This article proposes a robust deadbeat predictive current control (DPCC) method for the interior permanent magnet synchronous motor (IPMSM) based on a full parameter identification method. The DPCC method is innovatively combined with the high frequency currents injection method, which can observe inductances, flux linkage, and resistance values of the IPMSM online. After the parameter identification results are obtained, the initial crude parameters are replaced by the identification values in the DPCC method to enhance the robustness of the IPMSM control system. Moreover, a novel online accuracy verification method for parameter identification results is proposed to judge the error estimation level. The proposed method extracts the high bandwidth and the high parameter sensitivity characteristic of the DPCC method. The online identification and verification of IPMSM parameters are proceeded subsequently while achieving robust control of the IPMSM with the DPCC method. Finally, the proposed method is experimentally demonstrated with a 1.5 kW motor. The experimental results show that the IPMSM with the proposed method can still work well even in the situation of severe initial parameters mismatch.

The maximum torque per ampere (MTPA) control is significant for improving the efficiency of the interior permanent magnet synchronous motor (IPMSM). However, for the high saturation IPMSM, the change of the permanent magnet (PM) flux linkage is more complicated, which can cause the MTPA control to deviate from the optimal solution. Therefore, an improved MTPA control method for the high saturation IPMSM is proposed in this paper. Compared with other methods, the proposed method improves the conventional models of flux linkage and torque by analyzing the nonlinear variation of the PM flux linkage with the dq-axis currents. Subsequently, an expression suitable for the MTPA control of high saturated IPMSM is derived based on the improved models. The proposed parameter fitting models are then fitted using data from 11 operating points and incorporated into the MTPA optimization algorithm to obtain the MTPA curve. Finally, the effectiveness of the proposed method in enhancing the control accuracy of the MTPA angle is verified through simulations and experiments.

Torque is a significant parameter in the design and control of permanent magnet synchronous motor (PMSM). Torque measurement systems are usually expensive, which correspondingly require extra room and add weight. Alternatively, torque can be estimated by the product of the measured current and the estimated magnetic flux. In general, the conventional torque estimation method for PMSM is established based on ignoring core saturation. However, in special vehicles, due to the high power density and narrow installation space of the motors, the saturation degree of the core is high, and the nonlinear characteristic between torque and current is more prominent, which would bring significant errors to the conventional torque estimation method. In order to solve the aforementioned problem, this paper studies on the torque from the perspective of magnetomotive force (MMF). A saturation coefficient is proposed to modify the conventional torque model by considering the core reluctance. Then, a practical analytical expression of average torque and an improved torque estimation method are proposed. Compared with the conventional method, the proposed method significantly improves the accuracy of the estimation. At last, comprehensive simulation and experimental results based on a prototyped 300kW interior PMSM have fully demonstrated that the proposed method can get accurate torque under different load conditions.

To address the issues of slow dynamic response and complex parameter tuning associated with the traditional fixed-gain PI phase-locked loop (PLL) in sensorless drives for permanent magnet synchronous motors. An improved finite position set-PLL is proposed. A novel cost function is formulated using Taylor series expansion to achieve global convergence. An optimized search strategy combining the position bisection method and Newton’s iteration was employed, achieving a high-precision rotor position estimation of 2.07e-6 rad with only three iterations. The proposed method enhances the dynamic response performance of the system and reduces the computational burden without complex parameter tuning. The effectiveness of the proposed scheme was experimentally investigated using a 1.5 kW IPMSM laboratory prototype.