On the Sensorless PMSM Rotor Position Estimation Enhancement: Application of ADALINE-PLL

Considering the sensorless control of PMSM drives, a novel observer for improving the estimation perfomance is proposed in this paper. An Adaptive linear neuron (ADALINE)-based feed-forward harmonic compensation block is integrated into the classic PLL, which together form an ADALINE-PLL. Firstly, given a general input, the estimation error of a classic PLL is analytically investigated. It is shown that the estimation error contains several distinctive harmonics, which are related to the PLL non-linear structure and input harmonics. These harmonics are able to pass through the loop-filter and appear in the estimated phase and frequency as extra ripple. In light of the estimation error harmonics, the ADALINE-PLL is used for suppression of undesired harmonics. Secondly, the superior perfomance of ADALINE-PLL, compared to PLL, is verified through simulations in several different conditions. In case of acoustic noise-based or EMF-based PMSM sensorless control, the observer input signals contain several harmonics, which can easily distort the estimation performance if not properly repressed. As the result, the positive impact of ADALINE-PLL on the estimation performance is studied in details.