In order to improve the observation accuracy of rotor positions in the sensorless control of permanent magnet synchronous motors and to simplify the parameter adjustment process, this paper proposes an improved finite-time adaptive super-twisting sliding mode observer. First, a linear gain term is introduced into the conventional super-twisting sliding mode observer model as a way of improving the identification accuracy of the observer. Then, for the multi-parameter variable problem in the traditional observer model, a rotational speed variable function design is presented, which simplifies the multi-variables into a single adaptive variable. This reduces the complexity of the observer model while further improving the observation accuracy and stability of the improved observer algorithm (which is verified using Lyapunov’s stability theory). A new back EMF filter and an adaptive phase-locked loop are then used to improve the model’s speed tracking capability. Finally, through simulation and experimental tests, the improved algorithm’s ability to quickly observe changes in rotor position and speed, as well as its fast convergence, small jitter and high accuracy characteristics, are verified.

This paper studies the speed control strategy of a switched reluctance motor based on angle-position control (APC). The switched reluctance motor has three control parameters: turn-on angle, turn-off angle and voltage PWM duty cycle. This paper studies the function of the three parameters and designs the control algorithms of the parameters, respectively, which can reduce the coupling degree, simplify the control process, and realize the optimal control of the switched reluctance motor. By studying the nonlinear characteristics of the switched reluctance motor, the optimal current waveform in the effective working range of the inductor is obtained, and then a control strategy of the turn-on angle is designed to realize the ideal winding current waveform. According to the torque characteristics of the motor, taking the coincidence of the freewheeling zero point and the position angle at the end of the maximum inductance interval as the control target, a control strategy for the turn-off angle that makes full use of the effective inductance working interval is proposed, which improves the efficiency of the system. For the nonlinear and time-variant switched reluctance motor running process, a data-driven model-free adaptive control algorithm is introduced, and a switched reluctance motor speed control algorithm based on voltage PWM duty cycle is designed. The main contribution of this paper is to propose a control strategy that is generally applicable to switched reluctance motors, which does not depend on the precise mathematical model of the motor. The control algorithms are designed separately for the three control parameters according to the characteristics of the motor, which reduces the degree of coupling among them. A switched reluctance motor drive system based on angle-position control is designed. This strategy is especially suitable for driving the load with sudden large torque pulsation.

The purpose of this paper is to study the sensor-less rotor position estimation method for permanent magnet synchronous motors, and to achieve accurate estimation of rotor position in different conditions. Firstly, the traditional super-twisting observer algorithm is analyzed, and a new discrete variable gain sliding mode observer is designed to solve the buffeting problem in discrete systems, taking the reaction force as the disturbance signal. By estimating the back potential of the observer, the buffeting problem in the sliding mode algorithm can be effectively improved as shown by the simulation results. Then, to solve the problem of phase delay in rotor position estimation, an adaptive orthogonal phase-locked loop method is used to compensate the estimation error caused by the change in motor speed and increase the estimation accuracy of rotor position. The stability of the method can be proven by Lyapunov’s second method. Simulation experiments verify the accuracy of the proposed PMSM rotor position estimation method.

This article proposes the design of a miniaturized integrated starter–generator (ISG) system applied to a portable mobile power plant. The system utilizes a single-stator and single-rotor axial flux permanent magnet (PM) machine to meet the demands of light weighting and compaction. The stator adopts fractional slot concentrated winding to save space. The rotor is constructed in segmented PMs, resulting in an 83% reduction in eddy current loss. A quasi-3D magnetic equivalent circuit model is proposed for fast and accurate electromagnetic analysis. By optimizing the initial design using a multi-objective genetic algorithm, the power density of the optimized design reaches 1.23 kW/kg. To handle the axial attraction force, a fixing solution with stepped-shape PMs and aluminum alloy rings is introduced. In addition, the external heat of the engine and the anisotropic heat transfer coefficient of silicon steel are fully considered in computational fluid dynamics. The results show the efficient performance of the designed air-cooled structure. Finally, a prototype is manufactured and tested in the modes of starter and generator. The experimental results validate the prediction of the analytical method and the high performance of the ISG machine.

The high accuracy and flexibility of the digital phase-locked loop (DPLL) make it a versatile tool with a wide range of applications in modern sensor technology. This article designs a new controller based on the traditional SOGI-PLL (second-order generalized integral phase-locked loop) and the Ultra-Local Model (ULM). The proposed algorithm does not rely on the detailed structure of each part of the PLL, but instead uses a ULM to replace the PLL structure and closed-loop loop. Firstly, the unknown disturbance of the ULM is estimated through a finite-time stability observer (FSO). Then, a discrete-time second integral sliding-mode controller (DSISMC) is designed based on the integral sliding surface, and the DPLL model is corrected offline using the obtained data. The theoretical results are mathematically rigorously proved, and the results of the simulation study show that the proposed method exhibits faster and superior performance in signal estimation and tracking compared to traditional PID algorithms.

In order to improve the control performance of the position sensorless control system of permanent magnet synchronous motors and to reduce the influence of external uncertainties on the control system, such as inertia ingestion and load disturbance, this paper proposes a novel position sensorless control algorithm for permanent magnet synchronous motors based on an interleaved parallel extended sliding mode observer. Firstly, in order to identify the time-varying moment of inertia, load torque and viscous friction coefficient of the system, a novel interleaved parallel extended sliding mode observer based on a single-observer model is proposed, and a robust activator is designed to reduce the coupling between the parameters to be measured. Then, a new predefined-time sliding mode controller is designed for the face-mounted permanent magnet synchronous motor using sliding film control theory, which improves the response speed and control accuracy of the system. Then, the proposed novel interleaved parallel extended sliding mode observer and predefined-time sliding mode controller are used to design the permanent magnet synchronous motor control system, and the stability of the system is proved using the Lyapunov stability theorem. Finally, through simulation analysis and experimental tests, it is verified that the control strategy proposed in this paper can improve the identification accuracy of the motor parameters, reduce the time of identification, and improve the control accuracy and tracking speed.