A kalman filter-based asynchronous motor vector control method
Vector control of asynchronous motors using Kalman filtering technology solves the problems of high computational load and insufficient accuracy in existing technologies, and achieves accurate estimation of rotor time constant and stable operation of the motor.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HARBIN INST OF TECH AT WEIHAI
- Filing Date
- 2023-12-05
- Publication Date
- 2026-06-09
AI Technical Summary
Existing online parameter identification methods for asynchronous motors suffer from problems such as high computational load, insufficient accuracy, and slow convergence speed, making them particularly difficult to meet the requirements in engineering applications.
An asynchronous motor vector control method based on Kalman filtering is adopted. By acquiring motor parameters in real time, utilizing synchronous rotation calculation based on rotor magnetic field orientation and Kalman filter gain, the estimated value of rotor time constant is adaptively adjusted to achieve accurate estimation of rotor time constant.
It improves the accuracy and stability of asynchronous motor parameter identification, reduces the fluctuation of rotor time constant identification results, and ensures stable operation of the motor under dynamic and steady-state conditions.
Smart Images
Figure CN117614330B_ABST
Abstract
Claims
1. A vector control method for asynchronous motors based on Kalman filtering, used for vector control of asynchronous motors, characterized in that, Includes the following operations, Determine the target torque current for vector control of the asynchronous motor. Target flux current and the initial value T of the accurate estimate of the rotor time constant rini ; Repeatedly execute the following steps S1 to S6: S1, real-time acquisition of voltage, current and speed of asynchronous motor; S2, based on rotor magnetic field orientation, calculate the real-time values of stator torque current, stator flux current, stator torque voltage and stator flux voltage of the asynchronous motor during synchronous rotation. S3, Determine the rotor time constant identification measurement value T based on the adaptive rate of the asynchronous motor rotor time constant. r '; S4, based on the accurate estimate of the rotor time constant and its estimation error variance at the previous moment, determine the rough estimate of the rotor time constant and the Kalman filter gain at the current moment; S5. Based on the rotor time constant identification measurement, the coarse estimate of the rotor time constant at the current moment, and the Kalman filter gain, determine the accurate estimate of the rotor time constant at the current moment. S6 performs vector control on the asynchronous motor based on the accurate estimate of the rotor time constant, the target torque current, and the target flux linkage current at the current moment.
2. The asynchronous motor vector control method based on Kalman filtering according to claim 1, characterized in that, The initial value T of the accurate estimate of the rotor time constant rini Determined based on the following formula: Among them, L r R r These are the rotor inductance and rotor resistance of the asynchronous motor, respectively.
3. The asynchronous motor vector control method based on Kalman filtering according to claim 2, characterized in that, Step S2 further includes the following steps: S21, the transformation factor θ between the synchronous rotating coordinate system and the stationary coordinate system based on the rotor magnetic field orientation is determined based on the following formula. M : Among them, W f Let i be the slip angular velocity. ST i SM These are the stator torque current and the stator flux linkage current, respectively, T r Let p be the rotor time constant, and w be the differential operator. S W is the electric angular velocity. r The rotor's electric angular velocity; S22, based on the conversion factor θ M The voltage, current, and speed of the asynchronous motor collected in real time in step S1 are synchronously rotated based on rotor magnetic field orientation to obtain the stator torque current i in the synchronous rotation coordinate system. ST Stator flux linkage current i SM Stator torque voltage U ST and stator flux linkage voltage U SM The real-time value.
4. The asynchronous motor vector control method based on Kalman filtering according to claim 3, characterized in that, The adaptive rate based on the asynchronous motor rotor time constant mentioned in step S3 specifically refers to adaptively adjusting the rotor time constant identification measurement value T. r ', until the reactive power feedback error ΔQ reaches its minimum, where T r '、ΔQ satisfies the following equation: In the above formula, L s For the stator inductance of the asynchronous motor, k p and k i For PI parameters, L m For the equivalent magnetizing inductance, k w For the feedforward coefficient, w c This is the cutoff frequency.
5. The asynchronous motor vector control method based on Kalman filtering according to claim 1, characterized in that, The rough estimate of the rotor time constant at the current moment is determined by the following formula: T r (k∣k-1)=A*T r (k-1∣k-1)+B*U(k), Where A and B are system parameters, k is the current time, k-1 is the previous time, and T is the system parameter. r (k-1k-1) represents the precise estimate of the rotor time constant at the previous moment, U(k) represents the control variable at the current moment, and T r (kk-1) is a rough estimate of the rotor time constant at the current moment.
6. The asynchronous motor vector control method based on Kalman filtering according to claim 5, characterized in that, The Kalman filter gain at the current moment is determined by the following formula: K g (k)=P(k∣k-1)*H′ / (H*P(k∣k-1)*H′+R), Where H represents the parameters of the measurement system, H′ is the transpose of H, and K g (k) represents the Kalman filter gain at the current moment, R represents the variance of the measurement noise, and P(k|k-1) represents the error variance of the rough estimate of the rotor time constant at the current moment, determined by the following formula: P(k∣k-1)=A*P(k-1∣k-1)*A′+Q, Where P(k-1|k-1) is the error variance of the accurate estimate of the rotor time constant at the previous moment, A′ is the transpose of A, and Q is the variance of the system noise.
7. The asynchronous motor vector control method based on Kalman filtering according to claim 6, characterized in that, The precise estimate of the rotor time constant at the current moment is determined by the following formula: T r (k∣k)=T r (k∣k-1)+K g (k)*(T r '-H*T r (k∣k-1))。