CN117792197A - Full-speed-domain permanent magnet synchronous motor sensorless control method and system - Google Patents
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Abstract
The application provides a full-speed-domain permanent magnet synchronous motor sensorless control method and a full-speed-domain permanent magnet synchronous motor sensorless control system, wherein the position angle and the rotating speed of a motor are extracted through an extended Kalman filtering algorithm when the motor runs at a high speed; and secondly, when the motor runs at a low speed, extracting a two-phase high-frequency current envelope curve through square wave injection, and extracting the position angle and the rotating speed of the motor by using a phase-locked loop method. Then, a linear transition algorithm is utilized to finish the stable switching from zero low-speed operation to medium-high-speed operation; at medium and high speed, compared with the traditional sliding mode observer, the dynamic response is fast and the estimation precision is good through the extended Kalman filtering algorithm. At low speed, square wave injection is used, compared with sine wave injection, a filter is omitted, and the bandwidth of the system is improved. The linear weighted switching transition algorithm performs full-speed domain coverage on zero speed, low speed, medium speed and high speed, and compared with the traditional hysteresis switching transition strategy, the switching process is stable.
Description
Technical Field
The invention belongs to the field of motor control, and particularly relates to a full-speed-domain permanent magnet synchronous motor sensorless control method and system.
Background
Permanent magnet synchronous motors are an important technical advance in the field of motors. Unlike induction motors, permanent magnet synchronous motors have high power, power density, and fine control capabilities due to their unique design. Along with the continuous progress of the control method, particularly the sensorless control technology, the versatility and the efficiency of the permanent magnet synchronous motor are greatly improved. The sensorless control method for detecting the rotor position without an additional sensor improves the reliability of the motor and reduces the complexity and cost of the system. The continued evolution of sensorless control methods plays a critical role in the operating range of permanent magnet synchronous motors, especially in the full speed range. This evolution is critical to achieving precise control at various speeds for optimal performance and energy efficiency.
Existing position-free sensors are mainly divided into two categories: one is a back emf-based estimation method suitable for high-speed operation in an electric machine. Such as the extended kalman filter method, is a prominent technique for accurate position estimation. The EKF (Extended Kalman Filter ) algorithm combines a mathematical model of motor dynamics with measurements from available sensors (e.g., voltage and current sensors) to estimate rotor position and speed. The method is highly adaptable and can handle system uncertainty, so that the method is very suitable for medium-high speed applications, wherein accurate position detection is crucial for optimizing motor performance. At low speeds, the performance of extended kalman filtering decreases due to increased sensitivity to measurement noise. The accuracy of the estimated position is severely dependent on accurate sensor measurements. At low speeds, the back emf is difficult to estimate due to the weak sensor signal, and the filter's effect on accurately estimating rotor position is reduced, possibly resulting in position detection errors. And the other type is a high-frequency signal injection method suitable for the motor under the static or low-speed running state, and the high-frequency voltage signal is injected into the motor winding under the low-speed or static state. The high frequency signals will induce back emf in the motor windings, which is related to rotor position and can provide critical position information. By detecting and analyzing the back emf response generated by the high frequency injection signal, the position of the rotor can be inferred. This method enables accurate estimation of rotor position at low speed or in a stopped state even in the absence of conventional sensor signals. However, when the speed is too high, the counter electromotive force generated by the rotation of the motor affects the estimation accuracy of the high-frequency injection method. In order to realize the motor sensorless control of the full-speed domain, two algorithms are usually combined, and a hysteresis switching method is adopted to switch the estimated position and the speed in a transition zone, but the method can generate larger speed fluctuation in the switching process to influence the control performance. Therefore, a weighted switching method is adopted to make the low speed and the medium speed smoothly switched. In addition, the traditional position-free sensor estimation method also limits the quick response capability because of the slow convergence speed, and is unfavorable for a scene requiring quick change, so that the traditional sliding mode position detector is replaced by an extended Kalman filtering algorithm.
Therefore, a new full-speed-domain permanent magnet synchronous motor sensorless control scheme is needed.
Disclosure of Invention
The invention aims to provide a full-speed-domain permanent magnet synchronous motor sensorless control method and a full-speed-domain permanent magnet synchronous motor sensorless control system, wherein the method has good dynamic performance, high detection precision, good anti-interference performance and stronger noise resistance.
The invention discloses a full-speed-domain permanent magnet synchronous motor sensorless control method, which comprises the following steps:
(1) And estimating the rotor position of the motor during operation at medium and high speeds by an extended Kalman filtering method.
(2) The method of square wave injection is used at low speed to extract the envelope curve of the high-frequency current derivative of the motor at zero speed and low speed and the rotor position is estimated by using the phase-locked loop technology.
(3) And stably transiting the position detection algorithm at the middle and high speeds and the low speed by a linear weighted switching method.
Further, the step (1) includes the steps of
(11) Establishing a mathematical model of a motor under a two-phase rotation coordinate system
Rewritten as a current equation
Wherein U is d 、U q And I d 、I q Stator voltage and stator current in two-phase d-q rotation coordinate system, R is stator phase resistance, L d 、L q Is the stator axial phase inductance omega e Is the rotor electrical angle, ψ f Is the rotor flux linkage.
(12) Establishing a medium-high speed extended Kalman filter observer
Wherein,representing the state prediction value at time k +.>Representing the state predicted value at time K-1, B representing the input matrix, u (K-1) representing the known external control quantity, P (k|k-1) representing the predicted error covariance matrix at time K, P (K-1|k-1) representing the estimated covariance matrix at time K-1, Q representing the process noise covariance, K (k|k-1) representing the Kalman gain at time K, Y k Represents the k moment measurement value, R represents the covariance of the k moment measurement noise, P (k|k) represents the error covariance matrix of the k moment estimation, +.>The state estimation value at time k is shown.
Further, the implementation process of the step (2) is as follows:
when the motor is at a low speed, neglecting the resistance of a motor stator and counter electromotive force, and establishing a motor high-frequency signal model:
wherein U is dh 、U qh High-frequency voltages respectively representing d and q axes of the motor; i.e dh 、i qh Represents d, q-axis high-frequency current;
the square wave signal injected under the estimated rotor rotation coordinate system can be expressed as:
wherein V is h Is the amplitude of the injected square wave voltage.
Mathematical model of excited high-frequency current in stationary alpha beta coordinate system:
transforming the estimated dq axis by coordinates to the actual dq axis:
the mathematical expression of the high-frequency current substituted into the actual shaft dq is as follows:
the above expression is rewritten as follows, using the differential instead of the differential:
finally, when the estimated angle theta' is equal to the real angle theta by using a Phase-locked loop (PLL), the output angle is a real value.
err＝sinθcosθ′-cosθsinθ′＝sin(θ-θ′)＝0
Further, the implementation process of the step (3) is as follows:
wherein,the electric angle estimated value and the speed estimated value are respectively obtained after the fusion of the low-speed estimation algorithm and the medium-speed estimation algorithm; />v L 、v H The electric angle and the speed under the low-speed estimation algorithm and the medium-speed estimation algorithm are respectively calculated; λ is the weighting coefficient.
Based on the above inventive concept, a full-speed-domain permanent magnet synchronous motor sensorless control method and system are provided herein, comprising: the device comprises a speed loop PI controller, a d-axis current loop PI controller, a q-axis current loop PI controller, an inverse park transformation module, a space vector pulse width modulation SVPWM module, a three-phase inverter, a three-phase permanent magnet synchronous motor, a three-phase current acquisition module, a park transformation module, a two-phase static current signal extraction and rotor angle estimation module, a park transformation module, a square wave injection module, an extended Kalman position estimation module and a weighted switching module. The extended Kalman position estimation module is realized by a microcontroller algorithm, a state observer is constructed according to the input voltage and current, and the angle of the rotor is calculated. The square wave injection module is realized by a microcontroller algorithm, extracts the output high-frequency current signal, extracts the electrical angle in the high-frequency current by using a phase-locked loop, and calculates the angle of the rotor. And the weighted switching module completes smooth switching of the speed at low speed and medium and high speed.
The beneficial effects are that: compared with other high-frequency injection methods, the method using square wave injection reduces the use of a filter, improves the bandwidth and accelerates the response speed. The use of phase-locked loop techniques can provide highly accurate position estimates. By monitoring the phase change of the motor, the accurate tracking of the rotor position is realized, and compared with other methods, the method has higher measurement accuracy. Compared with a sliding mode position observer, the extended Kalman filter can better inhibit measurement noise, can provide more accurate state estimation, and can effectively process noise and uncertainty in a system, so that the stability and consistency of estimation are maintained, and the estimation of the rotor position is more accurate. The motor operates more smoothly in the full speed domain using a weighted switching method than a hysteresis switching method.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a full-speed domain permanent magnet synchronous motor sensorless control system;
FIG. 2 is a schematic diagram of a square wave injection position estimator;
fig. 3 is a schematic diagram of an extended kalman filter position estimator.
Detailed Description
Embodiments of the present application are described in detail below with reference to the accompanying drawings.
Other advantages and effects of the present application will become apparent to those skilled in the art from the present disclosure, when the following description of the embodiments is taken in conjunction with the accompanying drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. The present application may be embodied or carried out in other specific embodiments, and the details of the present application may be modified or changed from various points of view and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It is noted that various aspects of the embodiments are described below within the scope of the following claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present application, one skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, apparatus may be implemented and/or methods practiced using any number and aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should also be noted that the illustrations provided in the following embodiments merely illustrate the basic concepts of the application by way of illustration, and only the components related to the application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided in order to provide a thorough understanding of the examples. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details.
The invention is described in further detail below with reference to the accompanying drawings.
The invention provides a full-speed-domain permanent magnet synchronous motor sensorless control system, as shown in fig. 1, comprising: the device comprises a speed loop controller, a d-axis current loop controller, a q-axis current loop controller, an inverse park transformation module, a space vector pulse modulation (SVPWM) module, a three-phase inverter, a three-phase permanent magnet synchronous motor, a current sampling module, a clamp transformation module, a park transformation module, an extended Kalman filter, a square wave injection module and a linear weighting switching module. The speed loop controller is realized by a microcontroller algorithm, and the main function is to give a q-axis current command value according to the current speed error. The q-axis current loop controller is realized by a microcontroller algorithm, and the main function is to give a q-axis voltage command according to the current q-axis current error; the d-axis current loop controller is realized by a microcontroller algorithm, and has the main function of giving a d-axis voltage command according to the current d-axis current error; the inverse park transformation module is realized by a microcontroller algorithm, and has the main function of transforming the rotation voltage under the synchronous coordinate system of the rotor to a stationary two-phase coordinate system; the Space Vector Pulse Width Modulation (SVPWM) module is realized by a microcontroller algorithm, and has the main functions of generating six paths of pulse width modulation (pwm) signals through voltage commands under a given static two-phase coordinate system; the three-phase inverter can be realized through a driving chip and an NMOS tube, and has the main function of completing three-phase voltage control according to a modulation signal output by the SVPWM module; the three-phase permanent magnet synchronous motor is a controlled object; the current sampling module obtains three-phase current of the permanent magnet synchronous motor by using methods of a current sensor, a rotary transformer, a sampling resistor and the like. The clark conversion module is realized by a microcontroller algorithm, and has the main functions of converting the current under a static three-phase coordinate system into the current under a two-phase static coordinate system; the park transformation module is realized by a microcontroller algorithm, and has the main functions of converting the current under a two-phase static coordinate system into the current under a two-phase rotating coordinate system; the extended Kalman filter is realized by a microcontroller algorithm, a state observer is constructed mainly according to input current and voltage signals, and the rotation speed and the angle of a rotor are estimated by using the observer; the square wave injection estimator is realized by a microcontroller algorithm, and has the main functions of processing an input high-frequency current signal to obtain an envelope signal of a high-frequency current guide, and then estimating the rotating speed and the angle of a rotor by using a phase-locked loop. The linear weighting switching module is used for carrying out linear weighting on the angle and the rotating speed calculated by the position observers with medium and high speed and zero and low speed, and carrying out smooth transition on the operation process of the motor.
The specific process is as follows:
first, a given electric angular velocity ωe * And the angular velocity omega e estimated by the position observer is differenced and transmitted into a speed loop controller to obtain the quadrature command current iq * . When the id=0 control method is adopted, the direct current command current id is given * =0. The three phase line currents ia, ib, ic obtained by the current sampling module are converted into actual id and iq currents through clark conversion and park conversion. Id current to be measured and direct command current id * Subtracting to obtain d-axis current errorTransmitting into d-axis current loop controller to obtain d-axis voltage command ud, and superposing high-frequency square wave voltage v dh Transmitting into an inverse park transformation module, and converting the d-axis voltage command into u under an alpha beta axis α . The measured iq current and the direct current command current iq * Subtracting to obtain q-axis current error +.>The voltage command uq is obtained by transmitting the voltage command uq into a q-axis current loop controller and then transmitting the voltage command uq into a reverse park conversion module, and the voltage command of the q-axis is converted into u under an alpha beta shafting β . Will u α 、u β And the three-phase permanent magnet synchronous motor is input into the SVPWM module to obtain six paths of PWM signals to control the three-phase inverter to drive the three-phase permanent magnet synchronous motor. In order to obtain the rotor position at the middle and high speed, the current sampling module is required to obtain the three-phase currents Ia, ib and Ic of the permanent magnet synchronous motor. And (3) taking the three materials as inputs to be transmitted into the clark conversion and the park conversion to obtain stator currents id and iq under a two-phase rotation coordinate system. Ud, uq, id, iq is transmitted into an extended Kalman filter output rotating speed omega e1 and an angle theta e1 to enter a linear weighted switching module. To get zeroRotor position at low speed requires injection of high frequency square wave voltage v at d-axis dh Three-phase currents Ia, ib and Ic of the permanent magnet synchronous motor are obtained through a current sampling module, clark is input to be transformed to obtain ialpha and ibeta, a high-frequency current derivative envelope signal is obtained through a square wave injection module, a phase-locked loop technology is utilized to obtain the rotating speed omega e2 and the angle theta e2, and the rotating speed omega e2 and the angle theta e2 enter a linear weighting switching module. At v, the linear weighted switching module L At the speed, the weighting coefficient is 1, the rotating speed omega e and the angle theta e are estimated by using a high-frequency square wave injection method, and the speed v is the speed L -v H And in the section, a weighting method is adopted, and proper rotating speed omega e and angle theta e are obtained by adjusting the high-frequency square wave injection output rotating speed omega e2 and angle theta e2 and the extended Kalman filter output rotating speed omega e1 and angle theta e 1. At v H At speed, the weighting coefficient is 0, and the rotation speed ωe and the angle θe are estimated by using an extended kalman filter.
The invention also provides a method for controlling the position-free sensor of the medium-full-speed domain permanent magnet synchronous motor, which specifically comprises the following steps:
step 1: estimating the position angle of a rotor in the motor when the motor runs at a high speed through an extended Kalman filter observer:
first, a mathematical model of the motor under a two-phase rotation coordinate system is established
Rewritten as a current equation
Wherein U is d 、U q And I d 、I q Stator voltage and stator current in two-phase d-q rotation coordinate system, R is stator phase resistance, L d 、L q Is the stator axial phase inductance omega e Is the rotor electrical angle, ψ f Is the rotor flux linkage. (12) Establishing a medium-high speed extended Kalman filter observer
Wherein,representing the state prediction value at time k +.>Representing the state predicted value at time K-1, B representing the input matrix, u (K-1) representing the known external control quantity, P (k|k-1) representing the predicted error covariance matrix at time K, P (K-1|k-1) representing the estimated covariance matrix at time K-1, Q representing the process noise covariance, K (k|k-1) representing the Kalman gain at time K, Y k Represents the k moment measurement value, R represents the covariance of the k moment measurement noise, P (k|k) represents the error covariance matrix of the k moment estimation, +.>The state estimation value at time k is shown.
Step 2: the high-frequency square wave injection method is used for extracting a high-frequency current envelope signal of the motor during zero-speed and low-speed operation, and the phase-locked loop is used for extracting the rotor position angle at zero speed and low speed.
When the motor is at a low speed, neglecting the resistance of a motor stator and counter electromotive force, and establishing a motor high-frequency signal model:
wherein U is dh 、U qh High-frequency voltages respectively representing d and q axes of the motor; i.e dh 、i qh Represents d, q-axis high-frequency current;
the square wave signal injected under the estimated rotor rotation coordinate system can be expressed as:
wherein V is h Is the amplitude of the injected square wave voltage.
Mathematical model of excited high-frequency current in stationary alpha beta coordinate system:
transforming the estimated dq axis by coordinates to the actual dq axis:
the mathematical expression of the high-frequency current substituted into the actual shaft dq is as follows:
the above expression is rewritten as follows, using the differential instead of the differential:
and finally, when the estimated angle theta' is equal to the real angle theta by using the PLL quadrature phase-locked loop, the output angle is a real value.
err＝sinθcosθ′-cosθsinθ′＝sin(θ-θ′)＝0
Step 3: and stably transiting the position detection algorithm at the middle and high speeds and the low speed by a linear weighted switching method.
Wherein,the electric angle estimated value and the speed estimated value are respectively obtained after the fusion of the low-speed estimation algorithm and the medium-speed estimation algorithm; />v L 、v H The electric angle and the speed under the low-speed estimation algorithm and the medium-speed estimation algorithm are respectively calculated; λ is the weighting coefficient.
It is noted that the terms "first," "second," "third," "fourth," and the like in the description and claims of the invention and in the foregoing figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein.
The same and similar parts of the embodiments in this specification are all mutually referred to, and each embodiment focuses on the differences from the other embodiments. In particular, for the product embodiments described later, since they correspond to the methods, the description is relatively simple, and reference is made to the description of parts of the system embodiments.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (5)
1. The full-speed domain sensorless estimation and control method of the motor is characterized by comprising the following steps of:
(1) Estimating the position angle of a rotor in the motor when the motor runs at a high speed through an extended Kalman filter observer;
(2) Extracting a high-frequency current envelope signal of the motor during zero-speed and low-speed operation by a high-frequency square wave injection method, and extracting a rotor position angle at zero speed and low speed by a phase-locked loop;
(3) And the smooth switching of the motor from zero-speed to medium-high-speed operation is completed through a weighted switching transition strategy.
2. The motor full speed domain sensorless estimation and control method of claim 1, wherein said step (1) includes the steps of:
step (11) establishing a mathematical model of the motor under a two-phase rotation coordinate system
Rewritten as a current equation
Wherein U is d 、U q And I d 、I q Stator voltage and stator current in two-phase d-q rotation coordinate system, R is stator phase resistance, L d 、L q Is the stator axial phase inductance omega e Is the rotor electrical angle, ψ f Is a rotor flux linkage;
step (12) establishing a medium-high speed extended Kalman filter observer
Wherein,representing the state prediction value at time k +.>Representing the state predicted value at time K-1, B representing the input matrix, u (K-1) representing the known external control quantity, P (k|k-1) representing the predicted error covariance matrix at time K, P (K-1|k-1) representing the estimated covariance matrix at time K-1, Q representing the process noise covariance, K (k|k-1) representing the Kalman gain at time K, Y k Represents the k moment measurement value, R represents the covariance of the k moment measurement noise, P (k|k) represents the error covariance matrix of the k moment estimation, +.>The state estimation value at time k is shown.
3. The motor full speed domain sensorless estimation and control method of claim 1, wherein said step (2) includes the steps of:
when the motor is at a low speed, neglecting the resistance of a motor stator and counter electromotive force, and establishing a motor high-frequency signal model:
wherein U is dh 、U qh High-frequency voltages respectively representing d and q axes of the motor; i.e d 、i q Represents d, q-axis high-frequency current;
the square wave signal injected under the estimated rotor rotation coordinate system can be expressed as:
wherein V is h Is the amplitude of the injected square wave voltage;
mathematical model of excited high-frequency current in stationary alpha beta coordinate system:
transforming the estimated dq axis by coordinates to the actual dq axis:
substituting the mathematical expression of the high-frequency current of the actual shaft dq:
the above expression is rewritten as follows, using the differential instead of the differential:
finally, using PLL quadrature phase-locked loop to estimate angle theta ′ When the output angle is equal to the real angle theta, the output angle is a real value;
err＝sinθcosθ′-cosθsinθ′＝sin(θ-θ ′ ) =0 (formula eleven).
4. The motor full speed domain sensorless estimation and control method of claim 1, wherein said step (3) includes the steps of:
wherein,the electric angle estimated value and the speed estimated value are respectively obtained after the fusion of the low-speed estimation algorithm and the medium-speed estimation algorithm;v L 、v H the electric angle and the speed under the low-speed estimation algorithm and the medium-speed estimation algorithm are respectively calculated; λ is the weighting coefficient.
5. A motor full speed domain sensorless estimation and control system employing the method of claims 1-4, comprising: the device comprises a speed loop PI controller, a d-axis current loop PI controller, a q-axis current loop PI controller, an inverse park transformation module, a space vector pulse width modulation SVPWM module, a three-phase inverter, a three-phase permanent magnet synchronous motor, a three-phase current acquisition module, a park transformation module, a two-phase static current signal extraction and rotor angle estimation module, a Clarke transformation module, a square wave injection module, an extended Kalman position estimation module and a weighted switching module; the extended Kalman position estimation module is realized by a microcontroller algorithm, a state observer is constructed according to the input voltage and current, and the angle of the rotor is calculated; the square wave injection module is realized by a microcontroller algorithm, extracts the output high-frequency current signal, extracts the electrical angle in the high-frequency current by using a phase-locked loop, and calculates the angle of the rotor; and the weighted switching module completes smooth switching of the speed at low speed and medium and high speed.
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