Presently, the model-based sensorless control of permanent magnet synchronous motor (PMSM) is effective at medium and high speed region. Among the several model-based methods, the flux observation method can achieve the better performance because the rotor flux of PMSM is constant or calculable even when the speed or current is time varying. But due to the inverter nonlinearity, the initial position detection error and the current measurement bias, the estimated flux will inevitably contain the interfering signals such as ramp signal, DC bias, harmonics and so on. These interfering signals will reduce the steady-state accuracy of rotor position estimation, increase the speed fluctuation, and even lead to the system unstable in serious cases.
So, to solve this problem, a flux observer based on extended master-slave adaptive notch filter (EMAF) is proposed. The EMAF can track the signals which contain multi components by using the characteristics of them. So, considering the characteristic of interfering signals in estimated flux, we design the EMAF which can accurately track these interfering signals. Besides, by introducing a new variable in EMAF, the dc deviation of integral terms is tracked and compensated, thus the ramp signal caused by integrating is also eliminated. In this method, the rotor flux can be directly estimated without estimating the back-EMF first. Since there are many parameters in EMAF need to tune, to simplify the tuning process, a parameter tuning graphical method of EMAF is given, which transforms the multi parameters tuning into single parameter tuning.
In addition, under varying speed, the traditional phase locked loop (PLL) can not accurately track the frequency, which degrades the dynamic performance, So, a dynamic frequency tracking algorithm (DFT) is proposed. In this method, the motion equation is applied and the extended state observer (ESO) is designed to estimate the frequency. Since the varying rate of the rotor speed is considered in ESO, compared with phase locked loop or frequency locked loop, this method will be more applicable under changing speed. Based on EMAF and DFT, we design and implement the overall sensorless control system of PMSM.
In experiments, we compare the rotor position estimation results using the traditional flux sliding mode observer (FSMO) and the proposed EMAF under different speed. The results show that the EMAF can effectively reduce the interfering signals including the 5th and 7th harmonics, the dc bias, as well as the ramp signal, thus improving the accuracy of rotor position estimation and reducing the speed fluctuation. Then, we compare the frequency tracking results using traditional PLL and the proposed DFT under linear changing and sine changing speed. The bandwidths of PLL and DFT are same. The results show that DFT can greatly reduce the frequency tracking error when speed varies, thus improving the dynamic performance. Therefore, the proposed method is effective for enhancing the sensorless performance of PMSM.
葛扬, 宋卫章, 杨洋. 基于扩张式主从自适应陷波滤波器与动态频率跟踪的永磁同步电机无传感器控制[J]. 电工技术学报, 0, (): 20-20.
Ge Yang, Song Weizhang, Yang Yang. PMSM Sensorless Control Based on Extended Master-Slave Adaptive Notch Filter and Dynamic Frequency Tracking. Transactions of China Electrotechnical Society, 0, (): 20-20.
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