Novel motor current detection method without current sensor

Abstract

The invention discloses a novel motor current detection method without a current sensor. The method comprises the following steps: establishing a nonlinear state-space equation of a permanent magnet synchronous motor; estimating the current of the permanent magnet synchronous motor by using Kalman filtering; and coupling the voltage of the voltage sensor and the angular velocity sensor and the rotational speed feedforward control quantity to realize the current output of the permanent magnet synchronous motor. The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly provides a novel motor current detection method without a current sensor, which comprises the following steps of: performing one-step prediction on motor output current by utilizing a self-adaptive Kalman filtering method, and coupling feedforward control quantities of output voltage and angular velocity to obtain a current sensor-free motor current detection result. Rapid response control on the current without a current sensor is realized, and the defect of low current detection speed without the current sensor is overcome.

Description

Technical Field

[0001] The invention belongs to the technical field of permanent magnet synchronous motor control, relates to a method for predicting the current of a permanent magnet synchronous motor by using Kalman filtering, and specifically refers to a new motor current detection method without a current sensor. Background Art

[0002] Permanent magnet synchronous motors have the characteristics of high efficiency, small size, fast response speed, etc. With the development of motor manufacturing technology and motor control technology, permanent magnet synchronous motors are widely used in CNC systems, industrial control and automated production lines.

[0003] High-performance permanent magnet synchronous motor control systems generally include an inner current control loop and an outer speed and position control loop. This requires the drive controller system to have high-performance current, speed and position sensors to collect motor parameter indicators in real time for control. At present, sensor-less and sensor-free have become research hotspots, but due to positioning requirements, position and speed sensors are indispensable in the system. According to whether the working current is collected in the control strategy, the system is divided into two types: direct current control and indirect current control. Indirect control is based on the mathematical model of the motor, and indirectly controls the output current through the controller output voltage and angular velocity. It has the characteristics of simple manufacturing and low cost. The disadvantage is that the system has slow dynamic response. Direct control uses the sampling value of the current sensor for real-time feedback control, which has the characteristics of fast dynamic response, easy current limiting, and high control accuracy. The disadvantage is that the existence of the current sensor makes the system bulky and the manufacturing cost high.

[0004] Therefore, it is of great significance to study the fast response motor control system without current sensor. Summary of the invention

[0005] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides a new motor current detection method without current sensor, which uses an adaptive Kalman filtering method to perform a one-step prediction of the motor output current and recouple the output voltage and angular velocity feedforward control quantity to achieve rapid response control of the current without current sensor, thus overcoming the defect of slow current detection speed without current sensor.

[0006] The technical solution adopted by the present invention is as follows: A new motor current detection method without current sensor of the present invention comprises the following steps:

[0007] Step 1: Establish the nonlinear state space equation of the permanent magnet synchronous motor, and establish the state equation x(t+1) and observation equation y(t) respectively:

[0008] x(t+1)=f[x(t)]+Bu(t)+w(t)

[0009] y(t)=hx(t)+v(t)

[0010] In the formula, x=[i d i q ω] T is the state variable, x(t) is the current state variable, and x(t+1) is the next state variable; f[x(t)] is the variable about x, and the x vector is represented by i d 、i q ,ω three variables; u=[u d u q T l ] T is the input variable; y is the output variable; h = [0 0 1]; w(t), v(t) are the white noises in the prediction process, and their variance matrices are Q and R respectively; t is the simulation step length;

[0011] According to the state space equation and the mathematical model of the permanent magnet synchronous motor (based on the working characteristics of the motor, the mathematical formula is used to simulate the running state of the motor), the state transfer matrix f[x(t)] is:

[0012] h=[0 0 1]

[0013] In the above formula, f[x(t)] is the variable about x, B is the matrix about the variable L; R s Customize the resistance for the motor; L = L d =L q is the inductance of the motor in the equivalent d, q, o coordinate system; Ψ f is the excitation flux of the rotor permanent magnet pole; P n is the number of pole pairs of the motor stator winding; J is the moment of inertia of the motor shaft coupling; T e is the electromagnetic torque generated by the motor; T l is the load resistance torque of the motor; x=[i d i q ω] T is the state variable, x(t) is the current state variable, i d 、i q , ω are d-axis current, q-axis current and angular velocity respectively;

[0014] Step 2: Use Kalman filtering to estimate the current of the permanent magnet synchronous motor:

[0015] Calculate the one-step prediction of the state quantity: x(t+1|t)=f[x(t)]+Bu(t)+w(t);

[0016] Calculate the one-step prediction covariance matrix: P(t+1|t)=fP(t|t)f T +Q;

[0017] Calculate the filter gain matrix: K(t+1)=P(t+1|t)h T [hP(t+1|t)h T +R] -1 ;

[0018] The state is updated in one step: x(t+1|t+1)=x(t+1|t)+K(t+1)[Y(k+1)-hx(t+1|t)];

[0019] Covariance update: P(t+1|t+1)=[I n -K(t+1)h]P(t+1|t);

[0020] Step 3: Couple the voltage sensor and the angular velocity sensor’s voltage and speed feedforward control to achieve the current output of the permanent magnet synchronous motor:

[0021] Current component in d coordinate system: i d (t+1)=k 1 i d (t+1|t+1)+k 2 u d +k 3 ω;

[0022] Current component in q coordinate system: i q (t+1)=k 4 i q (t+1|t+1)+k 5 u q +k 6 ω;

[0023] Where, the voltage signal u in the d coordinate system is d , the voltage signal u in the q coordinate system q , angular velocity ω, k 1 , k 2 , k 3 , k 4 , k 5 , k 6 is the feed-forward coefficient.

[0024] The beneficial effects achieved by the present invention using the above scheme are as follows: This scheme is a new motor current detection method without current sensor, which utilizes an adaptive Kalman filter method to perform a one-step prediction of the motor output current, and then couples the output voltage and angular velocity feedforward control quantity, to achieve rapid response control of the current without current sensor, overcome the defect of slow current detection speed without current sensor, and thus achieve rapid detection of motor current without current sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1is an overall flow chart of the method of an embodiment of the present invention;

[0026] Figure 2 This is a one-step update flow chart for estimating the current of a permanent magnet synchronous motor using a Kalman filter in an embodiment of the present invention.

[0027] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] like Figure 1-2 As shown, the present invention provides a new motor current detection method without current sensor, comprising the following steps:

[0030] Step 1: Establish the nonlinear state space equation of the permanent magnet synchronous motor, and establish the state equation x(t+1) and observation equation y(t) respectively:

[0031] x(t+1)=f[x(t)]+Bu(t)+w(t)

[0032] y(t)=hx(t)+v(t)

[0033] In the formula, x=[i d i q ω] T is the state variable, x(t) is the current state variable, and x(t+1) is the next state variable; f[x(t)] is the variable about x, and the x vector is represented by i d 、i q ,ω three variables; u=[u d u q T l ] T is the input variable; y is the output variable; h = [0 0 1]; w(t), v(t) are the white noises in the prediction process, and their variance matrices are Q and R respectively; t is the simulation step length;

[0034] According to the state space equation and the mathematical model of the permanent magnet synchronous motor (based on the working characteristics of the motor, the mathematical formula is used to simulate the running state of the motor), the state transfer matrix f[x(t)] is:

[0035] h=[0 0 1]

[0036] In the above formula, f[x(t)] is the variable about x, B is the matrix about the variable L; R s Customize the resistance for the motor; L = L d =L q is the inductance of the motor in the equivalent d, q, o coordinate system; Ψ f is the excitation flux of the rotor permanent magnet pole; P n is the number of pole pairs of the motor stator winding; J is the moment of inertia of the motor shaft coupling; T e is the electromagnetic torque generated by the motor; T l is the load resistance torque of the motor; x=[i d i q ω] T is the state variable, x(t) is the current state variable, i d 、i q , ω are d-axis current, q-axis current and angular velocity respectively;

[0037] Common motor parameters reference: L = 8.5mH, R s =2.875Ω、Ψ f =0.175Wb, P n =4, J = 0.0008 kg·m 2 ω=700rpm、T e =3N·m, T l =6N·m;

[0038] Step 2: Use Kalman filtering to estimate the current of the permanent magnet synchronous motor. The specific implementation plan is as follows: Figure 1 As shown:

[0039] Calculate the one-step prediction of the state quantity: x(t+1|t)=f[x(t)]+Bu(t)+w(t);

[0040] Calculate the one-step prediction covariance matrix: P(t+1|t)=fP(t|t)f T +Q;

[0041] Calculate the filter gain matrix: K(t+1)=P(t+1|t)h T [hP(t+1|t)h T +R] -1 ;

[0042] The state is updated in one step: x(t+1|t+1)=x(t+1|t)+K(t+1)[Y(k+1)-hx(t+1|t)];

[0043] Covariance update: P(t+1|t+1)=[In -K(t+1)h]P(t+1|t);

[0044] Step 3: Couple voltage and angular velocity feedforward, voltage signal u in d coordinate system d , the voltage signal u in the q coordinate system q , angular velocity ω;

[0045] Step 4: Get the final permanent magnet synchronous motor current:

[0046] Current component in d coordinate system: i d (t+1)=k 1 i d (t+1|t+1)+k 2 u d +k 3 ω;

[0047] Current component in q coordinate system: i q (t+1)=k 4 i q (t+1|t+1)+k 5 u q +k 6 ω;

[0048] In the formula, k 1 , k 2 , k 3 , k 4 , k 5 , k 6 is the feed-forward coefficient.

[0049] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0050] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0051] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A new motor current detection method without current sensor, characterized in that: The following steps are involved: Step 1: Establish the nonlinear state space equation of the permanent magnet synchronous motor, and establish the state equation x(t+1) and observation equation y(t) respectively: x(t+1)=f[x(t)]+Bu(t)+w(t) y(t)=hx(t)+v(t) In the formula, x=[i d i q ω] T is the state variable, x(t) is the current state variable, and x(t+1) is the next state variable; f[x(t)] is the variable about x, and the x vector is represented by i d 、i q ,ω three variables; u=[u d u q T l ] T is the input variable; y is the output variable; h = [0 0 1]; w(t), v(t) are the white noises in the prediction process, and their variance matrices are Q and R respectively; t is the simulation step length; According to the state space equation and the mathematical model of permanent magnet synchronous motor, the state transfer matrix f[x(t)] is: h＝[0 0 1] In the above formula, f[x(t)] is the variable about x, B is the matrix about the variable L; R s Customize the resistance for the motor; L = L d =L q is the inductance of the motor in the equivalent d, q, o coordinate system; Ψ f is the excitation flux of the rotor permanent magnet pole; P n is the number of pole pairs of the motor stator winding; J is the moment of inertia of the motor shaft coupling; T e is the electromagnetic torque generated by the motor; T l is the load resistance torque of the motor; x=[i d i q ω] T is the state variable, x(t) is the current state variable, i d 、i q , ω are d-axis current, q-axis current and angular velocity respectively; Step 2: Use Kalman filtering to estimate the current of the permanent magnet synchronous motor: Calculate the one-step prediction of the state quantity: x(t+1|t)=f[x(t)]+Bu(t)+w(t); Calculate the one-step prediction covariance matrix: P(t+1|t)=fP(t|t)f T +Q; Calculate the filter gain matrix: K(t+1)=P(t+1|t)h T [hP(t+1|t)h T +R] -1 ; The state is updated in one step: x(t+1|t+1)=x(t+1|t)+K(t+1)[Y(k+1)-hx(t+1|t)]; Covariance update: P(t+1|t+1)=[I n -K(t+1)h]P(t+1|t); Step 3: Couple the voltage sensor and the angular velocity sensor’s voltage and speed feedforward control to achieve the current output of the permanent magnet synchronous motor: Current component in d coordinate system: i d (t+1)=k1i d (t+1|t+1)+k2u d +k3ω; Current component in q coordinate system: i q (t+1)=k4i q (t+1|t+1)+k5u q +k6ω; In the formula, k1, k2, k3, k4, k5, and k6 are feedforward coefficients.

2. A new motor current detection method without current sensor according to claim 1, characterized in that: The mathematical model of the permanent magnet synchronous motor in step 1 is obtained by simulating the operating state of the motor using mathematical formulas according to the working characteristics of the motor.

3. A new motor current detection method without current sensor according to claim 2, characterized in that: In step 3, the coupling voltage and angular velocity feedforward are used to generate the voltage signal u in the d coordinate system. d , the voltage signal u in the q coordinate system q , angular velocity ω, and thus obtain the final current of the permanent magnet synchronous motor.

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