This article presents an improved linear active disturbance rejection control (LADRC) method for interior permanent magnet synchronous motor (IPMSM) drives. The proposed method adopts a dual LADRC structure. The outer LADRC-based speed regulator adopts position feedback instead of speed feedback so that the low-pass filter for speed calculation can be eliminated. The inner LADRC-based current regulator incorporates a maximum torque per ampere (MTPA) operation scheme to improve the torque output capacity and the efficiency of the motor. In addition, considering the variation of load inertia in real applications, a systematic modelling and analysis on the effect of inertia mismatch is presented. To enhance the robustness of the drive system to inertia mismatch, an inertia identification method is proposed, in which the inertia information is extracted from the estimated disturbance of speed loop LESO. Finally, the effectiveness of the proposed method is verified on a 1.0-kW IPMSM drive platform.

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 a-b 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 estimation 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.