In order to reduce the cost of the sensor for switched reluctance motors (SRMs) and improve the accuracy of position estimation, a sensorless control strategy based on the orthogonal flux linkage and improved phase-locked loop (PLL) is proposed in this article, along with a fault-tolerant control scheme to ensure operational performance under single-phase fault conditions. The proposed control strategy is applied during the medium-high speed stage. First, the nonlinear rotor flux linkage containing position and speed information is expanded into a Fourier form. By using a dual second-order generalized integrator quadrature signal generator, the DC bias and high-order harmonics are eliminated, and a set of mutually orthogonal flux linkage signals is generated. Then, the differential of the motor speed is taken as the extended state variable of the extended state observer, the rotor estimated position and speed can be obtained by using the extended state observer-based phase-locked loop to process the orthogonal signals. Furthermore, a fault-tolerant control strategy is proposed to enhance the performance of this control strategy in the case of single-phase fault. Finally, a comparative experiment is conducted on a six-phase 12/10 SRM against the traditional method. The experimental results show that this control strategy not only validates the superiority of the proposed sensorless control strategy, but also demonstrates its satisfactory estimation performance under single-fault conditions.

To address the problems of flux linkage nonlinearity and reduce the cost of estimation in position estimation of sensorless switched reluctance motors (SRMs) at medium to high speeds, a sensorless SRM control scheme based on harmonic elimination and interval position estimation is proposed in this article. In addition, a single-phase fault-tolerant control strategy is proposed to address the possible occurrence of single-phase faults. First, the flux linkage-related quantity containing rotor position information is processed by Fourier expansion to obtain the flux linkage function. Then, by enhancing the harmonic signal elimination (HSE) operator, a multistage harmonic elimination flux observer (MSHE-FO) is designed, which enables the generation of a set of orthogonal flux linkage signals. Subsequently, the proposed interval search estimation (ISE) method is utilized to obtain the optimal estimated position. Furthermore, this article proposes a single-phase fault-tolerant control strategy based on the logical relationship between the phase current and the phase winding operational mode. Finally, experiments are conducted on a six-phase 12/10 SRM experimental platform. The experimental result not only verifies that the proposed sensorless control strategy offers higher control accuracy than the conventional phase-locked loop (PLL) method but also confirms the effectiveness of the fault-tolerant control strategy.

To address the problems of reluctance discontinuity and integral drift in sensorless control of switched reluctance motors (SRMs) during low-speed operation, this paper proposes a sensorless SRM control scheme based on high-frequency (HF) voltage injection and reluctance correction. First, HF voltage is injected into the non-conducting phase to obtain the phase reluctance over a full cycle, thereby resolving the discontinuity problem of the reluctance curve. Then, an amplitude correction algorithm (ACA) and a drift compensation algorithm (DCA) are designed to correct the reluctance and suppress drift in the reluctance curve. Subsequently, joint position estimation is performed by detecting the negative zero-crossing of the slope at the misaligned position of the reluctance and the slope detection interval at the position where the rotor and stator begin to overlap. This approach does not rely on a single characteristic point, significantly improving the robustness and accuracy of position estimation. Finally, the proposed sensorless control strategy is experimentally validated on a six-phase 12/10 SRM test platform.

To improve the slow convergence speed and chattering phenomenon in the traditional sliding mode observer (SMO), a speed sensorless control strategy of a bearingless induction motor (BIM) based on SMO with improved double power reaching law (IDPRL) is proposed. First, the stator current error is selected as the sliding surface, and SMO for the stator current and rotor magnetic flux are constructed. Second, based on the analysis of traditional reaching laws, an IDPRL is designed. To realise the adaptive control of the system state and reduce chattering and convergence time, the state variable is introduced into the IDPRL. Third, the stability of the proposed reaching law is proved by Lyapunov's theorem, and a speed adaptive observer is constructed based on the coupling terms to achieve accurate observation of the motor speed. Finally, simulations are conducted on the Matlab/Simulink platform, and experimental validation is performed on a prototype. The results show that the proposed speed sensorless control strategy not only improves the accuracy of the speed estimation but also reduces the chattering and convergence time, as well as has good suspension performance.

To further improve the accuracy and expand the applicability of sensorless control, an improved scheme is proposed in this article which uses a sliding mode observer (SMO) and a phase-locked loop (PLL) for a dual three-phase permanent magnet synchronous hub motor (DTP-PMSHM). First, the supertwisting algorithm (STA) is combined with the adaptive algorithm and applied to the observer to improve its accuracy and expand its applicable speed range. Second, an iterative algorithm based on the Secant method is introduced into the PLL designing an infinite position set (IPS) PLL (IPS-PLL) to avoid conventional defects and to improve the rotor position information estimation. Finally, a series of experiments are conducted to compare various performances of the proposed control scheme with the conventional control scheme. The superiority and feasibility of the proposed sensorless control scheme are demonstrated by experimental results on a DTP-PMSHM. The proposed scheme has fewer parameters and is portable, and improves the accuracy of control, which has practical significance in improving the control precision and practical application.

To address the parameter sensitivity issue of Flexible Joint Permanent Magnet Synchronous Motors (FJ-PMSMs) when employing a candidate voltage vector strategy, an adaptive method based on the Lyapunov function predictive model is proposed. By using the finite control set model predictive control (FCS-MPC) approach, the continuous input control law is transformed into relevant constraints of the FCS-MPC optimization problem. Specific equations are constructed through online adaptive laws to ensure system robustness, thereby tracking performance and minimizing current ripple. The effectiveness of the strategy is verified by experiments, the proposed strategy is compared with conventional MPC control methods. It effectively resolved the parameter uncertainties and load disturbance issues of the FJ-PMSM, showing superior current quality over traditional methods.

To reduce the parameter sensitivity of flexible joint permanent magnet synchronous motors, a robust adaptive resonant control strategy is proposed in this article. The robustness and overall performance of traditional adaptive resonant controllers are often compromised by their high sensitivity to aperiodic disturbances such as load torque, motor parameters, and friction torque. To address these issues, the proposed strategy uses a linear extended state observer to accurately estimate and compensate for the disturbance effects. The proposed control strategy dynamically compensates for magnetic flux linkage variations and implements real-time parameter estimation, effectively mitigating the adverse effects of motor parameter drift on control system performance. The effectiveness of the control strategy is verified by experiments. The speed fluctuation of the motor is reduced by about 20%, and its control performance is better than that of the traditional resonant controller.

This paper focuses on optimizing a sensorless control scheme for dual three-phase permanent magnet synchronous hub motors (DTP-PMSHMs). The proposed scheme introduces a novel methodology involving the injection of two high-frequency (HF) square-wave signals into the harmonic subspace which leverages the characteristics of the harmonic subspace, resulting in reduced torque ripple. Subsequently, the information containing the rotor position is extracted by discretizing the obtained response current and modulating it. Motived by the finite control set-model predictive control (FCS-MPC), a novel observer is designed to determine rotor position. The proposed IPS-observer achieves superior convergence speed and accuracy through the optimization of cost function and iterative method. The effectiveness and feasibility of the proposed scheme are validated through comprehensive experiments on an experimental platform.

First, to handle the fault identification of displacement sensors for a bearingless induction motor (BIM), a fault diagnosis strategy based on wavelet transform and asymmetric displacement sensors is proposed. An initial diagnosis is made by analyzing the numerical relationship between the output values of asymmetric displacement sensors. Then, the final diagnosis is completed by combining the local maximum value of the output signal from the sensor after the wavelet transform. Second, to achieve the normal operation of the BIM after the failure of the displacement sensor, a fault-tolerant control system is established using an asymmetric structure and a coordinate transformation matrix. Different coordinate transformation matrices are selected according to the specific combinations of sensor faults. The simulation and experimental results demonstrate that the proposed fault diagnosis strategy can accurately identify six different combinations of faulty sensors. Furthermore, after a fault occurs, the fault-tolerant control system enables the motor to restore normal operation within 0.02 s, significantly improving the reliability and operational stability of the BIM.

To enhance the suspension performance of a bearingless induction motor (BIM), the Maxwell force equation is deduced based on an accurate analytic method, and a novel magnetic-balanced module is proposed in this article. First, according to the Gauss theory, the expression of Maxwell force at the air-gap is obtained, and it is divided into two parts of suspension force and unbalanced pulling. Second, considering the impact of high-order components of rotor eccentricity, the precise expressions of the two types of Maxwell force are changed into the form of infinite series, and their general formulas are concluded by mathematical induction. Based on analyzing the Maxwell force's infinite series with different poles, a magnetic-balanced control module is proposed in the control system. Finally, the control system of the new type of BIM is constructed, and an experimental platform is built to verify its feasibility and superiority. By simulation and experimental results, it has been validated that the proposed BIM with magnetic-balanced module can effectively reduce the high-order components of rotor eccentricity and has a better suspension performance compared with the initial machine.

With the growing demand for high-performance electric motors in various applications, particularly in electric vehicles, the need for advanced control strategies is critical. Model Predictive Current Control (MPCC) has emerged as an effective solution for addressing current ripple, dynamic performance, and efficiency. This paper presents a multi-vector switching model predictive current control (MVS-MPCC) method for a five-phase permanent magnet synchronous hub motor based on optimal virtual vector duty cycle optimization. Firstly, a multi-vector switching method is proposed and an automatic switching area is set to solve the problem of poor steady-state performance in single-vector methods and high switching frequency in multi-vector methods. This approach enhances steady-state control performance at a specified switching frequency, maintains a quick dynamic response, and reduces computational complexity. Secondly, an optimal duty cycle optimization method based on virtual voltage vectors is proposed. This technique maintains the benefit of eliminating harmonic voltage while enhancing DC voltage utilization and expanding the speed range. Additionally, the method exclusively uses large vectors to reduce common mode voltage. Finally, the effectiveness and feasibility of the proposed scheme are verified on the experimental platform by comparing it with existing methods.

Conventional deadbeat predictive current control (DPCC) is an efficient strategy for permanent magnet synchronous motors (PMSMs) due to the advantages of quick response, easy implementation and high performance. However, parameter mismatch will degrade the entire control system’s performance. To solve this problem, a robust DPCC based on current error compensation is proposed. The motor parameters are updated by calculating the relative terms of inductance and flux linkage of the motor system. The current error compensator is designed to obtain the compensation current and identify the inductance and flux linkage in real time. Finally, the robustness of the proposed method under parameter mismatch and the accuracy of parameter identification are verified by experiments.

An enhanced nonlinear ADRC strategy is proposed in this article to address the frequency-domain characteristic deficiencies in traditional active disturbance rejection position control (ADRC) systems. This article improves the extended state observer (ESO) and feedback control law. The linear feedback control law constrained by both proportional and derivative-proportional gains is employed, while a fourth-order enhanced nonlinear ESO (EH-NESO) is designed based on the nonlinear ESO framework. The proposed method combines nonlinear functions and disturbance derivative observation techniques, exhibiting superior dynamic response performance and control stability under certain conditions. Experimental validation on the flexible joint permanent magnet synchronous motor (FJ-PMSM) demonstrates that the position control strategy proposed in this article exhibits outstanding disturbance rejection performance.

In bearingless induction motors (BIM), the performance is significantly influenced by two sets of windings embedded in the stator slots for suspension and torque. To enhance the suspension and torque performance of BIMs, a multi-objective optimisation design method for BIM stator slot parameters was proposed in this paper. Firstly, based on the analysis of the mechanism for generating suspension force in BIMs and the identification of optimisation parameters for the motor's stator slots, high-sensitivity optimisation parameters had been determined through experiments using the Taguchi method and sensitivity analysis. Secondly, the BIM stator slots were modelled using the response surface methodology, combined with an enhanced multi-objective non-dominated sorting genetic algorithm (NSGA-II). A comprehensive optimisation was conducted for the high-sensitivity parameters, namely slot width Hs0, slot opening depth Hs1, and slot depth Bs0, to identify the optimal parameter combination that maximises both suspension and torque performance. The effectiveness of stator parameter optimisation was verified by comparing the motor's torque and suspension force performance before and after optimisation. Finally, a physical prototype of the optimised motor was constructed, and an experimental platform was established to test the performance of the optimised motor. Both simulation and experimental results indicated that the optimised motor experienced an increase in average suspension force, with reductions in both torque and suspension force ripple, leading to a significant enhancement in BIM performance.

To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, an improved model-free predictive current control based on extended state observer (ESO) with voltage source inverter (VSI) nonlinearity compensation is proposed. First, an improved model-free predictive current control (MFPCC) based on the ESO of PMSM drives is introduced, which does not require motor parameters and needs less tuning work. Then, a voltage source inverter nonlinearity compensation method is proposed to reduce the current distortion resulting from the added dead time in the three-phase bridge voltage source inverter. The approximate parameters are obtained through adjusting in the simulation, and then applied to the experiment for further fine-tuning. The model-free control based on ESO and voltage source inverter (VSI) nonlinearity compensation are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, the experimental results prove its robustness to both periodic and aperiodic disturbances.

This article proposes a model predictive current control (MPCC) with enhanced robustness for a six-phase switched reluctance motor (six-phase SRM) based on an improved Lehuy model (ILM). First, based on the six-phase SRM's nonlinear characteristics and the conventional Lehuy model (CLM), a high-fidelity ILM is established, demonstrating its advantages in reducing modeling errors. Next, the MPCC for the six-phase SRM is introduced, including current prediction calculation, selection, and optimization of candidate voltage vectors (CVVs). Then, the impact of parameter mismatch during motor operation is quantitatively analyzed. Sliding mode disturbance observer (SMDO) is used to compensate for predicted current and observe parameter disturbances in real-time, a composite control system for the six-phase SRM is constructed. Experimental results suggest that compared with conventional MPCC, the composite MPCC controller based on ILM can effectively address the degradation of control performance caused by parameter mismatch. The implementation of this method provides an effective notion for six-phase SRM's advanced control.

To enhance the rotor radial displacement identification accuracy of a bearingless induction motor (BIM) in displacement sensorless control, a displacement sensorless control strategy based on modified high-frequency signal injection is proposed. Firstly, a BIM flux linkage equation is analyzed, and by integrating the principle of the conventional high-frequency signal injection method, a self-detection model for the BIM rotor radial displacement is established. Secondly, a cascade notch filter and a low-pass filter are used in the signal demodulation process of the modified high-frequency signal injection. This strategy enables the DC component relevant to rotor displacement to be extracted from the high-frequency current?and obtains the rotor radial displacement equations. Finally, compared with the conventional high-frequency signal injection control, the proposed BIM displacement sensorless control system based on the modified high-frequency signal injection has higher displacement identification accuracy under different operation conditions, such as no-load, sudden load, and radial displacement mutation, as shown in simulation and experimental results. Overall, the motor performs well in terms of speed and suspension.

In the context of applying direct torque control (DTC) to switched reluctance motors (SRMs), negative torque is generated to track the demanded torque, which reduces the system efficiency. To reduce torque ripple and enhance system output efficiency, this article proposes an optimization strategy based on online adjustment of sector positions for DTC method of a six-phase SRM. First, using the magnetic characteristics and torque generation properties of DTC, a new voltage vector is designed, and phase commutation rules are reformulated to reduce the occurrence of negative torque and enhance the torque-ampere ratio. Then, an optimal torque ripple constraint algorithm is proposed, allowing for real-time adjustment of the DTC sector positions based on the prevailing operating conditions, thereby reducing the significant torque ripple during commutation and optimizing torque control. Finally, the effectiveness of the proposed approach is validated through a 12/10-pole six-phase SRM.