In this paper, the 12-phase switched flux (SF) permanent magnet (PM) (SFPM) machine and three surface-mounted PM (SPM) machines designed for direct-drive wind power generation are comparatively analyzed. Firstly, feasible stator-slot/rotor-pole combinations for symmetrical 12-phase winding layout are investigated for both machine topologies. Secondly, the key design parameters of the PM generators including the split ratio and stator teeth width ratio are optimized by finite element (FE) analysis, to achieve a high phase fundamental EMF per turn and a low cogging torque, both of which are desired by the direct-drive wind power generator. Thirdly, electromagnetic performances including air-gap field, cogging torque, static torque, inductance, output voltage and its regulation factor, output power and efficiency of the generators are compared. A 10 kW 24-slot/22-pole SFPM prototype is built and tested to validate the FE predicted results.

In this paper, two flux-switching permanent-magnet (FSPM) wind power generators with 9- and 12-phase windings are designed and comparatively analyzed. Both two generators are designed under the rated specifications of 10 kW output power and 220 V phase voltage at 500 r/min. The static characteristics and power generating performances including output voltage, power, and efficiency at rated and variable load/speed conditions are predicted by finite-element analysis and validated by experimental tests based on the two FSPM prototypes. It shows that the 12-phase 24-stator-slot/22-rotor-pole FSPM generator exhibits a higher air-gap flux density, a higher torque/power density, and a lower voltage regulation factor. Besides, it has a better overload capability than its 9-phase 36-stator-slot/34-rotor-pole counterpart when the load and wind speed exceed the rated levels. The comparative study reveals the benefits of the lower leakage flux and permeance from the larger stator-slot opening and longer magnetic circuit.

A correct understanding of fluid flow and heat transfer characteristics in oil injection cooling for hairpin end winding is crucial for accurate thermal analysis. This article utilizes a meshless computational fluid dynamics (CFD) approach, based on moving particle simulation (MPS), to develop a simplified numerical model. The model provides qualitative insights into fluid dynamics and heat transfer mechanism in hairpin end winding. Experimental validation is conducted to compare the numerical data and identify key factors influencing oil coverage rate (OCR) and heat transfer coefficient (HTC), including the number and placement of inlets, coolant flow rate and temperature, and rotation speed. The results indicate that increasing the number of inlets and optimizing their placement enhances cooling uniformity. Furthermore, the HTC is strongly influenced by the coolant flow rate and temperature, with an average HTC of 130 W/m²/K achieved at an inlet temperature of $40~^{\circ }$ C and a flow rate of 8 L/min. The highest HTC values are found in the lower winding layers due to the downward flow of oil. Rotation also improves the OCR and HTC by approximately 20% and 37%, respectively, at 1000 r/min, as oil droplets are sprayed onto the winding surfaces, particularly near the rotor. However, at higher rotational speeds, the cooling efficiency stabilizes, and the effect of rotation becomes less significant.

The recent emergence of wide bandgap power devices enables higher switching frequencies in electric motor drives. The subsequent possibility for higher efficiency and smaller size requires accurate prediction of harmonic losses in motors. Therefore, in this article, an original analysis of harmonic losses arising in inverter-fed two-pole slotless permanent-magnet machines with axially segmented ring magnets is presented. The developed three-dimensional time-efficient numerical model is successfully validated under high-speed no-load operation using a silicon carbide based three-phase inverter and rotors carrying a broad range of magnet segment thicknesses (3-12.6 mm). The model enables harmonic loss prediction capability (including loss separation) with an accuracy of 15% over a wide frequency range (8-120 kHz), which is a unique contribution. The sensitivity analysis primarily emphasizes the importance of taking into account the axial segmentation, and secondarily the rotor-shaft magnetoelasticity effects for accurate modeling of harmonic losses. The conducted case study demonstrates that wide bandgap transistors effectively can contribute to eliminating the need for inductive filters in motor drives.

Prediction of iron loss in electrical machines is known to be a challenging task. The concept of a building factor to account for discrepancy between predicted and measured loss is widely used. From literature, these building factors may need to be as high as 1.5 to 2, i.e., a discrepancy of up to 100%, leading to different impact on total losses for every electrical machine. To calibrate the building factor, modelling and testing are required. This paper describes an extensive test campaign on PM synchronous machines at no-load with magnetized and dummy rotors. Several challenges to accurately quantify no-load iron loss by dynamic testing for model calibration are reported, highlighting the benefits of rotor temperatures monitoring, and performing repeatability checks. For accurate prediction of iron loss impacted by mechanical stress (due to cut edge damage or shrink-fit for example), advanced modelling approaches require electrical steel properties (BH and loss density) as function of tensile and compressive stress. Such measurements with a dedicated single sheet tester have not yet been standardized. Repeatability issues and spread of measured data are presented and their influence mitigated by a pre-cycling procedure. A novel method to compare the impact of stress on several electrical steel grades including thicknesses from 0.1 mm to 0.35 mm indicates different grades follow similar trends. However, the changes are grade-specific, requiring characterization of each material grade at multiple stress level, frequency, and flux density for advanced modelling of e-machine performance.