Search Results (102)

Electric motors play a decisive role in electric vehicles by converting electrical energy into mechanical motion across various drivetrain components. However, failures in these motors can interrupt the motor function, with approximately 40% of these failures stemming from bearing issues. Key contributors to bearing degradation include shaft voltage, bearing current, and electric discharge material spalling current, especially in motors powered by inverters or variable frequency drives. This review explores the tribological and vibrational aspects of bearing currents, analyzing their mechanisms and influence on electric motor performance. It addresses the challenges faced by electric vehicles, such as high-speed operation, elevated temperatures, electrical conductivity, and energy efficiency. This study investigates the origins of bearing currents, damage linked to shaft voltage and electric discharge material spalling current, and the effects of lubricant properties on bearing functionality. Moreover, it covers various methods for measuring shaft voltage and bearing current, as well as strategies to alleviate the adverse impacts of bearing currents. This comprehensive analysis aims to shed light on the detrimental effects of bearing currents on the performance and lifespan of electric motors in electric vehicles, emphasizing the importance of tribological considerations for reliable operation and durability. The aim of this study is to address the engineering problem of bearing failure in inverter-fed EV motors by integrating electrical, tribological, and lubrication perspectives. The novelty lies in proposing a conceptual link between lubricant breakdown and damage morphology to guide mitigation strategies. The study tasks include literature review, analysis of bearing current mechanisms and diagnostics, and identification of technological trends. The findings provide insights into lubricant properties and diagnostic approaches that can support industrial solutions. Full article

Split-shaft wind turbines decouple the turbine’s shaft from the generator’s shaft, enabling several modifications in the drivetrain. One of the significant achievements of a split-shaft drivetrain is the reduction in size of the excitation circuit. The grid-side converter is eliminated, and the rotor-side converter can safely reduce its size to a fraction of a full-size excitation. Therefore, this low-power-rated converter operates at low voltage and handles regular operations well. However, fault conditions may expose weaknesses in the converter and push it to its limits. This paper investigates the effects of the reduced-size rotor-side converter on the voltage ride-through capabilities required from all wind turbines. Four different protection circuits, including the active crowbar, active crowbar along a resistor–inductor circuit (C-RL), series dynamic resistor (SDR), and new-bridge fault current limiter (NBFCL), are employed, and their effects are investigated and compared. Wind turbine controllers are also utilized to reduce the impact of faults on the power electronic converters. One effective method is to store excess energy in the generator’s rotor. The proposed low-voltage ride-through strategies are simulated in MATLAB Simulink (2022b) to validate the results and demonstrate their effectiveness and functionality. Full article

Large turbine generators rely on shaft earthing brushes to safely divert harmful shaft currents to ground, protecting bearings from electrical damage. This paper presents a novel deep learning-based diagnostic framework to detect and classify faults in shaft earthing brushes of large turbine generators. A key innovation lies in the use of FFT-derived spectrograms from both voltage and current waveforms as dual-channel inputs to the CNN, enabling automatic feature extraction of time–frequency patterns associated with different SEB fault types. The proposed framework combines advanced signal processing and convolutional neural networks (CNNs) to automatically recognize fault-related patterns in shaft grounding current and voltage signals. In the approach, raw time-domain signals are converted into informative time–frequency representations, which serve as input to a CNN model trained to distinguish normal and faulty conditions. The framework was evaluated using data from a fleet of large-scale generators under various brush fault scenarios (e.g., increased brush contact resistance, loss of brush contact, worn out brushes, and brush contamination). Experimental results demonstrate high fault detection accuracy (exceeding 98%) and the reliable identification of different fault types, outperforming conventional threshold-based monitoring techniques. The proposed deep learning framework offers a novel intelligent monitoring solution for predictive maintenance of turbine generators. The contributions include the following: (1) the development of a specialized deep learning model for shaft earthing brush fault diagnosis, (2) a systematic methodology for feature extraction from shaft current signals, and (3) the validation of the framework on real-world fault data. This work enables the early detection of brush degradation, thereby reducing unplanned downtime and maintenance costs in power generation facilities. Full article

This study proposes an improved super-twisting sliding mode (STSM) control method for a brushless doubly fed induction generator (BDFIG) used in standalone ship shaft power generation systems. Focusing on the problem of the low tracking accuracy of the power winding (PW) voltages caused by the parameter perturbation of BDFIG systems, a mismatched uncertain model of the BDFIG is constructed. Additionally, an improved STSM control method is proposed to address the power load variation and compensate for the mismatched uncertainty through virtual control technology. Based on the direct vector control of the control winding (CW), the proposed method ensured that the voltage amplitude error of the power winding could converge to the equilibrium point rather than the neighborhood. Finally, in the experimental investigation of the BDFIG-based ship shaft independent power system, the dynamic performance in the startup and power load changing conditions were analyzed. The experimental results show that the proposed improved STSM controller has a faster dynamic response and higher steady-state accuracy than the proportional integral control and the linear sliding mode control, with strong robustness to the mismatched uncertainties caused by parameter perturbations. Full article

During the manufacturing process of oil-immersed current transformers, metallic particles may become embedded in the insulation wrapping, and the resulting electric field distortion is one of the primary causes of failure. Historically, the shape of metallic particles has often been simplified to a standard sphere, whereas in practice, these particles are predominantly irregular. In this study, ellipsoidal and flaky particles were selected to represent smooth and angular surfaces, respectively. Using COMSOL Multiphysics^® (version 6.2) software, a three-dimensional simulation model of an oil-immersed inverted current transformer was developed, and the influence of defect position and size on electric field characteristics was analyzed. The results indicate that both types of defects cause electric field distortion, with longer particles exerting a greater influence on the electric field distribution. Under the voltage of a 220 kV system, elliptical particles (9 mm half shaft) lead to the maximum electric field intensity of main insulation of up to 45.1 × 10⁶ V/m, while the maximum field strength of flaky particles (length 30 mm) is 28.9 × 10⁶ V/m. Additionally, the closer the particles are to the inner side of the main insulation, the more significant their influence on the electric field distribution becomes. The findings provide a foundation for fault analysis and propagation studies related to the main insulation of current transformers. Full article

Large steam turbine generators are increasingly vulnerable to damage from shaft voltages and bearing currents due to the widespread adoption of modern power electronic excitation systems and more flexible operating regimes. Earthing brushes provide a critical path for discharging these shaft currents and voltages, but their effectiveness depends on the timely detection of brush degradation or faults. Conventional monitoring of shaft voltage and current is often rudimentary, typically limited to peak readings, making it challenging to identify specific fault conditions before mechanical damage occurs. This study addresses this gap by systematically analyzing shaft voltage and current signals under various controlled earthing brush fault conditions (floating brushes, worn brushes, and oil/dust contamination) in several large turbine generators. Experimental site tests identified distinct electrical signatures associated with each fault type, demonstrating that online shaft voltage and current measurements can reliably detect and classify earthing brush faults. These include unique RMS, DC, and harmonic patterns in both voltage and current signals, enabling accurate fault classification. These findings highlight the potential for more proactive maintenance and condition-based monitoring, which can reduce unplanned outages and improve the reliability and safety of power generation systems. Full article

Turbine generators are essential for power generation, but the presence of shaft voltages and currents poses significant challenges to their reliability, efficiency, and operational lifespan. These phenomena, arising from electromagnetic induction, poor shaft grounding, rotor excitation systems, and varying operational conditions, can lead to severe damage to bearings and rotors, resulting in costly downtime and maintenance. This study reviews the mechanisms behind shaft voltage and current generation, their impact on turbine generators, and the effectiveness of various mitigation strategies, including shaft earthing brushes, bearing insulation, and advanced health monitoring systems. Furthermore, it explores emerging techniques for measuring and diagnosing shaft voltage and current, as well as advancements in predictive maintenance and condition monitoring. This study further explores the integration of artificial intelligence and machine learning in predictive maintenance, leveraging real-time condition monitoring and fault diagnostics. By analyzing existing and emerging mitigation strategies, this study provides a comprehensive evaluation of solutions aimed at minimizing these electrical effects. The findings underscore the importance of proactive management strategies to enhance generator reliability, optimize maintenance practices, and improve overall power system stability. This research serves as a foundation for future advancements in shaft voltage mitigation, contributing to the long-term sustainability of power generation infrastructure. Full article

To address the complexity of power allocation in parallel operation systems combining single-shaft and split-shaft gas turbine generators, this paper proposes a coordinated power allocation strategy based on enhanced voltage droop control for marine power systems integrated with hybrid energy storage comprising flywheel and battery subsystems. Furthermore, to mitigate significant power sharing deviations during transient/pulsed load conditions in shipboard application, a feedforward compensation strategy is developed. Simulation results demonstrate that the improved droop control maintains power sharing deviations below 3.5% across steady-state operations and gradual load variations, ensuring system stability and balanced power distribution. However, abrupt load changes induce over 20% deviations, compromising parallel operation reliability. The proposed feedforward compensation strategy effectively restricts deviations within 4% under specified transient and pulsed load scenarios, satisfying both parallel operation criteria and grid power quality requirements. Validation is performed on a parallel system comprising two distinct gas turbine configurations. Full article

In electric vehicles (EVs), bearings in traction motors are increasingly prone to electrical damage under operational currents and voltages, leading to accelerated wear and reduced lifespan. This study examines the extent of bearing damage under low-speed, electrically charged conditions to understand wear behavior at boundary lubrication better. Bearings were driven at low speed by a motor, with inner and outer rings connected to a pulsed power supply’s positive and negative terminals, simulating real-world shaft voltage conditions. The applied electrical parameters included voltages from 5 V to 240 V and frequencies of 10 kHz, leading to voltages at the bearing peaking between 0.1 and 12 V measured by an oscilloscope and multimeter. The tested bearings were disassembled, and scanning electron microscopy (SEM) was used to assess the damage associated with varying electrical stresses. The results revealed distinct wear patterns and degradation effects when the shaft current and peak voltage reached 2.5 A and 12 V, emphasizing the critical need for protective strategies. Future work will focus on evaluating the impact of higher rotational speeds and controlled power supply conditions to analyze the effects of increased power supply settings and compare outcomes to low-speed scenarios. Full article

This study explores the integration of wind power generation into urban infrastructure via a rooftop vertical-axis wind turbine. A rigorous experimental framework was established by installing a small-scale turbine on an urban building for performance assessment under controlled conditions. Simulated environmental conditions were created using a pedestal fan and blower to evaluate mechanical interactions between the components and electrical output efficiency of the turbine. Extensive numerical modeling was conducted to analyze turbine performance, by computational fluid dynamics using ANSYS FLUENT. The results reveal that the turbine operates efficiently even at low to moderate wind speeds (0.5–6 m/s), demonstrating its feasibility for urban deployment. Performance tests indicated that, as the shaft rotational speed increased from 55 rpm to 115 rpm, the output voltage, current and power varied nonlinearly in the ranges of 3–11.9 V, 20–130 mA and 0.05–2.7 W, respectively. Vibration measurement at specified turbine locations revealed nonlinear variation in displacement, velocity, acceleration and frequency without fixed patterns. Good agreement was observed between the experimental and numerical results. The numerical model yielded interesting profiles related to velocity and turbulence distributions, apart from torque, mechanical power and electrical voltage. Important conclusions were drawn from the entire work. Full article

The underwater electric field signal can be excited by underwater vehicles, such as the shaft-rate electric field and the corrosion electric field. The electric field signature of each vehicle exhibits significant differences in time and frequency domain, which can be exploited to determine target positions. In this paper, a novel passive localization method for underwater targets is presented, leveraging a uniform linear electrode array (ULEA). The ULEA manifold along the axial direction is derived from the electric field propagation in an infinite lossy medium, which provides the nonlinear mapping relationship between the target position and the voltage data acquired by the ULEA. In order to locate the targets, the multiple signal classification (MUSIC) algorithm is applied. Then, capitalizing on the rotational invariance of matrix operations and exploiting the symmetry inherent in the ULEA, we streamline the six-dimensional spatial spectral scanning onto a two-dimensional plane, providing azimuth and distance information for the targets. This method significantly reduces computational overhead. To validate the efficacy of our proposed method, we devise a localization system and conduct a simulation environment to estimate targets. Results show that our method achieves satisfactory direction and reliable distance estimations, even in scenarios with low signal-to-noise ratios. Full article

High-speed rotating flywheel bearings, designed for space applications, generate a high-resistance hydrodynamic lubrication film, which isolates the rotor, transforming it into a conductor. This phenomenon introduces a novel failure mode—flywheel bearing electrical damage caused by space charging effects. This paper first reviews the sources of common shaft voltages in flywheels and the mechanisms of electrical damage and improves the principle of deep charge causing shaft voltages in flywheel bearings, proposing that surface charge is another source of shaft voltages. The quantified analysis model of flywheel bearing electrical damage in relation to rotational speed and high-energy electron flux is derived, indicating that the damage caused by space charge–discharge to the bearing is of small magnitude and only becomes apparent after long-term accumulation, thus being easily overlooked. Based on the causal chain of electrical damage, a correlation analysis model consistent with physical principles is constructed, and the correlation between on-orbit anomalies of the flywheel and high-energy electron flux is confirmed through the use of big data. Preliminary experiments are conducted to validate all of the research results. Finally, suggestions are given for the reliable design, application, and testing of flywheels. Full article

This study investigates a novel short electric arc vertical turning method for machining titanium alloy shafts. The method was successfully applied to titanium alloy rods, and its effects on material removal rate (MRR), surface roughness, roundness, and cross-sectional morphology were analyzed at varying processing voltages. The results indicate that the MRR and surface quality improve with increased voltage, reaching a maximum of 231 mm³/min and 26 μm surface roughness at 32 V. However, surface roughness deteriorates with higher duty cycles and voltages due to unstable discharges. Roundness deviations are minimized with higher rotational speeds, which enhance uniform material removal and arc stability. Metallographic analysis revealed an increased heat-affected zone and recast layer thickness at higher voltages. This method demonstrates high machining efficiency and improved surface quality, making it suitable for titanium alloy shaft manufacturing in advanced engineering applications. Full article

The present paper deals with a review on bearing currents in electrical machines, with major emphasis on mechanisms, impacts, and mitigation strategies. High-frequency common-mode voltages from the inverter-driven system have been found to be the main reason for bearing current leading to motor bearing degradation and eventual failure. This paper deals with bearing currents—electrical discharge machining (EDM) currents, circulating bearing currents, and rotor-to-ground bearing currents—and the various methods of their generation and effects that are harmful to the bearings and lubricants of a motor. Mitigation techniques, among which the following have been taken into account, are studied in this context: the optimization of PWM modulation, and the use of shaft grounding brushes, insulated bearings, and passive or active filters. Finally, advantages, limitations, and implementation challenges are discussed. A review comparing three-phase and dual three-phase inverters showed that, due to the increased degree of freedom in modulation strategies, it is possible to eliminate common-mode voltages through active modulation techniques. Such added flexibility will reduce the risk of bearing currents effectively. It also highlights future research directions in bearing current suppression, including the development of multi-phase motor systems, real-time monitoring technologies with artificial intelligence, and the use of new insulation materials for the enhancement of bearing reliability. The results obtained should guide future research and engineering practices in suppressing bearing currents to improve motor durability with high performance. Full article

Plasma electrolytic oxidation (PEO) has emerged as a promising surface coating technique producing high-quality ceramic coating for light metals like Al, Mg, Ti, and their alloys. AA7075 is one of the commonly used Al alloys for aircraft structures, gears and shafts, and automotives as it provides high yield and tensile strength. However, Al and its alloys have drawbacks that limit their further application. Thus, surface treatments are proposed to improve the metal and its alloy’s properties. In this study, the PEO of AA7075 was carried out with an AC power source under a pulsed unipolar potentiostatic mode at varying voltages of 425 and 450 V in 1000 Hz and at 80% duty cycles of 30 m. The effect of varying voltages on the morphology, coating thickness, and corrosion resistance of the PEO-coated samples was investigated. Surface morphology, elemental distribution, and phase composition were characterized using SEM, EDX, and XRD. A porous structure with a pancake-like shape, a crater, and nodular structures were observed with coating thickness ranges from 12.1 to 55.3 ± 4.67 µm. Al, α-alumina, and γ-alumina were detected in all surface coatings. The PEO-coated sample at 450 V exhibited higher corrosion resistance evaluated via potentiodynamic polarization and EIS. Full article