Speed loop is the key factor affecting the performance of induction machine (IM) drives. Conventionally, the proportional integral (PI) controller is applied for its simple implementation and static-errorless; however, its performance degrades apparently under external load torque sudden changes. To address this problem, this paper presents a nonlinear control strategy, combining the conventional PI control with a high-order fast terminal sliding-mode (HOFTSM) load torque observer. The external load torque is online estimated by the proposed HOFTSM observer, and then the estimated torque is used as feed-forward compensation for the PI controller. Moreover, the designed HOFTSM observer shows superiorities in fast convergence rate and chattering elimination. Comparison experiments show that the load torque rejection of the IM speed loop is significantly enhanced by using the proposed approach.

Although the stability of speed adaptive full-order observer (AFO) has been studied for sensorless induction motor (IM) ultra-low speed operation, few researchers concern its dynamic performance simultaneously. To address this problem, this paper proposed a novel feedback gain selection principle of AFO considering both stability and dynamic performance. Compared with the conventional stability-based feedback gain selection, the proposed method applied the zero-point locus diagram and Bode diagram to further limit the range of stabilized feedback gain, leading to improved dynamic performance. Moreover, the robustness of AFO is guaranteed with the proposed feedback gain under IM parameter mismatch. The validity of the proposed method is confirmed by comparative experiments.

There are many adaptive full-order observer (AFO)- based simultaneous speed and stator resistance estimation techniques for speed-sensorless induction motor (IM) drives. However, they still need to be improved since the stator resistance estimator is sensitive to speed and load torque variations, especially under low-speed and light-load conditions. In response to this problem, an improved “phase-shift”-based compensation method is proposed for the stator resistance estimation in this paper. Compared with the existing methods, the proposed stator resistance estimation approach is decoupled with the speed estimator by adopting an operating-point-tracking compensation coefficient. Accordingly, the robustness of the stator resistance estimation is guaranteed to speed and load torque variations. The neglected estimated rotor flux error is first introduced for the proposed stator resistance estimator to distinguish the stator resistance error component. Then, the sensitivity analysis of the proposed compensation coefficient against parameters variations is carried out. Furthermore, the stability of the speed estimator and the stator resistance estimator is guaranteed owing to the proposed method. The experimental results highlight the effectiveness of the proposed method for improving the accuracy and the stability of the stator resistance estimator under different speeds and load torque conditions.

The stability of adaptive full-order observer (AFO) can be improved by feedback gain tuning and speed adaptive scheme modification for sensorless induction motor (IM) drives in low-speed regenerating mode. However, few researches concern this problem with attention to IM operating point changes. To cope with this problem, this paper proposes an operating-point tracking method to design feedback gain and speed adaptive scheme for AFO. Compared with the existing approaches, lower synchronous speed can be accessible during step speed and load changes in low-speed regenerating mode without signal injection. Addressing the operating point changes, the estimated flux error is derived by adapting the projection of estimated current error with respect to speed and torque. The derivative estimated flux error with changing parameters is taken as an additional variable to design feedback gain. Meanwhile, the speed adaptive scheme is modified by the operating-point tracking expression. As a result, the proposed method acquires the capacity to track the operating point in real time. The experimental results on a 2.2kW IM experimental setup confirm the effectiveness of the proposed method.

For speed-sensorless induction motor (IM) drives, the observability of rotor speed is still a challenging problem under steady-state operations at low synchronous frequencies. To cope with this problem, an enhanced magnetizing current-oriented low frequency ride-through (EMCOLFRT) method is proposed for adaptive full-order observers to ensure the observability of rotor speed. The adaptive changes of magnetizing current reference are generated to maintain the speed observable margin near zero synchronous frequency. Compared with existing methods, it avoids the noises caused by direct rotor flux reference calculation. In addition, the feedback matrix is employed to narrow the unstable regenerating region, and enlarge the observable margin. Addressing the detailed implementation, the analyses are provided with respect to output torque constraint, magnetizing current selection, and observability. Finally, the effectiveness of proposed method is validated on a 2.2kW IM experimental bench during low frequency ride-through.

To increase torque density, a combined-Halbach array for the axial flux permanent magnet machine (AFPMM) with a yokeless and segmented armature (YASA) is presented in this article. First, the YASA machine models with conventional axial magnets and combined-Halbach array magnets are established by using 3-D finite-element method (FEM). Then, the torque, torque per magnet-volume, and no-load back electromotive force (back EMF) are calculated, and the performance of the two machines is analyzed and compared. It is demonstrated that the combined-Halbach array can improve the torque density of the machine and the utilization rate of the magnets. Finally, the combined-Halbach array rotor is optimized, where the rotor with unequal-thickness magnets is established, and its torque density is calculated under different thickness. The results show that the combined-Halbach array with unequal-thickness magnets can decrease the amount of permanent magnet (PM) materials, thus improving the utilization of magnets and reducing the costs.