基于自适应陷波滤波器的内置式永磁电机转子位置观测方法

Adaptive Notch Filter Based Rotor Position Estimation for Interior Permanent Magnet Synchronous Motors

针对逆变器非线性和磁场空间谐波引起定子电流及反电动势产生6k±1次谐波,进而导致6k次转子位置脉动观测误差,提出一种改进的基于有效磁链模型的自适应滤波转子位置观测方法,实现无位置传感器内置式永磁同步电机(interior permanent magnet synchronous motor,IPMSM)矢量控制系统准确解耦控制,改善其控制性能。通过自适应陷波滤波器(adaptive notch filter,ANF)滤除指定的反电动势观测值谐波分量,从而提高正交软件锁相环获得转子位置信息的精度。该方法根据谐波分析结果,通过最小均方算法(least mean square,LMS)在线连续调整滤波器参数,保证了转子位置观测器的快速收敛性。最后通过2.2k W IPMSM无传感器矢量控制系统验证了控制策略的有效性。

The （6k±1）th harmonic exists in the stator current and the back electromotive force （EMF） estimates due to the influence of the inverter nonlinearities and the flux spatial harmonics, which gives rise to the （6k）th harmonic ripple in the rotor position estimate. To accomplish accurate decoupling and further improve the performance for the position sensorless interior permanent magnet synchronous motor （IPMSM） drives, an improved active flux model based adaptive filtering rotor position observer was presented. The selective ripple harmonic components of the equivalent EMF can be eliminated through the proposed adaptive notch filter （ANF）, whereby, the accuracy of the rotor position obtained from the sottware quadrature phase-locked loop （PLL） can be improved. On the basis of the estimated harmonic information, the filter coefficients can be updated continuously online through the least mean square （LMS） algorithm which guarantees the fast convergence rate of the rotor position observer. Experiments on a 2.2kW IPMSM sensorless vector controlled drive were carried out to verify the proposed scheme.