阅读说明：本技术 一种永磁同步电机无位置传感器控制中的参数辨识方法 (Parameter identification method in permanent magnet synchronous motor position sensorless control ) 是由 徐永向 王杨睿 邹继斌 于 2019-11-11 设计创作，主要内容包括：本发明公开了一种永磁同步电机无位置传感器控制中的参数辨识方法,所述方法需要配合永磁同步电机的无位置控制算法,由无位置控制算法提供永磁同步电机稳态运行时电流,估计转子速度和估计反电势幅值信息。本发明利用电机在不同运行状态下的电流,无位置控制算法估计的反电势和转速信息来计算表贴式永磁同步电机的相电阻、相电感、永磁体磁链和逆变器电压误差的等效幅值,不需要额外的硬件,能够应用于通用的永磁同步电机驱动器,具有极高的应用价值和经济价值。与传统的辨识技术相比,本发明的方法不需要向绕组注入高频测试信号,降低了辨识损耗,提高了电机性能,而且摆脱了对位置传感器的依赖。(The invention discloses a parameter identification method in the control of a permanent magnet synchronous motor without a position sensor, which needs to be matched with a position-free control algorithm of the permanent magnet synchronous motor, and the position-free control algorithm provides current for the permanent magnet synchronous motor in steady state operation, estimates the speed of a rotor and estimates the amplitude information of back electromotive force. The invention utilizes the current of the motor in different running states and back electromotive force and rotating speed information estimated by a position-free control algorithm to calculate the equivalent amplitude of the phase resistance, the phase inductance, the permanent magnet flux linkage and the voltage error of the inverter of the surface-mounted permanent magnet synchronous motor, does not need extra hardware, can be applied to a universal permanent magnet synchronous motor driver, and has extremely high application value and economic value. Compared with the traditional identification technology, the method does not need to inject high-frequency test signals into the winding, reduces the identification loss, improves the motor performance, and gets rid of the dependence on the position sensor.)

1. A parameter identification method in permanent magnet synchronous motor position sensorless control is characterized by comprising the following steps:

step one, in the process that the permanent magnet synchronous motor is operated without a position sensor, at least four groups of data of the permanent magnet synchronous motor under different stable states are obtained by changing the current and the rotating speed of the motor, wherein the data comprise the average value of the d 'q' axis current under different stable statesAnd

Step two, substituting the data obtained in the step one into a formula (1), and calculating to obtain the mean value of the estimated flux linkage

Step three, substituting the data in the step one and the step two into a formula (2) to obtain a data matrix x_i：

In the formula, the lower corner mark i is used for distinguishing data in different steady states;

step four, estimating parameter matrix

step five, during the k iteration, calculating an estimated value according to a formula (3)

Sixthly, calculating data matrixes y (k), Z (k) according to the formula (4) and the formula (5):

step seven, calculating a parameter matrix according to the result of the calculation in the step six

Step eight, calculating a parameter matrix according to a formula (7)

In the formula, the value of m is reset to an initial value;

nine steps, handle

step ten, if y' meets any one of the following two conditions, then m is added with 1, and the step eight is skipped, otherwise, the step eleven is skipped:

condition 1:

eleven steps,

step twelve, calculating the parameters of the motor through a formula (8):

in the formula, L_m、R_mIs a parameter of the motor model in the position-free algorithm;

step thirteen, if lambda (k +1), R (k +1), L (k +1), V_dead(k +1) satisfies

2. The method of claim 1, wherein the parameter identification method is used in PMSM position sensorless control

3. The method of claim 1, wherein the initial value of m is a natural number, and w is a number between 0 and 1.

Technical Field

The invention relates to an online multi-parameter identification method, in particular to an online multi-parameter identification method for surface-mounted permanent magnet synchronous motor position sensorless control.

Background

The existing permanent magnet synchronous motor online parameter identification method comprises a high-frequency signal injection method, wherein the method comprises the steps of injecting a high-frequency voltage (current) test signal into a motor winding by controlling an inverter, and then calculating the parameter of the motor according to a sampled current (voltage) response signal. Because a high-frequency signal needs to be injected, the method can increase the loss of the motor and reduce the performance of the motor, and only the resistance and inductance information of the motor can be calculated. The other motor parameter identification method utilizes a motor steady state mathematical model, and the method can identify the parameters of the permanent magnet synchronous motor by utilizing the current, voltage and other information of the motor in different working states. The method can calculate the equivalent amplitude of the motor resistance, inductance, flux linkage and inverter voltage error, however, the method needs a position sensor (a rotary transformer, an encoder and the like), so the method cannot be applied to the position sensorless control of the permanent magnet synchronous motor.

Disclosure of Invention

The invention aims to provide a parameter identification method in the control of a permanent magnet synchronous motor without a position sensor. The method utilizes the current of the motor in different running states and back electromotive force and rotating speed information estimated by a position-free control algorithm to calculate equivalent amplitudes of phase resistance, phase inductance, permanent magnet flux linkage and inverter voltage error of the surface-mounted permanent magnet synchronous motor, does not need additional hardware, can be applied to a universal permanent magnet synchronous motor driver, and has extremely high application value and economic value.

The purpose of the invention is realized by the following technical scheme:

a parameter identification method in permanent magnet synchronous motor position sensorless control comprises the following steps:

step one, in the process that the permanent magnet synchronous motor is operated without a position sensor, at least four groups of data of the permanent magnet synchronous motor under different stable states are obtained by changing the current and the rotating speed of the motor, wherein the data comprise the average value of the d 'q' axis current under different stable statesAnd

mean value of rotor electrical angular velocity estimated without position algorithm

Mean value of motor back electromotive force amplitude estimated by position-free algorithm

Step two, substituting the data obtained in the step one into a formula (1), and calculating to obtain the mean value of the estimated flux linkage

Average of angle between sum current vector and estimated rotor position

Step three, substituting the data in the step one and the step two into a formula (2) to obtain a data matrix x_i：

In the formula, the lower corner mark i is used for distinguishing data in different steady states;

step four, estimating parameter matrix

Calculated by an iterative method using

Indicating at the k-th iteration

The value of (a) is,

to represent

Is set to the initial value of (a),

value of (2) to ensure the estimated value of step fiveIf the number is a real number, initializing internal parameters m and w, wherein the initial value of m is a natural number, and w is a number between 0 and 1;

step five, during the k iteration, calculating an estimated value according to a formula (3)

Sixthly, calculating data matrixes y (k), Z (k) according to the formula (4) and the formula (5):

step seven, calculating a parameter matrix according to the result of the calculation in the step six

Step eight, calculating a parameter matrix according to a formula (7)

In the formula, the value of m is reset to an initial value;

nine steps, handle

Substituting equation (3) to calculate f (x)_iTheta') of a handle

Substituting the formula (4) and the formula (5) to calculate y';

step ten, if y' meets any one of the following two conditions, then m is added with 1, and the step eight is skipped, otherwise, the step eleven is skipped:

condition 1:

condition 2:

eleven steps,

Resetting the value of m to an initial value;

step twelve, calculating the parameters of the motor through a formula (8):

in the formula, L_m、R_mIs a parameter of the motor model in the position-free algorithm;

step thirteen, if lambda (k +1), R (k +1), L (k +1), V_dead(k +1) satisfies

The algorithm ends, otherwise it jumps to step five, where α is λ, R, L and V_deadAnd ε is a minimum value greater than 0.

Compared with the prior art, the invention has the following advantages:

1. the method can realize the identification of equivalent amplitudes of the resistance, the inductance, the permanent magnet flux linkage and the inverter error without adding any hardware equipment, and reduces the hardware cost of parameter identification.

2. Compared with the traditional identification technology, the method does not need to inject high-frequency test signals into the winding, reduces the identification loss, improves the motor performance, gets rid of the dependence on the position sensor, and can be applied to the position-sensorless control of the permanent magnet synchronous motor.

Drawings

FIG. 1 is a structural relationship diagram of an identification method and no position control, in which:

and

is a dq-axis current reference value, wherein

Default values are 0A, u_dAnd u_qIs the dq-axis voltage, U_dcIs the bus voltage of the drive, i_abcIs the three-phase winding current of the permanent magnet synchronous motor i_αβIs an α β axis current, from i_abcObtained by clark coordinate change, i_dqIs dq-axis current, from i_abcObtained by clark and park transformation,

is the electrical angle position of the motor rotor estimated by the position-free algorithm,is the magnitude of the back emf estimated by the no position algorithm;

FIG. 2 is a graph showing the recognition result of the data in Table 1;

FIG. 3 shows the recognition result of the method of the present invention using the data in Table 2.

Detailed Description

The technical solution of the present invention is further described below with reference to the accompanying drawings, but not limited thereto, and any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention shall be covered by the protection scope of the present invention.

The invention provides a parameter identification method in permanent magnet synchronous motor position sensorless control, which needs to be matched with a position sensorless control algorithm of a permanent magnet synchronous motor, the position sensorless control algorithm provides current when the permanent magnet synchronous motor runs in a steady state, rotor speed and back electromotive force amplitude information are estimated, a structural relation between the identification method and the position sensorless control is shown in figure 1, in the figure, ab phase current is obtained by sampling of a current sensor of a driver, the ab phase current is converted into d 'q' axis current through clark and park conversion, wherein the park conversion needs position information, and the rotating speed of the estimated position information and the back electromotive force amplitude are calculated and provided by the position sensorless algorithm. The specific implementation steps are as follows:

step one, in the process that the permanent magnet synchronous motor runs without a position sensor, the data under at least 4 different motor working states are obtained by controlling the rotating speed and the direct axis current of the motor, and the data comprise the average value of the d 'q' axis current under different steady statesAnd

mean value of rotor electrical angular velocity estimated without position algorithmMean value of motor back electromotive force amplitude estimated by position-free algorithm

Step two, replacing the data obtained in the step oneEntering the formula (1), calculating to obtain the mean value of the estimated flux linkage

Average of angle between sum current vector and estimated rotor position

Step three, substituting the data in the step one and the step two into a formula (2) to obtain a data matrix x_i：

In the formula, the lower subscript i is used to distinguish data at different steady states.

Step four, estimating parameter matrix

Needs to be calculated by an iterative method

To indicate at the k-th iteration

The value of (a) is,

to represent

Is set to the initial value of (a),

the estimated value of the fifth step should be ensured

Is a real number and is,the initial value can be selected as

In addition, initializing parameters m and w, wherein m and w are internal parameters in an iterative algorithm, m is a natural number variable, the change rule of the variable is detailed in steps eight to ten, w is a number between 0 and 1 and can be set randomly, the initial value of m can be selected to be 0, and w needs to be a real number between 0 and 1.

Step five, during the k iteration, calculating an estimated value according to a formula (3)

Is formed by estimating parameters

Calculated

An estimate of (d).

Sixthly, calculating data matrixes y (k), Z (k) according to the formula (4) and the formula (5):

step seven, calculating a parameter matrix according to the result of the calculation in the step six

Step eight, calculating a parameter matrix according to a formula (7)

In the formula, the value of m is initialized to 0 in step four.

Nine steps, handleSubstituting equation (3) to calculate f (x)_iTheta') of a handle

Substituting equation (4) and equation (5) to calculate y'.

Step ten, if y' meets any one of the following two conditions, then m is added with 1, and the step eight is skipped, otherwise, the step eleven is skipped:

condition 1:

condition 2:

eleven steps,m＝0。

Step twelve, calculating the parameters of the motor through a formula (8):

in the formula, L_m、R_mAre parameters of the motor model in the position-free algorithm.

Step thirteen, ifλ(k+1)，R(k+1)，L(k+1)，V_dead(k +1) satisfiesThe algorithm ends, otherwise it jumps to step five, where α is λ, R, L and V_deadAnd ε is a minimum value greater than 0.