CN110198150B - Permanent magnet synchronous motor multi-parameter online identification method - Google Patents
Permanent magnet synchronous motor multi-parameter online identification method Download PDFInfo
- Publication number
- CN110198150B CN110198150B CN201910513208.6A CN201910513208A CN110198150B CN 110198150 B CN110198150 B CN 110198150B CN 201910513208 A CN201910513208 A CN 201910513208A CN 110198150 B CN110198150 B CN 110198150B
- Authority
- CN
- China
- Prior art keywords
- permanent magnet
- frequency
- current
- formula
- equation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000001360 synchronised effect Effects 0.000 title claims abstract description 50
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000004907 flux Effects 0.000 claims abstract description 21
- 230000005284 excitation Effects 0.000 claims abstract description 11
- 238000013178 mathematical model Methods 0.000 claims abstract description 4
- 238000000819 phase cycle Methods 0.000 claims description 22
- 230000008569 process Effects 0.000 claims description 12
- 238000002347 injection Methods 0.000 claims description 10
- 239000007924 injection Substances 0.000 claims description 10
- 150000001875 compounds Chemical class 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 9
- 230000009466 transformation Effects 0.000 claims description 9
- 230000004044 response Effects 0.000 claims description 7
- 230000001131 transforming effect Effects 0.000 claims description 6
- 230000000737 periodic effect Effects 0.000 claims description 4
- 230000003068 static effect Effects 0.000 claims description 4
- 101000744515 Homo sapiens Ras-related protein M-Ras Proteins 0.000 claims description 3
- 102100039789 Ras-related protein M-Ras Human genes 0.000 claims description 3
- 230000005611 electricity Effects 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 229910052761 rare earth metal Inorganic materials 0.000 description 1
- 150000002910 rare earth metals Chemical class 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
Images
Classifications
-
- 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
- H02P21/24—Vector control not involving the use of rotor position or rotor speed sensors
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Control Of Ac Motors In General (AREA)
Abstract
A permanent magnet synchronous motor multi-parameter online identification method comprises the following steps: step 1, establishing a mathematical model of a permanent magnet synchronous motor under a high-frequency voltage signal; step 2, calculating the current of the PMSM and the dq axis inductance under the excitation of the rotating high-frequency voltage signal; step 3, calculating the resistance of the PMSM under excitation; and 4, calculating the permanent magnet flux linkage of the PMSM. The method adopts the rotating high-frequency voltage signal to inject into the dq-axis inductance of the permanent magnet synchronous motor for on-line identification, adopts the square wave current signal to on-line identify the resistance of the permanent magnet synchronous motor, adopts the model reference self-adaptive method to on-line identify the permanent magnet flux linkage of the permanent magnet synchronous motor, realizes the multi-parameter on-line identification of the motor, can be applied to the control without a position sensor, and improves the control precision.
Description
Technical Field
The invention belongs to the technical field of permanent magnet synchronous motor control, and relates to a permanent magnet synchronous motor multi-parameter online identification method.
Background
In recent years, with the development of power electronics and rare earth materials, Permanent Magnet Synchronous Motors (PMSM) are widely used in industrial automation, aerospace, and daily life of people. A high-performance permanent magnet synchronous motor speed regulating system needs a rotor position and a speed signal to realize speed closed-loop control. Although these signals can be accurately detected by mechanical sensors, mechanical position sensors are expensive and mechanically cumbersome, reducing the reliability of the system. In the field of high-reliability motor driving systems such as aerospace and the like, the high-reliability motor driving system is limited by self space, and a position or speed sensor is installed, so that the weight and the complexity of the system are increased, and the failure rate of the system is increased.
In order to realize the position sensorless control of the permanent magnet synchronous motor speed regulating system, motor parameters are required to be accurate as much as possible. In practical applications, the motor parameters may change with changes in ambient temperature, magnetic saturation effects, operating frequency, and the like. Therefore, online parameter identification of the motor is important for implementation of a high performance control strategy.
Disclosure of Invention
In order to solve the above mentioned drawbacks in the background art, the present invention provides a method for online identifying multiple parameters of a permanent magnet synchronous motor. The electrical parameters of the permanent magnet synchronous motor comprise stator resistance, rotor flux linkage, direct axis inductance and quadrature axis inductance, and the following multi-parameter identification problem refers to identification of the four parameters. Currently, the PMSM parameter identification research mainly focuses on multiple parameter identifications. Firstly, due to the lack of rank of the established system model, most algorithms can only identify one to two parameters, and for the identification of three parameters, the convergence and uniqueness of the result lack theoretical basis; secondly, under an identification algorithm, parameters are identified by methods of injecting external signals, changing the running state of the motor and the like, but the parameters are not suitable for online identification of the motor parameters; thirdly, the complexity and the amount of computation of the algorithm make the solution difficult to implement.
The technical scheme proposed for solving the technical problems is as follows:
a multi-parameter online identification method for a permanent magnet synchronous motor comprises the following steps:
step 1, establishing a mathematical model of the permanent magnet synchronous motor under a high-frequency voltage signal, wherein the process is as follows:
1.1 under dq two-phase synchronous rotating coordinate system, the voltage state equation of the IPMSM of the interior permanent magnet synchronous motor is expressed in a matrix form as follows
In the formula ud、uq、idAnd iqStator voltage and current, R, respectively in a synchronous rotating coordinate systemsIs stator resistance, Ld、LqD, q-axis inductance, ωeIs the electrical angular velocity, #fIs the permanent magnet rotor flux linkage amplitude;
1.2 the frequency of the high-frequency injection signal is far higher than the fundamental frequency of the motor, so that the three-phase PMSM is regarded as an RL circuit; because the resistance is very small relative to the reactance at high frequency, it is ignored; at this time, the high-frequency voltage equation of the three-phase PMSM is simplified to
In the formula udh、uqh、idh、iqhHigh-frequency voltage and current components of d and q axes respectively; the subscript h represents a high frequency quantity;
step 2, calculating the current of the PMSM and the dq axis inductance under the excitation of the rotating high-frequency voltage signal, and the process is as follows:
2.1 defining the frequency of the injected high-frequency signal as ωhAmplitude of UhThe injected high-frequency voltage signal is represented as
In the formula uαh、uβhHigh-frequency voltage components which are respectively an alpha beta axis;
2.2 uαβhtransformation into complex variables in complex planes
2.3 transforming the formula (4) to a synchronous rotating coordinate system to obtain
2.4 substituting the formula (5) into the formula (2) to obtain the current response equation of the three-phase PMSM under the excitation of high-frequency voltage in the rotating coordinate system as
2.5 transforming the formula (6) to a static coordinate system to obtain
In the formula IcpBeing the amplitude of the high-frequency current component of positive phase sequence, i.e.
IcnOf the magnitude of the high-frequency current component of negative phase sequence, i.e.
From equation (7), the high frequency current response contains two components: the first is a positive phase-sequence component, the rotation direction of which is the same as the direction of the injection voltage vector, and the amplitude of which is related to the average inductance; the second is a negative phase-sequence component, the rotation direction of which is opposite to the direction of the injection voltage vector, and the amplitude of which is related to half-difference inductance;
the high-pass filter of the synchronous shaft system transforms the high-frequency current vector into a reference coordinate system which synchronously rotates with the injected high-frequency voltage vector through coordinate transformation, and the high-frequency current vector of the positive phase sequence is changed into direct current and is easily filtered by the conventional high-pass filter; then, restoring the signal by an inverse coordinate system of the previous reference coordinate system, and finally extracting the amplitude of the negative sequence current by transformation; similarly, extracting the amplitude of the positive sequence current; finally, calculating the dq axis inductance through the extracted positive and negative sequence current amplitude values;
3.1 the equation for the voltage of the PMSM at the estimated dq coordinate system is given by
In the formula (I), the compound is shown in the specification,
in order to perform the park transformation,
to estimate the angle between the dq axis and the actual dq axis, θeIn order to be the actual rotor position,
in order to estimate the position of the rotor,
is the difference in rotational speed, ωeIn order to be the actual rotational speed,
in order to estimate the speed of rotation,
for estimating the voltage and current, L, of the dq axis, respectivelyΣ＝(Ld+Lq) A/2 is the mean inductance, LΔ＝(Ld-Lq) The/2 is the differential inductance;
3.2 when the position error is small, equation (10) reduces to
3.3 because the d-axis voltage equation is relatively simple, it is used to identify stator resistance
3.4 when the motor is running at constant speed,
equation (12) reduces to
3.5 to identify the resistance stably on-line, a periodic square wave current with positive and negative alternating amplitudes is injected on the estimated d-axis
In the formula (I), the compound is shown in the specification,
3.6 after the estimated d-axis current reaches the reference value, the voltage on the estimated d-axis is stored and averaged; using two average voltages, an estimated resistance is obtained
Wherein "-" represents an average value;
step 4, calculating the permanent magnet flux linkage of the PMSM, wherein the process is as follows:
4.1 the current equation of PMSM in dq coordinate system is
4.2 according to equation (16), the current equation of PMSM under the estimated dq coordinate system is
In the formula (I), the compound is shown in the specification,
to estimate the permanent magnet flux linkage;
4.3 definition
Is a generalized error vector and is represented by formula (16) and formula(17) To obtain an error equation of state
Wherein A, B, C are the coefficient matrixes of the actual system respectively,
respectively, are the coefficient matrices of the estimation system,
are the difference of the coefficient matrix, respectively;
4.4 Using equation (18), introduce a linear compensation matrix D that converts MRAS into an equivalent feedback system of
4.5 taking D as a unit array E, ensuring the rigor and trueness of a feedforward linear model, and considering the Popov integral inequality
4.6 satisfying the formula (20), selecting the self-adaptive law of the proportional plus integral structure according to the self-adaptive rule of the traditional form to obtain the self-adaptive law of the permanent magnet flux linkage
And (3) obtaining the dq-axis inductance, the resistance and the permanent magnet flux linkage of the motor according to the formulas (8), (9), (15) and (21), and realizing the multi-parameter online identification of the permanent magnet synchronous motor.
The method adopts a rotating high-frequency voltage signal to inject into dq-axis inductance of the permanent magnet synchronous motor for on-line identification, adopts a square wave current signal to identify the resistance of the permanent magnet synchronous motor on line, and adopts a model reference self-adaptive method to identify the permanent magnet flux linkage of the permanent magnet synchronous motor on line, thereby realizing the multi-parameter on-line identification of the motor.
The technical conception of the invention is as follows: aiming at multi-parameter online identification of the permanent magnet synchronous motor, a rotating high-frequency voltage signal is superposed on a fundamental wave, then current response in the permanent magnet synchronous motor is detected, negative phase sequence and positive phase sequence high-frequency current are extracted through demodulation and processing of the signal, and finally dq axis inductance of the motor is calculated by using the amplitude of the positive and negative phase sequence high-frequency current. The d-axis voltage and the q-axis current are detected by injecting the periodic square wave d-axis current with positive and negative alternating amplitudes, and then the resistance of the permanent magnet synchronous motor is calculated. And obtaining a self-adaptive law of the permanent magnet flux linkage by using a model reference self-adaptive method, and calculating the permanent magnet flux linkage of the permanent magnet synchronous motor by acquiring experimental data on line.
The invention has the beneficial effects that: through signal injection, the underrank problem of multi-parameter identification of the permanent magnet synchronous motor is solved, multi-parameter online identification of the permanent magnet synchronous motor is realized, the method can be applied to control without a position sensor, and the control precision is improved.
Drawings
FIG. 1 is a block diagram of the overall system architecture of the present invention;
fig. 2 is a schematic diagram of the positional relationship between the two stationary coordinate systems, the actual two synchronous rotating coordinate systems, and the estimated two synchronous rotating coordinate systems.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 and 2, a method for online identifying multiple parameters of a permanent magnet synchronous motor includes the following steps:
step 1, establishing a mathematical model of the permanent magnet synchronous motor under a high-frequency voltage signal, wherein the process is as follows:
1.1 under dq two-phase synchronous rotating coordinate system, the voltage state equation of the IPMSM of the interior permanent magnet synchronous motor is expressed in a matrix form as follows
In the formula ud、uq、idAnd iqStator voltage and current, R, respectively in a synchronous rotating coordinate systemsIs stator resistance, Ld、LqD, q-axis inductance, ωeIs the electrical angular velocity, #fIs the permanent magnet rotor flux linkage amplitude;
1.2 the frequency of the high-frequency injection signal is far higher than the fundamental frequency of the motor, so that the three-phase PMSM is regarded as an RL circuit; because the resistance is very small relative to the reactance at high frequency, it is ignored; at this time, the high-frequency voltage equation of the three-phase PMSM is simplified to
In the formula udh、uqh、idh、iqhHigh-frequency voltage and current components of d and q axes respectively; the subscript h represents a high frequency quantity;
step 2, calculating the current of the PMSM and the dq axis inductance under the excitation of the rotating high-frequency voltage signal, and the process is as follows:
2.1 defining the frequency of the injected high-frequency signal as ωhAmplitude of UhThe injected high-frequency voltage signal is represented as
In the formula uαh、uβhHigh-frequency voltage components which are respectively an alpha beta axis;
2.2 uαβhtransformation into complex variables in complex planes
2.3 transforming the formula (4) to a synchronous rotating coordinate system to obtain
2.4 substituting the formula (5) into the formula (2) to obtain the current response equation of the three-phase PMSM under the excitation of high-frequency voltage in the rotating coordinate system as
2.5 transforming the formula (6) to a static coordinate system to obtain
In the formula IcpBeing the amplitude of the high-frequency current component of positive phase sequence, i.e.
IcnOf the magnitude of the high-frequency current component of negative phase sequence, i.e.
From equation (7), the high frequency current response contains two components: the first is a positive phase-sequence component, the rotation direction of which is the same as the direction of the injection voltage vector, and the amplitude of which is related to the average inductance; the second is a negative phase-sequence component, the rotation direction of which is opposite to the direction of the injection voltage vector, and the amplitude of which is related to half-difference inductance;
in order to extract negative phase sequence high-frequency current, signals such as fundamental frequency current, low-order harmonic current, PWM switching frequency harmonic current, positive phase sequence high-frequency current and the like of motor end current must be well filtered; the amplitude difference between the fundamental current and the high-frequency current is large, the carrier frequency is far higher than the injected high-frequency, and the fundamental current and the high-frequency current can be filtered by a conventional band-pass filter; the rotation directions of the positive phase sequence component and the negative phase sequence component of the carrier current are opposite, so that the positive sequence current component can be filtered by a high-pass filter of a synchronous shaft system;
the high-pass filter of the synchronous shaft system transforms the high-frequency current vector into a reference coordinate system which synchronously rotates with the injected high-frequency voltage vector through coordinate transformation, and the high-frequency current vector of the positive phase sequence is changed into direct current and is easily filtered by the conventional high-pass filter; then, restoring the signal by an inverse coordinate system of the previous reference coordinate system, and finally extracting the amplitude of the negative sequence current by transformation; similarly, extracting the amplitude of the positive sequence current; finally, calculating the dq axis inductance through the extracted positive and negative sequence current amplitude values;
the high-frequency signal is injected into the alpha beta axis instead of the dq axis, so that errors caused by inaccuracy of a coordinate system of the dq axis cannot be generated in the identification of the inductor in a static coordinate system, the expression of the inductor does not contain physical quantities such as electrical angular velocity and the like, the calculation amount is small, and the engineering implementation is easy;
3.1 the equation for the voltage of the PMSM at the estimated dq coordinate system is given by
In the formula (I), the compound is shown in the specification,
in order to perform the park transformation,
to estimate the angle between the dq axis and the actual dq axis, θeIn order to be the actual rotor position,
in order to estimate the position of the rotor,
is the difference in rotational speed, ωeIn order to be the actual rotational speed,
in order to estimate the speed of rotation,
for estimating the voltage and current, L, of the dq axis, respectivelyΣ＝(Ld+Lq) A/2 is the mean inductance, LΔ＝(Ld-Lq) The/2 is the differential inductance;
3.2 when the position error is small, equation (10) reduces to
3.3 because the d-axis voltage equation is relatively simple, it is used to identify stator resistance
3.4 when the motor is running at constant speed,
equation (12) reduces to
3.5 to identify the resistance stably on-line, a periodic square wave current with positive and negative alternating amplitudes is injected on the estimated d-axis
In the formula (I), the compound is shown in the specification,
3.6 after the estimated d-axis current reaches the reference value, the voltage on the estimated d-axis is stored and averaged; using two average voltages, an estimated resistance is obtained
Wherein "-" represents an average value;
step 4, calculating the permanent magnet flux linkage of the PMSM, wherein the process is as follows:
4.1 the current equation of PMSM in dq coordinate system is
4.2 according to equation (16), the current equation of PMSM under the estimated dq coordinate system is
In the formula (I), the compound is shown in the specification,
to estimate the permanent magnet flux linkage;
4.3 definition
The error state equation is obtained by the formula (16) and the formula (17) as a generalized error vector
Wherein A, B, C are the coefficient matrixes of the actual system respectively,
respectively, are the coefficient matrices of the estimation system,
are the difference of the coefficient matrix, respectively;
4.4 Using equation (18), introduce a linear compensation matrix D that converts MRAS into an equivalent feedback system of
4.5 taking D as a unit array E, ensuring the rigor and trueness of a feedforward linear model, and considering the Popov integral inequality
4.6 satisfying the formula (20), selecting the self-adaptive law of the proportional plus integral structure according to the self-adaptive rule of the traditional form to obtain the self-adaptive law of the permanent magnet flux linkage
And (3) obtaining the dq-axis inductance, the resistance and the permanent magnet flux linkage of the motor according to the formulas (8), (9), (15) and (21), and realizing the multi-parameter online identification of the permanent magnet synchronous motor.
Claims (1)
1. A permanent magnet synchronous motor multi-parameter online identification method is characterized by comprising the following steps: the method comprises the following steps:
step 1, establishing a mathematical model of the permanent magnet synchronous motor under a high-frequency voltage signal, wherein the process is as follows:
1.1 under dq two-phase synchronous rotating coordinate system, the voltage state equation of the IPMSM of the interior permanent magnet synchronous motor is expressed in a matrix form as follows
In the formula ud、uq、idAnd iqStator voltage and current, R, respectively in a synchronous rotating coordinate systemsIs stator resistance, Ld、LqD, q-axis inductance, ωeIs the electrical angular velocity, #fIs the permanent magnet rotor flux linkage amplitude;
1.2 the frequency of the high-frequency injection signal is far higher than the fundamental frequency of the motor, so that the three-phase PMSM is regarded as an RL circuit; because the resistance is very small relative to the reactance at high frequency, it is ignored; at this time, the high-frequency voltage equation of the three-phase PMSM is simplified to
In the formula udh、uqh、idh、iqhHigh-frequency voltage and current components of d and q axes respectively; the subscript h represents a high frequency quantity;
step 2, calculating the current of the PMSM and the dq axis inductance under the excitation of the rotating high-frequency voltage signal, and the process is as follows:
2.1 defining the frequency of the injected high-frequency signal as ωhAmplitude of UhThe injected high-frequency voltage signal is represented as
In the formula uαh、uβhHigh-frequency voltage components which are respectively an alpha beta axis;
2.2uαβhtransformation into complex variables in complex planes
2.3 transforming the formula (4) to a synchronous rotating coordinate system to obtain
2.4 substituting the formula (5) into the formula (2) to obtain the current response equation of the three-phase PMSM under the excitation of high-frequency voltage in the rotating coordinate system as
2.5 transforming the formula (6) to a static coordinate system to obtain
In the formula IcpBeing the amplitude of the high-frequency current component of positive phase sequence, i.e.
IcnOf the magnitude of the high-frequency current component of negative phase sequence, i.e.
From equation (7), the high frequency current response contains two components: the first is a positive phase-sequence component, the rotation direction of which is the same as the direction of the injection voltage vector, and the amplitude of which is related to the average inductance; the second is a negative phase-sequence component, the rotation direction of which is opposite to the direction of the injection voltage vector, and the amplitude of which is related to half-difference inductance;
the high-pass filter of the synchronous shaft system transforms the high-frequency current vector into a reference coordinate system which synchronously rotates with the injected high-frequency voltage vector through coordinate transformation, and the high-frequency current vector of the positive phase sequence is changed into direct current and is easily filtered by the conventional high-pass filter; then, restoring the signal by an inverse coordinate system of the previous reference coordinate system, and finally extracting the amplitude of the negative sequence current by transformation; similarly, extracting the amplitude of the positive sequence current; finally, calculating the dq axis inductance through the extracted positive and negative sequence current amplitude values;
step 3, calculating the resistance of the PMSM under excitation, wherein the process is as follows:
3.1 the equation for the voltage of the PMSM at the estimated dq coordinate system is given by
In the formula (I), the compound is shown in the specification,
in order to perform the park transformation,
to estimate the angle between the dq axis and the actual dq axis, θeIn order to be the actual rotor position,
in order to estimate the position of the rotor,
is the difference in rotational speed, ωeIn order to be the actual rotational speed,
in order to estimate the speed of rotation,
for estimating the voltage and the electricity of the dq axis, respectivelyFlow, LΣ＝(Ld+Lq) A/2 is the mean inductance, LΔ＝(Ld-Lq) The/2 is the differential inductance;
3.2 when the position error is small, equation (10) reduces to
3.3 because the d-axis voltage equation is relatively simple, it is used to identify stator resistance
3.4 when the motor is running at constant speed,
equation (12) reduces to
3.5 to identify the resistance stably on-line, a periodic square wave current with positive and negative alternating amplitudes is injected on the estimated d-axis
In the formula (I), the compound is shown in the specification,
3.6 after the estimated d-axis current reaches the reference value, the voltage on the estimated d-axis is stored and averaged; using two average voltages, an estimated resistance is obtained
In the formula "-"represents an average value;
step 4, calculating the permanent magnet flux linkage of the PMSM, wherein the process is as follows:
4.1 the current equation of PMSM in dq coordinate system is
4.2 according to equation (16), the current equation of PMSM under the estimated dq coordinate system is
In the formula (I), the compound is shown in the specification,
to estimate the permanent magnet flux linkage;
4.3 definition
The error state equation is obtained by the formula (16) and the formula (17) as a generalized error vector
Wherein A, B, C are the coefficient matrixes of the actual system respectively,
respectively, are the coefficient matrices of the estimation system,
are the difference of the coefficient matrix, respectively;
4.4 Using equation (18), introduce a linear compensation matrix D that converts MRAS into an equivalent feedback system of
4.5 taking D as a unit array E, ensuring the rigor and trueness of a feedforward linear model, and considering the Popov integral inequality
4.6 satisfying the formula (20), selecting the self-adaptive law of the proportional plus integral structure according to the self-adaptive rule of the traditional form to obtain the self-adaptive law of the permanent magnet flux linkage
And (3) obtaining the dq-axis inductance, the resistance and the permanent magnet flux linkage of the motor according to the formulas (8), (9), (15) and (21), and realizing the multi-parameter online identification of the permanent magnet synchronous motor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910513208.6A CN110198150B (en) | 2019-06-14 | 2019-06-14 | Permanent magnet synchronous motor multi-parameter online identification method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910513208.6A CN110198150B (en) | 2019-06-14 | 2019-06-14 | Permanent magnet synchronous motor multi-parameter online identification method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110198150A CN110198150A (en) | 2019-09-03 |
| CN110198150B true CN110198150B (en) | 2021-05-18 |
Family
ID=67754536
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910513208.6A Active CN110198150B (en) | 2019-06-14 | 2019-06-14 | Permanent magnet synchronous motor multi-parameter online identification method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110198150B (en) |
Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112564569A (en) * | 2019-09-26 | 2021-03-26 | 杭州先途电子有限公司 | Controller and motor parameter identification device |
| CN110912482B (en) * | 2019-12-11 | 2023-08-18 | 长沙市日业电气有限公司 | Permanent magnet synchronous motor flux linkage and temperature estimation method |
| CN113037168B (en) * | 2019-12-25 | 2023-05-09 | 大族激光科技产业集团股份有限公司 | Method for identifying inductance and resistance parameters of permanent magnet synchronous motor |
| CN111064409A (en) * | 2020-01-08 | 2020-04-24 | 东南大学 | Self-adaptive current control method with rotor position observation and multi-parameter identification |
| CN111641362B (en) * | 2020-05-07 | 2022-04-05 | 浙江工业大学 | Method for quickly identifying inductance of double-pulse high-frequency square wave voltage injection permanent magnet synchronous motor |
| CN112821838A (en) * | 2020-11-24 | 2021-05-18 | 华能海南发电股份有限公司东方电厂 | Method for improving performance of air compressor permanent magnet synchronous motor control system |
| CN112803854A (en) * | 2021-01-04 | 2021-05-14 | 北京理工大学 | Model reference self-adaption based permanent magnet synchronous motor parameter online identification method |
| CN112968644B (en) * | 2021-03-08 | 2022-11-11 | 上海交通大学 | Permanent magnet synchronous motor parameter online identification method, system, terminal and medium |
| CN113141133B (en) * | 2021-04-26 | 2022-08-02 | 湖南大学 | Modular multi-winding permanent magnet motor parameter identification method and system based on least square method |
| CN113328665B (en) * | 2021-06-30 | 2022-08-16 | 东南大学 | Synchronous reluctance motor position sensorless control method based on inductance identification |
| CN114499323B (en) * | 2022-04-02 | 2022-07-12 | 南京凌博电子科技有限公司 | Motor parameter identification method based on high-frequency voltage injection method considering phase resistance |
| CN114844414B (en) * | 2022-04-15 | 2023-10-31 | 合肥工业大学 | Permanent magnet synchronous motor inductance online identification method and system |
| CN114785228B (en) * | 2022-05-18 | 2023-02-07 | 哈尔滨工业大学 | Permanent magnet synchronous motor inductance parameter online identification method based on virtual shafting injection |
| CN114744941B (en) * | 2022-06-09 | 2022-09-23 | 浙江大学 | Permanent magnet synchronous motor permanent magnet demagnetization online monitoring method and system |
| CN115411995B (en) * | 2022-07-15 | 2024-06-18 | 重庆大学 | Permanent magnet synchronous motor offline parameter identification method |
| CN116317791B (en) * | 2023-05-17 | 2023-08-15 | 国网山西省电力公司太原供电公司 | Method and device for identifying inductance of synchronous reluctance motor without position sensor |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2693226A4 (en) * | 2011-03-30 | 2016-03-02 | Shenzhen Invt Electric Co Ltd | Inductance parameter identification method of synchronous motor and implementation system thereof |
| US20140327379A1 (en) * | 2013-05-03 | 2014-11-06 | Texas Instruments Incorporated | Position sensorless drive system and method for permanent magnet motors |
| CN103560736B (en) * | 2013-10-28 | 2016-04-13 | 华南理工大学 | A kind of static off-line parameter identification method of permagnetic synchronous motor |
| CN108847800B (en) * | 2018-06-28 | 2020-05-05 | 闽江学院 | Off-line identification method for resistance inductance parameters of surface-mounted permanent magnet synchronous motor |
-
2019
- 2019-06-14 CN CN201910513208.6A patent/CN110198150B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110198150A (en) | 2019-09-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110198150B (en) | Permanent magnet synchronous motor multi-parameter online identification method | |
| CN110429886B (en) | Permanent magnet synchronous motor low-speed domain rotor position identification method | |
| Benjak et al. | Review of position estimation methods for IPMSM drives without a position sensor part I: Nonadaptive methods | |
| CN110022106B (en) | Permanent magnet synchronous motor position sensorless control method based on high-frequency signal injection | |
| CN108288936B (en) | Low-speed position-sensorless control method for permanent magnet linear motor | |
| CN110311608B (en) | High-frequency square wave voltage injection permanent magnet synchronous motor position-sensorless control method with optimal injection angle | |
| CN110165959B (en) | Active-disturbance-rejection position-sensorless control method and control device for permanent magnet synchronous motor | |
| CN112737450A (en) | High-frequency injection compensation method for SPMSM rotor position estimation | |
| CN114598206B (en) | Design method of permanent magnet synchronous motor wide-speed-domain rotor position observer | |
| CN115173774B (en) | Permanent magnet synchronous motor sensorless control method and system | |
| CN111181458A (en) | Surface-mounted permanent magnet synchronous motor rotor flux linkage observation method based on extended Kalman filter | |
| CN105227010A (en) | A kind of permagnetic synchronous motor position-sensor-free position detection error harmonic pulse removing method | |
| CN112511059B (en) | High-precision position estimation method for permanent magnet synchronous motor | |
| CN112532133B (en) | Filtering compensation sliding mode active-disturbance-rejection control method suitable for permanent magnet synchronous motor | |
| CN111769779A (en) | PMSM direct torque control method based on improved Luenberger observer | |
| CN110912485A (en) | Permanent magnet synchronous motor position sensorless control method considering iron loss resistance | |
| CN109194224B (en) | Permanent magnet synchronous motor sensorless control method based on extended state observer | |
| CN113890438A (en) | Speed-sensorless control method based on built-in permanent magnet synchronous motor | |
| CN113037163A (en) | Novel permanent magnet synchronous motor position observation method with dynamic error compensation | |
| CN108649849B (en) | Simple sensorless permanent magnet synchronous motor speed estimation method | |
| CN113965129B (en) | Compensation method for current measurement offset error of permanent magnet synchronous motor control system | |
| CN113078865B (en) | Built-in permanent magnet synchronous motor sensorless control method | |
| CN113783494B (en) | Maximum torque current ratio control of position-sensor-free built-in permanent magnet synchronous motor | |
| CN112953333A (en) | Permanent magnet synchronous motor torque ripple suppression method based on adaptive filter | |
| CN110149082B (en) | Position-sensor-free control method under condition of asymmetric three-phase inductance of motor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220130 Address after: 310051 Room 405, block a, building 1, No. 57, jianger Road, Changhe street, Binjiang District, Hangzhou, Zhejiang Province Patentee after: Hangzhou Lingxin Microelectronics Co.,Ltd. Address before: The city Zhaohui six districts Chao Wang Road Hangzhou City, Zhejiang province 310014 18 Patentee before: ZHEJIANG University OF TECHNOLOGY |