CN112003522A - Parameter identification-based single current sensor control method for permanent magnet synchronous motor - Google Patents

Parameter identification-based single current sensor control method for permanent magnet synchronous motor Download PDF

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CN112003522A
CN112003522A CN202010712669.9A CN202010712669A CN112003522A CN 112003522 A CN112003522 A CN 112003522A CN 202010712669 A CN202010712669 A CN 202010712669A CN 112003522 A CN112003522 A CN 112003522A
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permanent magnet
current
stator
parameter identification
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CN112003522B (en
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张硕
董岳林
张承宁
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Beijing Institute of Technology BIT
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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
    • 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
    • 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
    • H02P21/141—Flux estimation
    • 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
    • H02P21/22—Current control, e.g. using a current control loop
    • 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
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/022—Synchronous motors
    • 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
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
    • 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
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
    • H02P2207/055—Surface mounted magnet motors

Abstract

A permanent magnet synchronous motor single current sensor control method based on parameter identification is characterized in that a parameter identification equation of stator inductance and permanent magnet flux linkage is decoupled by using current errors, parameters are identified on line by using a recursive least square method with a forgetting factor, phase current reconstruction is carried out based on a motor model, phase current information obtained through reconstruction replaces phase current information measured by a sensor and is fed back to a motor control system to realize predictive control, the speed of a parameter identification process is high, the followability of an identification result can be improved, and the method has a high application value.

Description

Parameter identification-based single current sensor control method for permanent magnet synchronous motor
Technical Field
The invention relates to the technical field of permanent magnet synchronous motor control, in particular to permanent magnet synchronous motor single-phase current sensor control, which is realized based on online parameter identification and is suitable for a permanent magnet synchronous motor control system with only a single phase current sensor.
Background
In various control strategies for a permanent magnet synchronous motor, motor phase current information needs to be accurately acquired, in order to obtain three-phase current information, at least two current sensors are usually installed on hardware to complete acquisition of phase current information, but most of the high-accuracy current sensors are expensive and occupy a space in a motor controller. In some industrial fields sensitive to production cost and aerospace fields with high requirements on the reliability of the driver, the single current sensor is used for reconstructing three-phase current, so that errors caused by parameter differences among different sensors can be solved, the size and the weight of the driver can be reduced, the cost of the whole system is reduced, and the method has very important practical significance.
The current common single current sensor control method mainly comprises single current sensor control based on direct current bus current detection and single current sensor control based on single-phase current detection. The control method of the single current sensor based on the direct current bus current detection has the defects that a phase current reconstruction blind area exists, and when a space voltage vector is large or a certain basic voltage vector is too large, phase current information cannot be accurately obtained, and in addition, the phase current information obtained by the method often comprises more harmonic information.
The parameter identification of the motor is generally classified into an off-line parameter identification and an on-line parameter identification. The off-line parameter identification method is a parameter obtained under the conditions of motor idling and motor stalling, the motor parameter still changes in the actual operation process, and the motor parameter must be identified on line. Therefore, how to utilize the advantages of the existing single current sensor control method and the suitable parameter identification method to realize the control of the permanent magnet synchronous motor with better effect and strong practicability is a technical problem which needs to be solved urgently in the field.
Disclosure of Invention
In view of this, the present invention provides a method for controlling a single current sensor of a permanent magnet synchronous motor based on parameter identification, which specifically includes the following steps:
the method comprises the following steps of firstly, acquiring the rotating speed, the rotor position angle and the a-phase current of the permanent magnet synchronous motor in real time;
step two, establishing a simplified mathematical model of the permanent magnet synchronous motor under an alpha and beta axis coordinate system;
discretizing the differential quantity in the simplified mathematical model, and deducing a parameter identification equation of the stator inductance and the rotor flux linkage based on the a-phase measured current;
step four, performing online parameter identification on the stator inductance and the rotor flux linkage by adopting a recursive least square method;
fifthly, reconstructing phase current based on a model by using the actual motor parameters obtained by parameter identification;
and step six, performing permanent magnet synchronous motor prediction control by using the three-phase current obtained by phase current reconstruction.
Further, the simplified mathematical model of the permanent magnet synchronous motor under the α β axis coordinate system established in the second step is specifically based on the following assumptions:
(1) the magnetic circuit characteristic of the permanent magnet synchronous motor is linear, and the phenomena of magnetic hysteresis and magnetic circuit saturation are avoided;
(2) the three-phase winding parameters of the stator are the same, the angles are 120 degrees apart, and the magnetic field formed in the air gap is in sinusoidal distribution;
(3) air gaps formed between the stator windings and the rotor permanent magnets are uniformly distributed;
the permanent magnet synchronous motor adopts a surface-mounted structure, and a simplified mathematical model established from the structure is as follows:
Figure BDA0002597142900000021
in the formula uα、uβIs the stator voltage under an alpha beta coordinate system; i.e. iα、iβIs the stator current under an alpha beta coordinate system; ΨrIs a permanent magnet flux linkage; rsIs a stator resistor; l issIs a stator inductance; omegaeIs the electrical angular velocity of the rotor; θ is the rotor position angle and t is time.
Further, the step three of deriving a parameter identification equation based on the stator inductance and the rotor flux linkage of the a-phase measured current specifically includes:
discretizing the differential quantity in the equation in the time of k-k +1, and making:
Figure BDA0002597142900000022
and substituting the original equation to obtain a model of the discretized permanent magnet synchronous motor under an alpha beta axis coordinate system:
Figure BDA0002597142900000023
wherein iα(k-1)、iβ(k +1) are stator current vectors at the moment k +1, respectively; i.e. iα(k)、iβ(k) Stator current vectors at time k are respectively; ts is a sampling interval;
because only one phase current sensor is adopted in the method, only a-phase current, namely alpha-axis current, can be obtained, and the subsequent parameter identification equations are derived based on the alpha-axis equation.
Adding the variation of the actual parameters of the motor into an alpha-axis stator current equation at the sampling moment of k +1 to obtain alpha-axis current at the sampling moment of k +1 considering the variation of the parameters of the motor: ,
Figure BDA0002597142900000024
wherein, i'α(k +1) is the α -axis stator current at the k +1 sampling time, Δ L, taking into account the variation of the motor parametersAs a component of stator inductance variation, Δ RsAs a component of stator resistance variation, Δ ΨrIs a permanent magnet flux linkage variation component;
calculating disturbance quantity of alpha-axis stator current:
Figure BDA0002597142900000031
calculating the difference value between the current disturbance quantity at the k moment and the current disturbance quantity at the k-1 moment as follows:
Figure BDA0002597142900000032
in the case of a sufficiently short system sampling time, the voltage term in the above equation is much larger than the other two terms, so only the voltage term remains in subsequent calculations:
Figure BDA0002597142900000033
fifthly, the actual value L of the stator inductance is measureds+ΔLsAnd (3) arranging the parameters into an equation form suitable for least square method parameter identification:
Figure BDA0002597142900000034
the actual value psi of the permanent magnet flux linkage is derived nextr+ΔΨrThe least square method parameter identification equation:
the equation in the fifth step is arranged to obtain:
Figure BDA0002597142900000035
substituting the equation in the sixth step into the alpha axis voltage equation of the permanent magnet synchronous motor to obtain the actual value psi of the permanent magnet flux linkager+ΔΨrThe least square method parameter identification equation:
Figure BDA0002597142900000036
further, the recursive least square method adopted in the fourth step is provided with a forgetting factor λ, that is, a forgetting coefficient is added to the data acquired each time, the forgetting coefficient of the newly acquired data is 1, and the forgetting coefficient of the ith data is λiWherein 0 is<λ<The values of 1, λ are adjusted as the application scenario changes.
Further, the current reconstruction in the fifth step includes reconstructing the stator current in the α β coordinate system by using the following equation:
Figure BDA0002597142900000041
in the formula iα(k)、iβ(k) For reconstructing the stator current i at the previous momentα(k+1)、iβ(k +1) is the reconstructed stator current at the current moment; wherein the actual value L of the stator inductances+ΔLsAnd the actual value Ψ of the permanent magnet flux linkager+ΔΨrAnd updating in real time along with the result of parameter identification.
By applying a reconstructed current iα、iβAnd (4) carrying out coordinate change to obtain the dq axis current information of the permanent magnet synchronous motor, and realizing predictive control on the permanent magnet synchronous motor based on the current information.
According to the method provided by the invention, a parameter identification equation of the stator inductance and the permanent magnet flux linkage is decoupled by using the current error, the parameters are identified on line by using a recursive least square method with a forgetting factor, phase current reconstruction is carried out based on a motor model, phase current information obtained by reconstruction replaces phase current information actually measured by a sensor and is fed back to a motor control system to realize predictive control, the speed of the parameter identification process is high, the followability of an identification result can be improved, and the method has a high application value.
Drawings
FIG. 1 is a flow chart of a control method provided by the present invention;
FIG. 2 is a comparison of an identified value of stator inductance with a motor setpoint;
FIG. 3 is a comparison of an identification value of a permanent magnet flux linkage with a motor setpoint;
FIG. 4 is a graph of simulation results of rotational speed, torque, and three-phase current during operation of the motor.
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 parameter identification-based permanent magnet synchronous motor single current sensor control method, as shown in fig. 1, which specifically comprises the following steps:
the method comprises the following steps of firstly, acquiring the rotating speed, the rotor position angle and the a-phase current of the permanent magnet synchronous motor in real time;
step two, establishing a simplified mathematical model of the permanent magnet synchronous motor under an alpha and beta axis coordinate system;
discretizing the differential quantity in the simplified mathematical model, and deducing a parameter identification equation of the stator inductance and the rotor flux linkage based on the a-phase measured current;
step four, performing online parameter identification on the stator inductance and the rotor flux linkage by adopting a recursive least square method;
fifthly, reconstructing phase current based on a model by using the actual motor parameters obtained by parameter identification;
and step six, performing permanent magnet synchronous motor prediction control by using the three-phase current obtained by phase current reconstruction.
In a preferred embodiment of the present invention, the step two of establishing the simplified mathematical model of the permanent magnet synchronous motor in the α β axis coordinate system is specifically based on the following assumptions:
(1) the magnetic circuit characteristic of the permanent magnet synchronous motor is linear, and the phenomena of magnetic hysteresis and magnetic circuit saturation are avoided;
(2) the three-phase winding parameters of the stator are the same, the angles are 120 degrees apart, and the magnetic field formed in the air gap is in sinusoidal distribution;
(3) air gaps formed between the stator windings and the rotor permanent magnets are uniformly distributed;
the permanent magnet synchronous motor adopts a surface-mounted structure, and a simplified mathematical model established from the structure is as follows:
Figure BDA0002597142900000051
in the formula uα、uβIs the stator voltage under an alpha beta coordinate system; i.e. iα、iβIs the stator current under an alpha beta coordinate system; ΨrIs a permanent magnet flux linkage; rsIs a stator resistor; l issIs a stator inductance; omegaeIs the electrical angular velocity of the rotor; θ is the rotor position angle and t is time.
In a preferred embodiment of the present invention, the step three of deriving a parameter identification equation based on the measured a-phase current for the stator inductance and the rotor flux linkage specifically includes:
discretizing the differential quantity in the equation in the time of k-k +1, and making:
Figure BDA0002597142900000052
and substituting the original equation to obtain a model of the discretized permanent magnet synchronous motor under an alpha beta axis coordinate system:
Figure BDA0002597142900000053
wherein iα(k+1)、iβ(k +1) are stator current vectors at the moment k +1, respectively; i.e. iα(k)、iβ(k) Stator current vectors at time k are respectively; ts is a sampling interval;
because only one phase current sensor is adopted in the method, only a-phase current, namely alpha-axis current, can be obtained, and the subsequent parameter identification equations are derived based on the alpha-axis equation.
Adding the variation of the actual parameters of the motor into an alpha-axis stator current equation at the sampling moment of k +1 to obtain alpha-axis current at the sampling moment of k +1 considering the variation of the parameters of the motor: ,
Figure BDA0002597142900000054
wherein, i'α(k +1) is k +1 sampling taking into account the variation of the motor parametersStator current of time alpha axis, DeltaLsAs a component of stator inductance variation, Δ RsAs a component of stator resistance variation, Δ ΨrIs a permanent magnet flux linkage variation component;
calculating disturbance quantity of alpha-axis stator current:
Figure BDA0002597142900000061
calculating the difference value between the current disturbance quantity at the k moment and the current disturbance quantity at the k-1 moment as follows:
Figure BDA0002597142900000062
in the case of a sufficiently short system sampling time, the voltage term in the above equation is much larger than the other two terms, so only the voltage term remains in subsequent calculations:
Figure BDA0002597142900000063
fifthly, the actual value L of the stator inductance is measureds+ΔLsAnd (3) arranging the parameters into an equation form suitable for least square method parameter identification:
Figure BDA0002597142900000064
the actual value psi of the permanent magnet flux linkage is derived nextr+ΔΨrThe least square method parameter identification equation:
the equation in the fifth step is arranged to obtain:
Figure BDA0002597142900000065
substituting the equation in the sixth step into the alpha axis voltage equation of the permanent magnet synchronous motor to obtain the actual value psi of the permanent magnet flux linkager+ΔΨrLeast square method parameter identification methodThe process:
Figure BDA0002597142900000066
in a preferred embodiment of the present invention, the recursive least square method adopted in the fourth step is provided with a forgetting factor λ, that is, a forgetting coefficient is added to each acquired data, the forgetting coefficient of the latest acquired data is 1, and the forgetting coefficient of the ith previous data is λiWherein 0 is<λ<1, adjusting the value of lambda along with the change of an application scene, and specifically executing the following steps:
the system equation for the first m measurements is:
Ym＝Xmθ
in the formula, Xm、YmRespectively forming vectors by data measured in the previous m times, wherein theta is a parameter to be identified;
according to the least square method theory, the result identified by the previous m times of measurement data is obtained
Figure BDA0002597142900000071
At the m +1 th measurement:
Ym+1＝Xm+1θ
Figure BDA0002597142900000072
Figure BDA0002597142900000073
wherein x (m +1) and y (m +1) are the m +1 th measurement result
It is possible to obtain:
Figure BDA0002597142900000074
defining:
Figure BDA0002597142900000075
after m +1 observations:
Figure BDA0002597142900000076
using matrix identities
(A+BC)-1＝A-1-A-1B(E+CA-1B)-1CA-1
The recurrence equation can be found as follows:
Figure BDA0002597142900000077
Figure BDA0002597142900000078
γ(m+1)＝1/[λ+XT(m+1)P(m)X(m+1)]
lambda is a forgetting factor, can generally take a value of 0.9-1.0, and gamma (m +1) is used for simplifying the formula.
The identification results based on the actual values of the stator inductance and the permanent magnet flux linkage of the motor in the preferred embodiment are shown in fig. 2 and 3.
In a preferred embodiment of the present invention, the current reconstruction in the fifth step includes reconstructing the stator current in the α β coordinate system by using the following equation:
Figure BDA0002597142900000079
in the formula iα(k)、iβ(k) For reconstructing the stator current i at the previous momentα(k+1)、iβ(k +1) is the reconstructed stator current at the current moment; wherein the actual value L of the stator inductances+ΔLsAnd the actual value Ψ of the permanent magnet flux linkager+ΔΨrAnd updating in real time along with the result of parameter identification.
By applying a reconstructed current iα、iβAnd (4) carrying out coordinate change to obtain the dq axis current information of the permanent magnet synchronous motor, and realizing predictive control on the permanent magnet synchronous motor based on the current information.
And step six, performing finite set-model predictive control on the permanent magnet synchronous motor by using the current information reconstructed in the step five.
The current prediction model of the permanent magnet synchronous motor is as follows:
Figure BDA0002597142900000081
Figure BDA0002597142900000082
by substituting 8 voltage vectors into the formula, 8 groups i can be predictedd、iqThen, determining a group of voltage vectors which can minimize the evaluation function by using the evaluation function;
in a preferred embodiment of the invention, the following evaluation function may be used:
Figure BDA0002597142900000083
in one example of application of the invention, the parameters of the machine are as follows, the nominal voltage U being given 310V, the nominal current I being given 10A, the stator resistance per phase winding Rs0.365 omega, stator inductance Ls0.001225H, rotor permanent magnet flux linkage ΨfAt 0.1667Wb, the motor model gives a torque step of (3N to 5N) at 0.04s and a speed step of (1000r/min to 2000r/min) at 0.06 s. In the running process, the inductance change of the stator is assumed to be 200% of a rated value, the flux linkage change of the permanent magnet is assumed to be 50% of the rated value, and the rotating speed, the torque and the three phases of the motor are adopted in the running processThe simulation result graph of the current is shown in fig. 4.
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 (5)

1. A permanent magnet synchronous motor single current sensor control method based on parameter identification is realized based on-line parameter identification and is characterized in that: the method specifically comprises the following steps:
the method comprises the following steps of firstly, acquiring the rotating speed, the rotor position angle and the a-phase current of the permanent magnet synchronous motor in real time;
step two, establishing a simplified mathematical model of the permanent magnet synchronous motor under an alpha and beta axis coordinate system;
discretizing the differential quantity in the simplified mathematical model, and deducing a parameter identification equation of the stator inductance and the rotor flux linkage based on the a-phase measured current;
step four, performing online parameter identification on the stator inductance and the rotor flux linkage by adopting a recursive least square method;
fifthly, reconstructing phase current based on a model by using the actual motor parameters obtained by parameter identification;
and step six, performing permanent magnet synchronous motor prediction control by using the three-phase current obtained by phase current reconstruction.
2. The method of claim 1, wherein: the simplified mathematical model of the permanent magnet synchronous motor under the alpha and beta axis coordinate system is established in the second step and is specifically based on the following assumptions:
(1) the magnetic circuit characteristic of the permanent magnet synchronous motor is linear, and the phenomena of magnetic hysteresis and magnetic circuit saturation are avoided;
(2) the three-phase winding parameters of the stator are the same, the angles are 120 degrees apart, and the magnetic field formed in the air gap is in sinusoidal distribution;
(3) air gaps formed between the stator windings and the rotor permanent magnets are uniformly distributed;
the permanent magnet synchronous motor adopts a surface-mounted structure, and a simplified mathematical model established from the structure is as follows:
Figure FDA0002597142890000011
in the formula uα、uβIs the stator voltage under an alpha beta coordinate system; i.e. iα、iβIs the stator current under an alpha beta coordinate system; ΨrIs a permanent magnet flux linkage; rsIs a stator resistor; l issIs a stator inductance; omegaeIs the electrical angular velocity of the rotor; θ is the rotor position angle and t is time.
3. The method of claim 2, wherein: the step three of deriving a parameter identification equation of the stator inductance and the rotor flux linkage based on the a-phase measured current specifically comprises the following steps of:
discretizing the differential quantity in the equation in the time of k-k +1, and making:
Figure FDA0002597142890000012
and substituting the original equation to obtain a model of the discretized permanent magnet synchronous motor under an alpha beta axis coordinate system:
Figure FDA0002597142890000013
wherein iα(k+1)、iβ(k +1) are stator current vectors at the moment k +1, respectively; i.e. iα(k)、iβ(k) Stator current vectors at time k are respectively; ts is miningSample spacing;
adding the variation of the actual parameters of the motor into an alpha-axis stator current equation at the sampling moment of k +1 to obtain alpha-axis current at the sampling moment of k +1 considering the variation of the parameters of the motor: ,
Figure FDA0002597142890000021
wherein, i'α(k +1) is the α -axis stator current at the k +1 sampling time, Δ L, taking into account the variation of the motor parametersAs a component of stator inductance variation, Δ RsAs a component of stator resistance variation, Δ ΨrIs a permanent magnet flux linkage variation component;
calculating disturbance quantity of alpha-axis stator current:
Figure FDA0002597142890000022
calculating the difference value between the current disturbance quantity at the k moment and the current disturbance quantity at the k-1 moment as follows:
Figure FDA0002597142890000023
only the reserved voltage term is available:
Figure FDA0002597142890000024
fifthly, the actual value L of the stator inductance is measureds+ΔLsAnd (3) arranging the parameters into an equation form suitable for least square method parameter identification:
Figure FDA0002597142890000025
the actual value psi of the permanent magnet flux linkage is derived nextr+ΔΨrLeast square method parameter identification methodThe process:
the equation in the fifth step is arranged to obtain:
Figure FDA0002597142890000026
substituting the equation in the sixth step into the alpha axis voltage equation of the permanent magnet synchronous motor to obtain the actual value psi of the permanent magnet flux linkager+ΔΨrThe least square method parameter identification equation:
Figure FDA0002597142890000031
4. the method of claim 1, wherein: the recursive least square method adopted in the fourth step is provided with a forgetting factor lambda, namely a forgetting coefficient is added to the data acquired each time, the forgetting coefficient of the newly acquired data is 1, and the forgetting coefficient of the ith forward data is lambdaiWherein 0 is<λ<The values of 1, λ are adjusted as the application scenario changes.
5. The method of claim 3, wherein: the current reconstruction in the step five comprises the step of reconstructing the stator current under the alpha and beta coordinate system through the following equation:
Figure FDA0002597142890000032
in the formula iα(k)、iβ(k) For reconstructing the stator current i at the previous momentα(k+1)、iβ(k +1) is the reconstructed stator current at the current moment; wherein the actual value L of the stator inductances+ΔLsAnd the actual value Ψ of the permanent magnet flux linkager+ΔΨrAnd updating in real time along with the result of parameter identification.
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Cited By (2)

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Publication number Priority date Publication date Assignee Title
CN113285647A (en) * 2021-05-20 2021-08-20 北京理工大学 Permanent magnet synchronous motor feedback adjustment method and device and permanent magnet synchronous motor
CN114531083A (en) * 2022-03-15 2022-05-24 北京理工大学 Permanent magnet synchronous motor single current sensor prediction control and parameter identification method

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