Search Results (1,740)

Aiming at the deterioration in Noise, Vibration and Harshness (NVH) performance caused by broadband torsional vibration in the integrated electric drive system (IEDS) of electric vehicles, most existing studies independently focus on electromagnetic excitation suppression or torsional vibration control of mechanical transmissions. Few researchers consider the coupling characteristics between the electromagnetic nonlinearity of motors and the nonlinearity of gear transmissions, making it difficult to realize the coordinated suppression of high- and low-frequency torsional vibration. In this paper, a seven-degree-of-freedom electromechanical coupling dynamic model is firstly established, which incorporates the electromagnetic torque ripple of the motor, the time-varying meshing stiffness of gears, meshing errors, and gear backlash nonlinearity. Through modal analysis and Campbell diagram solution, the natural characteristics and critical speed range of the system are clarified, and the generation mechanism of full-frequency band torsional vibration as well as the high–low frequency coupling characteristics are systematically revealed. On this basis, a coordinated active control strategy based on PD pole placement and harmonic current injection (PD-HCI) is proposed. The PD pole placement controller is adopted to suppress the low-frequency torsional vibration (0–20 Hz) of the transmission system, and the 5th/7th harmonic current injection is used to counteract the high-frequency torque ripple (above 200 Hz) of the motor, thereby achieving the coordinated suppression of broadband torsional vibration. The Matlab/Simulink R2023a simulation results show that the proposed control strategy reduces the torque fluctuation rate from 3.11% to 1.96%, the speed fluctuation rate from 0.10% to 0.03%, and the total harmonic distortion (THD) of stator current from 8.69% to 1.77% under steady-state operating conditions. Under transient operating conditions with sudden load changes, the stabilization time of fluctuations in speed and half-shaft torque is shortened by more than 80%, the impact amplitude is significantly reduced, and there is no loss in the vehicle’s dynamic response and speed tracking performance. Experimental results show that the coefficients of determination R2 of vehicle speed, motor speed, acceleration and torque are 0.9990, 0.9982, 0.9997 and 0.9997, respectively, which verifies the reliability of the established model. Full article

In single-phase PWM rectifiers, due to the inherent time-varying characteristics of the source voltage and current as well as the periodic operation of the converter bridge, the instantaneous input power on the AC side inevitably exhibits a twice-fundamental-frequency pulsation. This phenomenon consequently generates a double-line-frequency (100 Hz) voltage ripple on the DC-link capacitor, which causes an inherent contradiction in conventional voltage outer-loop control between steady-state ripple suppression and dynamic response speed. To address this issue, this paper proposes a control strategy based on an Adaptive Time-Delayed Feedforward Neural Network (Adaptive TD-FNN). The proposed method explicitly introduces the delayed voltage error of half a ripple period into the network state input, thereby achieving time-domain decoupling of the 100 Hz low-frequency disturbance. In addition, a physics-driven training framework is constructed by integrating the rectifier’s discrete difference equation, thereby strengthening the network’s capacity to learn the dynamic characteristics of the system. On this basis, a dynamic adaptive smoothness-weight penalty mechanism is designed to adjust the weighting factor of the current command smoothness constraint in the loss function according to the system operating state. Specifically, the penalty weight is increased under steady-state conditions to suppress command oscillations caused by ripple disturbances, while it is rapidly reduced during load or grid-voltage transients to release the network’s transient optimization capability. Simulation and experimental results show that the proposed Adaptive TD-FNN controller can simultaneously achieve smooth steady-state current command output and fast dynamic voltage regulation without introducing additional complex digital notch-filtering algorithms. Compared with conventional dual-loop control, the proposed strategy reduces the total harmonic distortion (THD) of the grid-side input current from 8.45% to 3.42%, satisfying grid-connected power quality requirements. Meanwhile, under large load transients and grid-voltage disturbance conditions, the DC-link voltage recovery time is about 40 ms, verifying the comprehensive advantages of the proposed method in ripple suppression, dynamic response, and operating-condition adaptability. Full article

This work concerns the harmonization of geospatial data to improve linkages between place-based characteristics and health outcomes. Such data are typically available as geographic layers, each representing a distinct attribute (e.g., income or distance to a clinic). Since layers are typically constructed independently, their boundaries tend to be spatially incongruent, which can create inconsistencies and introduce bias. This motivates developing algorithmic approaches for aligning such layers while aiming to preserve spatial integrity. This paper formalizes the problem of aligning k collections of m spatial supports over n spatial units in a d-dimensional Euclidean space such that maximum distortion to any collection is minimized. In the above setting, k is the number of layers; n is an indivisible population unit (e.g., census tract); m denotes supports, which are larger regions aggregating a set of contiguous units in order to capture broader regional patterns or enhance statistical stability; and $d=2$. It is shown that: (1) the one-dimensional case is solvable in time polynomial in k, m, and n; (2) the two-dimensional case is NP-hard for two collections of two supports each; and (3) a heuristic can be provided for aligning a set of collections in the two-dimensional case, which is of practical importance. Full article

Photoplethysmography (PPG) is a widely used non-invasive optical technique for assessing cardiovascular dynamics and related hemodynamic processes. However, conventional noise-reduction methods can alter signal timing and distort waveform morphology, thereby affecting the identification of physiologically relevant events. Here, we propose a frequency-domain Gaussian filtering framework for selectively extracting harmonics from PPG signals. The method combines a Gaussian band-reject filter centered at 0 Hz to suppress the dominant DC component, reduce the non-pulsatile baseline, and attenuate low-frequency contributions associated with slow modulation processes. Symmetric Gaussian bandpass filters are then applied to isolate harmonic components, with the number of retained bands adapted to the requirements of a given application. As a proof of concept, the framework was applied to both a simulated PPG waveform and an experimental PPG recording. Because of the symmetric zero-phase properties of the filters, the temporal alignment of key PPG events, including the systolic peak, diastolic decay, and dicrotic notch, can be preserved while phase distortion is avoided. Reconstruction from filtered harmonics further suggests that low-order harmonics retain much of the observable waveform structure in the signals analyzed. Overall, this harmonic-based Gaussian filtering provides a promising framework for analysis of PPG signals and motivates further investigation of its potential for extracting physiologically related information from harmonic components, such as bedside monitoring. Full article

In industrial applications such as in situ leaching and uranium mining, permanent magnet synchronous motors (PMSMs) for submersible pumps are frequently connected to frequency converters via long cables. During this long-distance transmission, traveling wave reflections induced by high-frequency pulse width modulation (PWM) generate severe transient overvoltages that threaten motor insulation. Because installation space at deep-well motor terminals is severely restricted, overvoltage suppression must be implemented at the inverter output. Here, the parameter design and optimization of a passive LC filter specifically developed for 250 Hz high-frequency PMSMs are presented. The optimal inductance and capacitance parameters were determined by balancing multiple operational constraints, including fundamental voltage drop, high-frequency harmonic attenuation, and the avoidance of low-order harmonic resonance. Furthermore, the anti-saturation performance of the magnetic core material, evaluated thermal characteristics through electromagnetic-thermal co-simulation, and analyzed the risk of self-excited oscillation between the filter capacitors and the motor was analyzed. Finally, hardware experiments conducted on a 20 m cable test bench validate that the designed LC filter effectively mitigates terminal overvoltage. The peak terminal voltage was reduced from 900 V to 505 V, and total harmonic distortion (THD) was limited to below 5%. This design provides a highly reliable, space-efficient solution for overvoltage suppression in high-speed, long-cable motor drive systems. Full article

This paper is devoted to defining and analyzing a new subclass $M(\nu ,\tau ,q)$ of q-valent harmonic mappings in the unit disk D, as well as investigating its connection with close-to-convex analytic functions. First, we prove that this newly defined class is non-empty and discuss its relationship with several known classes of harmonic mappings. Using arguments similar to those employed in the study of Mocanu-type harmonic mappings, we establish the close-to-convexity of functions belonging to this class. Necessary coefficient estimates for the analytic part are obtained, and auxiliary lemmas which play an essential role in the investigation of geometric properties of the class are derived. In particular, we establish distortion estimates for the derivative of the analytic part, which lead to a growth and distortion theorem for functions in the newly defined class $M(\nu ,\tau ,q)$. Furthermore, a covering theorem is obtained for these harmonic mappings. In addition, we also derive sharp bounds for the Fekete–Szegö-type functionals and several graphical examples are presented to analyze the geometric structure of the mappings in the class $M(\nu ,\tau ,q)$ that demonstrate how the parameters $q,\nu ,$ and $\tau ,$ affect the deformation of the unit disk. Full article

A quasi-continuous-wave (QCW) laser module based on a half-bridge structure is proposed for the low-voltage silicon photonics application, which forms a continuous-wave (CW) laser output when it equally distributes the heat dissipation into all lasers. Such a QCW laser module is modulated into a CW laser source for the chip-to-chip or board-to-board communication. The source current is alternatively diverted to the high-side and the low-side lasers by turning the corresponding gallium nitride high-electron-mobility transistor (GaN HEMT) on and off. The current redirection modulates multiple QCW laser outputs into a CW laser output; however, an undesirable laser downtime is produced during the transition time of the current redirection. Although for the 10 Gbps data rate transmission, a short laser downtime period may be scheduled for the time to perform either the laser steering task of the free-space optics (FSO) operation or the data pause for the fan-out delay, which is still preferred to be minimized for higher data rate transmission. The power efficiency and the laser downtime are functions of the parameters of the laser diodes, switch parasitic capacitances, input voltage, and the inductor. According to the mathematical derivation of the circuit response, the circuit design rules and the switching control strategy are provided to achieve high efficiency and low laser downtime. In the experiment, we implemented a laser module to achieve an FSO specification with a laser downtime of less than 3 ns, total harmonic distortion (THD) less than 10%, power efficiency greater than 60% and laser power higher than 1 W. Full article

The increasing penetration of nonlinear loads aggravates grid harmonic distortion and imposes higher requirements on the control performance of the shunt active power filter (SAPF). To address the problems of fixed parameters in conventional PI controllers and the dependence of existing improved methods on accurate models with relatively high computational complexity, this paper proposes a TD3-based model-free adaptive control method for online coordinated tuning of dual-loop PI parameters in the SAPF system. The proposed method dynamically adjusts PI parameters through agent–environment interaction without requiring an accurate system model or a complex control structure. Simulation results show that the proposed strategy outperforms fixed-parameter PI control, PI-SMC, and DDPG methods in both steady-state and dynamic performance, and maintains good control performance under unseen composite disturbances such as capacitive inrush and load variation. RT-LAB-based hardware-in-the-loop (HIL) validation further demonstrates that the proposed method can achieve effective harmonic compensation and DC-link voltage regulation on a real-time simulation platform. Meanwhile, during online deployment, only Actor-network forward inference is required to update the PI parameters, indicating a low additional computational burden and engineering implementation potential for SAPF real-time control systems. Full article

The increasing penetration of power electronic devices and distributed generation is significantly altering power quality conditions in low-voltage systems. While power quality assessment is commonly based on RMS currents, voltage quality indicators, and overall distortion metrics, these parameters may not fully reveal phase-selective harmonic behaviour in modern converter-dominated installations. This paper presents a measurement-based power quality assessment of a secondary school building equipped with a grid-connected photovoltaic (PV) system. A one-week monitoring campaign was conducted at the point of common coupling (PCC), capturing voltage, current, harmonic distortion, and power flow characteristics under real operating conditions. The results reveal pronounced phase-selective current harmonic distortion, with substantially elevated total harmonic distortion (THD_I) and total demand distortion (TDD) in one phase despite relatively balanced RMS current levels and acceptable voltage quality. The harmonic spectrum is dominated by low-order odd harmonics, whereas voltage distortion remains comparatively low and well balanced across phases. The study demonstrates that significant harmonic asymmetry may remain hidden in apparently balanced three-phase systems when assessment relies primarily on conventional RMS-based indicators. The findings highlight the importance of detailed current harmonic analysis and show that acceptable voltage quality does not necessarily imply acceptable current quality. The presented results provide measurement-based evidence of hidden harmonic asymmetry in modern low-voltage buildings and contribute to a better understanding of power quality challenges associated with nonlinear loads and distributed energy resources. Full article

With the rapid growth of transportation electrification and smart energy systems, the reliable operation of electric vehicle (EV) charging infrastructure has become an important issue for sustainable transport, since charging faults may interrupt service and shorten equipment lifetime. However, practical charging environments are often characterized by heterogeneous operating conditions and severely imbalanced fault distributions, which limit the effectiveness of conventional fault diagnosis methods. To address these challenges, this study proposes a lightweight Proto-Contrastive Discriminative Learning (PCDL) framework for intelligent fault diagnosis in EV charging systems. The proposed method combines supervised contrastive learning with a prototype-distance discrimination mechanism to improve the identification of rare abnormal states under long-tailed data conditions. Heterogeneous charging features, including discrete control signals and continuous total harmonic distortion (THD) indicators, are projected into a discriminative embedding space, while anomaly detection is performed according to the relative distances between samples and class prototypes. Experimental results on a publicly available EV charging-pile monitoring dataset, containing 122,144 samples with four discrete control/safety features and two THD-based power-quality features, demonstrate that the proposed framework maintains stable detection performance under imbalance ratios of 1:1, 1:10, and 1:100. Under the most challenging 1:100 condition, the proposed method achieves an F1-score of 84.21%, representing a 29.08% improvement over the strongest baseline method. In addition, the framework requires only approximately 11 KB of memory and maintains CPU inference latency below 6.3 ms, demonstrating strong potential for real-time deployment on resource-constrained edge devices. These results suggest that the proposed framework can provide a lightweight diagnostic tool for practical charging stations and support safer and more reliable EV charging operation. Full article

Permanent magnet synchronous generators (PMSGs) are inevitably subject to aperiodic and periodic disturbances due to complex operating conditions and internal coupling effects. To improve speed regulation under such disturbances, this paper develops a hierarchical control framework that integrates a parameter-decoupled extended state observer (DESO) with quasi-resonant control. A novel parameter decoupling method enables independent tuning of the observer bandwidth and controller parameters, while the quasi-resonant control module specifically targets periodic torque ripples caused by the tower shadow effect. Simulation results under stochastic wind conditions confirm that the proposed QR-DESO significantly outperforms conventional methods, reducing the speed tracking root mean square error (RMSE) by $61.8\%$ and the total harmonic distortion (THD) to $0.17\%$. The system also exhibits strong robustness against $\pm 20\%$ parameter mismatches, validating its effectiveness for offshore wind power applications. Full article

The increasing integration of photovoltaic (PV) systems and nonlinear loads intensifies harmonic distortion and reactive power imbalance in modern power networks. Conventional shunt active power filters (SAPFs) often employ control strategies that perform poorly under uncertain and dynamic grid conditions. This paper develops a hybrid sliding mode control with disturbance observer (SMC+DOB) technique for a PV-integrated SAPF to achieve effective harmonic mitigation, reactive power compensation, and enhanced system robustness. The study models the PV-SAPF system in MATLAB/Simulink (R2025b), where the SMC ensures robust current tracking, while the DOB estimates and suppresses unknown disturbances in real-time. The controller’s performance is evaluated under varying nonlinear and reactive load conditions, as per IEEE 519-2014 standards. Simulation results show that the proposed SMC+DOB scheme reduces total harmonic distortion (THD) by 96.7%—from 31.45% to 1.05%—while maintaining DC-link voltage stability and unity power factor. The integrated control architecture enhances the dynamic performance of SAPF, providing superior harmonic suppression, fast transient recovery, and improved grid stability for PV-connected systems. Full article

The rapid global deployment of wind energy requires robust and efficient control strategies for doubly fed induction generator (DFIG)-based systems. Conventional proportional–integral (PI) controllers tuned by classical or metaheuristic methods often exhibit poor adaptability to turbulence, parameter drift, and grid disturbances. This paper introduces an adaptive owl search optimisation (A-OSO) algorithm for the real-time tuning of PI controllers in DFIG back-to-back converters. Unlike traditional OSO, the adaptive variant dynamically adjusts its exploration–exploitation balance based on the severity of system disturbances, enabling faster convergence and improved resilience. The study benchmarks the proposed method against particle swarm optimisation (PSO), genetic algorithm (GA), simulated annealing (SA), and owl search optimisation (OSO) simulation studies in MATLAB/Simulink, coupled with hardware-in-the-loop (HIL) tests on an FPGA platform, demonstrating that A-OSO achieves superior efficiency (97.1%), lower power losses (35 kW), faster low voltage ride-through (LVRT) recovery (less than 150 ms), and reduced total harmonic distortion (THD) (2.4%). These findings establish A-OSO as a practical, grid-compliant optimisation strategy for next-generation smart wind farms. Full article

Vegetation phenology refers to the cyclical growth patterns of vegetation in nature, which are influenced by climatic conditions, human activities, and genetic factors. It plays an irreplaceable role in regulating carbon cycling and energy flow within natural ecosystems. However, the combination of a cloudy and rainy climate with a landscape characterized by the interplay of land and water and fragmented patches has long posed challenges for remote sensing phenological monitoring data, including a scarcity of valid observations, frequent temporal gaps, and spectral distortion in mixed pixels. These issues make it difficult to reliably support the needs of wetland phenological inversion and mapping. To address this issue, this study uses vegetation inversion in the Poyang Lake wetlands as a case study and reconstructs high-spatiotemporal-resolution time-series kNDVI data based on multi-source remote sensing data. Methodologically, we propose an improved and enhanced spatiotemporal adaptive reflectance fusion model, IESTARFM. This model enhances the homogeneity of similar pixel selection through adaptive matching windows and land cover constraints. Additionally, it explicitly incorporates cloud probability and time-lag factors into the weighting structure to systematically downweight unreliable observations, and further employs quadratic term corrections to account for the nonlinear growth response of kNDVI. Using the reconstructed dataset, key phenological information is extracted by combining third-order harmonic analysis with a dynamic thresholding method, thereby enhancing the robust characterization of seasonal trajectories under conditions of missing data and noise. Accuracy evaluation results show that the 10m/8d high-frequency kNDVI dataset reconstructed by IESTARFM achieves at least a 12.61% improvement in fusion accuracy compared to classical methods such as ESTARFM, STARFM, and FSDAF, with a maximum reduction in RMSE of 0.026, and effectively restores details in areas with thin cloud cover. The reconstructed kNDVI series achieved a coefficient of determination $R^2$ = 0.875 and RMSE = 0.066 relative to Sentinel-2 observations, indicating that the reconstructed series closely reproduces the reference imagery in both amplitude and spatial structure. The phenological parameters derived from kNDVI exhibit an RMSE of 4.81 days compared to field observations, demonstrating that the reconstructed time series reliably captures the timing of key phenological events. It should be noted that the proposed approach is designed for post-event time-series reconstruction and is not intended for real-time forecasting. In summary, this study collaboratively enhanced the reliability of high-resolution index time-series reconstruction and phenological identification in cloudy and rainy wetlands through three key aspects: cloud noise suppression, heterogeneous boundary preservation, and nonlinear growth characterization. It provides a generalizable technical foundation for dynamic monitoring of wetland vegetation, ecological restoration assessment, and refined management in regions with frequent cloud and rainfall. Full article

This paper investigates the accuracy of conventional inductive current transformers (iCTs) and Rogowski coils (RCs) in measuring distorted currents, evaluating compliance with the WB0 (up to the 13th harmonic) and WB1 (up to the 60th harmonic) accuracy classes according to the IEC 61869-1 standard. A custom reference iCT, calibrated via the ampere-turns method to achieve a superior baseline accuracy (0.02%), served as the primary benchmark. A zero-flux electronic transducer was utilized strictly to verify this reference. Despite inherent core nonlinearity, tested conventional iCTs with reduced to minimum secondary burdens successfully met the class 0.5-WB1 requirements. In the case of tested Rogowski coils, the study reveals that their wideband performance depends on physical design of the particular type. High-sensitivity coils suffer from increased parasitic capacitance and self-inductance, causing significant additional phase shift at higher frequencies, whereas low-sensitivity, small-diameter coils offer superior linearity. Overall, the tested RCs generally ensured compliance with the 0.5-WB1 class across the evaluated frequency range, with certain units successfully achieving the more restrictive 0.2-WB1 class. Ultimately, conventional iCTs remain a highly reliable solution for metering purposes in low-voltage networks, while properly selected Rogowski coils provide a valuable alternative for power quality analysis and harmonic distortion measurements. Full article