CN112422002A - Robust permanent magnet synchronous motor single current sensor prediction control method - Google Patents
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- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
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- 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
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- H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
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Abstract
A single current sensor prediction control method of a permanent magnet synchronous motor with robustness is disclosed, wherein alpha axis expansion state quantity can change along with voltage disturbance caused by parameter disturbance in real time, and the beta axis expansion state quantity can synchronously follow beta axis voltage disturbance when motor model parameters are inaccurate by combining the deduced relation between the alpha axis expansion state quantity and the beta axis expansion state quantity, so that the robustness of the parameters is realized, and the restriction of the inaccurate motor model parameters on the accuracy of current reconstruction is effectively overcome. Besides the parameters of the rotor electrical angular velocity, the rotor position, the stator voltage and the motor phase a current, the reconstruction of the complete information of the motor three-phase current can be realized without other additional parameters in the algorithm execution process of the extended state observer, and the difficulty in obtaining the parameters of the extended state observer and the calculation amount in the reconstruction process are obviously reduced.
Description
Technical Field
The invention relates to the technical field of permanent magnet synchronous motor control, in particular to a single-phase current sensor prediction control technology for improving robustness.
Background
At present, in some prior arts for controlling a permanent magnet synchronous motor, a single current sensor is used for realizing the control, and compared with the permanent magnet synchronous motor control without a position sensor, the technical means can not only realize the purpose of reducing the number of physical sensors, but also realize a good motor speed control effect under the condition of low speed of the motor.
The existing single current sensor control implementation mode mostly adopts a single direct current bus current sensor, and reconstructs the three-phase current of the motor according to the relation between the bus current and the phase current, but the method firstly introduces noise errors which cannot be eliminated, secondly has a current reconstruction blind area, and the method for compensating the current reconstruction blind area is complex. In the few recent prior arts, phase current reconstruction based on a single phase current sensor is considered, but most of the current reconstruction methods using a single phase current sensor are based on a motor model method, so that the defect that the dependence of the reconstruction effect on the accuracy of motor model parameters is extremely high exists.
Disclosure of Invention
In view of this, it is preferable that,
in order to solve the problem that the reconstruction of phase current excessively depends on the accuracy of motor model parameters in the prediction control of a single phase current sensor of the existing permanent magnet synchronous motor, the invention provides a robust prediction control method of the single phase current sensor of the permanent magnet synchronous motor, which specifically comprises the following steps:
firstly, acquiring a-phase current, a rotating speed and a rotor position angle of a permanent magnet synchronous motor in real time on line;
and step two, taking the phase-a current, the rotating speed and the rotor position angle collected in the step one as input quantities in an alpha-beta coordinate system, and deducing the relation of the voltage disturbance quantities of an alpha axis and a beta axis:
fα=-ΔRs×iα+ωe×Δψf×sinθ
in the formula (f)α,fβThe voltage disturbance quantity caused by inaccurate motor model parameters; i.e. iαMeasuring the obtained alpha-axis stator current; delta psifEstimating an error for the motor flux linkage; Δ RsEstimating an error for the stator resistance; omegaeIs the electrical angular velocity of the rotor; theta is a rotor position angle;
establishing a phase current reconstruction equation based on an extended state observer algorithm, updating and calculating alpha-axis and beta-axis currents in an alpha-beta coordinate system in real time and outputting the alpha-axis and beta-axis currents to realize the reconstruction of abc three-phase currents, and then carrying out Park transformation on the alpha-axis and beta-axis currents to obtain d-axis and q-axis currents in a d-q coordinate system;
step three, establishing a dead-beat current prediction control model, and calculating the reference voltage at the next moment in real time by using the motor rotating speed, the rotor position angle and the current parameters acquired in the step one; and performing SVPWM control by using the calculated reference voltage.
Further, in the second step, the phase current reconstruction equation based on the extended state observer algorithm specifically adopts the following formula:
wherein,respectively are the observed values of alpha axis current and beta axis current; u. ofα,uβIs the stator voltage under an alpha-beta coordinate system; psir_changeIs the estimated rotor flux linkage; rs_changeIs an estimated stator resistance; l issIs a stator inductance; observing current with epsilon as alpha axisAnd measuring current iαThe difference value is obtained by comparing the difference value,is fαIs an adjustable parameter of the fal function for achieving the desired non-smooth feedback, beta01、β02All the parameters are adjustable parameters, and optimal control effect values are selected according to different motor parameters; t is time;
the current observed value under the alpha-beta coordinate system can be obtained by the formulaTaking the current observed valueAs an output current value of the extended state observer;
the fal function in the extended state observer equation is:
wherein, alpha, delta are adjustable parameters, and are adjusted according to the control requirement, when alpha is less than 1, the fal function has: small error, large gain; large error and small gain.
Since, the transformation of the three-phase coordinate system current into the α - β coordinate system current:
due to ia+ib+icBy (i) < 0 >a+ib) In place of icThen the above formula can be expressed as:
it can be seen that: alpha axis current i under alpha-beta static coordinate systemα=iaThen the alpha axis current i under the alpha-beta coordinate systemαNamely the collected a-phase current, the beta axis current i is estimated only under the alpha-beta coordinate systemβAnd complete three-phase current information can be obtained. Thus, using the above extended observer yields iβThe current is applied. Namely, the reconstruction of the abc three-phase current is completed.
Further, the obtaining of the reference voltage at the next time by using the deadbeat current prediction control model in the third step specifically includes:
in the formula ud(k)、uq(k) The stator voltage at the current moment; u. ofd(k+1)、uq(k +1) is the reference voltage at the next time; t issIs a control period; i.e. iqrefIs a q-axis reference current; psirIs a motor rotor flux linkage.
According to the method provided by the invention, the alpha-axis expansion state quantity can change along with the voltage disturbance caused by parameter disturbance in real time, and the beta-axis expansion state quantity can synchronously follow the beta-axis voltage disturbance when the motor model parameter is inaccurate by combining the deduced relation between the alpha-axis expansion state quantity and the beta-axis expansion state quantity, so that the parameter robustness is realized, and the restriction of the motor model parameter inaccuracy on the current reconstruction accuracy is effectively overcome. Besides the parameters of the rotor electrical angular velocity, the rotor position, the stator voltage and the motor phase a current, the reconstruction of the complete information of the motor three-phase current can be realized without other additional parameters in the algorithm execution process of the extended state observer, and the difficulty in obtaining the parameters of the extended state observer and the calculation amount in the reconstruction process are obviously reduced.
Drawings
FIG. 1 is a block diagram of a PMSM control model according to the method of the present invention;
fig. 2 is a graph showing the operation of a permanent magnet synchronous motor in which predictive control is implemented according to a preferred embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a robust permanent magnet synchronous motor single current sensor predictive control method, as shown in fig. 1, which specifically comprises the following steps:
firstly, acquiring a-phase current, a rotating speed and a rotor position angle of a permanent magnet synchronous motor in real time on line;
and step two, taking the phase-a current, the rotating speed and the rotor position angle collected in the step one as input quantities in an alpha-beta coordinate system, and deducing the relation of the voltage disturbance quantities of an alpha axis and a beta axis:
fα=-ΔRs×iα+ωe×Δψf×sinθ
in the formula (f)α,fβThe voltage disturbance quantity caused by inaccurate motor model parameters; i.e. iαMeasuring the obtained alpha-axis stator current; delta psifEstimating an error for the motor flux linkage; Δ RsEstimating an error for the stator resistance; omegaeIs the electrical angular velocity of the rotor; theta is a rotor position angle;
establishing a phase current reconstruction equation based on an extended state observer algorithm, updating and calculating alpha-axis and beta-axis currents in an alpha-beta coordinate system in real time and outputting the alpha-axis and beta-axis currents to realize the reconstruction of abc three-phase currents, and then carrying out Park transformation on the alpha-axis and beta-axis currents to obtain d-axis and q-axis currents in a d-q coordinate system;
step three, establishing a dead-beat current prediction control model, and calculating the reference voltage at the next moment in real time by using the motor rotating speed, the rotor position angle and the current parameters acquired in the step one; and performing SVPWM control by using the calculated reference voltage.
In the first step, the phase a current of the permanent magnet synchronous motor is acquired on line in real time, and because the conversion from the abc three-phase coordinate system current to the alpha-beta coordinate system current is as follows:
due to ia+ib+icBy (i) < 0 >a+ib) In place of icThen the above formula can be expressed as:
it can be seen that: alpha axis current i under alpha-beta static coordinate systemα=iaThen the alpha axis current i under the alpha-beta coordinate systemαNamely the collected a-phase current, the beta axis current i is estimated only under the alpha-beta coordinate systemβAnd complete three-phase current information can be obtained. Thus, using the above extended observer yields iβThe current is applied. Namely, the reconstruction of the abc three-phase current is completed.
In the second step, firstly, a voltage equation of the permanent magnet synchronous motor under an alpha-beta coordinate system is established:
in the formula uα,uβIs the stator voltage under an alpha-beta coordinate system; i.e. iα,iβIs stator current under an alpha-beta coordinate system; psirIs the actual rotor flux linkage; rsActual stator resistance; l issIs a stator inductance; omegaeIs the electrical angular velocity of the rotor; θ is the rotor position angle.
According to the voltage equation of the formula, when the estimated motor parameters are inaccurate, the voltage equation of the permanent magnet synchronous motor model under an alpha-beta coordinate system can be obtained:
in the formula,stator currents of alpha and beta axes in the motor model are respectively; psif_changeIs an estimated motor rotor flux linkage; rs_changeIs an estimated stator resistance; f. ofα,fβRespectively unknown disturbance quantities of alpha and beta axis voltages caused by inaccurate motor model parameters; the rest parameters are the same as the above formula.
The subtraction of the two equations yields:
if the observation current of the motor model is to be realizedAre respectively equal to the actual current iα,iβThen, it needs to satisfy:
(Rs_change-Rs)×iα-ωe×(ψf_change-ψf)×sinθ+fα=0
(Rs_change-Rs)×iβ+ωe×(ψf_change-ψf)×cosθ+fβ=0
fα=-ΔRs×iα+ωe×Δψf×sinθ
fβ=-ΔRs×iβ-ωe×Δψf×cosθ
wherein: Δ Rs=(Rs_change-Rs) Representing the motor model resistance estimation error, Δ ψf=(ψf_change-ψf) And representing the flux linkage estimation error of the motor model.
The transformation formula from the α - β coordinate system to the d-q coordinate system: i.e. id=iα×cosθ+iβX sin theta and reference currentThen one can approximate:
the current observed value is substituted into the relation between the current observed value and the actual current to obtain the following result:
fα=-ΔRs×iα+ωe×Δψf×sinθ
the formula shows that: voltage caused by inaccurate parameters of motor model under alpha-beta coordinate system
thus, in conjunction with the extended state observer theory, let fα,fβAs an extended state variable, a phase current reconstruction equation based on an extended state observer algorithm is available:
wherein iαMeasuring the obtained alpha-axis stator current;respectively are the observed values of alpha axis current and beta axis current; u. ofα,uβIs the stator voltage under an alpha-beta coordinate system; f. ofα,fβUnknown disturbance quantities of alpha axis voltage and beta axis voltage respectively; psir_changeIs the estimated rotor flux linkage; rs_changeIs an estimated stator resistance; l issIs a stator inductance; omegaeIs the electrical angular velocity of the rotor; theta is a rotor position angle; observing current with epsilon as alpha axisAnd measuring current iαA difference value;is fαA derivative of (a); α 1, α 2, δ are adjustable parameters of the fal function for achieving the desired non-smooth feedback; beta is a01、β02All the parameters are adjustable parameters, and optimal control effect values are selected according to different motor parameters;
the current observed value under the alpha-beta coordinate system can be obtained by the formulaTaking the current observed valueIs the output current value of the extended state observer;
preferably, in order to preventTending to infinity, causes transient current pulses that should be clipped, in one example of the invention:
the fal function in the extended state observer equation is:
when α < 1, the fal function has: small error, large gain; large error and small gain.
In the third step, a dead-beat current prediction control model is used to obtain a reference voltage at the next moment, which specifically includes:
in the formula ud(k)、uq(k) The stator voltage at the current moment; u. ofd(k+1)、uq(k +1) is the reference voltage at the next time; t issIs a control period; i.e. iqrefIs a q-axis reference current; psirIs a motor rotor flux linkage.
Preferably, when the calculated reference voltage exceeds the maximum output voltage limit of the SVPWM, the output reference voltage needs to be adjusted to obtain a reference voltage within the SVPWM output range:
in the formula,the reference voltage within the corrected SVPWM output voltage range under the d-q coordinate system is obtained; u shapedcIs the dc bus voltage.
FIG. 2 shows a preferred embodiment according to the invention, in psir_change=1.5*ψrAnd when the motor is used, a single current sensor is adopted, and the reconstructed current information of the extended state observer is utilized to carry out predictive control on the rotating speed, the torque and the reconstructed three-phase current curve. As can be seen from fig. 2, under the condition that the estimated flux linkage is 1.5 times of the actual flux linkage, the three-phase current reconstructed by the extended state observer has only small current fluctuation, and the current waveform is very close to a perfect sine wave; the rotating speed change condition of the motor shows that the three-phase current reconstructed by the extended state observer is used for the prediction control of the motor, and the rotating speed can accurately follow the control requirement in time; according to the torque change condition of the motor, the motor is subjected to predictive control by using the three-phase current reconstructed by the extended state observer, and the motor has only small torque ripple (less than 10% of the maximum torque). Simulation results show that the single current sensor predictive control method with robustness can well reconstruct three-phase current information when motor model parameters are inaccurate, and the reconstructed three-phase current can completely replace actual three-phase current to be used as closed-loop feedback quantity to control the motor.
It should be understood that, the sequence numbers of the steps in the embodiments of the present invention do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A robustness permanent magnet synchronous motor single current sensor prediction control method is characterized in that: the method specifically comprises the following steps:
firstly, acquiring a-phase current, a rotating speed and a rotor position angle of a permanent magnet synchronous motor in real time on line;
and step two, taking the phase-a current, the rotating speed and the rotor position angle collected in the step one as input quantities in an alpha-beta coordinate system, and deducing the relation of the voltage disturbance quantities of an alpha axis and a beta axis:
fα=-ΔRs×iα+ωe×Δψf×sinθ
in the formula (f)α,fβThe voltage disturbance quantity caused by inaccurate motor model parameters; i.e. iαMeasuring the obtained alpha-axis stator current; delta psifEstimating an error for the motor flux linkage; Δ RsEstimating an error for the stator resistance; omegaeIs the electrical angular velocity of the rotor; theta is a rotor position angle;
establishing a phase current reconstruction equation based on an extended state observer algorithm, updating and calculating alpha-axis and beta-axis currents in an alpha-beta coordinate system in real time and outputting the alpha-axis and beta-axis currents to realize the reconstruction of abc three-phase currents, and then carrying out Park transformation on the alpha-axis and beta-axis currents to obtain d-axis and q-axis currents in a d-q coordinate system;
step three, establishing a dead-beat current prediction control model, and calculating the reference voltage at the next moment in real time by using the motor rotating speed, the rotor position angle and the current parameters acquired in the step one; and performing SVPWM control by using the calculated reference voltage.
2. The method of claim 1, wherein: in the second step, the phase current reconstruction equation based on the extended state observer algorithm specifically adopts the following formula:
wherein,respectively are the observed values of alpha axis current and beta axis current; u. ofα,uβIs the stator voltage under an alpha-beta coordinate system; psir_changeIs the estimated rotor flux linkage; rs_changeIs an estimated stator resistance; l issIs a stator inductance; observing current with epsilon as alpha axisAnd measuring the current iαThe difference value of (a) to (b),is fαThe derivatives of (a 1), (a 2), and (δ) are adjustable parameters of the fal function; beta is a01、β02Are all adjustable parameters; t is time;
the fal function in the extended state observer equation is:
wherein alpha and delta are adjustable parameters.
3. The method of claim 2, wherein: in the third step, a dead-beat current prediction control model is used to obtain a reference voltage at the next moment, which specifically includes:
in the formula ud(k)、uq(k) The stator voltage at the current moment; u. ofd(k+1)、uq(k +1) is the reference voltage at the next time; t issIs a control period; i.e. iqrefIs a q-axis reference current; psirIs a motor rotor flux linkage.
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