1.3, obtaining an initial control variable u0 of the controller for the induction motor according to the error signal e1; Step 1.4, control the torque disturbance signal z2 to track the initial control variable u0, and obtain the final control variable u(t) of the controller by introducing the proportional factor 1 / b and the compensation factor a to calculate the reference electromagnetic torque T of the induction motor. e* .

3. The method for improving ASD voltage tolerance based on improved control strategy according to claim 2, characterized in that: The speed of the induction motor is w r (t) is: Where a is the compensation factor and z2 is estimated by the following formula: In the formula, c1 and c2 are nonlinear factors, and the adjustment rule of their values ​​is 0<c2<c1<1; δ is the filtering factor; α0 and α1 are adjustable parameters; and are the differentials of z1 and z2 respectively; fbl(e1,c,δ) is a nonlinear function, and its specific expression is as follows: c is a nonlinear factor, and α is an adjustable parameter; Calculate the reference electromagnetic torque T according to the output control signal u(t) e* : In the formula, K=1.

4. A device for improving ASD voltage tolerance capability based on an improved control strategy, the device being used to execute the method for improving ASD voltage tolerance capability based on an improved control strategy according to claim 1, characterized in that: include: Active disturbance rejection controller, based on the speed reference w of the induction motor ref (t) and speed w r (t), the reference electromagnetic torque T of the induction motor is obtained through the ADRC model e* , under different voltage conditions, the speed of the induction motor is w r (t) Maintain the speed reference value w ref (t); The model predictive controller is based on the current signal i in the two-phase rotating coordinate system d,q , voltage signal V d,q , the expected value of the flux linkage of the induction motor ψ(k+2) is calculated by the discrete model; The cost function calculator is configured to calculate the reference electromagnetic torque T. e* , the flux reference value ψ ref and the expected value ψ(k+2) of the flux linkage to calculate the voltage switching vector through the switching vector table, and obtain the voltage switching vector state that the ASD controller needs to output; a voltage switching vector calculator, which obtains a voltage switching vector according to the voltage switching vector state; The inverter controls the motor speed to be close to the speed reference value w based on the voltage switch vector ref (t).

5. The ASD voltage tolerance enhancement device based on improved control strategy according to claim 4, characterized in that: The active disturbance rejection controller comprises: The state tracker uses the speed reference value w ref (t) obtaining its differential signal v1; The extended state observer is based on the speed w r (t) and the actual electromagnetic torque T of the induction motor e , obtaining a torque tracking signal z1 and a torque disturbance signal z2 based on the torque tracking signal z1, wherein the torque tracking signal z1 tracks the differential signal v1 to obtain an error signal e1 as an output signal for judging whether the torque tracking signal z1 is tracking normally; An error controller, which obtains an initial control variable u0 of the controller for the induction motor according to the error signal e1; The extended state observer controls the torque disturbance signal z2 to track the initial control variable u0, and obtains the final control variable u(t) of the controller by introducing the proportional factor 1 / b and the compensation factor a to calculate the reference electromagnetic torque T of the induction motor. e* .

6. The ASD voltage tolerance enhancement device based on improved control strategy according to claim 4, characterized in that: The model predictive controller is connected to the induction motor through a coordinate converter and a flux observer. The coordinate converter converts the current signal i s And the voltage signal V s Transformed into the current signal i in the two-phase rotating coordinate system d,q And the voltage signal V d,q , and input it to the flux observer, and the actual motor flux value ψ(k) is obtained by calculation of the flux observer; the model prediction controller includes a current prediction controller and a flux prediction controller, and the current prediction controller is based on the current i at time k. d,q The magnitude and rate of change of current at time k The current prediction value id, q(k+1) is calculated and obtained. The current prediction value i d,q (k+1) and the voltage signal V in the two-phase rotating coordinate system d,q Obtain the expected value of magnetic flux ψ(k+2).

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