CN111431460A - Sensorless model prediction flux linkage control method for permanent magnet synchronous motor - Google Patents

Sensorless model prediction flux linkage control method for permanent magnet synchronous motor Download PDF

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CN111431460A
CN111431460A CN202010335878.6A CN202010335878A CN111431460A CN 111431460 A CN111431460 A CN 111431460A CN 202010335878 A CN202010335878 A CN 202010335878A CN 111431460 A CN111431460 A CN 111431460A
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flux linkage
load
torque
rotation speed
sliding mode
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CN111431460B (en
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张蔚
翟良冠
王家乐
金鑫
杨泽贤
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Nantong University
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/24Vector control not involving the use of rotor position or rotor speed sensors
    • H02P21/28Stator flux based control
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/0007Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using sliding mode control
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/13Observer control, e.g. using Luenberger observers or Kalman filters
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/18Estimation of position or speed
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P6/00Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/10Arrangements for controlling torque ripple, e.g. providing reduced torque ripple
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P6/00Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/14Electronic commutators
    • H02P6/16Circuit arrangements for detecting position
    • H02P6/18Circuit arrangements for detecting position without separate position detecting elements
    • H02P6/182Circuit arrangements for detecting position without separate position detecting elements using back-emf in windings
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P2203/00Indexing scheme relating to controlling arrangements characterised by the means for detecting the position of the rotor
    • H02P2203/03Determination of the rotor position, e.g. initial rotor position, during standstill or low speed operation

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  • Power Engineering (AREA)
  • Control Of Ac Motors In General (AREA)

Abstract

The invention belongs to the field of electromechanical control and discloses a sensorless model prediction flux linkage control method for a permanent magnet synchronous motor. Firstly, observing the rotation speed omega and the rotor position angle theta of the motor through a sliding mode observer and a phase-locked loop based on SOGIe(ii) a Then, the rotation speed ω is given*And the rotation speed omega is used for obtaining the given torque T through a rotation speed ring SMC controllere *(ii) a Then, the rotational speed ω and the d/q axis current id/iqObserving load disturbancesDynamic value
Figure DDA0002466577660000011
And perturbing the load by a value
Figure DDA0002466577660000012
Feed forward compensation to a given torque Te *(ii) a Finally, the observed rotating speed omega and the rotor position angle theta are measuredeGiven torque Te *Load disturbance value
Figure DDA0002466577660000013
And the three-phase voltage u obtained by samplinga/ub/ucThree-phase current ia/ib/icAnd substituting the model prediction flux linkage control module for operation. The method adopts a mode of a sliding mode observer and an improved phase-locked loop to improve the estimation precision of the rotor position, simultaneously predicts flux linkage control based on a model, does not need current loop parameter and weight coefficient setting, combines the sliding mode control with a load disturbance observer, and improves the robustness and the anti-interference capability of a system.

Description

Sensorless model prediction flux linkage control method for permanent magnet synchronous motor
Technical Field
The invention relates to the field of electromechanical control, in particular to a sensorless model prediction flux linkage control method for a permanent magnet synchronous motor.
Background
The permanent magnet synchronous motor position sensorless control technology utilizes related electric signals in a winding to estimate the position and the rotating speed of a rotor, thereby omitting a mechanical sensor, reducing the volume and the cost of a motor and increasing the reliability of a system. Current position estimation algorithms can be divided into two categories, signal injection-based and observer-based. The former uses the salient polarity of the motor to estimate the position of the rotor, but the continuous injection of the excitation signal requires complex signal processing, resulting in low utilization rate of the inverter voltage and slow dynamic response. The latter estimates the rotating speed by means of the counter electromotive force in a dynamic model, and is easy to realize in engineering. The sliding mode observer algorithm is one of the latter, has simple structure, strong robustness and fast dynamic response, but also has the problems of difficult filtering, large estimation error of a rotor position angle, delayed estimation value from an actual value, poor low-speed performance and the like.
In addition, for the position sensorless control technology of the permanent magnet synchronous motor, researchers have conducted extensive research based on various control technologies, such as vector control, direct torque control, sliding mode control, fuzzy control and the like, but these control technologies all have certain disadvantages in application, such as large torque ripple, poor robustness, poor dynamic effect, complex algorithm and the like. Therefore, the research on the position-sensor-free control algorithm with accurate rotor position tracking, strong system robustness, small torque pulsation and good dynamic effect has wide development prospect.
Disclosure of Invention
In view of this, the present invention provides a sensorless model predictive flux linkage control method for a permanent magnet synchronous motor, which can accurately track rotor position information, improve system robustness, suppress torque ripple, and improve dynamic operation effect.
The invention provides a sensorless model prediction flux linkage control method for a permanent magnet synchronous motor, which comprises the following steps of:
s1, sampling three-phase current ia/ib/icAnd voltage ua/ub/ucObtaining αβ axis current i after coordinate transformation of C L ARK and PARKα/iβAnd αβ Axis Voltage uα/uβAnd dq-axis current id/iqαβ axis current iα/iβAnd αβ Axis Voltage uα/uβEstimation of extended back electromotive force E by substituting sliding mode observerαAnd Eβ
S2, expanding the counter electromotive force EαAnd EβSubstituting into a phase-locked loop based on SOGI (second-order generalized integrator), and observing the rotation speed omega and the rotor position angle thetae
S3, mixing the dq axis current id/iqSubstituting the sum of the rotation speed omega into a load disturbance observer to obtain a load disturbance value
Figure BDA0002466577640000011
S4, setting the rotating speed omega*And the rotating speed omega obtains the given torque T through a rotating speed ring SMC (sliding mode control) controllere *Given a torque Te *Obtaining a given flux linkage psi via MTPAs *
S5, disturbing the load
Figure BDA0002466577640000012
Feed forward compensation to a given torque Te *And with torque TeObtaining a torque error Te 'by subtracting, and obtaining a load angle deviation delta through the torque error Te' by a PI controllersfCalculated value of angle of lift and loadsfObtaining the load angle reference value by differencesf *
S6, enabling the voltage vector u of the three-phase inverter to besSubstituting the rotation speed omega and the dq axis current id/iq into a flux linkage prediction module to predict and obtain a flux linkage psi at the moment of k +1d(k+1)/ψq(k+1);
S7, giving a magnetic linkage psis *Reference value of load anglesf *Magnetic linkage psi at time k +1d(k+1)/ψq(k +1), rotor position angle θeSubstituting the sum of the rotation speed omega into a minimum cost function module to output a duty ratio signal Sa、Sb、ScThen the duty ratio signal Sa、Sb、ScAnd the input three-phase inverter controls the on and off of the three-phase inverter, so that the permanent magnet synchronous motor is driven.
Further, the extended back electromotive force E is generated in step S1αAnd EβThe estimation formula of (c) is:
Figure BDA0002466577640000013
wherein sat(s) is a sliding mode surface control function,
Figure BDA0002466577640000014
in the formula: z is a radical ofα、zβControlling a function component for the sliding mode surface;
Figure BDA0002466577640000021
to estimate the current component; Δ is the boundary layer thickness; k is a radical ofsatAdaptive rate, k, of sinusoidal saturation function of varying boundary layersat=kl·ω,klIs a positive real number, and ω is the rotational speed.
Further, the rotation speed ω and the rotor position angle θ are set in step S2eThe calculation formula of (2) is as follows:
Figure BDA0002466577640000022
θe=∫ωdt,
wherein λ ═ Ld-Lq)(ωid-piq)+ωψf;Kp/KiRespectively, proportional/integral coefficients;
Figure BDA0002466577640000023
is the transfer function of the SOGI;θ(s) is the amount of positional angle error; 'θ(s) is the filtered position angle error amount; k is a radical ofθIs an error amplification factor.
Further, the load disturbance value in step S3
Figure BDA0002466577640000024
The calculation formula of (2) is as follows:
Figure BDA0002466577640000025
in the formula: u is a sliding mode surface control function; g is a feedback gain;
Figure BDA0002466577640000026
is an electrical angular velocity estimate.
Further, in step S4, a torque T is givene *The calculation formula of (2) is as follows:
Figure BDA0002466577640000027
in the formula:
Figure BDA0002466577640000028
c is the sliding mode surface coefficient, α and knAll the coefficients are exponential approach rate coefficients and satisfy the following conditions:>0,α≥2,kn>0。
compared with the prior art, the invention has the advantages and effects that:
the method comprises the steps of applying a model prediction flux linkage control algorithm to control of a position-free sensor, designing a sliding mode observer, a rotating speed loop SMC controller and a load disturbance observer by adopting a boundary layer variable sine type saturated function to reduce system buffeting, adding an SOGI into a phase-locked loop and introducing real-time rotating speed to achieve self-adaptive filtering regulation, wherein the rotating speed and the rotor position angle obtained by the phase-locked loop based on the SOGI are more accurate and are further input or fed back to the rotating speed loop SMC controller and the load disturbance observer to optimize deviation regulation and disturbance compensation, so that the dynamic effect and robustness of a control system are improved, and torque pulsation is restrained. Meanwhile, the salient-polarity permanent magnet synchronous motor is used as a research object, and the application range of the control method is widened.
Drawings
Fig. 1 is a control block diagram of a sensorless model predictive flux linkage control method for a permanent magnet synchronous motor according to an embodiment of the present invention;
FIG. 2 is a schematic block diagram of an SOGI-based phase-locked loop according to an embodiment of the present invention;
FIG. 3 is a schematic block diagram of a load disturbance observer provided by an embodiment of the present invention;
FIG. 4 is a functional block diagram of a speed loop SMC controller provided by an embodiment of the present invention;
FIG. 5 is a diagram of simulation results of the PMSM speed without the position sensor control algorithm provided by the embodiment of the present invention;
FIG. 6 is a comparison graph of simulation results of rotor position angle errors of a PMSM between a position sensorless control algorithm and a conventional position sensorless control algorithm according to an embodiment of the present invention;
FIG. 7 is a comparison graph of simulation results of PMSM torque for a position sensorless control algorithm and a conventional position sensorless control algorithm provided in an embodiment of the present invention;
fig. 8 is a control block diagram of a conventional sensorless control method of a permanent magnet synchronous motor.
Detailed Description
The present invention will be described in further detail below by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and are not to be construed as limiting the present invention.
As shown in fig. 1, the present invention provides a sensorless model predictive flux linkage control method for a permanent magnet synchronous motor, comprising the following steps:
s1, sampling three-phase current ia/ib/icAnd voltage ua/ub/ucObtaining αβ axis current i after coordinate transformation of C L ARK and PARKα/iβAnd αβ Axis Voltage uα/uβAnd dq-axis current id/iqαβ axis current iα/iβAnd αβ Axis Voltage uα/uβEstimation of extended back electromotive force E by substituting sliding mode observerαAnd Eβ
Specifically, the invention extends the back electromotive force EαAnd EβThe estimation process of (2) is illustrated as follows:
αβ the stator voltage equation for the coordinate system is:
Figure BDA0002466577640000031
Figure BDA0002466577640000032
in the formula uα、uβRespectively αβ axis voltage iα、iβαβ axis currents, Ld、LqDq-axis inductances, respectively; r is a stator resistor; ω is the rotational speed; p is a differential operator; eα、EβTo extend the back emf; psifIs a permanent magnet flux linkage; thetaeIs the rotor position angle.
The equation (1) is rewritten as a current state equation with the stator current as a state variable:
Figure BDA0002466577640000033
selecting a sliding mode surface s (x) as 0 on a stator current track as follows:
Figure BDA0002466577640000034
in the formula:
Figure BDA0002466577640000035
to estimate the current component;
Figure BDA0002466577640000036
to estimate the current error component.
To obtain extended back emf, the sliding mode observer is designed as:
Figure BDA0002466577640000037
in the formula: z is a radical ofα、zβIs a sliding mode surface control function component.
And (3) subtracting the equations (6) and (3) to obtain an error equation of the stator current as follows:
Figure BDA0002466577640000038
the sliding mode surface control function in the formulas (5) and (6) is shown as a formula (7).
Figure BDA0002466577640000039
Figure BDA00024665776400000310
In the formula: Δ is the boundary layer thickness, ksatAdaptive rate, k, of sinusoidal saturation function of varying boundary layersat=kl·ω,klIs a positive real number, and ω is the rotational speed. The sliding mode surface control function can effectively reduce the buffeting of the system and has the capability of real-time adjustment along with the change of the rotating speed.
When the state variable reaches the sliding mode surface, i.e., s (x) is 0, the observer state will be maintained. According to the equivalent control principle of the sliding mode variable structure control, the following can be obtained:
Figure BDA00024665776400000311
s2, expanding the counter electromotive force EαAnd EβSubstituting the phase-locked loop based on the SOGI to observe and obtain the rotating speed omega and the rotor position angle theta through the phase-locked loop based on the SOGIe
Specifically, the rotational speed ω and the rotor position angle θ in the present inventioneThe calculation process of (a) is illustrated as follows:
the transfer function of the SOGI is:
Figure BDA0002466577640000041
wherein λ ═ Ld-Lq)(ωid-piq)+ωψfθ(s) is a position angle error amount'θ(s) is the amount of position angle error after filtering, kθIs an error amplification factor.
Expanding the counter electromotive force E in the formula (9)αAnd EβInputting a phase-locked loop based on the SOGI to obtain the rotation speed omega and the rotor position angle thetaeThe schematic block diagram is shown in fig. 2. The SOGI is added into a phase-locked loop and the real-time rotating speed is introduced to adjust the bandwidth and the error so as to improve the self-adaptive filtering effect of the phase-locked loop, thereby reducing the harmonic interference caused by the buffeting of the system and improving the estimation precision of the rotor position angle.
Figure BDA0002466577640000042
In the formula: kpIs a proportionality coefficient, KiIs an integral coefficient.
S3, mixing the dq axis current id/iqSubstituting the sum of the rotation speed omega into a load disturbance observer to obtain a load disturbance value
Figure BDA0002466577640000043
Specifically, the load disturbance value in the present invention
Figure BDA0002466577640000044
The calculation process of (a) is illustrated as follows:
the voltage equation in dq coordinate system is:
Figure BDA0002466577640000045
the torque equation:
Figure BDA0002466577640000046
equation of motion:
Figure BDA0002466577640000047
in the formula, TlIs the load torque; b is friction torque viscosity coefficient; j is moment of inertia.
According to PMSM torque and motion equations shown in equations (13) and (14), and taking the load torque as an extended state variable, constructing an extended state equation as follows:
Figure BDA0002466577640000048
in the formula: since the electrical time constant is much smaller than the mechanical time constant, the load torque can be considered constant during the control period, i.e. the load torque is constant
Figure BDA0002466577640000049
Based on the equation (15), the load torque and the rotor electrical angular velocity are used as state variables, the velocity estimation error is used as a sliding mode switching surface, and a sliding mode plane is defined as
Figure BDA00024665776400000410
An extended sliding-mode observer is established as
Figure BDA00024665776400000411
In the formula:
Figure BDA00024665776400000412
g is a feedback gain;
Figure BDA00024665776400000413
respectively an electrical angular velocity estimate and a load disturbance estimate.
According to the equivalent control principle of sliding mode variable structure control, the load disturbance estimation value can be obtained
Figure BDA0002466577640000051
The functional block diagram is shown in fig. 3:
Figure BDA0002466577640000052
according to the formula (17), the load disturbance observer also adopts a sliding mode surface control function with the real-time adjustment capability along with the change of the rotating speed, so that the obtained load disturbance estimation value is more real-time and accurate.
S4, setting the rotating speed omega*And the rotation speed omega obtains the given torque T through a rotation speed ring SMC controllere *Given a torque Te *Obtaining a given flux linkage psi via MTPAs *
Specifically, the predetermined torque T is set in the present inventione *And a given flux linkage psis *The calculation process of (a) is illustrated as follows:
the rotating speed state equation is constructed as follows:
Figure BDA0002466577640000053
from formulae (14) and (18):
Figure BDA0002466577640000054
selecting a linear sliding mode surface function as follows: s ═ cx1+x2(20)
The following is derived from equation (20):
Figure BDA0002466577640000055
substituting (21) for formula (20) to obtain:
Figure BDA0002466577640000056
the design index approach rate is: s ═ x |1|αsat(s)-kns,>0,α≥2,kn>0 (23)
The exponential approximation rate is substituted into formula (22) to obtain the given torque Te *The schematic block diagram is shown in fig. 4:
Figure BDA0002466577640000057
as can be seen from formula (24), in-x1|αs and-kns, the state variable can rapidly approach the sliding mode surface to be stable, and sat(s) can further reduce the buffeting of the system.
Will be provided with
Figure BDA0002466577640000058
And (3) as a system disturbance feedforward compensation to load torque input, obtaining a torque error as follows:
Figure BDA0002466577640000059
the stability of the approach rate proves that:
Figure BDA00024665776400000510
the reference value of the flux linkage amplitude is calculated by an MTPA algorithm, the method considers the influence of weak magnetism and efficiency when the motor runs, and the calculation formula is as follows:
Figure BDA00024665776400000511
s5, disturbing the load
Figure BDA00024665776400000512
Feed forward compensation toConstant torque Te *And with torque TeMaking a difference to obtain a torque error Te', torque error Te' obtaining the load angular deviation Delta through a PI controllersfCalculated value of angle of lift and loadsfObtaining the load angle reference value by differencesf *
In step S5, the load angle reference value in the present inventionsf *The calculation process of (a) is illustrated as follows:
the mathematical model of the permanent magnet synchronous motor under dq coordinates is as follows:
Figure BDA00024665776400000513
Figure BDA0002466577640000061
equation (27) is substituted for equation (12) to derive the current differential equation:
Figure BDA0002466577640000062
discretization of equation (29) yields:
Figure BDA0002466577640000063
in the formula: t issIs a control cycle.
Substituting equation (30) into (29) yields the predicted stator flux linkage at time (k +1) as:
Figure BDA0002466577640000064
the sampled stator current i at the current moments(k) Applied to equations (27) - (29), the stator flux linkage vector ψ at time ks(k) And torque Te(k) Can be calculated. According to the definition of the load angle, the load angle at the moment ksf(k) Can be calculated as:
Figure BDA0002466577640000065
will give a given torque Te *Torque T at time ke(k) The difference value is input into a PI controller, and the load angle deviation is obtained as follows:
Figure BDA0002466577640000066
load angle at time ksf(k) Deviation from load angle Δsf(k) The reference load angle at the (k +1) time is obtained by additionsf *(k +1) is:
Figure BDA0002466577640000067
in the formula, KPTAnd KITRespectively, a proportional gain and an integral gain of the rotating speed PI controller.
S6, converting the voltage vector u of the two-level voltage source type invertersSubstituting the rotation speed omega and the dq axis current id/iq into a flux linkage prediction module to predict and obtain a flux linkage psi at the moment of k +1d(k+1)/ψq(k+1);
S7, giving a magnetic linkage psis *Reference value of load anglesf *Magnetic linkage psi at time k +1d(k+1)/ψq(k +1), rotor position angle θeSubstituting the sum of the rotation speed omega into a minimum cost function module to output a duty ratio signal Sa、Sb、ScThen the duty ratio signal Sa、Sb、ScAnd the input three-phase inverter controls the on and off of the three-phase inverter, so that the permanent magnet synchronous motor is driven.
Step S6, the flux linkage ψ at time k +1 is described in the present inventiond(k+1)/ψqThe prediction process of (k +1) is illustrated as follows:
combining equation (33) and equation (34), the reference value of the flux linkage vector at time (k +1) in the dq coordinate system is:
Figure BDA0002466577640000068
step S7, the operation principle of the minimum cost function module in the present invention is described as follows:
predicting flux linkage vectors under the action of 7 different basic voltage vectors (us is u0 or u7, u1, … and u6), respectively calculating corresponding objective functions of the different flux linkage vectors, and selecting the voltage vector which enables the objective function to be minimum as the optimal output of the converter, wherein the objective function is as follows:
Figure BDA0002466577640000071
in the formula: psid(k+1)/ψq(k +1) is the flux linkage vector at time k +1, psid *(k+1)/ψq *And (k +1) is a reference value of the flux linkage vector at the time of (k + 1).
According to a control block diagram shown in figure 1, MAT L AB/SIMU L INK software is used for building a permanent magnet synchronous motor sensorless model to predict flux linkage control system simulation, and motor parameters are selected as follows, wherein the motor parameters comprise a rated power of 600W, a rated rotating speed of 750rpm, a rated torque of 7.6 N.m, a pole pair number of 13, a permanent magnet flux linkage amplitude of 0.08Wb, an armature winding resistance of 0.8 omega, quadrature-direct axis inductances of 6.5mH and 6.3mH respectively, and a rotational inertia of 0.004 kg.m2The friction torque viscosity coefficient was 0.0004N · m · s. The simulation gives conditions as follows: the idling speed is initially given at 50rpm, the speed is abruptly changed to 500rpm at 0.2s, and the load is 4 N.m at 0.4 s. Under the above conditions, the simulation results of the rotation speed under the method of the present patent are shown in fig. 5, and the simulation results of the rotor position angle error and the motor torque under the conventional sensorless method and the method of the present patent are shown in fig. 6 and 7. A control block diagram of the conventional sensorless control method is shown in fig. 8. As can be seen from FIG. 5, the method of the invention can effectively track the actual rotating speed, the estimated rotating speed has small pulsation, the overshoot is small when the rotating speed is suddenly changed, the given rotating speed value can be tracked in a short time when the torque is suddenly changed, and the robustness is good; as can be seen from FIGS. 6 and 7, the method of the present invention has the advantages of more accurate tracking of the rotor position angle and stronger suppression capability to the torque ripple.
The above description of the present invention is intended to be illustrative. Various modifications, additions and substitutions for the specific embodiments described may be made by those skilled in the art without departing from the scope of the invention as defined in the accompanying claims.

Claims (5)

1. A sensorless model prediction flux linkage control method for a permanent magnet synchronous motor is characterized by comprising the following steps: comprises the following steps:
s1, sampling three-phase current ia/ib/icAnd voltage ua/ub/ucObtaining αβ axis current i after coordinate transformation of C L ARK and PARKα/iβAnd αβ Axis Voltage uα/uβAnd dq-axis current id/iqαβ axis current iα/iβAnd αβ Axis Voltage uα/uβEstimation of extended back electromotive force E by substituting sliding mode observerαAnd Eβ
S2, expanding the counter electromotive force EαAnd EβSubstituting the phase-locked loop based on the SOGI to observe the rotation speed omega and the rotor position angle thetae
S3, mixing the dq axis current id/iqSubstituting the sum of the rotation speed omega into a load disturbance observer to obtain a load disturbance value
Figure FDA0002466577630000011
S4, setting the rotating speed omega*And the rotation speed omega obtains the given torque T through a rotation speed ring SMC controllere *Given a torque Te *Obtaining a given flux linkage psi via MTPAs *
S5, disturbing the load
Figure FDA0002466577630000012
Feed forward compensation to a given torque Te *And with torque TeMaking difference to obtain a torque error T'eTorque error T'eObtaining the load angle deviation delta through a PI controllersfCalculated value of angle of lift and loadsfObtaining the load angle reference value by differencesf *
S6, enabling the voltage vector u of the three-phase inverter to besSubstituting the rotation speed omega and the dq axis current id/iq into a flux linkage prediction module to predict and obtain a flux linkage psi at the moment of k +1d(k+1)/ψq(k+1);
S7, giving a magnetic linkage psis *Reference value of load anglesf *Magnetic linkage psi at time k +1d(k+1)/ψq(k +1), rotor position angle θeSubstituting the sum of the rotation speed omega into a minimum cost function module to output a duty ratio signal Sa、Sb、ScThen the duty ratio signal Sa、Sb、ScAnd the input three-phase inverter controls the on and off of the three-phase inverter, so that the permanent magnet synchronous motor is driven.
2. The sensorless model predictive flux linkage control method for the permanent magnet synchronous motor according to claim 1, wherein the extended back electromotive force E is used in step S1αAnd EβThe estimation formula of (c) is:
Figure FDA0002466577630000013
wherein sat(s) is a sliding mode surface control function,
Figure FDA0002466577630000014
zα、zβcontrolling a function component for the sliding mode surface;
Figure FDA0002466577630000015
to estimate the current component; Δ is the boundary layer thickness; k is a radical ofsatAdaptive rate, k, of sinusoidal saturation function of varying boundary layersat=kl·ω,klIs a positive real number, and ω is the rotational speed.
3. A pmsm sensorless model predictive magnet in accordance with claim 1Chain control method, characterized in that in step S2, the rotation speed ω and the rotor position angle θ are seteThe calculation formula of (2) is as follows:
Figure FDA0002466577630000016
wherein λ ═ Ld-Lq)(ωid-piq)+ωψf;Kp/KiRespectively, proportional/integral coefficients;
Figure FDA0002466577630000017
is the transfer function of the SOGI;θ(s) is the amount of positional angle error; 'θ(s) is the filtered position angle error amount; k is a radical ofθIs an error amplification factor.
4. The sensorless model predictive flux linkage control method for the permanent magnet synchronous motor according to claim 3, wherein the load disturbance value in step S3
Figure FDA0002466577630000018
The calculation formula of (2) is as follows:
Figure FDA0002466577630000019
in the formula: u is a sliding mode surface control function; g is a feedback gain;
Figure FDA00024665776300000110
is an electrical angular velocity estimate.
5. The sensorless model predictive flux linkage control method of the permanent magnet synchronous motor according to claim 3, wherein the torque T is given in step S4e *The calculation formula of (2) is as follows:
Figure FDA00024665776300000111
in the formula:
Figure FDA0002466577630000021
c is the sliding mode surface coefficient, α and knAll the coefficients are exponential approach rate coefficients and satisfy the following conditions:>0,α≥2,kn>0。
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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111987943A (en) * 2020-07-23 2020-11-24 西安理工大学 Robust performance improving method for model predictive control of permanent magnet synchronous motor
CN112187127A (en) * 2020-10-26 2021-01-05 江苏省电力试验研究院有限公司 Permanent magnet synchronous motor control method
CN112311290A (en) * 2020-10-26 2021-02-02 江苏大学 Robust prediction permanent magnet synchronous hub motor sensorless controller
CN112448632A (en) * 2020-11-12 2021-03-05 湘潭大学 Novel SPMSM sensorless compound control method of double-sliding-mode observer
CN112701978A (en) * 2020-12-21 2021-04-23 南通斯迈尔精密设备有限公司 Mechanical numerical control machine tool self-vibration suppression method based on disturbance observer
CN112737457A (en) * 2020-12-25 2021-04-30 中车永济电机有限公司 Stability control method of permanent magnet auxiliary synchronous reluctance motor
CN113437912A (en) * 2021-07-09 2021-09-24 中南大学 Prediction control method and system for strong robustness model of permanent magnet synchronous motor
CN113644854A (en) * 2021-08-11 2021-11-12 吉林大学 Permanent magnet synchronous motor angle identification system and method
CN114204854A (en) * 2022-01-06 2022-03-18 江苏大学 Rotor flux observer-based five-phase permanent magnet synchronous motor open-circuit fault-tolerant position-free control method
CN114844405A (en) * 2020-09-04 2022-08-02 湖南工业大学 Integration sliding mode control system of permanent magnet synchronous motor
CN114859729A (en) * 2022-05-13 2022-08-05 中国第一汽车股份有限公司 Control method, device, equipment and storage medium
CN116248003A (en) * 2023-05-06 2023-06-09 四川省产品质量监督检验检测院 Sliding mode control-based method and system for controlling active disturbance rejection speed of switched reluctance motor
CN117639581A (en) * 2023-11-08 2024-03-01 北方工业大学 Permanent magnet synchronous motor sensorless control method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108322120A (en) * 2018-01-30 2018-07-24 天津大学 Robust nonlinear suitable for permanent magnet synchronous motor predicts method for controlling torque
CN108631672A (en) * 2018-05-07 2018-10-09 南通大学 Meter and the permanent magnet synchronous motor of optimal duty ratio modulation predict flux linkage control method
CN109873586A (en) * 2019-04-12 2019-06-11 湖南大学 A kind of electromechanics parameter identification method and system based on High-Order Sliding Mode observer

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108322120A (en) * 2018-01-30 2018-07-24 天津大学 Robust nonlinear suitable for permanent magnet synchronous motor predicts method for controlling torque
CN108631672A (en) * 2018-05-07 2018-10-09 南通大学 Meter and the permanent magnet synchronous motor of optimal duty ratio modulation predict flux linkage control method
CN109873586A (en) * 2019-04-12 2019-06-11 湖南大学 A kind of electromechanics parameter identification method and system based on High-Order Sliding Mode observer

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
杜昭平等: "基于SOGI-PLL的永磁同步电机转子位置估计方法" *

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