Search Results (155)

Tidal flats are shrinking and eroding due to sea-level rise and human activities. Ecological submerged breakwaters (ESBs) offer a novel solution combining coastal protection and ecological restoration, but their effects on sediment dynamics lack field evidence. This study presents synchronous in situ measurements from an inner tidal flat (WN01) and an outer shallow area (WN02) of a newly built riprap slope-type ESB on the northern coast of the Sheyang River Estuary, Jiangsu, China. Using Acoustic Doppler Velocimeters (ADVs) and wave-tide gauges, we examined hydrodynamics, suspended sediment concentration (SSC), bed shear stress, erosion–accretion, and sediment transport under normal-weather and strong wave events. Within the constraints of a 14-day observation at two stations, our results indicate that: (1) The ESB reduced wave height and weakened currents, shifting dominant bed shear stress from wave-dominated outside to tide-dominated inside. Under normal weather, both sides were accretive. (2) Strong wave events caused sharp increases in bed shear stress, net erosion on both sides, and a 2–3-fold SSC rise, breaking the normal balance. (3) Suspended sediment transport direction remained northwest inside during strong wave events but shifted to northeast/southeast outside, demonstrating effective isolation of wave-driven anomalies. Bedload was trapped inside, resulting in no net sediment loss, in contrast to the unprotected southern tidal flat. (4) We recommend moderately lowering the ESB crest elevation to prevent excessive accretion and implementing “grey-green” restoration (salt marshes or oyster reefs) to enhance coastal resilience against sea-level rise. Full article

To address the voltage over-limit issue in rural distribution networks caused by high-penetration distributed photovoltaic (DPV) integration, as well as the frequent voltage disturbances resulting from frequent load switching and variable operating conditions in agricultural grid systems, this paper proposes a dual-layer optimized configuration and adaptive voltage control method for grid-forming energy storage systems. First, an outer-layer siting and sizing model is established with constraints including voltage stability, deviation, network losses, and economic factors. The configuration scheme is solved using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Then, an inner-layer rolling optimized dispatch model is constructed with Model Predictive Control (MPC) as the core, and an adaptive reactive power–voltage control method based on Virtual Synchronous Generator (VSG) control is proposed to enhance transient voltage support under disturbance conditions. Simulation analysis based on an actual 10 kV rural distribution line verifies that the proposed method can effectively mitigate overvoltage issues and alleviate reverse power flow during typical daily operation, while significantly improving node voltage recovery speed and reactive power support capability under voltage disturbances. Full article

Outer rotor permanent magnet synchronous motors (ORPMSMs) are widely used in drone and aircraft propulsion due to their high power density. However, conventional arc-shaped designs involve an inherent trade-off between efficiency and torque ripple. Increasing the arc curvature improves the sinusoidal air gap flux density and reduces torque ripple, but it also increases rotor eddy current loss due to larger flux variations, thereby degrading efficiency. This paper investigates the effects of stator and rotor geometries on rotor eddy current loss and torque ripple in ORPMSMs. To address this trade-off, arc- and rectangular-shaped rotor and stator pole shoes are combined to form four design candidates. Their electromagnetic performance is evaluated using finite element analysis. Based on this comparison, a configuration with rectangular rotor and stator pole shoes is selected as the initial design and further optimized using a multi-objective genetic algorithm to simultaneously improve efficiency and torque ripple. The optimized design demonstrates significant improvements, achieving reductions of 56.67% in peak-to-peak torque ripple and 46.89% in rotor eddy current loss compared to the initial design. Full article

Model-Agnostic Meta-Learning (MAML) and Prototypical Networks (ProtoNet) establish the foundational paradigms for few-shot classification. However, MAML suffers from optimization instability caused by reconstructing classification boundaries for every new task. Conversely, ProtoNet lacks the internal mathematical capacity necessary for task-specific parameter adaptation under domain shifts. To reconcile these structural limitations, we introduce Metric-based Model-Agnostic Meta-Learning (M²AML). By completely excising the parameterized classification layer from the episodic adaptation sequence, our framework replaces traditional inner-loop classification with a dynamic self-exclusive geometric similarity metric. Substituting functional mappings with spatial distance optimizations efficiently resolves evaluation conflicts, thereby establishing perfectly synchronized inner and outer learning rates alongside substantially accelerated adaptation steps. Extensive experiments across mini-ImageNet, tiered-ImageNet, and CIFAR-FS validate our approach against a comprehensive array of established algorithms. To ensure strictly fair comparative evaluations, we meticulously reproduce the MAML, ProtoNet, and Proto-MAML baselines. Empirical results demonstrate that M²AML achieves state-of-the-art performance across most evaluation settings, delivering absolute accuracy improvements ranging from 0.1% to 2.1% over existing leading models. Full article

As power-electronic-interfaced renewable generation displaces synchronous machines, modern power systems face coupled day-ahead challenges: net-load variability demands peak shaving, while declining inertia necessitates explicit frequency-regulation scheduling. In sequential security-constrained unit commitment (SCUC) and Security-Constrained Economic Dispatch (SCED), the reserve procured in SCUC may lose deliverability after redispatch because the same storage bandwidth is reassigned to energy service. This paper proposes a two-stage day-ahead framework that addresses both challenges for low-inertia systems with high inverter-based resource (IBR) penetration. Stage I embeds Rate-of-Change of Frequency (RoCoF), frequency nadir, and quasi-steady-state (QSS) constraints in SCUC, with a piecewise-linear outer approximation for the non-convex nadir limit. Stage II strictly inherits the SCUC commitment and reserve reservation, and it applies bandwidth deduction to prevent peak-shaving redispatch from consuming committed frequency reserve. A technology-aware partition further assigns fast-response Lithium Iron Phosphate (LFP) batteries to sub-second frequency support and long-duration Vanadium Redox Flow Batteries (VRFBs) to energy shifting. Evaluated under the adopted reduced-order frequency-response framework and disturbance representation, tests on a modified IEEE 39-bus system under an extreme-wind scenario demonstrate that explicit frequency constraints eliminate all post-contingency violations, the inheritance mechanism closes a 23.85 MW reserve gap after redispatch, and heterogeneous storage partitioning preserves essentially the same disturbance sensitivity while increasing the peak-shaving ratio to 45.85%, lowering the day-ahead cost to CNY $10.483\times {10}^6$ and reducing the average system price to 209.33 CNY/MWh. Full article

Swallowing is a critical marker of neurological and emotional health. The ability to monitor it continuously and non-invasively, especially through smart ear-worn devices, holds significant promise for clinical applications. Despite this potential, no public audio datasets currently support reliable swallowing sound detection. Existing datasets focus primarily on speech and breathing, offering limited coverage and lacking detailed annotations for swallowing events. To address this gap, we introduce an in-ear audio dataset specifically designed to capture a wide range of verbal and non-verbal sounds. It includes comprehensive labeling focused on swallowing. The dataset was collected from 34 healthy adults (14 females and 20 males) between the ages of 20 and 29. Each participant performed a series of predefined tasks involving both non-verbal and verbal events. Non-verbal tasks included swallowing, clicking, forceful blinking, touching the scalp, and physical movements such as squatting or walking in place. Verbal tasks consisted of speaking (e.g., describing an image). Recordings were conducted in both quiet and noisy environments to better reflect real-world conditions. Data were captured using a combination of in-/outer-ear microphones, a chest belt to record electrocardiogram (ECG), respiration and acceleration signals, and an ultrasound probe to track tongue movement, which served as a reference for swallowing annotation. All signals were precisely synchronized. To ensure high data quality, the recordings were reviewed using both algorithmic analysis and manual inspection. Swallowing events were identified based on ultrasound signals and validated by an expert to guarantee accurate labeling. As a proof of concept that in-ear audio supports swallow classification, we fine-tune a fully connected neural network on YAMNet embeddings plus zero-crossing rate (ZCR) features. Across the completed folds, the model reaches an F1 score of 0.875 ± 0.013. Full article

This paper investigates the electromagnetic performance of an outer-rotor spoke-type permanent magnet synchronous generator intended for small wind turbine applications below 5 kW. The study focuses on the influence of structural ferromagnetic components on magnetic flux distribution and overall machine performance. The generator was initially designed and optimized using 2D finite element analysis, followed by a comprehensive 3D model to account for axial flux leakage and structural details; particular attention was given to the fastening screws used. Experimental validation on a dedicated laboratory test bench confirms the accuracy of the 3D model, mainly at lower wind speeds. The results highlight the necessity of including structural components in three-dimensional electromagnetic modeling for accurate performance prediction of flux-concentrating wind turbine generators. 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

To address the chattering phenomenon and sensitivity to load disturbances in conventional sliding mode observers (SMO) for sensorless permanent magnet synchronous motor (PMSM) control, this paper proposes a robust sensorless control strategy integrating a fuzzy adaptive SMO with an improved sliding mode speed controller. In the observer design, a continuous hyperbolic tangent function, $tanh \left(ax\right)$, replaces the traditional sign function, while a fuzzy logic controller adaptively tunes the convergence factor a to enhance estimation accuracy and suppress high-frequency chattering. Simultaneously, an adaptive quadrature phase-locked loop (AQPLL) is incorporated to achieve adaptive matching across various operating conditions by updating parameters online, which effectively reduces phase delay and improves the dynamic performance of rotor position and speed estimation. Furthermore, a non-singular terminal sliding mode control (NTSMC) strategy is employed in the outer speed loop with a proposed segmented terminal reaching law. This law ensures rapid response in large-error regions and mitigates steady-state oscillations in small-error regions, thereby strengthening system robustness against load disturbances. The stability of the proposed system is rigorously verified via Lyapunov stability analysis. Simulation and experimental results demonstrate that the proposed approach significantly reduces speed and position estimation errors under varying speeds and sudden load changes compared to the conventional SMO-PI method, while effectively suppressing system chattering to confirm its engineering feasibility. Full article

Low-voltage ride-through (LVRT) capability is essential for grid-connected photovoltaic (PV) systems, especially as rising renewable integration challenges grid stability during voltage disturbances. Existing LVRT methods often target isolated control functions, leading to limited system resilience. This paper presents a unified control strategy integrating DC-link voltage regulation, reactive power injection, and overvoltage mitigation using a coordinated fuzzy logic framework. The proposed architecture employs a cascaded control structure comprising an outer voltage loop and an inner current loop with feed-forward decoupling, synchronized via a Synchronous Reference Frame Phase-Locked Loop (SRF-PLL). At its core is a dual-input, single-output Fuzzy Logic Controller (FLC), featuring optimized membership functions and dynamic rule-based logic to manage multiple control objectives during grid faults. The proposed FLC-based unified LVRT controller for grid-tied PV system was implemented and validated for both symmetrical and asymmetrical fault conditions in MATLAB/Simulink 2023b platform. The proposed FLC-based LVRT controller achieves voltage sag compensation of 97.02% and 98.4% for symmetrical and asymmetrical faults, respectively, outperforming conventional PI control, which achieves 94.02% and 96.5%. The system maintains a stable DC-link voltage of 800 V and delivers up to 78% reactive power support during faults. Fault detection and recovery are completed within 200 ms, complying with Bangladesh grid code requirements. This integrated fuzzy logic approach offers a significant advancement for enhancing grid stability in high-renewable environments and supports reliable renewable utilization, and more sustainable grid operation in developing regions. Full article

With the increasing penetration of inverter-based resources (IBRs), modern power systems are experiencing undesirable dynamics, such as sub-synchronous oscillations in weak grids. Conventional PI control schemes, however, exhibit limited robustness against nonlinearities arising from varying operating points in weak grids, leading to instability. To address this challenge, we propose a robust controller for the outer loop of grid-side converters in IBRs based on robust μ-synthesis control theory. Specifically, this paper utilizes μ-synthesis to handle linearized model parameters associated with operating-point variations. The proposed controller replaces the PI controllers in the outer loop while retaining the established dq-frame control philosophy. Furthermore, during controller synthesis, the controller is optimized with a 2-by-2 multi-input multi-output structure to explicitly account for cross-coupling effects between the d- and q-axes. Finally, the proposed controller was validated using electromagnetic transient simulations of a detailed type-IV wind farm model implemented in MATLAB/Simulink R2025a, and its performance was compared with that of a conventional PI-based outer control loop. The wind farm was tested under very weak grid conditions, and the proposed controller demonstrated robust stability against varying operating points by providing superior damping performance. Full article

Recently, unmanned aerial vehicles (UAVs) based on electric propulsion systems are being increasingly adopted in various fields, including industrial and military applications. Outer-rotor surface-mounted permanent magnet synchronous motors (SPMSMs) are predominantly applied in UAV propulsion systems. However, these motors are vulnerable to the price fluctuations of rare-earth materials and supply chain instability. In addition, the magnets in these motors are prone to detachment at high rotational speeds, and demagnetization under high-temperature conditions may reduce output performance. To address these limitations, research is being actively conducted on non-permanent magnet motors, among which, wound-rotor synchronous motors (WRSMs) offer the advantage of controllable field excitation at high speeds. Furthermore, WRSMs can use both magnetic and reluctance torques, thereby increasing power density relative to other non-permanent magnet motors. However, the adoption of an additional field winding increases copper loss, thus reducing motor efficiency. This study investigates the application of the toroidal winding structure, which is already widely applied in permanent magnet and brushless direct current machines, to WRSMs. The performance of these motors is compared with that of motors using conventional tooth-coil windings. The toroidal windings are circumferentially distributed along both the inner and outer stator yoke paths, effectively reducing the end-turn length relative to that of conventional tooth-coil windings. Two WRSMs, one with tooth-coil and another with toroidal windings, are designed using identical specifications to compare performances via finite element analysis. The armature copper loss in the proposed model decreased by approximately 28% because the toroidal winding structure reduced the end-turn length. As a result, the efficiency increased by about 1.9% due to the reductions in copper, core, and eddy current losses. Full article

The control design of three-phase AC/DC converters is particularly challenging, as their dynamic behavior is governed by complex nonlinear interactions and strong coupling among system variables, conventional Proportional–Integral (PI) controllers often suffer from sluggish transient responses and limited immunity to interference. To address these issues, Sliding-Mode Control (SMC) is widely adopted for its robustness against parameter uncertainties and rapid dynamic performance. However, the chattering phenomenon inherent in traditional SMC near the sliding surface remains a critical challenge. To improve the dynamic performance of sliding-mode control, this work introduces a redesigned exponential reaching law into the control framework. The proposed strategy is implemented in a voltage–current cascaded (double closed-loop) structure, where the improved reaching law is embedded in the outer DC-link voltage loop and the inner loop regulates the grid currents in the synchronous dq frame. By modifying the reaching dynamics, the proposed approach effectively weakens chattering phenomena while enabling faster convergence of the system states. Comprehensive validation was conducted using Matlab/Simulink simulations and experimental prototypes. The results demonstrate that, compared to PI control and traditional exponential reaching law-based SMC, the proposed strategy significantly mitigates chattering while delivering superior static stability and faster dynamic response. Full article

This study used a 3D numerical model to investigate the heat-flow behavior of a 1 MW synchronous motor–generator by creating a conjugate heat transfer model that included the rotating parts. The computational model involved complex solid/fluid interfaces, a rotor–stator gap, and a fan-driven cooling path that passes through a stator’s external flow path in order to identify local temperature fields and flow distributions. Under design conditions, localized high-temperature regions were observed in the rotor coil because the cooling air was heated, and the airflow then diverged through the stator’s internal channels. On the contrary, periodic low-temperature areas were formed around the stator’s circumference as a result of conductive heat diffusion into the outer casing. A correlation was derived describing a relationship where the peak temperature decreased in a clear logarithmic manner as the cooling air mass flow rate increased. We confirmed that a cooling flow rate of at least 2.0 kg/s is needed to keep the rotor coil temperature below 120 °C within its operational limit under design points. Furthermore, the functional form of the temperature–flow rate relationship remained logarithmic, and the correlation coefficients in this relationship changed linearly with heat generation, even under off-design conditions, where the total heat generation was reduced to 88% of the design value and the ambient temperature was lowered. The study results will provide a practical basis for swiftly estimating peak temperature for various operating scenarios and for determining cooling paths and fan geometry to avoid repeating expensive simulations. Full article

Persistent discrepancies remain in the perceived far-field noise of automotive permanent-magnet synchronous motors (PMSMs) and the predictions of conventional NVH simulations. To bridge this gap, a Tri-source Electromagnetic Coupling NVH Integrated Framework (Tri-ECNVH) is developed, in which air-gap electromagnetic force harmonics, torque ripple, and cogging torque are treated as a coupled excitation system rather than as independent sources. Traditional workflows usually superpose their responses in the power domain, which tends to underestimate the radiating contribution of torque-related excitations and neglect their phase and order coupling with radial electromagnetic forces. In the proposed Tri-ECNVH framework, the three sources are mapped into the order domain, aligned by spatial order, and applied to the stator with phase consistency, so that inter-source coupling and cross terms are explicitly retained along a unified electromagnetic–structural–acoustic chain. Acoustic radiation is evaluated by prescribing the normal velocity on the stator outer surface as a Neumann boundary condition and computing the far-field A-weighted sound pressure level (SPL) using a boundary element method (BEM) model. Numerical results reveal pronounced cooperative amplification of the three sources at critical orders and within perceptually sensitive frequency bands; relative to independent-source modeling with power-domain summation, Tri-ECNVH predicts peak levels that are typically 5–10 dB higher and reproduces the spectral envelope and peak–valley evolution more faithfully. The framework therefore offers a practical, radiation-oriented basis for multi-source noise mitigation in traction PMSMs and helps narrow the gap between simulation and perceived sound quality in automotive applications. Full article