阅读说明：本技术 基于单电阻采样的异步电机无速度传感器矢量控制方法 (Asynchronous motor speed sensorless vector control method based on single resistance sampling ) 是由 瞿仁杰 王阳 胡文斌 罗淏天 袁逸凡 于 2020-12-23 设计创作，主要内容包括：本发明公开了一种基于单电阻采样的异步电机无速度传感器矢量控制方法。该方法为：首先基于异步电机矢量控制数学模型,建立状态观测系数矩阵方程,基于状态观测系数矩阵方程和预设初始量,进行状态观测器的初始化；然后基于逆变器的电压空间矢量脉宽调制方式,依据不同开关组合情况和电压矢量位置以及初始扇区或上周期EKF估计扇区进行相电流重构；再基于量测误差与预测协方差矩阵更新预测协方差矩阵,获得电机转速辨识信息和当前电机磁链；最后基于对当前电机磁链位置判断扇区所在位置,对下一次相电流重构提供辅助判断。本发明种准确性强、可靠性高,提高了电机在高电磁噪声环境下相电流重构的鲁棒性。(The invention discloses a vector control method of an asynchronous motor speed sensorless based on single resistance sampling. The method comprises the following steps: firstly, establishing a state observation coefficient matrix equation based on an asynchronous motor vector control mathematical model, and initializing a state observer based on the state observation coefficient matrix equation and a preset initial quantity; then based on the voltage space vector pulse width modulation mode of the inverter, reconstructing phase current according to different switch combination conditions, voltage vector positions and an initial sector or an EKF estimation sector of an upper period; updating the prediction covariance matrix based on the measurement error and the prediction covariance matrix to obtain motor rotating speed identification information and the current motor flux linkage; and finally, based on the position of the sector judged on the current motor flux linkage position, providing auxiliary judgment for the next phase current reconstruction. The method has the advantages of strong accuracy and high reliability, and improves the robustness of current reconstruction of the motor in a high electromagnetic noise environment.)

1. A vector control method of an asynchronous motor speed sensorless based on single resistance sampling is characterized by comprising the following steps:

step 1, reconstructing phase current according to different switch combination conditions, voltage vector positions and an initial sector or an EKF estimation sector of a previous period based on a voltage space vector pulse width modulation mode of an inverter;

step 2, establishing a state observation coefficient matrix equation based on the asynchronous motor vector control mathematical model;

step 3, initializing the state observer based on a state observation coefficient matrix equation and a preset initial quantity;

step 4, updating the prediction covariance matrix based on the measurement error and the prediction covariance matrix to obtain motor rotating speed identification information and the current motor flux linkage;

and 5, judging the position of the sector based on the current motor flux linkage position, and providing auxiliary judgment for the next phase current reconstruction.

2. The vector control method of the asynchronous motor speed sensorless based on single resistance sampling according to claim 1, wherein the inverter-based voltage space vector pulse width modulation method in step 1 performs phase current reconstruction according to different switch combination conditions and voltage vector positions, and an initial sector or an EKF estimation sector of a previous cycle, specifically as follows:

step 1.1, judging a current voltage vector according to a current voltage sampling result, and judging a current sector by combining an initial basic voltage vector or a last basic voltage vector;

step 1.2, judging whether the current sector is consistent with the last sector, if so, outputting the current sector, if not, comparing the current sector with the EKF estimation sector, if so, outputting the EKF estimation sector, otherwise, outputting the last sector; if the sector is initially started, directly outputting the current sector;

and step 1.3, judging the basic voltage vector and the switch state according to the voltage sampling value, updating the phase current of the corresponding phase, inheriting the last result of the phase current of the other basic voltage vector corresponding to the sector where the corresponding phase is located, and obtaining the phase current of the remaining phase according to the condition that the sum of the three-phase currents is zero.

3. The asynchronous motor speed sensorless vector control method based on single resistance sampling according to claim 1, characterized in that the asynchronous motor vector control mathematical model based on step 2 establishes a state observation coefficient matrix equation, specifically as follows:

establishing a state transition matrix equation based on the vector control mathematical model of the asynchronous motor, which specifically comprises the following steps:

in the formula i_sα、i_sβFor stator current, psi, in an alpha-beta coordinate system_sα、ψ_sβIs stator flux linkage u in an alpha-beta coordinate system_sα、u_sβIs stator voltage, omega, in an alpha-beta coordinate system_rIs angular velocity, R_sIs stator resistance, R_rIs rotor resistance, L_sFor stator equivalent two-phase winding self-inductance, L_rFor rotor equivalent two-phase winding self-inductance, L_mMutual inductance between the coaxial equivalent windings of the stator and the rotor, p is the pole pair number of the motor, J is the moment of inertia, and T is the number of the pole pairs_LFor load torque, σ is flux linkage term, σ is 1-L_m ²/L_rL_s；T_rIs the rotor time constant, T_r＝L_r/R_r。

4. The vector control method of the asynchronous motor speed sensorless based on the single resistance sampling as claimed in claim 1, wherein the initialization of the state observer based on the state observation coefficient matrix equation and the preset initial quantity in step 3 is specifically as follows:

the state quantity of the rotating speed and flux linkage estimation is selected as follows:

x＝[i_sα i_sβ ψ_sα ψ_sβ ω_r]^T

the observed quantity is:

Y＝[i_sα i_sβ]^T

the control quantity is as follows:

U＝[u_sα u_sβ]^T

the observation matrix is:

the equation of state is chosen as:

x_k+1＝f(x_k,u_k)+w_k

in the formula, x_kIs the n-dimensional state vector, x, of the system at time k_k+1N-dimensional state vector, u, for a system at time k +1_kControl input vector for time k, f is state transition matrix, w_kIs a process noise vector;

the observation equation is selected as follows:

y_k＝Hx_k+v_k

in the formula, y_kIs a measurement vector at time k, H is an observation matrix, v_kTo measure a noise matrix;

the initialization step includes an operation of setting an initial value of a state quantity observed quantity based on an initial value of a characteristic parameter of the motor.

5. The vector control method for the speed sensorless asynchronous motor based on the single resistance sampling as claimed in claim 1, wherein the step 4 is to update the prediction covariance matrix based on the measurement error and the prediction covariance matrix to obtain the motor speed identification information and the current motor flux linkage, specifically as follows:

the state update includes:

wherein the content of the first and second substances,the final result of the estimation of the system at time k, phi, is the state variable of the system at time k_k+1|kRepresenting the state transition matrix from time k to time k +1,preliminary estimation results of state variables for the system at the time k +1, P_k+1|kEstimating covariance update, Q, for time k +1_kA covariance matrix of system process noise at the moment k;

the measurement update includes:

P_k+1|k+1＝(I-K_k+1H_k+1)P_k+1|k

wherein K_k+1In the form of a matrix of the kalman gain,for the observed quantity data at time k +1, P_k|kTo estimate the error covariance matrix, R_k+1To measure the noise matrix.

Technical Field

The invention relates to the technical field of motor control, in particular to a vector control method of an asynchronous motor speed-free sensor based on single resistance sampling.

Background

In a modern high-performance alternating current motor speed regulation control system, the vector control technology is widely applied to the field of high-performance control of various alternating current motors due to the advantages of excellent performance, simple and reliable method and the like. In a high-performance alternating current motor vector control system, a corresponding speed sensor needs to be installed on a rotor shaft, and the rotating speed and position information of a motor are collected in real time, so that the problems of increased system cost, reduced reliability, poor environmental adaptability and the like are caused.

Because the common working condition of the working site of the motor is complex and the electromagnetic noise is large, the research on the speed sensorless sensor vector control system which is suitable for various environments and has high rotating speed estimation precision and good robustness has certain value and significance for improving the performance of the alternating current speed regulating system. Among a plurality of non-velocity sensors, the non-velocity sensor based on the extended Kalman filtering has high filtering precision and strong anti-interference performance, and has high research value and research significance.

The phase current reconstruction method based on single-resistor sampling is characterized in that a sampling resistor is connected in series on the side of a direct current bus, and is combined with SVPWMS (singular value pulse width modulation), and three-phase current can be directly reconstructed according to the relation between the direct current bus current and the instantaneous value of the three-phase current in different switching states. According to the method, a single sampling resistor is used for replacing a current sensor to carry out current sampling, so that the cost and the scale of the system are greatly reduced, but due to the fact that the number of the sensors is small, under the influence of high electromagnetic noise and the like, the risk that the frequency converter cannot run due to reconstruction failure of phase current exists.

An Extended Kalman Filter (EKF) algorithm is an extended form of Kalman filtering under a nonlinear condition, linearizes a nonlinear system by using Taylor expansion, and then filters a signal by using a Kalman filtering framework. However, when the high-order term of the nonlinear function Taylor expansion cannot be ignored, the linearization may cause the system to generate a large error, even the filter is difficult to stabilize; the filter has certain precision requirement on the original measurement data, and the tracking effect of the filter is poor or even invalid when the original data is wrong.

Disclosure of Invention

The invention aims to provide a speed sensorless vector control method of an asynchronous motor, which has the advantages of strong accuracy, high reliability, high robustness of motor operation and capability of operating in a high electromagnetic noise environment.

The technical solution for realizing the purpose of the invention is as follows: a vector control method of an asynchronous motor speed sensorless based on single resistance sampling comprises the following steps:

step 1, reconstructing phase current according to different switch combination conditions, voltage vector positions and an initial sector or an EKF estimation sector of a previous period based on a voltage space vector pulse width modulation mode of an inverter;

step 2, establishing a state observation coefficient matrix equation based on the asynchronous motor vector control mathematical model;

step 3, initializing the state observer based on a state observation coefficient matrix equation and a preset initial quantity;

step 4, updating the prediction covariance matrix based on the measurement error and the prediction covariance matrix to obtain motor rotating speed identification information and the current motor flux linkage;

and 5, judging the position of the sector based on the current motor flux linkage position, and providing auxiliary judgment for the next phase current reconstruction.

Compared with the prior art, the invention has the remarkable advantages that: (1) an extended Kalman no-speed sensor is introduced to perform auxiliary sector judgment on flux linkage estimation, so that the problem that a frequency converter cannot normally operate due to failure in phase current reconstruction of a single-resistor sampling no-speed sensor vector control system in a high electromagnetic noise environment is solved, and the accuracy and reliability of phase current reconstruction are improved; (2) by carrying out sector judgment in advance, the time for updating the three-phase current is shortened, and the operation efficiency is improved; (3) by estimating the flux linkage through the extended Kalman filter, the influence of disordered reconstruction of phase current in a non-observation area is avoided; (4) the reliability of current reconstruction under the high electromagnetic noise environment is improved, and the robustness of the asynchronous motor operation is improved.

Drawings

Fig. 1 is a flow chart of the asynchronous motor speed sensorless vector control method based on single resistance sampling.

Fig. 2 is a structural diagram of a vector control system of an asynchronous motor speed-free sensor based on single resistance sampling in the invention.

Fig. 3 is a flow chart of phase current reconstruction in the present invention.

Detailed Description

The invention is described in further detail below with reference to the figures and the specific embodiments.

With reference to fig. 1 and 2, the invention relates to a vector control method of a speed-free sensor of an asynchronous motor based on single resistance sampling, which comprises the following steps:

step 1, based on a voltage space vector pulse width modulation mode of an inverter, reconstructing phase current according to different switch combination conditions and voltage vector positions and an initial sector or an EKF estimation sector of a previous period, and referring to FIG. 3, the method specifically comprises the following steps:

step 1.1, judging a current voltage vector according to a current voltage sampling result, and judging a current sector by combining an initial basic voltage vector or a last basic voltage vector;

step 1.2, judging whether the current sector is consistent with the last sector, if so, outputting the current sector, if not, comparing the current sector with the EKF estimation sector, if so, outputting the EKF estimation sector, otherwise, outputting the last sector; if the sector is initially started, directly outputting the current sector;

and step 1.3, judging the basic voltage vector and the switch state according to the voltage sampling value, updating the phase current of the corresponding phase, inheriting the last result of the phase current of the other basic voltage vector corresponding to the sector where the corresponding phase is located, and obtaining the phase current of the remaining phase according to the condition that the sum of the three-phase currents is zero.

Step 2, establishing a state observation coefficient matrix equation based on the asynchronous motor vector control mathematical model, which comprises the following specific steps:

based on the vector control mathematical model of the asynchronous motor, a state transition matrix is established, which specifically comprises the following steps:

in the formula i_sα、i_sβFor stator current, psi, in an alpha-beta coordinate system_sα、ψ_sβIs stator flux linkage u in an alpha-beta coordinate system_sα、u_sβIs stator voltage, omega, in an alpha-beta coordinate system_rIs angular velocity, R_sIs stator resistance, R_rIs rotor resistance, L_sFor stator equivalent two-phase winding self-inductance, L_rFor rotor equivalent two-phase winding self-inductance, L_mMutual inductance between the coaxial equivalent windings of the stator and the rotor, p is the pole pair number of the motor, J is the moment of inertia, and T is the number of the pole pairs_LFor load torque, σ is flux linkage term, σ is 1-L_m ²/L_rL_s；T_rIs the rotor time constant, T_r＝L_r/R_r。

Step 3, initializing the state observer based on the state observation coefficient matrix equation and the preset initial quantity, wherein the initialization is as follows:

the state quantity of the rotating speed and flux linkage estimation is selected as follows:

x＝[i_sα i_sβ ψ_sα ψ_sβ Φ_r]^T

the observed quantity is:

Y＝[i_sα i_sβ]^T

the control quantity is as follows:

U＝[u_sα u_sβ]^T

the observation matrix is:

the equation of state is chosen as:

x_k+1＝f(x_k,u_k)+w_k

in the formula, x_kIs the n-dimensional state vector, x, of the system at time k_k+1N-dimensional state vector, u, for a system at time k +1_kControl input vector for time k, f is state transition matrix, w_kIs a process noise vector;

the observation equation is selected as follows:

y_k＝Hx_k+v_k

in the formula, y_kFor the measurement vector at time k, H is the observation matrix, v_kTo measure the noise matrix.

The initialization step mainly comprises the operation of setting an initial value of the state quantity observed quantity based on an initial value of the motor characteristic parameter.

Step 4, updating the prediction covariance matrix based on the measurement error and the prediction covariance matrix to obtain the motor rotating speed identification information and the current motor flux linkage, which is specifically as follows:

the state updating mainly comprises the following steps:

P_k+1|k＝Φ_k+1|kP_k|kΦ_kT_+1|k+Q_k

wherein the content of the first and second substances,the final result of the estimation of the system at time k, phi, is the state variable of the system at time k_k+1|kRepresenting the state transition matrix from time k to time k +1,preliminary estimation results of state variables for the system at the time k +1, P_k+1|kEstimating covariance update, Q, for time k +1_kA covariance matrix of system process noise at the moment k;

the measurement updating mainly comprises the following steps:

P_k+1|k+1＝(I-K_k+1H_k+1)P_k+1|k

in the formula, K_k+1In the form of a matrix of the kalman gain,for the observed quantity data at time k +1, P_k|kTo estimate the error covariance matrix, R_k+1To measure the noise matrix.

And 5, judging the position of the sector based on the current motor flux linkage position, and providing auxiliary judgment for next phase current reconstruction to prevent the phase current reconstruction from being influenced by high electromagnetic noise.

The flux linkage estimation is assisted by the aid of the extended Kalman no-speed sensor, so that the problem that a frequency converter cannot normally operate due to failure of phase current reconstruction in a single-resistor sampling no-speed sensor vector control system in a high electromagnetic noise environment is solved, and accuracy and reliability of phase current reconstruction are improved; by carrying out sector judgment in advance, the time for updating the three-phase current is shortened, and the operation efficiency is improved; by estimating the flux linkage through the extended Kalman filter, the influence of disordered reconstruction of phase current in a non-observation area is avoided; the reliability of current reconstruction under the high electromagnetic noise environment is improved, and the robustness of the asynchronous motor operation is improved.