Enhanced Position Estimation Based on Frequency Adaptive Generalized Comb Filter for Interior Permanent Magnet Synchronous Motor Drives

Accurate rotor position estimation is critical to ensure the high-performance operation of position sensorless interior permanent magnet synchronous motor (IPMSM) drives. However, the back electromotive force (BEMF) estimated by the model-based observers is usually nonideal, which may further degrade the position estimation accuracy. In this article, a frequency-adaptive generalized comb filter (FAGCF) with a quadrature phase-locked loop (PLL) is adopted to suppress the rotor position estimation errors by filtering out the dominant distortions in the BEMF, including the (6k±1)th harmonics caused by inverter nonlinearity and flux spatial harmonics, as well as the dc offset from the inaccurate current measurements. This proposed filter is constructed by multiple digital delay blocks and therefore has the advantage of easy implementation with less online parameters tuning effort. Meanwhile, a linearized model is derived for PLL parameter design, with which the stability of the FAGCF-PLL position estimation system can also be analyzed theoretically. The effectiveness of the proposed sensorless control strategy has been validated with the experimental results on a 1.5-kW IPMSM drive.