Search Results (724)

Large-diameter axial ventilation fans are widely used in poultry houses to regulate ai flow, temperature, and air quality. However, conventional induction motors driving these fans typically operate at fixed speed and suffer efficiency degradation under low-speed, high-torque conditions due to slip-induced rotor copper losses. This study presents an experimental investigation of a manufacturing constrained conversion of a commercial induction motor platform into a direct-drive surface permanent magnet synchronous motor (PMSM). Instead of developing a completely new motor design, the proposed approach reuses the existing stator lamination, housing structure, and winding production process while redesigning the rotor electromagnetic structure to incorporate surface-mounted permanent magnets. Experimental testing was conducted using a dynamo meter-based measurement system to evaluate the performance of both the commercial induction motor and the converted PMSM prototype. The results show that the commercial induction motor exhibits significant efficiency degradation at high torque due to increased slip, whereas the PMSM eliminates slip-dependent rotor copper losses and maintains efficiencies above 88% within the typical ventilation operating range of 650–750 rpm. This study further relates airflow demand to rotational speed using fan affinity laws, highlighting the cubic relationship between speed and input power and demonstrating the energy-saving potential of variable-speed PMSM drives. The proposed conversion framework therefore provides a practical pathway for improving the energy efficiency of agricultural ventilation systems while maintaining compatibility with existing motor manufacturing infrastructure. Full article

With the capacity of generators continuing to increase, higher demands are placed on the heat dissipation of epoxy resin (EP), the main insulation material used in stator bars and windings. To overcome its low thermal conductivity, a multiscale hybrid filler strategy was adopted to investigate the effects of spherical Al₂O₃ (10 and 1 μm), platelet BN (1 μm), and SiO₂ (50 nm) on the thermal and insulating properties of EP composites. Unlike conventional studies focusing on individual fillers, this work highlights the synergistic design of fillers with different sizes and morphologies. The filler ratios were optimized by finite element simulation, and the composites were prepared by melt blending. The results show that, at a total filler loading of 38.5 wt%, the EP composite filled with spherical Al₂O₃ particles of 10 and 1 μm, platelet BN of 1 μm, and nano-SiO₂ of 50 nm achieves a thermal conductivity of 0.5497 W/(m·K), corresponding to an increase of 158.2% compared with pure EP (0.2129 W/(m·K)). This enhancement is attributed to the synergistic effect of multiscale and multishape fillers, where large Al₂O₃ particles form the main thermally conductive framework, small Al₂O₃ particles fill the gaps, platelet BN acts as a bridging filler, and nano-SiO₂ improves the interfacial region. In addition, the composite exhibits low relative permittivity and dissipation factor tanδ in the frequency range of 10⁻²–10⁶ Hz, and its breakdown strength reaches 65.99 kV/mm. These results demonstrate that simulation-guided multiscale hybrid filler design is an effective strategy for improving the thermal conductivity of EP while maintaining acceptable insulating performance. Full article

To address the difficulty of detecting demagnetization severity in permanent magnet synchronous motors (PMSMs), this paper proposes a demagnetization severity detection method based on temperature signal and Convolutional Neural Network (CNN). First, the differences between local demagnetization and eccentricity fault in stator current harmonics are analyzed from an electromagnetic perspective, and fast Fourier transform (FFT) is used for frequency-domain analysis of the stator current to identify local demagnetization faults. On this basis, an electromagnetic–thermal coupling model is established by considering motor losses and heat dissipation boundary conditions to obtain the winding temperatures under different demagnetization severities and operating conditions. Furthermore, the temperature time series, together with speed and load torque, is constructed into a three-dimensional state space, and the proposed Conditionally Modulated Multi-Scale Convolutional Neural Network (CMSCNN) is introduced for feature learning to achieve demagnetization severity detection. Experimental results show that the proposed method achieves an average detection accuracy of 98.06% on the simulation test set and outperforms the baseline CNN model. On measured data collected from the faulty prototype, the average detection accuracy reaches 93.34%, verifying the effectiveness of the proposed method for demagnetization severity detection. Full article

With the increasing penetration of wind and solar renewable energy into modern power systems, grids exhibit ‘dual-high’ (i.e., a high proportion of both renewable energy and power electronic devices) and ‘dual-low’ (i.e., low equivalent rotational inertia and low short-circuit capacity) structural characteristics. This leads to critical challenges, notably insufficient short-circuit capacity, declining voltage and frequency stability, and weakened system damping. To address the stability requirements of new power systems, this study proposes and systematically investigates a variable-speed synchronous condenser based on AC excitation technology. The research encompasses the operational principles, starting mechanisms, and control strategies of the device, with a particular focus on analyzing its stator-flux-oriented vector control method and active–reactive power decoupling regulation mechanism. By independently adjusting the frequency, amplitude, and phase of the AC excitation on the rotor side, the system achieves a millisecond-level dynamic reactive power response, rapid frequency support, and self-starting capability without the need for external starting devices. To validate the effectiveness of the theoretical analysis and engineering practicality, this study presents grid-connected operational tests using a 3600 kVar engineering prototype at a wind farm. The test results demonstrate that the variable-speed synchronous condenser performs excellently in speed regulation, dynamic reactive power response, and primary frequency modulation. It effectively provides short-circuit capacity, enhances system damping, and significantly improves the voltage and frequency stability of power grids with high penetration of renewable energy. This study offers innovative technical pathways and empirical evidence for constructing a stability support system that meets the developmental needs of new power systems. It holds significant theoretical value and engineering guidance for promoting the smooth transition of power grids from synchronous machine-dominated to power electronics-based architectures. Full article

Epoxy-glass-mica composite materials are widely used as electrical insulating materials in high-voltage rotating machinery due to their layered structure and excellent dielectric properties. Taking the F-class epoxy glass with a small amount of rubber powder mica tape commonly used as the main insulation of wind turbine stator coils as the research object, 7-day, 14-day, 21-day, and 28-day low-temperature treatment tests were conducted at −50 °C. The surface morphology and chemical structure changes of the materials were characterized by SEM and FTIR, and the influence laws of low-temperature treatment on the electrical properties of the mica tape insulation materials were systematically studied. The experimental results show that the low-temperature environment will induce microcracks and interface delamination and other structural damages, but no obvious change in the chemical structure of the mica tape was observed. With the extension of the low-temperature treatment time, the electrical properties of the mica tape show a deteriorating trend, and after 28 days of low-temperature treatment, the breakdown field strength of the F-class mica tape decreased by approximately 18.5%, and the volume conductivity overall increased by about two orders of magnitude. This indicates that the microcrack defects induced by low-temperature will lead to an enhanced electrical-thermal coupling effect in the insulation structure, thereby accelerating the degradation process of the insulation material. This reveals the degradation mechanism of wind turbine stator main insulation from “structural damage” to “performance degradation” and then to “insulation aging” under low-temperature conditions, providing a theoretical basis for the design and reliability assessment of insulation systems in wind turbine generators in cold regions. Full article

This study investigates the primary electromagnetic sources of acoustic noise in single-phase induction motors and proposes design-oriented strategies for noise reduction. A 370 W, four-pole, 80-frame single-phase induction motor was designed, analyzed, and experimentally validated. Finite Element Method (FEM) simulations were conducted using Ansys Maxwell 2D to examine the effects of magnetic field distortion, magnetic saturation, and rotor eccentricity on torque ripple and inductance variation. The results demonstrate that these factors significantly increase electromagnetic force harmonics acting on the stator teeth and frame, leading to vibration and acoustic noise generation. In addition, inductance fluctuations caused by interphase magnetic coupling and air-gap harmonics were found to increase current harmonic content and potentially excite structural resonances. The influence of capacitor selection and winding configuration on magnetic saturation, phase displacement, and torque ripple was systematically evaluated. Prototype motors were manufactured and acoustic noise measurements were performed to experimentally validate the simulation results. Unlike previous studies that often investigate these parameters separately, this work presents a coupled analysis that explicitly links capacitor selection, winding configuration, and rotor eccentricity to inductance variation, torque ripple, and acoustic noise generation. The findings provide practical design guidelines for the development of low-noise single-phase induction motors and contribute to reducing electromagnetic vibration and acoustic emissions in electric machine design. Full article

Industrial predictive maintenance programs often rely on SCADA historian signals characterized by low-frequency sampling and asynchronous reporting intervals. These data constraints, specifically non-uniform scan rates and inter-tag time misalignment, limit the applicability of high-resolution or sensor-intensive prognostic models. This study proposes a lightweight, physics-informed health proxy, the temperature-weighted work (TWW) index, designed to monitor motor stator-winding degradation within these industrial limitations. The TWW index accumulates mechanical work derived from torque and speed measurements, weighted by an adaptive exponential temperature-emphasis function that penalizes operation at elevated temperatures. The formulation is inspired by practical thermal-aging heuristics such as Montsinger’s rule in the qualitative sense that higher temperatures are treated as disproportionately more damaging, but it is not intended as a direct implementation of a fixed absolute-temperature life law. Instead, it is designed as a lightweight adaptive index suitable for online SCADA-based implementation. To address SCADA-specific irregularities, the framework incorporates data synchronization and resampling techniques to align heterogeneous tags, alongside power-thresholding to isolate degradation-relevant load periods. The resulting cumulative index is mapped to a normalized health/RUL proxy using failure-referenced thresholds identified from historical events. Validation using field data from industrial three-phase motors demonstrates that the TWW index provides a monotonic degradation profile that is consistent with documented winding-related failures and proactive removals. Case studies confirm that the model enabled proactive maintenance interventions by signaling the terminal phase of insulation life before catastrophic breakdown, offering a hardware-free and scalable solution for real-time asset management. Full article

High-speed operation is a key pathway to higher power density in modern EV traction systems, and multi-parameter optimization is essential for enhancing its high-speed performance. This study investigates a 20,000 r/min interior double-V permanent-magnet flat-wire motor via finite-element simulations to systematically examine the effects of multiple interacting parameters—including flat-wire layer number, stator slot geometry, magnet grade, and rotor magnetic barrier angle—on the electromagnetic performance under high-speed operating conditions. The results indicate that increasing winding layers significantly reduces high-speed torque; an eight-layer design decreases torque by about 50% compared to a four-layer one, while a six-layer arrangement offers a favorable torque-loss trade-off. Wider slots lower the average torque but reduce torque ripple by approximately 27%, whereas deeper slots increase tooth flux density and reduce efficiency. Higher-grade magnets enhance air-gap flux and torque at elevated cost. Rotor magnet angle optimization reveals a trade-off between peak torque and ripple, with a symmetric 100°/100° design achieving balanced performance. These findings clarify structural–control interactions and support the multi-objective design of high-speed flat-wire permanent-magnet motors. Full article

Traditional stator-permanent magnet flux-reversal motors have the problems of large cogging torque, limited improvement of power density, and low fault-tolerant performance. Based on the traditional flux-reversal motor, this paper proposes a design scheme of a flux-reversal motor with a stator-segmented double-winding and double-sequence permanent magnet structure. The motor adopts a stator-segmented modular design, each independent stator segment is connected by permanent magnets, and a bipolar permanent magnet array is arranged on the teeth of the stator segment. Meanwhile, a double-winding system composed of independent power windings and fault-tolerant windings is configured to realize the dual characteristics of high power density and high reliability. A two-dimensional finite element model is established to simulate and analyze the motor, which verifies the feasibility of the motor structure design. The simulation results show that the motor has improved operation stability, better fault-tolerant performance, and theoretically lower maintenance cost, as well as being especially suitable for the petroleum and chemical industries, electric vehicles, aerospace, and other application fields with high requirements for motor reliability and power density. Full article

This study presents a stator-focused electromagnetic optimization of a 350 W, 27-slot, 30-pole outer-rotor brushless direct current (BLDC) motor developed for electric scooter applications. Unlike conventional redesign approaches that modify rotor topology or overall motor dimensions, the proposed methodology preserves the rotor structure and external geometry of a commercially validated reference motor and improves performance primarily through targeted stator geometric refinement, with minor adjustments in the winding configuration. A two-stage optimization strategy combining parametric analysis and genetic algorithm (GA)-based multi-objective optimization is implemented to minimize cogging torque and torque ripple while maximizing efficiency. Finite element analyses (FEA) were conducted to evaluate back electromotive force (back-EMF) characteristics, magnetic flux density distribution, torque behavior, and current density. Experimental validation confirms a 54.86% reduction in cogging torque (from 257 mNm to 116 mNm), a 19.6% decrease in torque ripple, a 6.17% reduction in maximum current density, and a 2–3% improvement in efficiency within the nominal load range (5.2–6.45 Nm), reaching 85.69% efficiency at 350 W output power. The results demonstrate that systematic stator geometry optimization, supported by minor winding modifications, can significantly enhance efficiency, torque smoothness, and thermal margin without increasing motor size, rated power, or manufacturing complexity. This work provides a practical and manufacturable design pathway for high-performance outer rotor BLDC motors in light electric vehicle (LEV) propulsion systems. Full article

The increasing demand for electric power in hybrid electric aircraft platforms prompts the development of multi-megawatt generators featuring high specific power, compactness and intrinsic fault tolerance. Air-core machines constitute a promising solution to overcome the magnetic saturation and mass limitations of conventional iron-core designs. This paper presents a comparative electromagnetic design study of two air-core synchronous generator topologies for aircraft applications, namely a permanent magnet machine with a Halbach array rotor and an electrically excited synchronous machine featuring a high-temperature superconducting field winding. Both the generators are designed for identical output and adopt a double three-phase stator winding to enhance safety and redundancy. The Halbach array machine is used as the reference configuration representative of a technologically mature solution, whereas the superconducting generator targets high magnetic loadings by means of the superconducting excitation, to minimize the active volume. The solutions proposed in this paper are developed in the frame of a national (Italian) research project dedicated to the study of stages of multi-megawatt fault-tolerant aircraft generators. Full article

Hydropower remains one of the primary sources of power generation. It can be operated as either a base-load or peak-load plant due to its rapid, easy start-up and stop-down capability. However, power plants, old or new, need to be operated and maintained optimally to meet energy demand and maximise economic returns. While the older plants without digital controls such as the Supervisory Control and Data Acquisition (SCADA) system are unable to leverage the evolving technology including big data and Artificial Intelligence (AI), the newer plants or plants that already have some form of data acquisition system have the advantage of leveraging the newer platforms for efficient operation, monitoring and fault diagnosis. Thus, an Artificial Neural Network (ANN), a machine learning (ML) algorithm, was chosen for this case study to predict the generator’s operational stator temperature by selecting six parameters that could potentially affect it. Real data from the 336 MW Chhukha Hydropower Plant (CHP) in Bhutan were used to train the ANN. The prediction of temperature using an ANN in MATLAB^® yielded an R² (correlation coefficient) of 96.8%, which is impressive but can be further improved through various optimisation and tuning methods with increased data volume and complexity. The performance of ANN prediction was validated against other regression models, and the ANN was found to outperform them. This demonstrated its capability to predict and detect generator temperature faults before failures, thereby enhancing hydropower operation and maintenance (O&M) efficiency. The model’s interpretation was also done through Shapley Additive ExPlanations (SHAP). Full article

In order to simplify the stator winding structure of traditional variable reluctance (VR) resolvers and enhance their performance under high-speed operating conditions, this paper proposes a design for a variable reluctance self-coupling resolver based on ultrahigh-frequency (UHF) square wave excitation. The proposed solution optimizes the traditional winding structure by eliminating the separate excitation winding and integrating both excitation and detection functions into the two-phase sine and cosine windings. By optimizing the arrangement of the sine and cosine windings, a single-layer equal-turn winding design is successfully implemented, significantly simplifying the winding layout and reducing copper usage. In terms of excitation signal, this paper innovatively replaces the traditional sinusoidal excitation with UHF square wave excitation. Compared to sinusoidal excitation, square wave excitation not only generates higher electromotive force (EMF) peaks but also simplifies engineering implementation, reducing the complexity of system hardware. To validate the feasibility and advantages of the proposed structure, a complete experimental testing platform was built, and comparative experiments were conducted under various rotational speeds. The experimental results show that the proposed self-coupling resolver can achieve high-precision rotor position detection across the entire speed range, significantly improving the detection accuracy and dynamic response of traditional methods under high-speed conditions. Ultimately, the design demonstrates strong engineering application potential and provides a new solution for high-precision, high-dynamic response rotor position detection. Full article

This paper investigates the feasibility of an interior permanent magnet (IPM) rotor for 1 MW-class high-speed permanent magnet synchronous machines (PMSMs) in a hybrid propulsion system of electrified aviation. A double-layer IPM machine and a surface-mounted PM (SPM) benchmark machine with Halbach-array PMs, which are typically employed in aviation applications; are designed using the same design specifications, the same stator, double-three-phase winding layout, physical air-gap length, outer and inner diameters of rotor; and the same materials. The rotor robustness of the IPM machine using high-strength iron material has been verified through mechanical strength analysis with an outstanding safety factor margin. The electromagnetic performances of IPM and SPM benchmark machines are compared. It is found that the IPM design can achieve similar high torque/power density and high efficiency to the SPM benchmark machine, using 48% less rare-earth PM materials and a simpler rotor structure without a carbon fiber sleeve for easy manufacturing. The investigation confirms the feasibility of IPM topology for MW-class high-speed aviation propulsion machines for lower cost and more sustainable purposes. Full article

In this paper, a novel approach for fault detection in the stator windings of induction motors is presented. The procedure is based on spectral analysis of the current signal. However, due to the specific target application, short duration signals (0.2 s) are utilized, which results in poor spectral resolution. To address this issue, a statistical methodology is developed to minimize uncertainty in decision-making. To construct a health indicator (HI), a statistical analysis is performed to identify spectral components that are both informative and robust. For the selected fault-related frequencies, the HI was created. Using confidence intervals and statistical testing, a fault detection scheme was proposed. The method was validated on an experimental dataset, including both healthy and faulty conditions. The method has been tested on current signals with five levels of fault severity and seven load conditions. Experimental studies on a dedicated test rig demonstrated the high efficiency of the proposed approach for such specific constraints. Full article