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The faulty degree assessment and faulty phase detection method of eVTOL propulsion motors Inter-Turn Short-Circuit (ITSC) are proposed in this paper based on the back electromotive force (back EMF) characteristics. A sliding mode observer (SMO) is utilized to dynamically monitor dq -axis back-EMF variations caused by ITSC faults. Faulty severity quantification is performed through second harmonic component analysis, while faulty phase identification is achieved by characterizing residual signals in the abc -axis back-EMF framework. The mathematical relationship between the rotational speed and the faulty degree evaluation indicator is established to overcome the limitation of the traditional method under variable rotational speed conditions, thereby enhancing the engineering applicability of the method is improved. Simulation and experimental results show that the proposed method remains effective under steady-state and variable-speed operating regimes.

This paper proposes a current model predictive control strategy for the permanent magnet synchronous motor (PMSM) based on a novel sliding mode observer to reduce the cost of PMSM and ensure good tracking performance. A super twisting sliding mode observer (STSMO) is designed to address the issues of high-frequency chattering and noise sensitivity caused by the large positive gain of traditional SMO. The discontinuous effect of the traditional SMO switching function is introduced into the derivative of the control rate, and a smooth estimate of the back electromotive force (EMF) is obtained through integration. Replace the sign function with a sigmoid function with smooth continuity to further reduce the chattering effect. To enhance the dynamic performance of the PMSM current loop, a finite control set model predictive control (FCS-MPC) strategy is employed in place of the conventional PI controller. Within each sampling period, all possible switching states are evaluated, and the optimal one is selected and directly applied to the inverter. Additionally, a dual-vector model predictive current control (DVMPCC) method is adopted to reduce current ripple. This approach synthesizes a voltage vector with arbitrary magnitude and direction by combining two voltage vectors within each sampling period. Numerical results demonstrate that the proposed sensorless PMSM predictive current control method achieves high accuracy in speed estimation and excellent dynamic response performance.

Aiming at the limitations of traditional dual-stator field-modulated machines (DS-FMMs) in torque density and permanent magnet (PM) utilization, this paper proposes the DS-FMM with asymmetric PM excitation on the stator. The proposed DS-FMM (model I) uses asymmetric PM excitation, which can effectively reduce magnetic leakage and improve the back-electromotive force (back-EMF) and air-gap flux density, so as to improve the torque performance while maintaining the overall volume and the amount of PM unchanged. Based on finite element analysis (FEA), four different DS-FMMs (model I, model II, model III and model IV) were compared. The results show that model I not only has higher average torque output, but also can effectively suppress torque ripple compared with model II, model III and model IV. These research results provide the new technical way for the development of FMM with high power density and high material utilization, and also provide the useful reference for the development of machine technology in the fields of electric vehicle drive and industrial servo system.

A fault-tolerant vernier permanent magnet machine (FTVPMM) with five phases for direct-drive occasions is designed and analyzed. The construction of the proposed FTVPMM is introduced and the principle of the vernier modulation effect is investigated. Parameters are designed and optimized by finite element analysis (FEA), including tooth width, slot opening, PM thickness, pole-arc coefficient, air-gap length, and rotor yoke. Furthermore, major electromagnetic performances are discussed, including cogging torque, no-load back electromotive force (BEMF), output torque, and fault-tolerant capability.

Brushless DC (BLDC) motors play a critical role in low-altitude applications such as unmanned aerial vehicles, where high power density and efficiency are imperative. However, under high-speed and heavy-load conditions, the inherent inductance of motor windings causes phase currents to lag significantly behind the back electromotive force, leading to considerable current distortion, reduced average torque, and decreased overall efficiency. To address these issues, this paper proposes an optimized control strategy for square-wave-driven BLDC motors, integrating a “three-three conduction” scheme during commutation intervals with optimal advanced commutation timing. This approach ensures matched current change rates between the turning-off and turning-on phases, compensating for current drop and minimizing torque ripple. Simultaneously, advanced commutation aligns the centerlines of the phase current and back EMF, counteracting the phase lag and enhancing power output. Theoretical analysis derives mathematical expressions for the optimal advance angle and the duty cycle of the turned-off phase during commutation. The proposed strategy is applicable to BLDC motors with varying resistance and inductance levels and requires no hardware modifications. Validation via an FPGA-based platform and experimental tests demonstrates that the method significantly reduces phase current fluctuation (e.g., from ∼50% to ∼15%), improves output power, and increases motor efficiency by 2.06% to 4.95%, confirming its effectiveness and practical value in weight-sensitive low-altitude applications.

Modern industrial automation systems are increasingly incorporating PMSMs, which drives the demand for improved control performance. Traditional control methods relying on position sensors can no longer meet requirements in terms of cost and reliability, making sensorless control a critical research focus. This paper addresses the challenge of weak back electromotive force (EMF) in PMSMs under zero-and low-speed conditions, which renders traditional methods such as sliding mode observers ineffective. The study thoroughly investigates the principles and applications of the pulsating high-frequency voltage injection method. Furthermore, a complete sensorless field-oriented control system diagram for PMSM was developed on the MATLAB/Simulink platform to analyze the effectiveness of the pulsating high-frequency voltage injection method in obtaining rotor position under various starting speed conditions. Simulation verification confirms the proposed approach achieves superior rotor position estimation accuracy in PMSM FOC systems operating at low speeds.

Considering the issue of significant total harmonic distortion in the no-load back electromotive force (EMF) and torque ripple of a brushless excitation synchronous motor (BESM) used in a compressor, a multiobjective optimization design method of a BESM based on the Taguchi method was proposed. By selecting the polar arc coefficient, stator slot width, damping winding pitch, and air gap length as the optimization parameters, the maximum no-load back EMF, minimum back EMF total harmonic distortion rate, and minimum torque ripple are selected as the optimization objectives. Then, the Taguchi method was employed to construct an orthogonal table to enhance the performance of the optimization objectives. This approach facilitated the determination of the optimal parameter combination for optimization. Finally, the simulation results indicate significant enhancements in each optimized aspect of the motor’s performance following the optimization process. This outcome serves as validation for the efficacy of the Taguchi method in achieving an optimal design for the BESM.

This paper proposes a phase-locked loop (PLL) with a low bandwidth and high estimation performance in terms of position and speed through speed feedforward compensation for driving extended back electromotive force (EEMF)-based sensorless control for an interior permanent magnet synchronous motor (IPMSM). In this case, lowering the bandwidth to reduce sensitivity to disturbances of the PI controller, where the position error is controlled to zero, may create a problem of decreased estimation performance. The proposed method calculates speed through mathematical calculations of the EEMF, which is observed using an EEMF-based IPMSM model, and adds it to the output of the PLL. The added speed feedforward compensation reduces the computational burden of the PI controller. Therefore, fast estimation dynamic characteristics can be obtained even at low bandwidths. The improvement of the estimation performance of the proposed method is evaluated by analyzing the equivalent block diagram using the final value theorem theory. Through this, the estimation performance is shown. It can be seen that the position estimation error for various types of speed inputs converges to zero. In addition, validity and implementation of this method are verified by experimental results.

Two new five-phase out-rotor inner-stator permanent magnet (PM) vernier machines (PMVM) with different PM arrays are proposed to investigate the performance compared with an existing PMVM. The Halbach arrays and consequent arrays are adopted to enhance torque density. Also, the operation principle of PMVM is discussed by an analytical method. Moreover, some parameters are optimized to achieve better performance. Finally, performance such as back electromotive force, torque, loss, and efficiency are discussed by the finite element method.

The permanent magnet direct drive wind turbine is the core equipment of the wind turbine. Barrier analysis ensures its safe and reliable operation. The demagnetization failure of the permanent magnet motor will occur because the wind energy equipment works under bad conditions. Taking the permanent magnet direct drive wind turbine as the research object, this paper uses ANSYS simulation software to build a two-dimensional electromagnetic field model of the generator to simulate the uniform demagnetization fault of the permanent magnet direct drive generator to obtain the back electromotive force waveform under different operating conditions and convert the back electromotive force waveform into images as input data for fault diagnosis of the improved residual neural network. Two kinds of materials are used to verify the effect of the diagnosis model, and the simulation results show that both materials can be used for demagnetizing fault diagnosis, which proves the effectiveness of the fault diagnosis strategy.