Search Results (2,586)

This paper addresses the issue of rotor swings in a high-power synchronous generator during stable operation with a stiff power grid. The analysis of electromechanical swings was conducted using a circuit model incorporating fractional-order derivatives. Assuming that variations in the load angle under small disturbances from a stable equilibrium are minor, a linearized differential equation describing the electrodynamic state of the synchronous machine was derived. Based on this linearized equation of motion and the identified parameters of the equivalent circuit, calculations were performed for a 200 MW turbogenerator. The results indicate that the electromechanical swings are characterized by a constant pulsation and a low damping factor. Calculations were also carried out using a lumped-parameter equivalent circuit model. Based on the obtained results, it can be stated that the fractional-order model provides a more accurate fit of the frequency characteristics compared with the classical model with the same number of rotor equivalent circuits. The relative approximation errors for the fractional-order model are, for the d-axis (one rotor equivalent circuit), relative magnitude error δ_m = 1.53% and relative phase error δ_φ = 6.32%, and for the q-axis (two rotor equivalent circuits), δ_m = 3.2% and δ_φ = 8.3%. To achieve comparable approximation accuracy for the classical model, the rotor electrical circuit must be replaced with two equivalent circuits in the d-axis and four equivalent circuits in the q-axis, yielding relative errors of δ_m = 2.85% and δ_φ = 6.51% for the d-axis, and δ_m = 1.86% and δ_φ = 5.49% for the q-axis. Full article

In-wheel motor (IWM)-driven electric vehicles (EVs) are susceptible to road excitation, which can induce eccentricity between the stator and rotor of the IWM. This eccentricity leads to unbalanced electromagnetic forces (UEFs) and electromechanical coupling (EMC) effects, severely degrading vehicle dynamic performance. To address this issue, this study first established an EMC system model encompassing UEF, IWM drive, and vehicle dynamics. Based on this model, four typical operating conditions—constant speed, acceleration, deceleration, and steering—were designed to thoroughly analyze the influence of EMC effects on vehicle dynamic response characteristics. The analysis results were validated through real-vehicle experiments. The results indicate that the EMC effects caused by motor eccentricity primarily affect the vehicle’s vertical dynamics performance (especially during acceleration and deceleration), leading to increased vertical body acceleration and reduced ride comfort, while having a relatively minor impact on longitudinal and lateral dynamics performance. Additionally, these effects significantly increase the relative eccentricity of the motor under various operating conditions, further degrading motor performance. To mitigate these negative effects, this paper designs an active suspension controller based on distributed model predictive control (DMPC). Simulation and experimental validation demonstrate that the proposed controller effectively improves ride comfort and body posture stability while significantly suppressing the growth of the motor’s relative eccentricity, thereby enhancing motor operational performance. Full article

In this paper, a nonlinear power transfer matrix model is presented for power control of Permanent Magnet Synchronous Generator (PMSG) wind turbines, incorporating the DC link dynamics to account for transient stability, thereby clarifying the technical aspect and purpose. The rising penetration of wind turbines (WTs) into the power grid necessitates that they remain connected during and after faults to ensure system reliability. During voltage dips, the stator and grid-side converter (GSC) of a permanent magnet synchronous generator (PMSG) system are directly impacted by the sudden voltage changes. These disturbances can induce large transient voltages and currents in the stator, which in turn may lead to uncontrolled current flow in the rotor circuit and stress the converter components. Moreover, Low Voltage Ride-Through (LVRT) is a critical requirement for grid connection to Wind Energy Conversion Systems (WECS). It ensures that WTs remain connected and operational during short periods of grid voltage dips (faults), instead of disconnecting immediately. This capability is essential for maintaining grid stability. However, in this paper, the authors propose an LVRT scheme for a grid-connected PMSG-based WECS. A sequence of attempts was performed to validate the effectiveness of the proposed control scheme under fault conditions and to improve its overall performance. Full article

This work presents an analytical 2D model for estimating eddy current losses in the permanent magnets (PMs) of a coaxial magnetic gear (CMG), with a focus on loss minimization through magnet segmentation. The model is applied under various operating conditions, including different rotational speeds, load levels, and segmentation configurations, to derive empirical expressions for eddy current losses in both the inner and outer rotors. A 1D lumped-parameter thermal model is then used to predict the steady-state temperature of the PMs, incorporating empirical correlations for the thermal convection coefficient. Both models are validated against finite element analysis (FEA) simulations. The analytical eddy current loss model exhibits excellent agreement, with a maximum error of 2%, while the thermal model shows good consistency, with a maximum temperature deviation of 5%. The results confirm that eddy current losses increase with rotational speed but can be significantly reduced through magnet segmentation. However, achieving an acceptable thermal performance at high speeds may require a large number of segments, particularly in the outer rotor, which could influence the manufacturing cost and complexity. The proposed models offer a fast and accurate tool for the design and thermal analysis of CMGs, enabling early-stage optimization with minimal computational effort. Full article

Magnetically levitated artificial hearts impose stringent requirements on the blood-pump motor: zero friction, minimal heat generation and full biocompatibility. Traditional mechanical-bearing motors and permanent-magnet bearingless motors fail to satisfy all of these demands simultaneously. A bearingless switched reluctance motor (BSRM), whose rotor contains no permanent magnets, offers a simple structure, high thermal tolerance, and inherent fault-tolerance, making it an ideal drive for implantable circulatory support. This paper proposes an 18/15/6-pole dual-stator BSRM (DSBSRM) that spatially separates the torque and levitation flux paths, enabling independent, high-precision control of both functions. To suppress torque ripple induced by pulsatile blood flow, a variable-overlap TSF-PWM-DITC strategy is developed that optimizes commutation angles online. In addition, a grey-wolf-optimized fast non-singular terminal sliding-mode controller (NRLTSMC) is introduced to shorten rotor displacement–error convergence time and to enhance suspension robustness against hydraulic disturbances. Co-simulation results under typical artificial heart operating conditions show noticeable reductions in torque ripple and speed fluctuation, as well as smaller rotor radial positioning error, validating the proposed motor and control scheme as a high-performance, biocompatible, and reliable drive solution for next-generation magnetically levitated artificial hearts. Full article

Background /Objectives: The rising prevalence of metabolic disorders, such as obesity, is linked to increased consumption of high-calorie foods and sedentary lifestyles. While conventional treatments rely on lifestyle modifications and pharmaceuticals, these often have limitations and adverse effects. As an alternative, natural compounds like β-caryophyllene (BCP), found in spices such as black pepper and cloves, have gained interest due to their anti-inflammatory and metabolic properties. This study investigated the effects of BCP on the gut–brain axis in obese C57BL/6J mice. Methods: Quantitative real-time PCR (RT-qPCR) was performed using a Rotor-GeneQ thermocycler (Qiagen). Relative gene expression levels were normalized to the reference gene’s transcript levels (2^−∆∆Ct method). Results: BCP was found to modulate key receptors, including FFAR3, LEPR, and GHSR, which are involved in appetite regulation and insulin sensitivity. Its action on the CNR2 (CB2 receptor) suggests additional benefits in energy balance and anorexigenic activity. Conclusions: These findings support BCP’s potential as a complementary therapy for obesity, though further studies are needed to confirm its efficacy in humans. Its safety profile and multifactorial effects make it a promising alternative to conventional treatments. Full article

Hybrid Aerial Underwater Vehicle (HAUV) is a new type of unmanned system that can operate both in air and water, and complete underwater and air operations tasks by carrying corresponding sensors. Owing to this dual-medium operational capability, HAUVs hold significant promise for coordinated air–sea surveillance and monitoring efforts. Optical methods enable high-resolution sampling across both spatial and temporal scales, offering enhanced contextual information for the interpretation of discrete observational data. In order to evaluate the feasibility of ocean optical profiling systems based on HAUVs, this paper reviews the design features of current HAUV models and summarizes advanced techniques that support their cross-medium mobility. Subsequently, we summarized the types of commercial optical instruments commonly used for underwater observation and compared the field deployment methods. By analyzing the underwater motion performance of HAUVs and the requirements for optical observation platforms, we believe that multi-rotor HAUVs can provide new observation methods for future underwater optical acquisition due to their smooth entry and exit characteristics and the ability to maintain a controlled orientation during underwater operation. Finally, the paper explores prospective applications and outlines key obstacles to be overcome in the advancement of amphibious platforms for ocean optical profiling. Full article

Induction motors (IM) play essential tasks in distinct production sectors because of their low cost and robustness. Considering that most of the energy demand in industry is allocated for powering up IM, recent research has focused on detecting and predicting faults to avoid severe disturbances. Broken rotor bars (BRB) in IM cause a significant deficit of energy, above all in those applications where constant changes in speed are required, increasing the probability of a catastrophic failure. Variable speed drives (VSD) introduce harmonic components to the power supply current controlling the IM rotating speed, which make it difficult to identify BRB. Therefore, in this work, an innovative methodology is proposed for detecting BRB in VSD-fed IM with a wide rotating-speed bandwidth during their start-up transient. The introduced procedure performs a statistical analysis for computing the mean, median, mode, variance, skewness, and kurtosis, to identify slight changes on the acquired current signal. These values are fed into an artificial neural network (ANN), which carries out the IM operational condition classification as healthy (HLT) or with BRB. Experimentally obtained results corroborate the effectiveness of the proposed approach to detecting BRB even for dynamically varying rotating speed, reaching a high accuracy of 99%, similar to recently reported techniques. Full article

Ripples in the electromagnetic torque of electric vehicle (EV) motors due to poor stator voltage and control cause jerky movements, equipment failure, discomfort for passengers and drivers, and damage to the associated civil works. This paper presents the implementation of Finite Control Set Model Predictive Control (FCSMPC) for a high-level modified W-type inverter (MWI) driving a three-phase induction motor (IM), along with validation of its performance. The proposed control strategy aims to minimize motor torque ripples and has been tested under various driving torque patterns. The results demonstrate a significant reduction in torque ripples—down to less than 1%—and acceptable levels of total harmonic distortion (THD), as verified through quality analysis of the stator currents. Moreover, a comparative assessment of voltage profiles for the electromagnetic torque and rotor speed curves has been presented for nine cases of simultaneous variations in multiple motor parameters; the results indicate that the MWI-fed motor has the best performance and the lowest sensitivity to the variations. Full article

To enhance wind farm frequency regulation in renewable-dominant power systems, this paper proposes a bi-level hybrid framework integrating deep learning and model predictive control (MPC) by retaining the critical wake propagation delay while neglecting higher-order turbulence effects. The upper layer employs a synthetic inertial intelligent control strategy based on contractive autoencoder (CAE) and deep neural network (DNN). Particle swarm optimization (PSO) obtains optimal synthetic inertial parameters for dataset construction, CAE extracts features from multi-dimensional inputs, and DNN outputs optimal coefficients to determine the total power deficit the wind farm needs to supply. The lower layer uses a nonlinear model predictive control (NMPC) strategy with the discretized rotor motion equation as the prediction model and optimization under constraints to allocate the total power deficit to each turbine. MATLAB/Simulink case studies show that, compared with fixed-coefficient synthetic inertial control, the proposed framework raises the frequency nadir by 0.01–0.02 Hz, shortens the settling time by over 200 s under 2–4% load disturbances, and maintains rotor speed within the safe range. This work significantly enhances the wind farm’s frequency regulation performance, contributing to power system and energy sustainability. Full article

This study focuses on improving the efficiency of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) compressors. Seven rotor topologies (B, dB, V, dV, D, U, and UV) were first compared, among which the U-type rotor demonstrated the highest efficiency and the lowest total loss. Subsequently, the influence of the turn number and rotor outer diameter (ROD) on the shift of the high-efficiency region was analyzed, and six key design variables were identified through Pearson correlation-based sensitivity analysis. Using these variables, a multi-objective optimization was performed in Ansys OptiSLang, which improved the integrated part load value (IPLV)-weighted efficiency from 91.05% to 92.29% and shifted the high-efficiency region closer to the main operating point. Experimental validation of the reference model confirmed the reliability of the FEM analysis, and the proposed optimal design is expected to enhance low-speed efficiency and reduce battery energy consumption in EV compressor applications. Full article

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. Full article

Auxiliary teeth are usually used in fractional-slot concentrated winding (FSCW) machines for fault tolerance. However, the influence of auxiliary teeth on torque and electromagnetic vibration performance differs with different slot–pole configurations. Thus, this paper investigates electromagnetic vibration and mitigation methods in FSCW permanent magnet (PM) machines with auxiliary teeth. The relationship between yoke forces and tooth parameters of two dual three-phase (DTP) FSCW-PM machines with 12-slot/14-pole configuration and 12-slot/10-pole configuration is studied and compared. Results reveal that (1) the 2p-order airgap electromagnetic force reduces second-order yoke force in the 12-slot/14-pole machine but increases it in the 12-slot/10-pole machine. (2) Through optimized tooth width, slot harmonics can be mitigated, but the fundamental winding magnetic field in the 12-slot/10-pole machine is also weakened, whereas the 12-slot/14-pole machine achieves fundamental field preservation or enhancement. Based on these findings, auxiliary tooth optimization and rotor pole profile shaping are proposed for vibration reduction in 12-slot/14-pole machine. Electromagnetic–mechanical coupled simulations conducted in ANSYS Maxwell/Workbench 2023 demonstrate that the optimized design reduces the cogging torque peak from 11.4 mN·m to 2.9 mN·m (74.6% reduction), suppresses housing surface vibration acceleration by 21%, and maintains the average output torque without reduction. Full article

This study proposes an optimal design approach incorporating rotor skew to reduce torque ripple in a 5 kW in-wheel axial flux permanent magnet (AFPM) motor. Nine design variables, including the skew angle, were selected for optimization. The variation ranges of these variables were defined, and sample points were generated using the optimal Latin hypercube design (OLHD). Response data corresponding to the sample points were obtained through three-dimensional finite element method (3D FEM) analysis. Metamodels were then constructed using five different methods and evaluated based on the root mean square error (RMSE). The optimization results showed that the average torque of the optimized model increased by 2.3% compared with the initial design, reaching 48.85 Nm. Torque ripple was reduced by 42.01% to 2.83 Nm, while peak-to-peak cogging torque decreased by 42.76% to 2.61 Nm. In addition, efficiency improved by 0.07% to 95.53%, and the total harmonic distortion (THD) of the back-EMF waveform was reduced by 50.72% to 2.4%. These findings demonstrate that the proposed method provides an effective and systematic design strategy for enhancing the performance of AFPM motors. Full article

In this study, a sensorless speed control method is proposed to enhance the speed control performance under load variations by utilizing a discrete-time flux observer in a V/f control environment. Due to their simple structure, low cost, and high reliability, induction motors are widely used in various fields, such as fans, pumps, and home appliances. Among the control methods for induction motors, V/f control operates as an open-loop system, without using speed sensors. It is mainly applied in industrial environments where fast dynamic performance is not required, due to its simple implementation and low cost. However, in cases of load variations or low-speed operation, it suffers from performance degradation and control limitations due to flux variations. To overcome these issues, this paper proposes a method that uses a discrete-time flux observer to estimate the stator flux. We calculate the rotor speed based on the estimated flux, and then improve V/f control performance by adding a compensation signal to the reference frequency, which signal is generated through a PI controller based on the difference between the estimated rotor speed and the reference speed. The proposed method is validated through MATLAB/Simulink-based simulations and experiments using a 5.5 kW induction motor M−G set, confirming that compared to conventional V/f control, the speed maintenance capability and overall robustness against load variations are enhanced. This study presents a practical solution to effectively improve the performance of existing V/f control systems without adding external sensors. Full article