Traditional sliding mode observers (SMOs) are prone to chattering, and existing improvement methods have limitations, such as increasing system complexity or suboptimal performance. To overcome these issues, this paper proposes an SMO based on the cooperative optimization of a sinusoidal saturation function and a dynamic gain, focusing on the switching function and observer gain. In this observer, the sign function is replaced with a sinusoidal saturation function, effectively suppressing chattering and improving estimation accuracy. Moreover, the need for a low-pass filter (LPF) is eliminated, thereby avoiding phase lag issues. Additionally, a variable gain function was designed, which is jointly controlled by the velocity error and state variables. This further reduces oscillations and errors, thereby improving the system's stability. Through Lyapunov stability analysis, the stability of the proposed observer is verified. Simulation results show that, compared to existing SMOs based on sign and saturation functions, the method proposed in this paper results in smaller speed chattering and position errors.

This paper focuses on the efficiency analysis and optimization of the Yoke-less Axial-flux Synchronous Motor (YASA), a structured axial flux permanent magnet motor. Firstly, the advantages of the YASA motor, as a new motor topology, are introduced, including high power density, high torque density, efficiency, and a slim design. Secondly, using the YASA motor as an example, a three-dimensional electromagnetic field calculation model is established, and the effects of the slot filling factor, tooth shoe thickness, and tooth shoe width coefficient on motor efficiency are analyzed. By optimizing these design variables, the iron core loss and eddy current loss of the motor are systematically reduced using response surface methodology and genetic algorithms, significantly improving the motor's efficiency. Finally, finite element analysis is used to verify the feasibility of the optimized scheme on a 10-pole, 12-slot motor. The results show that the iron core loss and eddy current loss of the motor are reduced by 36.5% and 37.8%, respectively.

While finite control set model predictive torque control (FCS-MPTC) offers fast response and direct torque control for permanent magnet synchronous motors (PMSMs), its reliance on manually tuned weighting factors in cost functions limits adaptability and robustness. To address this, a priority ranking-based voltage vector selection scheme is introduced to eliminate the need for weighting factors. Firstly, the limitations of traditional FCS-MPTC approaches are analyzed, emphasizing the necessity of replacing empirical weight tuning. Secondly, a sliding mode observer is designed to estimate torque, with Lyapunov-based analysis ensuring stability and robustness to parameter variations. Finally, a dual-priority ranking mechanism is applied to evaluate candidate voltage vectors based on dynamic performance and torque ripple, achieving effective control without increasing computational complexity. Finally, simulation is conducted on a three-phase PMSM to verify the effectiveness of the proposed FCS-MPTC strategy.

This paper proposes an improved position estimation method based on low-resolution hall sensor to meet the high-precision position feedback requirement of vector control. Firstly, this paper research on vector control theory and implementation of id=0 based motor control methods. Secondly, the space vector pulse width modulation technique is used to obtain the PWM inverter switching signal. Thirdly, the position estimation circuit uses an improved method to obtain high-resolution position information from the signal of the low-resolution position sensor. Compared to the traditional estimation method, the proposed one has the advantages of initial rotor position estimation and adaptation to Hall mounting error. The proposed position estimation method is verified by simulation conducted on a 2000.rpm BLDCM and it is confirmed that the proposed drive system can achieve high-performance current vector control.