Stator flux linkage oriented induction motor model predictive current control method

Abstract

The invention provides a stator flux linkage oriented induction motor model predictive current control method, which comprises the following steps: acquiring a d-axis stator current feedback value and a q-axis stator current feedback value according to a stator flux linkage vector and a stator flux linkage orientation strategy of an induction motor; a d-axis stator current reference value and a q-axis stator current reference value are generated through a rotating speed controller and a flux linkage controller; sequentially substituting the plurality of candidate voltage vectors into the established discrete prediction model, obtaining a d-axis stator current prediction value and a q-axis stator current prediction value by combining the d-axis stator current feedback value and the q-axis stator current feedback value, and calculating a value function value corresponding to each candidate voltage vector by combining the d-axis stator current reference value and the q-axis stator current reference value; and selecting the candidate voltage vector with the minimum value function value as the optimal voltage vector to drive the induction motor to operate. According to the method, the flux linkage orientation precision can be improved, and the robustness of a control system facing parameter changes is enhanced.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, specifically to a model predictive current control method for an induction motor with stator flux orientation. Background Technology

[0002] Induction motors, with their advantages of simple structure, low cost, and high reliability, are the most widely used type of AC motor in industrial drive systems. As modern industry increasingly demands high dynamic performance, high-precision speed regulation, and wide-range operation, advanced control technology has gradually become the core means to improve the performance of induction motors. Among them, Model Predictive Control (MPC) has received widespread attention in the field of motor drives in recent years due to its fast response speed, ability to effectively handle multi-constraint systems, and direct optimization of voltage vector selection.

[0003] Among existing induction motor MPC methods, Rotor Flux Oriented Control (RFOC) is the most common approach. Its basic idea is to orient the rotor flux in a synchronous rotating coordinate system, decoupling the motor's flux from torque control through mathematical transformations, thereby simplifying the current loop control structure and accelerating transient response. However, this strategy relies on accurate estimation of the rotor flux, which requires multiple motor parameters, including rotor resistance and leakage inductance. The rotor resistance of an induction motor varies significantly with temperature, and magnetic saturation can cause flux drift, reducing the accuracy of the rotor flux estimation. Inaccurate flux orientation leads to reduced decoupling of the dq components, affecting the accuracy of the prediction model and the controller's optimal voltage vector determination, ultimately resulting in decreased control performance, increased torque ripple, and even system instability. Therefore, traditional RFOC-based Model Predictive Current Control (MPCC) methods suffer from significant parameter sensitivity and insufficient robustness.

[0004] In summary, the existing technology has the following problems: (1) The high sensitivity to rotor parameters makes it difficult to guarantee the magnetic flux orientation accuracy.

[0005] (2) The error in flux estimation will directly affect the correctness of the prediction model.

[0006] (3) Insufficient robustness, making it difficult to adapt to the motor operation requirements under complex working conditions. Summary of the Invention

[0007] The purpose of this invention is to provide a model predictive current control method for induction motors with stator flux orientation, so as to at least solve the above-mentioned problems.

[0008] An embodiment of the present invention provides a model predictive current control method for an induction motor with stator flux orientation, comprising: obtaining, based on the stator flux vector and stator flux orientation strategy of the induction motor, a predictive current control method for an induction motor. d Shaft stator current feedback value and q Shaft stator current feedback value; generated by the speed controller and flux controller based on preset stator flux reference value and speed reference value. d Shaft stator current reference value and q The stator current reference value is used; a discrete prediction model is established using the stator current as the state variable; multiple candidate voltage vectors are sequentially substituted into the discrete prediction model, combined with the... d Shaft stator current feedback value and the q The shaft stator current feedback value is used to predict the next control cycle. d Shaft stator current prediction value and q Shaft stator current prediction value; constructing a value function based on the aforementioned d Shaft stator current prediction value, the q Shaft stator current prediction value, the d Shaft stator current reference value and the above q The reference value of the shaft stator current is used to calculate the value function value corresponding to each candidate voltage vector; the candidate voltage vector with the smallest value function value is selected as the optimal voltage vector to drive the induction motor.

[0009] Optionally, the step of obtaining the stator flux vector and stator flux orientation strategy of the induction motor is described. d Shaft stator current feedback value and q The stator current feedback value includes: determining the stator flux vector of the induction motor based on the stator voltage and stator current of the induction motor; and using the direction of the stator flux vector as the synchronous rotating coordinate system. d The axis is oriented to obtain the... d Shaft stator current feedback value and the q Shaft stator current feedback value.

[0010] Optionally, establishing a discrete prediction model using stator current as the state variable includes: establishing a dynamic mathematical model using stator current as the state variable; and discretizing the dynamic mathematical model to obtain the discrete prediction model.

[0011] Optionally, the dynamic mathematical model is represented in vector form as follows:

[0012] in, ; ; ; ; ; ; ; ; ; ; ; ; This indicates the stator flux linkage.

[0013] Optionally, the discrete prediction model is expressed as:

[0014] in, The sampling period.

[0015] Optionally, the method further includes performing delay compensation on the discrete prediction model to obtain a compensated discrete prediction model, expressed as: .

[0016] Optionally, the value function is expressed as:

[0017] in, For stator current d Axial components, For stator current q Axial components.

[0018] The present invention uses stator flux linkage as the orientation reference. Because stator-side parameters (especially stator resistance) are more stable and their variation patterns are easier to identify, the accuracy of flux linkage orientation can be significantly improved. This improvement effectively reduces the sensitivity of the control system to changes in motor parameters, thereby enabling the model predictive current controller (MPCC) to exhibit stronger robustness under complex operating conditions. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the steps of the method of the present invention.

[0021] Figure 2 A block diagram of a predictive current control system for a traditional induction motor model.

[0022] Figure 3This is a block diagram of the predictive current control system for an induction motor model based on stator flux orientation, according to the present invention.

[0023] Figure 4 This is a schematic diagram showing the speed response waveforms of SFO-MPCC and RFO-MPCC under sudden load increases and decreases.

[0024] Figure 5 This is a schematic diagram comparing the rotational speed response performance when the flux linkage observer parameters are mismatched.

[0025] Figure 6 This is a schematic diagram comparing the current response performance when the flux linkage observer parameters are mismatched. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Traditional model predictive control (MDC) for induction motors typically employs a rotor field-oriented strategy. This approach decouples the control motor's flux linkage and torque, but its orientation accuracy is highly dependent on motor parameters, making the control system extremely sensitive to parameter changes. Therefore, to reduce this dependence on parameters, this invention proposes a stator field-oriented MDC strategy based on existing rotor field-oriented MDC methods. This method avoids using complex and variable rotor-side parameters in the flux linkage observation stage, thereby enhancing the robustness of the control system to parameter variations.

[0028] See Figure 1 The present invention provides a method for predictive current control of an induction motor model with stator flux orientation, comprising the following steps: Step S1: Based on the stator flux vector and stator flux orientation strategy of the induction motor, obtain... d Shaft stator current feedback value and q Shaft stator current feedback value; Step S2: Based on preset stator flux reference values ​​and speed reference values, generate a speed controller and flux controller. d Shaft stator current reference value and q Shaft stator current reference value; Step S3: Establish a discrete prediction model using stator current as the state variable; Step S4: Substitute multiple candidate voltage vectors sequentially into the discrete prediction model, and combine them with the... dShaft stator current feedback value and the q The shaft stator current feedback value is used to predict the next control cycle. d Shaft stator current prediction value and q Predicted values ​​of shaft stator current; Step S5: Construct the value function, based on the... d Shaft stator current prediction value, the q Shaft stator current prediction value, the d Shaft stator current reference value and the above q Based on the reference value of the shaft stator current, calculate the value function value corresponding to each candidate voltage vector; Step S6: Select the candidate voltage vector with the smallest value function value as the optimal voltage vector to drive the induction motor.

[0029] Optionally, the step of obtaining the stator flux vector and stator flux orientation strategy of the induction motor is described. d Shaft stator current feedback value and q The stator current feedback value includes: determining the stator flux vector of the induction motor based on the stator voltage and stator current of the induction motor; and using the direction of the stator flux vector as the synchronous rotating coordinate system. d The axis is oriented to obtain the... d Shaft stator current feedback value and the q Shaft stator current feedback value.

[0030] Optionally, establishing a discrete prediction model using stator current as the state variable includes: establishing a dynamic mathematical model using stator current as the state variable; and discretizing the dynamic mathematical model to obtain the discrete prediction model.

[0031] Optionally, the dynamic mathematical model is represented in vector form as follows:

[0032] in, ; ; ; ; ; ; ; ; ; ; ; ; This indicates the stator flux linkage.

[0033] Optionally, the discrete prediction model is expressed as:

[0034] in, The sampling period.

[0035] Optionally, the method further includes performing delay compensation on the discrete prediction model to obtain a compensated discrete prediction model, expressed as: .

[0036] Optionally, the value function is expressed as:

[0037] in, For stator current d Axial components, For stator current q Axial components.

[0038] Specifically, the solution of the present invention is further described with reference to the following examples: 1. Mathematical Model of Induction Motor The mathematical model of an induction motor in a three-phase coordinate system consists of flux linkage equations, voltage equations, and torque equations, which are further converted into a mathematical model in a two-phase rotating orthogonal coordinate system.

[0039] (1) Magnetic flux linkage equation (1) In the formula: and For stator flux d , q Axial components; and For rotor flux d , q Axial components; and For stator current d , q Axial components; and For rotor current d , q Axial components; L s , L r , L m These are stator inductance, rotor inductance, and mutual inductance.

[0040] (2) Voltage equation (2) In the formula: and For stator voltage d , q Axial components; and For rotor voltage d , q Axial components; and For stator current d , q Axial components; and For rotor current d , q Axial components; ω 1 represents the rotor's angular velocity.

[0041] (3) Torque equation (3) In the formula: n p It is an extreme logarithm.

[0042] 2. Induction Motor Model Predictive Current Control Traditional model predictive current control (MPCC) for induction motors is generally based on rotor field orientation (RFO) strategies, and its overall control structure is as follows: Figure 2 As shown in the diagram, in this framework, the outer loop of the MPCC consists of a speed regulation loop and a flux regulation loop. The system first uses a flux observer to estimate the rotor flux amplitude and rotor position information, and then uses this information to orient the rotor flux. Subsequently, the flux controller and speed controller generate reference values ​​for the excitation and torque components of the stator current, respectively. These reference currents, along with the actually acquired voltage and current signals, are input to the predictive current controller module. In this module, the future current is predicted using a motor model, and the optimal voltage space vector is selected from the candidate voltage vector set based on a cost function. Finally, this vector is applied to the induction motor through the inverter to achieve the desired electromagnetic state control. This control flow constitutes the typical operating mechanism of the existing RFO-MPCC.

[0043] With stator current as the state variable, the state equation of the induction motor in a two-phase rotating coordinate system can be expressed as: (4) In the formula: ψ r Indicates rotor flux linkage; σ is the leakage flux coefficient of the electric motor. ; T r The rotor electromagnetic time constant is For ease of analysis, equation (4) can be expressed in vector form: (5) In the formula: ; ; ; ; ; ; ; ; ; ; ; .

[0044] In order to obtain the predicted current at the next moment in the digital control system, equation (5) is discretized: (6) In the formula: The sampling period is This is the predicted value of the stator current. In actual digital control systems, due to the inherent one-step delay of the controller, the voltage vector selected at the current moment cannot be immediately applied to the inverter, but can only be updated in the next sampling cycle. Therefore, in the implementation of model predictive current control, this time delay effect needs to be compensated. After time delay compensation, the corrected discrete prediction model can be obtained, as shown in equation (7): (7) Based on the above discretization model, the predicted value of the stator current for the next sampling period can be calculated. In order to select the optimal vector from the candidate voltage vectors, a value function needs to be constructed to evaluate the control performance. Since the core objective of MPCC is to enable the actual current to track its reference value quickly and accurately, the deviation between the predicted current and the reference current is usually used as the evaluation index, and its mathematical form is given by equation (8): (8) When making control decisions, each basic voltage vector is substituted into the discrete prediction model one by one to obtain the corresponding current prediction results; then these predicted currents are substituted into the value function for calculation. Finally, the voltage vector that minimizes the value function is selected as the optimal control vector for that sampling period and is used to drive the inverter.

[0045] 3. Predictive Current Control of Induction Motor Based on Stator Magnetic Field Orientation When an induction motor is oriented according to stator field orientation (SFO), d The axis and the stator flux linkage vector are in the same direction, at this time With stator current as the state variable, its dynamic mathematical model can be represented in vector form as follows: (9) In the formula: ; ; ; ; ; ; ; ; ; ; ; ; This indicates the stator flux linkage.

[0046] The block diagram of the predictive current control system for an induction motor model based on stator flux orientation of this invention is shown below. Figure 3 As shown. After discretizing formula (9), the prediction model of the stator current under the SFO control strategy can be obtained as follows: (10) Considering one-beat delay compensation, the compensated prediction model can be expressed as: (11) The value function is chosen as follows: (12) The stator-field-oriented MPCC maintains the same overall control steps as the traditional rotor-field-oriented strategy: candidate voltage vectors are sequentially substituted into the prediction model to obtain the corresponding predicted stator current values; then, a value function is used to evaluate the prediction results, and the voltage vector with the minimum value function is selected as the optimal control vector. Its control flow structure is basically the same as the traditional MPCC; the main difference lies only in the field orientation method. Because stator-field-oriented and rotor-field-oriented methods use different mathematical models, there are differences in the prediction model construction stage; apart from the prediction model part, the rest of the control flow maintains the same logical framework.

[0047] 4. Analysis and Verification To verify the effectiveness of the model predictive current control method based on stator flux orientation proposed in this invention, a corresponding induction motor MPCC control model was constructed and tested. Figure 4 This study demonstrates a comparison of the dynamic speed response of the motor under two field-oriented control methods when subjected to sudden increases and decreases in rated load. To ensure the fairness of the comparison, the RFO-MPCC also employs a closed-loop flux linkage structure, and the parameter settings for both control methods are completely identical. Figure 4 As can be seen, the SFO-MPCC exhibits smaller overshoot during acceleration and smaller speed drop during sudden load changes, demonstrating superior dynamic performance.

[0048] Furthermore, the stator resistance and mutual inductance parameters used by the flux linkage observers in the SFO and RFO control systems were simultaneously amplified to twice their actual values ​​to test the parameter robustness of the two strategies. Figure 5 and Figure 6 The response waveforms for rotational speed and current are presented separately. The results show that when the mutual inductance parameters deviate significantly, the rotational speed fluctuation of the RFO-MPCC is significantly enhanced, exhibiting greater overshoot and slower convergence speed under load step disturbances; its dq-axis current also shows obvious oscillations, and the actual current is difficult to track the reference value. In contrast, although the SFO-MPCC is somewhat sensitive to changes in stator resistance, it can still maintain good control quality within a reasonable parameter deviation range. Furthermore, since the stator resistance parameter is relatively easy to obtain, the MPCC scheme based on stator flux orientation in this invention exhibits stronger robustness than the traditional RFO-MPCC under parameter uncertainty environments.

[0049] In summary, the present invention uses stator flux linkage as the orientation reference. Because stator-side parameters (especially stator resistance) have higher stability and their variation patterns are easier to identify, the accuracy of flux linkage orientation can be significantly improved. This improvement effectively reduces the sensitivity of the control system to changes in motor parameters, thereby enabling the model predictive current controller (MPCC) to exhibit stronger robustness under complex operating conditions.

[0050] It should be noted that the present invention has been verified by simulation and experimentation, and it is completely feasible and effective.

[0051] Specific embodiments of the invention have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0052] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the embodiments of the present invention, and are not intended to limit the embodiments of the present invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the embodiments of the present invention. Therefore, all equivalent technical solutions also fall within the scope of the embodiments of the present invention, and the patent protection scope of the embodiments of the present invention should be defined by the claims.

Claims

1. A method for predictive current control of an induction motor model with stator flux orientation, characterized in that, include: Based on the stator flux linkage vector and stator flux linkage orientation strategy of the induction motor, obtain d Shaft stator current feedback value and q Shaft stator current feedback value; Based on preset stator flux reference values ​​and speed reference values, the speed controller and flux controller generate... d Shaft stator current reference value and q Shaft stator current reference value; A discrete prediction model is established using stator current as the state variable; Substitute multiple candidate voltage vectors sequentially into the discrete prediction model, and combine them with the... d Shaft stator current feedback value and the q The shaft stator current feedback value is used to predict the next control cycle. d Shaft stator current prediction value and q Predicted values ​​of shaft stator current; Construct a value function, based on the stated d Shaft stator current prediction value, the q Shaft stator current prediction value, the d Shaft stator current reference value and the above q Based on the reference value of the shaft stator current, calculate the value function value corresponding to each candidate voltage vector; The candidate voltage vector with the smallest value function value is selected as the optimal voltage vector to drive the induction motor.

2. The method according to claim 1, characterized in that, The method for obtaining the stator flux linkage vector and stator flux linkage orientation strategy of the induction motor is described. d Shaft stator current feedback value and q Shaft stator current feedback values ​​include: The stator flux linkage vector of the induction motor is determined based on the stator voltage and stator current of the induction motor. Using the direction of the stator flux linkage vector as the synchronous rotating coordinate system d The axis is oriented to obtain the... d Shaft stator current feedback value and the q Shaft stator current feedback value.

3. The method according to claim 1, characterized in that, The establishment of a discrete prediction model using stator current as the state variable includes: Establish a dynamic mathematical model with stator current as the state variable; The dynamic mathematical model is discretized to obtain the discrete prediction model.

4. The method according to claim 3, characterized in that, The dynamic mathematical model is represented in vector form as follows: in, ; ; ; ; ; ; ; ; ; ; ; ; This indicates the stator flux linkage.

5. The method according to claim 4, characterized in that, The discrete prediction model is expressed as follows: in, The sampling period.

6. The method according to claim 5, characterized in that, It also includes performing delay compensation on the discrete prediction model to obtain a compensated discrete prediction model, expressed as: 。 7. The method according to claim 1, characterized in that, The value function is expressed as: in, For stator current d Axial components, For stator current q Axial components.

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