Interturn short circuit (ITSC) fault is a common fault in electric machines, which may severely damage the machines if no protective measure is taken in time. There are numerous fault diagnosis methods under a steady-state condition. However, there is relatively limited research on fault diagnosis under dynamic conditions. The dynamic operation of motors, such as in electric cars, is a very common scenario. Hence, this paper proposes a search-coil based online method for detecting ITSC fault in permanent magnet synchronous machine (PMSM) under a dynamic condition. The search coils are placed on the stator circumference at equal intervals. Each search coil reflects the information about the magnetic field in its vicinity and also contains the fault information. In this paper, the voltage induced by the odd sideband harmonics around the even carrier (2ωc±ω0) is selected as the fault characteristic to be used in effectively improving the detected signal-to-noise ratio by excluding the interference of the counter-potential of the permanent magnet. Since two adjacent search coils are placed one pole apart, a set of quadrature signals can be acquired. The Digital Lock-In Amplifier (DLIA) technology is applied to extract the amplitude of the characteristic voltage, which overcomes the shortcomings of the traditional spectrum analysis in applying to non-stationary conditions. The amplitudes of the voltage at different search coils can be compared to further determine the occurrence of a fault and also its rough location if occurred. Experiments were conducted with a six-phase PMSM for demonstrating the effectiveness of the proposed method. The obtained results show that the proposed method can accurately determine the occurrence of a fault.

Shaftless propulsion technology delivers high efficiency and low noise for subsea installations and marine vessels. To enhance thrust performance, the streamlined aft-body contour imposes stringent demands on geometric compatibility between the rim-driven thruster (RDT) motor and hull. This necessitates advanced electromagnetic characterization of conical motors. This paper proposes an equivalent magnetic circuit model (EMCM) that accounts for end effects and magnetic saturation in both the stator and rotor cores for the magnetic field analysis of conical permanent magnet synchronous motor (CPMSM). A 3D EMCM is developed by decomposing the air-gap flux into radial/axial/tangential components. End-field nonlinearities are addressed via lumped-parameter network modeling. Innovatively, a trapezoidal expanded magnet layout and magnet-pole-trimming technology are adopted to ensure sinusoidal flux distribution. Finally, a 10.5 kW prototype with a conical angle of 6.7 degrees is designed using the EMCM and verified through a finite-element analysis (FEA) and experiments. This research provides a theoretical framework for the rapid electromagnetic analysis of the CPMSM.

Irreversible demagnetization of permanent magnets (PMs) in PM synchronous motors (PMSMs) degrades the performance and efficiency of a machine and its drive system. There are numerous fault diagnosis methods for detecting demagnetization under steady-state conditions. However, only a few works could be found on fault diagnosis under dynamic conditions, whereas the dynamic operation of a motor is a very common scenario, e.g., electric vehicles. The voltage and current signal-based traditional fault detection method is not only affected by the structure of the motor, but it also becomes complicated to extract signals involving fault characteristics. Hence, this paper proposes a search coil-based online method for detecting demagnetization faults in PMSMs under dynamic conditions, which are not affected by the motor structure. To gather the flux of the stator tooth, flexible Printed circuit board (FPCB) search coils are positioned at the stator slot. The search coil is made up of two branches that are one pole apart and arranged in reverse sequence. In this installation option, the output signal in the fault state cannot be eliminated, and the output signal in the health state is zero. This paper defines only that characteristic value related to the position angle of the rotor. Further, the aim was to simultaneously eliminate the influence of elements like the search coil installation error and the inherent dispersion of the permanent magnet on the detection results. To characterize the fault degree, the measurement differential between the health state and the fault state is further integrated according to a predetermined angle range. Last but not least, speed-independent detection of individual permanent magnet demagnetization faults is possible using rotor position and stator tooth flux. A six-phase PMSM was used in experiments to show the efficiency of the suggested approach. The findings of the experiment demonstrate that the suggested strategy may precisely ascertain when a defect will occur.

Tiltrotor aircraft, due to their vertical takeoff and landing capability and efficient high-speed cruise performance, are increasingly valuable in both modern military and civilian applications. However, traditional calibration methods for blade pitch control often lack the precision required for large actuator strokes, which limits the control accuracy. This study aims to overcome these limitations by introducing an improved polynomial fitting algorithm to model the nonlinear relationship between the blade pitch control angles and actuator strokes. Using a specific rotor model, a coordinate system was established for the pitch control mechanism and spatial geometric relationships were derived. Experimental comparisons demonstrate that the proposed cubic polynomial fitting algorithm reduces the collective pitch error by approximately 57% and cyclic pitch error by 33%, markedly outperforming traditional linear fitting methods. These improvements significantly enhance the control precision and operational stability. The findings provide a reliable theoretical and practical basis for improving tiltrotor flight performance and safety.

This paper proposes a two-dimensional (2D) generalized equivalent magnetic network (GEMN) model suitable for surface-mounted permanent magnet electric machines (SPEMs). The model divides the SPEM into eight types of regions: stator yoke, stator tooth body, stator tooth tips, stator slot body, stator slot openings, air gap, rotor permanent magnets, and rotor yoke. Each region is subdivided radially and tangentially into multiple 2D magnetic network units containing radial and tangential magnetic circuit parameters, forming a regular magnetic network covering all regions of the SPEM. The topology of this magnetic network remains unchanged during rotor rotation and can accommodate various surface-mounted permanent magnet structures including Halbach arrays, which enhances the generality of the model significantly. The proposed model can be used to calculate the 2D magnetic flux density distribution, winding electromotive force, electromagnetic torque, stator iron loss, and permanent magnet demagnetization in the influence of magnetic saturation, stator slotting, and current harmonic. Comparative analysis with the accurate subdomain method (ASDM) and finite element method (FEM) demonstrates that the GEMN model achieves a good balance between computational speed and accuracy, making it particularly suitable for efficient electromagnetic performance evaluation of SPEMs.