Abstract
This article presents a static-errorless rotor position estimation method based on the linear extended state observer (LESO) for interior permanent magnet synchronous motor (IPMSM) drives. Two second-order LESOs are utilized to estimate the α-β axis back-EMFs. A third-order LESO is incorporated into the quadrature phase-locked loop (QPLL) to achieve a high robustness of position tracking against external disturbance. In addition, considering that the nonideal back-EMF will bring DC and harmonic fluctuation errors to the estimated position, an enhanced LESO-based QPLL with static-errorless rotor position estimation is proposed. On the one hand, the DC position esti mation error caused by the phase lag of the back-EMF estimator is analyzed and compensated. On the other hand, to suppress the position harmonic fluctuations induced from the nonsinusoidal back-EMFs, a second-order generalize integrator (SOGI) is embedded in the feedforward path of the LESO-based QPLL. The experimental results on the 1.0 kW IPMSM drive platform show that, compared to the conventional method, the proposed method can achieve better position estimation performance both in steady-state operation and in transient-state operation.
Highlights
Academic Editors: Baoling Guo, In recent years, interior permanent magnet synchronous motors (IPMSMs) have been widely applied in household and industrial applications owing to the advantages of high efficiency, high torque density, and good dynamic response [1]
By adopting a properly designed quadrature phase-locked loop (QPLL), the rotor position and speed information can be extracted from the estimated back-EMF, thereby achieving closed-loop sensorless control of the IPMSM
Quency of the second-order generalize integrator (SOGI) is updated by the estimated speed to achieve adaptive harmonic supMeanwhile, the estimated speed is used for DC error elimination
Summary
Academic Editors: Baoling Guo, In recent years, interior permanent magnet synchronous motors (IPMSMs) have been widely applied in household and industrial applications owing to the advantages of high efficiency, high torque density, and good dynamic response [1]. In the typical field-oriented control (FOC) topology of an IPMSM drive, the rotor position information is the key to the accurate control of the motor’s torque and speed. It is of great significance to develop position sensorless control techniques that enable cost-effective system design, as well as provide reliable estimation of the position for the IPMSM drives. IPMSM sensorless control methods are commonly divided into two types according to the physics principle. The second type is the model-based methods [4–21]. In the medium-speed and high-speed operating ranges, the model-based methods hold a dominant role among various kinds of sensorless control methods. The second part is a position/speed estimator, which extracts the position and speed information from the estimated back-EMF. A large number of methods have been proposed to estimate the back-EMF, for example, the disturbance observer [4,5], the sliding-mode observer (SMO) [6–8], the model reference adaptive system (MRAS) [9], and the extended Kalman filter (EKF) [10] [11,12]
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