Sensorless Control of Permanent Magnet Synchronous Motors with Compensation for Parameter Uncertainty

Abstract

-Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.

Assessing Finite Control Set Model Predictive Speed Controlled PMSM Performance for Deployment in Electric Vehicles

“…Zhang et al evaluated an improvement on the existing MPC system by comparing it with FOC, in both high-speed and low-speed conditions along, with its switching frequency evaluation [10]. Adamopoulos et al and Yang etal., compared, specifically, the dynamic characteristics of FOC and MPC for a PMSM [11,12]. However, when addressing EV applications such as speed matching, evaluating steady-state characteristics is equally important.…”

Luenberger Position Observer Based on Deadbeat-Current Predictive Control for Sensorless PMSM

“…However, reliable operation of PMSM at high speeds still remains many challenges. For example, in medium-and high-speed, fundamental excitation model-based methods are applied to estimate position information [7][8][9][10][11][12][13][14][15][16][17]. Sliding model observer (SMO) is proposed in Reference [7] to estimate position, but signal chattering still exists in dynamic-state operation.…”

“…The method in [13] is based on cubature Kalman filter (CKF), which needs a large amount of calculation within one PWM control step, hence the method is difficult to realize in engineering. A Luenberger observer is built to observe position information in static-coordinate in References [14][15][16][17], which causes high phase-lag on estimated signal.…”