CN111431460B - Permanent magnet synchronous motor sensorless model prediction flux linkage control method - Google Patents
Permanent magnet synchronous motor sensorless model prediction flux linkage control method Download PDFInfo
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/24—Vector control not involving the use of rotor position or rotor speed sensors
- H02P21/28—Stator flux based control
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P21/0007—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using sliding mode control
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/13—Observer control, e.g. using Luenberger observers or Kalman filters
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
- H02P21/18—Estimation of position or speed
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/10—Arrangements for controlling torque ripple, e.g. providing reduced torque ripple
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/14—Electronic commutators
- H02P6/16—Circuit arrangements for detecting position
- H02P6/18—Circuit arrangements for detecting position without separate position detecting elements
- H02P6/182—Circuit arrangements for detecting position without separate position detecting elements using back-emf in windings
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P2203/00—Indexing scheme relating to controlling arrangements characterised by the means for detecting the position of the rotor
- H02P2203/03—Determination of the rotor position, e.g. initial rotor position, during standstill or low speed operation
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 motor rotation speed omega and the rotor position angle theta through a sliding mode observer and a phase-locked loop based on SOGI e The method comprises the steps of carrying out a first treatment on the surface of the Next, the rotation speed omega is set * And the rotating speed omega passes through a rotating speed ring SMC controller to obtain a given torque T e * The method comprises the steps of carrying out a first treatment on the surface of the Then, the rotational speed ω and the d/q axis current i d /i q Observing the load disturbance valueAnd the load disturbance value is calculatedFeedforward compensation to a given torque T e * The method comprises the steps of carrying out a first treatment on the surface of the Finally, the observed rotation speed omega and the rotor position angle theta e Given torque T e * Load disturbance valueThree-phase voltage u obtained by sampling a /u b /u c Three-phase current i a /i b /i c And the substitution model prediction flux linkage control module performs operation. The invention adopts a sliding mode observer and a phase-locked loop improving mode to improve the rotor position estimation precision, simultaneously predicts flux linkage control based on a model, does not need current loop parameters and weight coefficient setting, combines the sliding mode control and a load disturbance observer, and improves the system robustness and the anti-interference capability.
Description
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 control technology of the permanent magnet synchronous motor without the position sensor utilizes the related electric signals in the windings to estimate the position and the rotating speed of the rotor, thereby omitting a mechanical sensor, reducing the volume and the cost of the motor and increasing the reliability of the system. Current position estimation algorithms can be divided into two types of methods, signal injection-based and observer-based. The former estimates rotor position using saliency of the motor, but continuous injection of excitation signals requires complex signal processing, resulting in low inverter voltage utilization and slow dynamic response. The latter relies on back emf in the dynamic model to estimate rotational speed, which is easy to implement in engineering. The sliding mode observer algorithm is one of the latter, and has the advantages of simple structure, strong robustness, quick dynamic response, difficult filtering, large rotor position angle estimation error, lag of an estimated value, poor low-speed performance and the like.
In addition, for the sensorless control technology of the permanent magnet synchronous motor, researchers have conducted extensive researches based on various control technologies, such as vector control, direct torque control, sliding mode control, fuzzy control and the like, but the control technologies have certain disadvantages in application, such as large torque pulsation, poor robustness, poor dynamic effect, complex algorithm and the like. Therefore, the research on the position-sensor-free control algorithm with the advantages of accurate rotor position tracking, strong system robustness, small torque pulsation and good dynamic effect has wide development prospect.
Disclosure of Invention
In view of the above, the invention aims to provide a sensorless model prediction flux linkage control method for a permanent magnet synchronous motor, which can accurately track rotor position information, improve system robustness, inhibit torque pulsation and improve dynamic operation effect.
The invention provides a permanent magnet synchronous motor sensorless model prediction flux linkage control method, which comprises the following steps:
s1, sampling three-phase current i a /i b /i c Sum voltage u a /u b /u c The alpha beta axis current i is obtained after CLARK and PARK coordinate transformation α /i β And alphaBeta-axis voltage u α /u β And dq axis current i d /i q Will alpha beta axis current i α /i β And alpha beta axis voltage u α /u β Substituting sliding mode observer to estimate extended back EMF E α And E is β ；
S2, expanding the back electromotive force E α And E is β Substituting into SOGI (second order generalized integrator) -based phase-locked loop, observing rotational speed omega and rotor position angle theta e ；
S3, the dq axis current i d /i q Substituting the rotation speed omega into a load disturbance observer to obtain a load disturbance value
S4, setting a given rotating speed omega * And the rotation speed omega obtains a given torque T through a rotation speed ring SMC (slip form control) controller e * Given torque T e * Obtaining a given magnetic linkage psi through MTPA s * ；
S5, the load disturbance value is calculatedFeedforward compensation to a given torque T e * And with torque T e The difference is made to obtain a torque error Te ', and the torque error Te' is subjected to PI controller to obtain a load angle deviation delta sf Calculated from the load angle delta sf The difference is made to obtain a load angle reference value delta sf * ；
S6, the voltage vector u of the three-phase inverter is calculated s The rotation speed omega and dq axis current id/iq are substituted into a flux linkage prediction module to obtain a flux linkage psi at the moment k+1 in a prediction mode d (k+1)/ψ q (k+1)；
S7, giving a magnetic linkage psi s * Load angle reference delta sf * Flux linkage ψ at time k+1 d (k+1)/ψ q (k+1) rotor position angle θ e Substituting the sum rotation speed omega into the minimum cost function module to output a duty ratio signal S a 、S b 、S c Then the duty cycle signal S a 、S b 、S c And the input three-phase inverter controls the on-off of the input three-phase inverter to realize the driving of the permanent magnet synchronous motor.
Further, the extended back electromotive force E in step S1 α And E is β The estimation formula of (2) is:
wherein sat(s) is a sliding mode surface control function,wherein: z α 、z β Controlling a function component for the sliding mode surface; />To estimate the current component; delta is boundary layer thickness; k (k) sat To change the self-adaptive rate, k of boundary layer sine saturation function sat ＝k l ·ω，k l Is a positive real number, ω is the rotational speed.
Further, the rotational speed ω and the rotor position angle θ in step S2 e The calculation formula of (2) is as follows:
θ e ＝∫ωdt,
wherein: lambda= (L) d -L q )(ωi d -pi q )+ωψ f ；K p /K i Proportional/integral coefficients, respectively;is the transfer function of the SOGI; epsilon θ (s) is the amount of positional angle error; epsilon' θ (s) is the filtered position angle error amount; k (k) θ Is an error amplification factor.
Further, in step S3, the load disturbance valueThe calculation formula of (2) is as follows:
wherein: u is a sliding mode surface control function; g is the feedback gain;is an electrical angular velocity estimate.
Further, the torque T is given in step S4 e * The calculation formula of (2) is as follows:
wherein:c is the sliding mode surface coefficient, ε, α and k n All are index approach rate coefficients, and satisfy: epsilon>0，α≥2，k n >0。
Compared with the prior art, the invention has the following advantages and effects:
the model prediction flux linkage control algorithm is applied to position-sensor-free control, a sliding mode observer, a rotating speed loop SMC controller and a load disturbance observer are designed by adopting a variable boundary layer sinusoidal saturation function so as to reduce system buffeting, SOGI is added into a phase-locked loop and real-time rotating speed is introduced to realize self-adaptive filtering adjustment, namely the rotating speed and rotor position angle obtained by the phase-locked loop based on the SOGI are more accurate, and the self-adaptive filtering adjustment is further input or fed back to the rotating speed loop SMC controller and the load disturbance observer to optimize deviation adjustment and disturbance compensation, so that the dynamic effect and robustness of a control system are improved, and torque pulsation is restrained. Meanwhile, the salient pole permanent magnet synchronous motor is used as a research object, so that the application range of the control method is widened.
Drawings
FIG. 1 is a control block diagram of a permanent magnet synchronous motor sensorless model predictive flux linkage control method provided by an embodiment of the invention;
fig. 2 is a schematic block diagram of an SOGI-based phase-locked loop provided by an embodiment of the present invention;
FIG. 3 is a functional block diagram of a load disturbance observer provided by an embodiment of the present invention;
FIG. 4 is a schematic block diagram of a rotational speed loop SMC controller provided by an embodiment of the present invention;
fig. 5 is a diagram of simulation results of the rotational speed of the permanent magnet synchronous motor of the sensorless control algorithm provided by the embodiment of the invention;
FIG. 6 is a comparison chart of simulation results of rotor position angle errors of a permanent magnet synchronous motor according to a position sensorless control algorithm and a conventional position sensorless algorithm provided by an embodiment of the present invention;
FIG. 7 is a graph comparing simulation results of torque of a permanent magnet synchronous motor with a sensorless control algorithm and a conventional sensorless control algorithm according to 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 by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and not limited to the following examples.
As shown in fig. 1, the invention provides a permanent magnet synchronous motor sensorless model prediction flux linkage control method, which comprises the following steps:
s1, sampling three-phase current i a /i b /i c Sum voltage u a /u b /u c The alpha beta axis current i is obtained after CLARK and PARK coordinate transformation α /i β And alpha beta axis voltage u α /u β And dq axis current i d /i q Will alpha beta axis current i α /i β And alpha beta axis voltage u α /u β Substituting sliding mode observer to estimate extended back EMF E α And E is β ；
Specifically, the invention expands the back electromotive force E α And E is β The estimation process of (2) is described as follows:
the stator voltage equation for the αβ coordinate system is:
wherein u is α 、u β Respectively alpha and beta axis voltages; i.e α 、i β Respectively alpha and beta axis currents; l (L) d 、L q Respectively dq axis inductances; r is stator resistance; omega is the rotational speed; p is a differential operator; e (E) α 、E β To extend back emf; psi phi type f Is a permanent magnet flux linkage; θ e Is the rotor position angle.
The equation (1) is rewritten as a current state equation having a stator current as a state variable:
the slip plane s (x) =0 is chosen on the stator current trajectory as:
wherein:to estimate the current component; />To estimate the current error component.
To obtain the extended back emf, the sliding mode observer is designed to:
wherein: z α 、z β The function component is controlled for the sliding mode surface.
Taking the difference between equations (6) and (3), the error equation for the resulting stator current is:
the sliding mode surface control functions in the formulas (5) and (6) are shown as a formula (7).
Wherein: delta is boundary layer thickness, k sat To change the self-adaptive rate, k of boundary layer sine saturation function sat ＝k l ·ω，k l Is a positive real number, ω is the rotational speed. The sliding mode surface control function can effectively reduce 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 slip plane, i.e. s (x) =0, the observer state will be maintained. The equivalent control principle according to the sliding mode variable structure control can be obtained:
s2, expanding the back electromotive force E α And E is β Substituting into SOGI-based phase-locked loop, and observing rotation speed omega and rotor position angle theta through SOGI-based phase-locked loop e ；
Specifically, the rotational speed ω and the rotor position angle θ in the present invention e The calculation process of (1) is described as follows:
the transfer function of the SOGI is:
wherein: lambda= (L) d -L q )(ωi d -pi q )+ωψ f ，ε θ (s) is the position angle error amount ε' θ (s) is the filtered position angle error amount, k θ Is an error amplification factor.
Expanding the counter electromotive force E in the formula (9) α And E is β Inputting into a phase-locked loop based on SOGI to obtain rotation speed omega and rotor position angle theta e The functional block diagram is shown in fig. 2. The SOGI is added into the phase-locked loop and introduced into the real-time rotating speed to carry out bandwidth and error adjustment, so that the self-adaptive filtering effect of the phase-locked loop is improved, harmonic interference caused by buffeting of a system is reduced, and the estimation precision of the rotor position angle is improved.
Wherein: k (K) p Is a proportionality coefficient, K i Is an integral coefficient.
S3, the dq axis current i d /i q Substituting the rotation speed omega into a load disturbance observer to obtain a load disturbance value
In particular, the load disturbance value in the present inventionThe calculation process of (1) is described as follows:
the voltage equation under the dq coordinate system is:
torque equation:
equation of motion:
wherein T is l Is the load torque; b is friction torque viscosity coefficient; j is the moment of inertia.
According to PMSM torque and motion equation shown in formulas (13) and (14), and taking load torque as an expansion state variable, constructing an expansion state equation as follows:
wherein: since the electrical time constant is much smaller than the mechanical time constant, it can be considered that the load torque is constant during the control period, i.e
Based on the equation (15), the slip mode plane is defined by using the load torque and the rotor electric angular velocity as state variables, using the velocity estimation error as a slip mode switching planeEstablishing an extended sliding mode observer as
Wherein:g is the feedback gain; />An electrical angular velocity estimate and a load disturbance estimate, respectively.
According to the equivalent control principle of sliding mode variable structure control, the load disturbance estimated value can be obtainedThe functional block diagram is shown in fig. 3:
as can be seen from equation (17), the load disturbance observer also adopts a sliding mode surface control function with the capability of real-time adjustment along with the change of the rotating speed, so that the obtained load disturbance estimated value is more real-time and accurate.
S4, setting a given rotating speed omega * And the rotation speed omega obtains a given torque T through a rotation speed ring SMC controller e * Given torque T e * Obtaining a given magnetic linkage psi through MTPA s * ；
Specifically, the given torque T in the present invention e * Given flux linkage ψ s * The calculation process of (1) is described as follows:
the rotational speed state equation is constructed as follows:
from formulae (14) and (18):
the linear sliding mode surface function is selected as follows: s=cx 1 +x 2 (20)
Deriving formula (20):
substituting (21) into formula (20) to obtain:
the design index approach rate is: s= - ε|x 1 |αsat(s)-k n s，ε>0，α≥2，k n >0 (23)
Substituting the index approach rate into the equation (22) to obtain a given torque T e * The functional block diagram is shown in fig. 4:
as can be seen from formula (24), at- ε|x 1 | α s and-k n Under the combined action of s, the state variable can quickly approach the sliding mode surface to be stable, and sat(s) can further reduce system buffeting.
Will beAs a system disturbance feedforward compensation to a load torque input, the obtained torque error is:
the stability of the approach rate proves that:
the reference value of the flux linkage amplitude is calculated by an MTPA algorithm, and the method considers the influence of weak magnetism and efficiency when the motor operates, and the calculation formula is as follows:
s5, the load disturbance value is calculatedFeedforward compensation to a given torque T e * And with torque T e Difference is made to obtain torque error T e ' Torque error T e ' obtaining the load angle deviation delta via PI controller sf Calculated from the load angle delta sf The difference is made to obtain a load angle reference value delta sf * ；
In step S5, the load angle reference value delta in the invention sf * The calculation process of (1) is described as follows:
the mathematical model of the permanent magnet synchronous motor under dq coordinates is as follows:
substituting equation (27) into equation (12), the derivative of the current is:
discretizing the formula (29) yields:
wherein: t (T) s For the control period.
Substituting equation (30) into (29) yields a predicted stator flux linkage at time (k+1) as:
the stator current i at the current moment obtained by sampling s (k) Applied in equations (27) - (29), the stator flux linkage vector ψ at time k s (k) And torque T e (k) Can be calculated. According to the definition of the load angle, the load angle delta at the moment k sf (k) Can be calculated as:
will give a torque T e * Torque T at time k e (k) The difference value of (2) is input into a PI controller to obtain the load angular deviation as follows:
the load angle delta at time k sf (k) Angular deviation from load delta sf (k) The reference load angle delta at time (k+1) is obtained by addition sf * (k+1) is:
wherein K is PT And K IT The proportional gain and the integral gain of the rotational speed PI controller are respectively.
S6, voltage vector u of two-level voltage source type inverter s The rotation speed omega and dq axis current id/iq are substituted into a flux linkage prediction module to obtain a flux linkage psi at the moment k+1 in a prediction mode d (k+1)/ψ q (k+1)；
S7, giving a magnetic linkage psi s * Load angle reference delta sf * Flux linkage ψ at time k+1 d (k+1)/ψ q (k+1) rotor position angle θ e Substituting the sum rotation speed omega into the minimum cost function module to output a duty ratio signal S a 、S b 、S c Then the duty cycle signal S a 、S b 、S c And the input three-phase inverter controls the on-off of the input three-phase inverter to realize the driving of the permanent magnet synchronous motor.
Step S6, the flux linkage psi at time k+1 in the invention d (k+1)/ψ q The prediction process of (k+1) is described as follows:
combining equation (33) and equation (34), the (k+1) moment flux linkage vector reference value in dq coordinate system is:
step S7, the operation principle of the minimum cost function module in the 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 u 6), respectively calculating corresponding objective functions of the different flux linkage vectors, and selecting a voltage vector with the minimum objective function as the optimal output of the converter, wherein the objective functions are as follows:
wherein: psi phi type d (k+1)/ψ q Flux linkage vector of moment k+1 (k+1), ψ d * (k+1)/ψ q * And (k+1) is a flux linkage vector reference value at the time (k+1).
According to the control block diagram shown in fig. 1, MATLAB/SIMULINK software is used for constructing a permanent magnet synchronous motor sensorless model prediction flux linkage control system simulation, and motor parameters are selected as follows: rated power 600W, rated rotating speed 750rpm, rated torque 7.6N.m, pole pair number 13, permanent magnet flux linkage amplitude 0.08Wb, armature winding resistance 0.8Ω, AC-DC axis inductances of 6.5mH, 6.3mH, rotational inertia 0.004 kg.m 2 Friction torque viscosity coefficient is 0.0004n·m·s. The given conditions for simulation are: the initial set no-load speed 50rpm,0.2s time mutation to 500rpm,0.4s time loading 4N m. Under the above conditions, the simulation results of the rotational 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 fig. 7. A control block diagram of a 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 rotation speed, the estimated rotation speed pulsation is small, overshoot is small when the rotation speed is suddenly changed, the rotation speed value can be set on short-time tracking when the torque is suddenly changed, and the robustness is good; as can be seen from fig. 6 and 7, the rotor position angle tracking method of the invention is more accurate, and has stronger torque pulsation suppression capability.
The foregoing description of the invention is merely exemplary of the invention. Various modifications or additions to the described embodiments may be made by those skilled in the art to which the invention pertains or in a similar manner, without departing from the spirit of the invention or beyond the scope of the invention as defined in the appended claims.
Claims (4)
1. A permanent magnet synchronous motor sensorless model prediction flux linkage control method is characterized in that: comprises the following steps:
s1, sampling three-phase current i a /i b /i c Sum voltage u a /u b /u c The alpha beta axis current i is obtained after CLARK and PARK coordinate transformation α /i β And alpha beta axis voltage u α /u β And dq axis current i d /i q Will alpha beta axis current i α /i β And alpha beta axis voltage u α /u β Substituting sliding mode observer to estimate extended back EMF E α And E is β ；
Wherein the extended back electromotive force E α And E is β The estimation formula of (2) is:
wherein sat(s) is a sliding mode surface control function,z α 、z β controlling a function component for the sliding mode surface; /> To estimate the current component; delta is boundary layer thickness; k (k) sat To change the self-adaptive rate, k of boundary layer sine saturation function sat ＝k l ·ω，k l Is a positive real number, and omega is the rotating speed;
s2, expanding the back electromotive force E α And E is β Substituting into SOGI-based phase-locked loop to observe rotational speed omega and rotor position angle theta e ；
S3, the dq axis current i d /i q Substituting the rotation speed omega into a load disturbance observer to obtain a load disturbance value
S4, setting a given rotating speed omega * And the rotation speed omega obtains a given torque T through a rotation speed ring SMC controller e * Given torque T e * Obtaining a given magnetic linkage psi through MTPA s * ；
S5, the load disturbance value is calculatedFeedforward compensation to a given torque T e * And with torque T e Difference is made to obtain torque error T' e Torque error T' e Obtaining the load angle deviation delta through a PI controller sf Calculated from the load angle delta sf Difference is made to obtain the load angle reference value +.>
S6, the voltage vector u of the three-phase inverter is calculated s The rotation speed omega and dq axis current id/iq are substituted into a flux linkage prediction module to obtain a flux linkage psi at the moment k+1 in a prediction mode d (k+1)/ψ q (k+1)；
S7, giving a magnetic linkage psi s * Load angle reference valueFlux linkage ψ at time k+1 d (k+1)/ψ q (k+1) rotor position angle θ e Substituting the sum rotation speed omega into the minimum cost function module to output a duty ratio signal S a 、S b 、S c Then the duty cycle signal S a 、S b 、S c The input three-phase inverter controls the on-off of the input three-phase inverter to realize the permanent magnet synchronizationAnd (3) driving a motor.
2. A sensorless model predictive flux linkage control method of permanent magnet synchronous motor according to claim 1, wherein said rotation speed ω and rotor position angle θ in step S2 e The calculation formula of (2) is as follows:
θ e ＝∫ ω dt
wherein: lambda= (L) d -L q )(ωi d -pi q )+ωψ f ；K p /K i Proportional/integral coefficients, respectively;is the transfer function of the SOGI; epsilon θ (s) is the amount of positional angle error; epsilon' θ (s) is the filtered position angle error amount; k (k) θ Is an error amplification factor.
3. The sensorless model predictive flux linkage control method of permanent magnet synchronous motor according to claim 2, wherein the load disturbance value in step S3The calculation formula of (2) is as follows:
wherein: u is a sliding mode surface control function; g is the feedback gain;is an electrical angular velocity estimate.
4. A sensorless model predicted magnet for a permanent magnet synchronous motor according to claim 2The chain control method is characterized in that the torque T is set in step S4 e * The calculation formula of (2) is as follows:
wherein: c is the sliding mode surface coefficient, ε, α and k n All are index approach rate coefficients, and satisfy: epsilon>0，α≥2，k n >0。
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| CN111987943B (en) * | 2020-07-23 | 2022-11-11 | 西安理工大学 | Robust performance improving method for model predictive control of permanent magnet synchronous motor |
| CN114844405A (en) * | 2020-09-04 | 2022-08-02 | 湖南工业大学 | Integration sliding mode control system of permanent magnet synchronous motor |
| CN112311290B (en) * | 2020-10-26 | 2022-03-22 | 江苏大学 | Robust prediction permanent magnet synchronous hub motor sensorless controller |
| CN112187127B (en) * | 2020-10-26 | 2022-02-01 | 江苏省电力试验研究院有限公司 | Permanent magnet synchronous motor control method |
| CN112448632B (en) * | 2020-11-12 | 2022-05-27 | 湘潭大学 | SPMSM sensorless composite 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 |
| CN112737457B (en) * | 2020-12-25 | 2023-08-01 | 中车永济电机有限公司 | Stability control method for permanent magnet auxiliary synchronous reluctance motor |
| CN113437912B (en) * | 2021-07-09 | 2022-11-01 | 中南大学 | Prediction control method and system for strong robustness model of permanent magnet synchronous motor |
| CN113644854B (en) * | 2021-08-11 | 2023-08-08 | 吉林大学 | Permanent magnet synchronous motor angle identification system and method |
| CN114204854B (en) * | 2022-01-06 | 2024-03-19 | 江苏大学 | Open-circuit fault-tolerant position-free control method for five-phase 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 |
| CN116248003B (en) * | 2023-05-06 | 2023-07-28 | 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 |
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