A Flux Observer Based on a Dual-Layer Adaptive Algorithm for SPMSMs Position Sensorless Drive

To achieve a high-performance position sensorless drive of surface-mounted permanent magnet synchronous motors (SPMSMs) in a wide speed range, a dual-layer adaptive sliding mode algorithm for a hybrid active flux model is proposed in this article. The variation of motor parameters will affect the estimation accuracy of the flux observer, which in turn will affect the observation of rotor position information. To eliminate the influence of disturbance, including parameter variation, on the flux observer, a dual-layer adaptive sliding mode disturbance estimation (ASMDE) algorithm is proposed to establish an improved flux observer. By the aid of the fixed-time sliding mode control, the proposed dual-layer ASMDE algorithm can estimate the disturbance within a finite time while the ranges of the disturbance and its derivatives are unknown. Furthermore, to improve dynamic performance and robustness to load disturbance, the dual-layer ASMDE algorithm is also adopted to design a speed observer that can estimate disturbance in real-time. Afterward, the estimated disturbance is feedforward compensated to the current loop. The finite time convergence and stability of the dual-layer ASMDE algorithm have been proved according to the Lyapunov function. The comparative experiments of this method have been conducted on an SPMSM. The experimental results show that the proposed method can operate stably within the range of 1.5%–100% rated speed. Besides, compared with existing methods, the position estimation error has been reduced by at least 0.27 rad when the speed is reversed, and by at least 0.15 rad when stator resistance mismatch occurs. After disturbance compensation, the acceleration time from 1000 to 2000 r/min with about 50% rated load is reduced by about 0.95 s.