CN115494722A - Model reference self-adaption method and device, electronic equipment and storage medium - Google Patents
Model reference self-adaption method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a model reference self-adaptive method, a model reference self-adaptive device, electronic equipment and a storage medium. The method comprises the following steps: determining the phase of the power side winding voltage according to the phase-locked loop; determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system; transforming coordinates corresponding to control side winding current obtained by sampling in advance to a synchronous coordinate system to determine a reference model; determining a linearization error between the adjustable model and the reference model; determining PI parameters according to the linearization errors to obtain estimated rotation speed information, and determining estimated position information according to the estimated rotation speed information; and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner to control the brushless doubly-fed motor. The method reduces the use of the flux linkage observer, improves the error calculation method between the adjustable model and the reference model, improves the sensitivity to the angle difference in a larger range, and improves the practicability.
Description
Technical Field
The present application relates to the field of motor control technologies, and in particular, to a model reference adaptive method and apparatus, an electronic device, and a storage medium.
Background
In the related art, the calculation of the adjustable model in the model reference adaptive system is too complex, multiple flux linkage integrals and coordinate transformation are involved, and the error between the reference model and the adjustable model is calculated in the related art, and is insensitive to the large-range angle difference, so that the difficulty of PI design is increased. Furthermore, the related art requires the use of a flux linkage observer, the cut-off frequency of which is not easy to design. Therefore, the related art has the problems that the calculation is complex, the design parameters of the PI controller are difficult to determine, and the motor control is complex and the practicability is low.
Disclosure of Invention
In view of the above, an object of the present application is to provide a model reference adaptive method, apparatus, electronic device and storage medium.
In view of the above, in a first aspect, the present application provides a model reference adaptive method, comprising:
determining the phase of the power side winding voltage according to the phase-locked loop;
determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system;
transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model;
determining a linearization error between the adjustable model and the reference model;
determining PI parameters according to the linearization errors to obtain estimated rotating speed information, and determining estimated position information according to the estimated rotating speed information;
and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner so as to control the brushless doubly-fed motor.
In a possible implementation manner, the determining an adjustable model in a synchronous coordinate system according to the mathematical model of the brushless doubly-fed machine in the phase and synchronous coordinate system includes:
performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Representing the power side winding resistance, i 1 Representing the power side winding current, # 1 Representing the power side winding flux linkage vector, j representing the imaginary unit, ω 1 Representing grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, ω, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control-side winding voltage, R 2 Representing the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
in a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented by
Where dq denotes the d-axis and q-axis in the synchronous coordinate system.
In a possible implementation manner, the performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed machine further includes:
representing the rotor current using the power side winding voltage and the power side winding current; wherein the rotor current is represented by
Determining the estimated control side winding current under a synchronous coordinate system according to the mathematical model, the rotor flux linkage and the rotor current, and determining the estimated control side winding current as the adjustable model; the adjustable model is represented as
In one possible implementation, the linearization error is calculated by:
wherein the content of the first and second substances,
indicating a cross product and an as indicating a dot product.
In a possible implementation manner, the determining a PI parameter according to the linearization error to obtain estimated rotation speed information and determining estimated position information according to the estimated rotation speed information includes:
determining PI controller parameters to determine estimated rotational speed information based on the linearization error
The estimated rotating speed information is processed
Integrating to determine estimated location information
In a second aspect, the present application provides a model reference adaptation apparatus, comprising:
a first determination module configured to determine a phase of a power side winding voltage from a phase locked loop;
the second determination module is configured to determine an adjustable model in a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed machine in the synchronous coordinate system;
the third determination module is configured to transform coordinates corresponding to control side winding current acquired by sampling in advance to the synchronous coordinate system so as to determine a reference model;
a fourth determination module configured to determine a linearization error between the adjustable model and the reference model;
a fifth determining module configured to determine a PI parameter according to the linearization error to obtain estimated rotation speed information, and determine estimated position information according to the estimated rotation speed information;
and the control module is configured to feed back the estimated position information into coordinate transformation corresponding to the control side winding current in a closed loop mode so as to control the brushless doubly-fed motor.
In one possible implementation, the second determining module is further configured to:
performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Represents the power side winding resistance, i 1 Representing the power side winding current, # 1 Representing the power side winding flux linkage vector, j representing the imaginary unit, ω 1 Representing the grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, omega, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control-side winding voltage, R 2 Represents the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
in a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented as
Where dq denotes the d-axis and q-axis in the synchronous coordinate system.
In one possible implementation, the fifth determining module is further configured to:
determining PI controller parameters from the linearization error to determine estimated speed information
The estimated rotating speed information is obtained
Integrating to determine estimated location information
In a third aspect, the application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the model reference adaptation method according to the first aspect when executing the program.
In a fourth aspect, the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the model reference adaptation method of the first aspect.
As can be seen from the foregoing, the present application provides a model reference adaptive method, apparatus, electronic device, and storage medium for determining a phase of a power side winding voltage according to a phase-locked loop; determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system; transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model; determining a linearization error between the adjustable model and the reference model; determining PI parameters according to the linearization errors to obtain estimated rotating speed information, and determining estimated position information according to the estimated rotating speed information; and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner so as to control the brushless doubly-fed motor. The adjustable model and the reference model are converted into a synchronous coordinate system, a dynamic process is omitted, the use of a flux linkage observer is reduced, the whole control method is simpler, the calculation method of the error between the adjustable model and the reference model is improved, the linear error between the adjustable model and the reference model is calculated, the sensitivity to the angle difference in a large range is improved, the parameter design of the PI controller is simplified, the calculated amount of the whole motor control method is reduced, simplicity and convenience are realized, and the practicability is improved.
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In order to more clearly illustrate the technical solutions in the present application or the related art, the drawings needed to be used in the description of the embodiments or the related art will be briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 shows an exemplary structural schematic diagram of a brushless doubly-fed motor speed regulation control system provided by an embodiment of the application.
Fig. 2 illustrates an exemplary flowchart of a model reference adaptive method provided in an embodiment of the present application.
Fig. 3 shows a schematic view of a motor control architecture framework according to an embodiment of the present application.
FIG. 4 shows a graph of steady state experimental results for robust predictive control at 350rpm in accordance with an embodiment of the present application.
FIG. 5 shows a graph of steady state experimental results for robust predictive control at 600rpm according to an embodiment of the present application.
FIG. 6 is a graph illustrating experimental results of steady state estimation error at 350rpm for robust predictive control in accordance with an embodiment of the present application.
FIG. 7 is a graph illustrating experimental results of steady state estimation error at 580rpm for robust predictive control in accordance with an embodiment of the present application.
FIG. 8 illustrates experimental waveforms for robust predictive control under control side winding mutual inductance variation in a controller according to embodiments of the application.
FIG. 9 is a graph illustrating experimental estimation error experimental results under control side winding mutual inductance variation in a controller according to an embodiment of the application.
FIG. 10 is a graph illustrating experimental results of a simulation waveform under actual control side winding mutual inductance variation according to an embodiment of the application.
FIG. 11 is a diagram illustrating experimental results of simulated estimation error under actual control side winding mutual inductance variation according to an embodiment of the application.
Fig. 12 shows a graph of dynamic experimental results of robust predictive control at power step according to an embodiment of the application.
Fig. 13 is a diagram illustrating experimental results of a dynamic estimation error under a power step for robust predictive control according to an embodiment of the application.
Fig. 14 shows a graph of experimental results of dynamic experiments under a change of a rotation speed for robust predictive control according to an embodiment of the present application.
FIG. 15 illustrates dynamic estimation errors under speed change for robust predictive control in an embodiment in accordance with the application.
Fig. 16 shows an exemplary structural diagram of a model reference adaptive device provided in an embodiment of the present application.
Fig. 17 shows an exemplary structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings in combination with specific embodiments.
It should be noted that technical terms or scientific terms used in the embodiments of the present application should have a general meaning as understood by those having ordinary skill in the art to which the present application belongs, unless otherwise defined. The use of "first," "second," and similar terms in the embodiments of the present application do not denote any order, quantity, or importance, but rather the terms are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
As described in the background section, in the related art, a model reference adaptive system obtains the rotation speed and the position by constructing a reference model (without position information) and an adjustable model (with position information) for observing the same variable and then by using an adaptive law, and the model reference adaptive system has a simple principle and an accurate structure and is widely researched and applied to a transmission system. But the adjustable model of the traditional method is too complex to calculate, and a plurality of flux linkage integrals and coordinate transformation are involved. The error between the reference model and the adjustable model is calculated by using a traditional method, and the error is insensitive to a large range of angle difference, so that the difficulty of PI design is increased. Moreover, the traditional method needs to use a flux linkage observer, and the cut-off frequency of the flux linkage observer is not easy to design.
The inventor finds that, in a related art, in order to reduce the use of a flux linkage observer, a brushless double-feeder model reference adaptive method without the flux linkage observer is proposed, but a certain error exists in position estimation. In another related art, the design of PI is simplified according to the error of linearization. However, these methods do not simplify the calculation of the adjustable model and are relatively complex.
That is, the related art cannot satisfy both: 1) The adjustable model is easy to calculate; 2) The error is sensitive to a large range of angular differences; 3) The PI controller is simple in design; 4) The use of a flux linkage observer is reduced.
As such, the present application provides a model reference adaptive method, apparatus, electronic device, and storage medium, which determine a phase of a power side winding voltage according to a phase-locked loop; determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system; transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model; determining a linearization error between the adjustable model and the reference model; determining PI parameters according to the linearization errors to obtain estimated rotating speed information, and determining estimated position information according to the estimated rotating speed information; and feeding back the estimated position information to the coordinate transformation corresponding to the control side winding current in a closed loop manner so as to control the brushless doubly-fed motor. The adjustable model and the reference model are converted into a synchronous coordinate system, a dynamic process is omitted, the use of a flux linkage observer is reduced, the whole control method is simpler, the calculation method of the error between the adjustable model and the reference model is improved, the linear error between the adjustable model and the reference model is calculated, the sensitivity to the angle difference in a large range is improved, the parameter design of the PI controller is simplified, the calculated amount of the whole motor control method is reduced, simplicity and convenience are realized, and the practicability is improved.
The model reference adaptive method provided by the embodiments of the present application is specifically described below by specific embodiments.
Fig. 1 shows an exemplary structural schematic diagram of a brushless doubly-fed motor speed regulation control system provided in an embodiment of the present application.
Referring to fig. 1, fig. 1 is a hardware circuit structure diagram of the present invention, which includes a three-phase voltage source, a brushless double-fed motor, a three-phase two-level inverter, a dc-side capacitor, a voltage and current sampling circuit, a dSPACE real-time simulation system, and a driving circuit. The voltage and current sampling circuit respectively collects three-phase voltages of a direct current side, a power side a, a power side b and a power side c, three-phase voltages of a control side a, a power side b and a power side c, two-phase currents of the power side a and the power side b and two-phase currents of the control side a and the power side b by using the voltage Hall sensor and the current Hall sensor, and sampling signals enter the dSPACE real-time simulation system after passing through the signal conditioning circuit and are converted into digital signals. The dSPACE real-time simulation system finishes the operation of the method provided by the invention, outputs six switching pulses, and then obtains final driving signals of six switching tubes of the inverter after passing through the driving circuit.
Fig. 2 illustrates an exemplary flowchart of a model reference adaptive method provided in an embodiment of the present application.
Referring to fig. 2, a model reference adaptive method provided in the embodiment of the present application specifically includes the following steps:
s202: the phase of the power side winding voltage is determined from the phase locked loop.
S204: and determining an adjustable model under the synchronous coordinate system according to the phase and the mathematical model of the brushless doubly-fed motor under the synchronous coordinate system.
S206: and transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model.
S208: a linearization error between the adjustable model and the reference model is determined.
S210: and determining a PI parameter according to the linearization error to obtain estimated rotation speed information, and determining estimated position information according to the estimated rotation speed information.
S212: and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner so as to control the brushless doubly-fed motor.
Fig. 3 shows a schematic view of a motor control architecture framework according to an embodiment of the present application.
Referring to fig. 2 and fig. 3, a coordinate transformation can be performed on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Representing the power side winding resistance, i 1 Representing the power side winding current, # 1 Denotes the power side winding flux linkage vector, j denotes the imaginary unit, ω 1 Representing the grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, omega, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control-side winding voltage, R 2 Representing the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
to simplify the tunable model, the dynamic process can be omitted. In a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented by
Where dq denotes the d-axis and q-axis in the synchronous coordinate system.
Since the denominator of the above equation is large, it can be considered that the rotor flux linkage is approximately equal to 0. Similarly, rotor currenti rdq The power side winding voltage u can be used 1dq And current i 1dq Represents:
obtaining the estimated control side winding current in the synchronous coordinate system from the mathematical model of the brushless doubly-fed motor in the synchronous coordinate system and the two formulas
Namely the adjustable model:
in some embodiments, based on the tunable model and the reference model, a linearization error ξ between the two may be calculated as follows:
wherein the content of the first and second substances,
indicating a cross product, an indication a dot product.
In some embodiments, the PI controller parameters are designed to obtain an estimated rotation speed according to the obtained linearization error xi
Integrating the estimated rotation speed to obtain estimated position information
Closed-loop feedback of estimated position information to sampled control side winding current i 2 In the coordinate transformation of (2).
The effectiveness of the method provided by the application can be obtained through simulation and experimental results. All simulations and experiments have closed-loop substitution of estimated position and rotational speed into robust predictive control based on an extended state observer.
FIG. 4 shows a graph of steady state experimental results for robust predictive control at 350rpm in accordance with an embodiment of the present application.
FIG. 5 shows a graph of steady state experimental results for robust predictive control at 600rpm according to an embodiment of the present application.
Referring to fig. 4 and 5, the active power reference value is-350W and the reactive power reference value is 0Var. The waveforms are active power, reactive power, power side three-phase current and control side three-phase current from top to bottom in sequence. From the comparison between fig. 3 and fig. 4, it can be found that the real active power value and the real reactive power value of the two methods can track the reference value, the fluctuation is small, and the good control effect can be obtained under different rotating speeds.
FIG. 6 is a graph illustrating experimental results of steady state estimation error at 350rpm for robust predictive control in accordance with an embodiment of the present application.
FIG. 7 is a graph illustrating experimental results of steady state estimation error at 580rpm for robust predictive control in accordance with an embodiment of the present application.
Referring to fig. 6 and 7, the waveforms from top to bottom are rotor speed, rotor position, estimated speed error, and estimated position error, respectively. From a comparison of fig. 5 and fig. 6, it can be seen that there is a periodic fluctuation in the rotation speed and position of the two methods, and the frequency of occurrence of the pulsation is related to the rotation speed, and when the rotation speed is 350rpm, the observed pulsation occurs approximately every 0.17s (60/350); when the rotation speed is 600rpm, the interval time is 0.1s.
FIG. 8 illustrates experimental waveforms for robust predictive control under control side winding mutual inductance variation in a controller according to embodiments of the application.
Fig. 9 is a diagram showing experimental estimation error experimental results of robust predictive control under control of side winding mutual inductance variation in a controller according to an embodiment of the application.
FIG. 10 is a graph illustrating experimental results of a simulation waveform under actual control side winding mutual inductance variation according to an embodiment of the application.
FIG. 11 is a diagram illustrating experimental results of simulated estimation error under actual control side winding mutual inductance variation according to an embodiment of the application.
In order to verify the parameter robustness of the optimization model reference adaptive method based on the control side winding current, fig. 8, 9, 10 and 11 show the experimental and simulation results of changing the control side winding mutual inductance parameter, respectively. In fig. 8, 9, the motor parameters in the controller are periodically stepped. Fig. 9 shows that at the instant of parameter change, the estimated rotation speed and the position are stepped to some extent, but the estimated rotation speed can converge quickly, and the magnitude of the position step is relatively small, and it can also be seen from fig. 8 that the parameter change has little influence on the control effect. As can be seen from fig. 10, when the actual motor parameters are changed in the simulation, the system operating state changes, requiring a period of time to re-stabilize. As can be seen from fig. 11, the stabilized power can accurately track the reference value and the rotation speed estimation is accurate. Therefore, the robust prediction control based on the optimization model reference adaptive method still has strong parameter robustness.
Fig. 12 shows a graph of dynamic experimental results of robust predictive control at power step according to an embodiment of the application.
Fig. 13 shows a graph of experimental results of dynamic estimation error at power step for robust predictive control in an embodiment according to the application.
Referring to fig. 13, it can be seen from the observed errors that the rotational speed has a large error at the instant of the power step, and the position observation error becomes about 0.1rad. Over time, the observed rotational speed quickly converges to the actual value, while the position error remains at approximately 0.1rad. As can be seen from fig. 12, the response time of the power step becomes slow due to the time required for convergence, but eventually the power reference value can be stably tracked.
Fig. 14 shows a graph of experimental results of dynamic experiments under a change of a rotation speed for robust predictive control according to an embodiment of the present application.
FIG. 15 illustrates dynamic estimation errors under speed change for robust predictive control in an embodiment in accordance with the application.
Referring to fig. 14 and 15, it can be seen from fig. 14 and 15 that, for the rotation speed change, the observation convergence speed is faster than the rotation speed change speed, and the power tracking effect is still good. However, in the non-position control method based on the rotating speed observer, large periodic pulsation still occurs in the estimated rotating speed.
From the foregoing, it can be seen that a model reference adaptive method, apparatus, electronic device, and storage medium are provided for determining a phase of a winding voltage on a power side according to a phase-locked loop; determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system; transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model; determining a linearization error between the adjustable model and the reference model; determining PI parameters according to the linearization errors to obtain estimated rotating speed information, and determining estimated position information according to the estimated rotating speed information; and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner so as to control the brushless doubly-fed motor. The adjustable model and the reference model are converted into a synchronous coordinate system, a dynamic process is omitted, the use of a flux linkage observer is reduced, the whole control method is simpler, the calculation method of the error between the adjustable model and the reference model is improved, the linear error between the adjustable model and the reference model is calculated, the sensitivity to the angle difference in a large range is improved, the parameter design of the PI controller is simplified, the calculated amount of the whole motor control method is reduced, simplicity and convenience are realized, and the practicability is improved.
It should be noted that the method of the embodiment of the present application may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment, and the multiple devices interact with each other to complete the method.
It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 16 shows an exemplary structural diagram of a model reference adaptive device provided in an embodiment of the present application.
Based on the same inventive concept, corresponding to the method of any embodiment, the application also provides a model reference self-adaptive device.
Referring to fig. 16, the model reference adaptive apparatus includes: the device comprises a first determination module, a second determination module, a third determination module, a fourth determination module, a fifth determination module and a control module; wherein the content of the first and second substances,
a first determination module configured to determine a phase of a power side winding voltage from a phase locked loop;
the second determination module is configured to determine an adjustable model in a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed machine in the synchronous coordinate system;
the third determination module is configured to transform coordinates corresponding to control side winding current acquired by sampling in advance to the synchronous coordinate system so as to determine a reference model;
a fourth determination module configured to determine a linearization error between the adjustable model and the reference model;
a fifth determining module configured to determine a PI parameter according to the linearization error to obtain estimated rotation speed information, and determine estimated position information according to the estimated rotation speed information;
and the control module is configured to feed back the estimated position information into coordinate transformation corresponding to the control side winding current in a closed loop mode so as to control the brushless doubly-fed motor.
In one possible implementation, the second determining module is further configured to:
performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Representing the power side winding resistance, i 1 Representing the power side winding current, # 1 Denotes the power side winding flux linkage vector, j denotes the imaginary unit, ω 1 Representing the grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, omega, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control-side winding voltage, R 2 Representing the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
in a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented by
Wherein dq denotes a d axis and a q axis in a synchronous coordinate system.
In one possible implementation, the second determining module is further configured to:
representing the rotor current using the power side winding voltage and the power side winding current; wherein the rotor current is represented by
Determining the estimated control side winding current under a synchronous coordinate system according to the mathematical model, the rotor flux linkage and the rotor current, and determining the estimated control side winding current as the adjustable model; the adjustable model is represented as
In one possible implementation, the linearization error is calculated by:
wherein the content of the first and second substances,
indicating a cross product, an indication a dot product.
In one possible implementation, the fifth determining module is further configured to:
determining PI controller parameters from the linearization error to determine estimated speed information
The estimated rotating speed information is obtained
Integrating to determine estimated location information
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more pieces of software and/or hardware in the practice of the present application.
The apparatus of the foregoing embodiment is used to implement the corresponding model reference adaptive method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Fig. 17 shows an exemplary structural diagram of an electronic device provided in an embodiment of the present application.
Based on the same inventive concept, corresponding to any of the above embodiments, the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the model reference adaptive method described in any of the above embodiments is implemented. Fig. 17 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1710, a memory 1720, an input/output interface 1730, a communication interface 1740, and a bus 1750. Wherein the processor 1710, memory 1720, input/output interface 1730, and communication interface 1740 enable communication connections within the device to each other via a bus 1750.
The processor 1710 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1720 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1720 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1720 and called for execution by the processor 1710.
The input/output interface 1730 is used for connecting input/output modules to input and output information. The input/output module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The bus 1750 includes a path to transfer information between various components of the device, such as the processor 1710, the memory 1720, the input/output interface 1730, and the communication interface 1740.
It is to be appreciated that while the above-described device illustrates only the processor 1710, the memory 1720, the input/output interface 1730, the communication interface 1740, and the bus 1750, in particular implementations, the device may include other components necessary for proper operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
The electronic device of the foregoing embodiment is used to implement the corresponding model reference adaptive method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to any of the above-described embodiment methods, the present application further provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the model reference adaptation method according to any of the above embodiments.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The computer instructions stored in the storage medium of the foregoing embodiment are used to enable the computer to execute the model reference adaptive method according to any one of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the context of the present application, technical features in the above embodiments or in different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures for simplicity of illustration and discussion, and so as not to obscure the embodiments of the application. Furthermore, devices may be shown in block diagram form in order to avoid obscuring embodiments of the application, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the application are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the application, it should be apparent to one skilled in the art that the embodiments of the application can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present application has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures, such as Dynamic RAM (DRAM), may use the discussed embodiments.
The present embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalents, improvements, and the like that may be made without departing from the spirit or scope of the embodiments of the present application are intended to be included within the scope of the claims.
Claims (10)
1. A model reference adaptive method is applied to a brushless doubly-fed motor and comprises the following steps:
determining the phase of the power side winding voltage according to the phase-locked loop;
determining an adjustable model under a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed motor under the synchronous coordinate system;
transforming coordinates corresponding to control side winding current acquired by pre-sampling to the synchronous coordinate system to determine a reference model;
determining a linearization error between the adjustable model and the reference model;
determining PI parameters according to the linearization errors to obtain estimated rotating speed information, and determining estimated position information according to the estimated rotating speed information;
and feeding back the estimated position information to coordinate transformation corresponding to the winding current of the control side in a closed loop manner so as to control the brushless doubly-fed motor.
2. The method according to claim 1, wherein the determining the adjustable model in the synchronous coordinate system according to the mathematical model of the brushless doubly fed machine in the phase and synchronous coordinate system comprises:
performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Representing the power side winding resistance, i 1 Representing the power side winding current, # 1 Representing the power side winding flux linkage vector, j representing the imaginary unit, ω 1 Representing grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, ω, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control-side winding voltage, R 2 Representing the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
in a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented by
Where dq denotes the d-axis and q-axis in the synchronous coordinate system.
3. The method according to claim 2, wherein the coordinate transformation is performed on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed machine, and then further comprising:
representing the rotor current with a power side winding voltage and a power side winding current; wherein the rotor current is represented by
Determining the estimated control side winding current under a synchronous coordinate system according to the mathematical model, the rotor flux linkage and the rotor current, and determining the estimated control side winding current as the adjustable model; the adjustable model is represented as
4. The method of claim 3, wherein the linearization error is calculated by:
wherein the content of the first and second substances,
indicating a cross product, an indication a dot product.
5. The method of claim 1, wherein determining the PI parameter from the linearization error to obtain estimated speed information and determining the estimated position information from the estimated speed information comprises:
determining PI controller parameters from the linearization error to determine estimated speed information
The estimated rotating speed information is obtained
Integrating to determine estimated location information
6. A model reference adaptation apparatus, comprising:
a first determination module configured to determine a phase of a power side winding voltage from a phase locked loop;
the second determination module is configured to determine an adjustable model in a synchronous coordinate system according to the phase and a mathematical model of the brushless doubly-fed machine in the synchronous coordinate system;
the third determination module is configured to transform coordinates corresponding to control side winding current acquired by sampling in advance to the synchronous coordinate system so as to determine a reference model;
a fourth determination module configured to determine a linearization error between the adjustable model and the reference model;
a fifth determining module configured to determine a PI parameter according to the linearization error to obtain estimated rotation speed information, and determine estimated position information according to the estimated rotation speed information;
and the control module is configured to feed back the estimated position information into coordinate transformation corresponding to the control side winding current in a closed loop mode so as to control the brushless doubly-fed motor.
7. The apparatus of claim 6, wherein the second determining module is further configured to:
performing coordinate transformation on the synchronous coordinate system according to the phase to determine a mathematical model of the brushless doubly-fed motor; wherein the mathematical model is represented as
Wherein u is 1 Representing the power side winding voltage, R 1 Representing the power side winding resistance, i 1 Representing the power side winding current, # 1 Representing the power side winding flux linkage vector, j representing the imaginary unit, ω 1 Representing the grid voltage angular velocity, R r Representing the rotor winding resistance, i r Representing rotor current, # r Representing the rotor flux linkage vector, t representing the differential time, p 1 Representing the number of pole pairs, omega, of the power side winding m Representing the mechanical angular speed, u, of the rotor 2 Representing the control side winding voltage, R 2 Representing the control side winding resistance, i 2 Indicating the control side winding current, # 2 Representing the control-side winding flux linkage vector, p 2 Represents the number of pole pairs, L, of the control side winding 1 Representing the power side winding inductance, L m1 Representing power side winding mutual inductance, L r Representing rotor winding inductance, L m2 Indicating control side winding mutual inductance, L 2 Representing the control side winding inductance;
in a steady state, representing the rotor flux linkage in the mathematical model under a synchronous coordinate system by using rotor current to determine an adjustable model; wherein the rotor flux linkage is represented by
Where dq denotes the d-axis and q-axis in the synchronous coordinate system.
8. The method of claim 6, wherein the fifth determination module is further configured to:
determining PI controller parameters from the linearization error to determine estimated speed information
The estimated rotating speed information is obtained
Integrating to determine estimated location information
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 5 when executing the program.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to implement the method of any one of claims 1 to 5.
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