Search Results (156)

The rapid growth of battery energy storage systems, renewable energy integration, electric vehicles, and DC microgrids has significantly increased the demand for compact, efficient, and bidirectional isolated DC–DC converters. Conventional Dual Active Bridge (DAB) converters commonly employ high-frequency transformers to provide galvanic isolation and bidirectional power transfer. Although transformer-based DAB converters offer excellent performance, their magnetic components increase converter volume, weight, core losses, leakage inductance, manufacturing complexity, and overall cost. Consequently, recent research has explored alternative high-frequency energy transfer techniques based on capacitive coupling, aiming to reduce magnetic components while preserving efficient resonant power conversion.This paper proposes a Capacitively Coupled Dual Active Bridge (CC-DAB) converter employing high-power metallized polypropylene (MKPH) capacitors as the high-frequency energy transfer medium. The proposed converter operates at a relatively low switching frequency while investigating the safe operating conditions of the capacitive coupling network to ensure reliable and efficient power transfer. A microcontroller-based single-phase-shift (SPS) modulation strategy is implemented to generate the gate-driving signals of the full bridges, whereas the switching frequency is selected to achieve zero-voltage switching (ZVS) throughout the investigated operating range. The phase-shift angle ($\varphi$) regulates the transferred power by controlling the voltage difference between the primary and secondary bridges across the capacitive coupling network. The proposed converter is analyzed theoretically and validated through simulation and experimental testing. Experimental results demonstrate stable bidirectional power transfer, soft-switching operation, and a peak conversion efficiency of 91.3% at a relatively low switching frequency of 52 kHz. The experimental verification confirms the practical feasibility of capacitive coupling for resonant bidirectional power conversion and demonstrates its potential as an alternative architecture for low- and medium-power applications requiring compact size, high efficiency, reduced magnetic component requirements, and reversible energy transfer. Furthermore, the proposed topology contributes to the ongoing development of transformerless resonant converters by experimentally validating a high-frequency capacitive coupling network capable of supporting efficient bidirectional power flow under practical operating conditions. Full article

Wind power integration into mountainous power grids amplifies probabilistic forecasting challenges arising from strong non-stationarity, multi-source meteorological redundancy and frequent curtailment events. To address the limitations of existing approaches, this paper proposes a multi-horizon probabilistic forecasting framework integrating multi-perspective entropy-weighted fusion, permutation-entropy-guided decomposition, and residual-anchored probability modelling. First, an Entropy-Weighted Multi-criteria Permutation Feature Importance (EW-MPFI) module fuses KSG mutual information, Tree-SHAP, and elastic-net permutation importance through entropy-based weighted aggregation, distilling 23-dimensional meteorological inputs into eight informative features while suppressing single-criterion bias. Then, a three-stage decomposition strategy applies ICEEMDAN primary decomposition, permutation-entropy and sample-entropy guided band reconstruction, and SSA secondary refinement on high-frequency components, achieving complexity-aligned multi-scale separation. Finally, a decomposition-aware patch-based Transformer backbone (DPC-Former) generates three-quantile point forecasts, upon which an NGBoost residual layer models the conditional distribution via natural-gradient optimization in the information-geometric parameter space. Case studies on a 130 MW mountainous wind farm in Sichuan, China, covering 8736 15-min samples with 566 curtailment samples (6.48% of the dataset), show that, under the partition-wise offline batch-evaluation protocol, the proposed framework achieves an NMAE of 5.21%, an NCRPS of 3.74%, and a PICP80 of 0.84 across forecasting horizons from 15 min to 4 h. Ablation analysis attributes NMAE improvements of 25.36% and 24.57% to the decomposition and feature-selection modules, respectively, while 50-seed ensembling further reduces NCRPS, NMAE, and NRMSE by 7.40%, 7.00%, and 13.70% relative to single-seed training. A fixed-checkpoint test-block diagnostic further shows limited sensitivity at approximately weekly and three-day decomposition cadences, but a material degradation at a one-day cadence. The reported metrics should therefore be interpreted as offline best-case results rather than as performance under strictly causal real-time deployment. Full article

Low-frequency alternating magnetic field (LF-AMF) was applied to liquid fermentation of Pleurotus citrinopileatus for the production of extracellular polysaccharides (EPS). Two types of EPS (POL1 and POL2) were secreted by P. citrinopileatus under normal fermentation conditions, while only one type of EPS (POL3) was produced under LF-AMF-assisted fermentation. The study demonstrated that LF-AMF-assisted fermentation altered the monosaccharide composition, molar ratios of component monosaccharides, and molecular weight distribution of EPS. LF-AMF enhanced the flocculation activity of EPS in a concentration-dependent and dosage-specific manner. Transcriptomic analysis revealed a total of 32,413 differentially expressed genes (DEGs) (|log2(fold-change)| ≥ 1, p < 0.05) between P. citrinopileatus under LF-AMF-assisted fermentation and normal fermentation. Of those, 5818 genes were up-regulated and 26,595 genes were down-regulated. The DEGs were enriched in metabolic pathways and biosynthesis of secondary metabolite. Genes involved in glycolysis and gluconeogenesis, such as hexokinase, 6-phosphofructokinase, fructose-1,6-phosphate aldolase, glyceraldehyde 3-phosphate dehydrogenase and glucose-1,6-diphosphatase were up-regulated. Additionally, genes in the tricarboxylic acid (TCA) cycle, including citrate synthase, isocitrate dehydrogenase and α-ketoglutarate dehydrogenase were also up-regulated. These findings suggest that LF-AMF-induced transcriptional alterations in glycolysis may modulate the metabolic supply of precursors for EPS biosynthesis, thereby affecting the biosynthetic process and altering the compositional characteristics of EPS. Full article

Background/Objectives: Large-scale dysfunction in the default mode (DMN), salience (SN), and central executive (CEN) networks characterises conditions affecting affective, cognitive, and autonomic regulation. Chronic low back pain (CLBP) shows hyperactive salience signalling, disrupted DMN processing, and impaired executive regulation. Chiropractic adjustments modulate cortical excitability, yet whether these extend to oscillatory reorganisation is unknown. This exploratory secondary analysis aimed to determine whether chiropractic care is associated with frequency- and network-specific changes in source-localised EEG connectivity within and between the DMN, SN, and CEN in adults with CLBP. Methods: Seventy-six adults with CLBP were randomised to chiropractic plus usual care (n = 38) or usual care alone (n = 38). EEG was recorded during resting-state and SEP paradigms at baseline, post-intervention, and four weeks. Source activity was reconstructed with sLORETA and PLI computed across theta, alpha, beta, and gamma bands. For each condition, Fisher-z network-mean PLI was analysed in separate network-by-band linear mixed-effects models with Group, Session, and their interaction as fixed effects and a random intercept for a unique participant identifier; ROI-level changes were examined with cluster-based permutation tests, with inference at the connected-component level. Results: Resting-state alpha-band connectivity within the default mode network was higher in the chiropractic group both immediately after care and at four-week follow-up (both $q<0.001$), alongside additional frequency- and network-specific effects. Region-level analyses identified a distributed alpha-band network spanning most triple-network regions, in which resting-state connectivity increased in the chiropractic group after care ($p_{FWE}=0.003$; Holm-adjusted $p=0.042$). For the somatosensory evoked recordings, no network-level interaction survived multiple-comparison correction; the distributed connectivity changes identified in exploratory region-level analyses are therefore considered preliminary. Conclusions: Chiropractic adjustments are associated with frequency-specific changes in resting-state connectivity within the DMN, SN, and CEN. These findings are hypothesis-generating and require confirmation in adequately powered, pre-registered trials before they can be interpreted as a neurophysiological basis for improvements in pain, mood, fatigue, sleep, or quality of life. Full article

This paper addresses the challenge of maintaining low current stress and high efficiency in dual-active-bridge (DAB) microinverters, where the voltage conversion ratio and instantaneous transferred power vary continuously over the line-frequency cycle. A mode-switching, four-degree-of-freedom, variable-frequency modulation strategy with analytical parameter calculation is proposed. Four representative low-current-stress operating modes are selected for the $G<1$ and $G>1$ regions. Under unity-power-factor and sinusoidal grid-current-tracking constraints, analytical switching-frequency expressions are derived for each mode, enabling coordinated control of the primary-side duty ratio, secondary-side duty ratio, external phase-shift ratio, and switching frequency without iterative online optimization. Duty-ratio limits, switching-frequency bounds, ZVS commutation-current requirements, and an SPS-based hysteresis transition near $G=1$ are incorporated. A 500 W experimental prototype was built for validation. The proposed strategy achieved a peak efficiency of 97.2% at 300 W and an efficiency of 96.5% with a grid-current THD of 2.8% at 500 W. Compared with a fixed-frequency minimum-current-stress TPS strategy, the measured peak leakage-inductor current at 500 W was reduced from 8.23 A to 7.42 A. The results validate the proposed modulation method under the reported experimental conditions. Full article

With the rapid development of renewable energy, pumped storage power plants have taken on critical functions such as frequency regulation and grid stabilization. Consequently, higher demands are placed on their core component—the pump-turbine—requiring further improvements in efficiency, extended service life, and reduced cavitation to ensure reliable and stable operation. Tip leakage flow (TLF) is a complex three-dimensional flow structure in pump turbines, as well as in other turbomachinery. In particular, it generates tip leakage vortex (TLV), which leads to severe damage of pump turbines in pumped storage power plants, such as dramatic efficiency decreases. It originates from the clearance between the blade tip and the casing. The pressure difference between the two sides of the blade drives fluid from the pressure side through the tip gap into the suction side. The process produces a distinct shear layer, leakage jet, and secondary vortex structures. In turbomachinery, performance degradation and structural failure often arise from unsteady flow features. One critical case is vortex breakdown (VB) caused by the TLV. This paper reviews unsteady mechanisms linked to vortex breakdown, including Kelvin-Helmholtz (KH) instability, cavitation, and, finally, the paper discusses geometric modulation to improve system efficiency and reduce cavitation. These factors act both as signals and as triggers of instability. KH structures, vortex breakdown, and cavitation modes together define the instability of tip leakage flows. Geometric and boundary conditions serve as tuning knobs for system sensitivity. Full article

To investigate the influence of fin–wall subcooling regulation on moist-air condensation dehumidification, this study numerically investigates the dehumidification performance and energy response of a thermoelectric cooling system under three subcooling control strategies: gradient subcooling, frequency-modulated subcooling, and amplitude-modulated subcooling. Under strictly identical gas-phase parameters and geometric conditions, the moisture removal rate per unit area, the friction-mass-transfer factor, and the moisture-removal energy efficiency are adopted as evaluation indicators. The results show that gradient subcooling exerts a pronounced non-monotonic influence on dehumidification performance, with an optimal subcooling range around 32–33 K. Further increases in subcooling lead to reduced dehumidification performance accompanied by significantly increased energy-related indicators, indicating a transition toward a high-energy, low-benefit operating regime. Compared with gradient subcooling, frequency-modulated subcooling provides a more favorable balance between dehumidification performance and energy efficiency under relatively high subcooling conditions, demonstrating a clear frequency–subcooling coupling effect. In contrast, amplitude-modulated subcooling plays only a secondary role and shows limited influence on both dehumidification performance and energy-related indicators within the investigated parameter range. Full article

Geosynchronous spaceborne–airborne frequency-modulated continuous-wave bistatic synthetic aperture radar (GEO SA FMCW BiSAR) offers cost-effective and persistent target monitoring. However, both the maneuvers of the receiver during the signal propagation delay and the continuous movements of the radar platforms within the sweep complicate the received echo signal. These factors invalidate the “stop-and-go” assumption, which presumes constant-velocity motion. This paper proposes an echo model that simultaneously considers intra-pulse motion and accelerated motion of the high-maneuvering receiver. The introduction of receiver acceleration leads to nonlinear range terms in the bistatic range history, which will degrade the focusing performance if not properly compensated. Since the acceleration term is a small second-order quantity relative to the time delay, it is approximated by segmenting the aperture and applying the “stop-and-go” assumption within each sub-aperture. After dechirp, the two-dimensional (2-D) spectrum for imaging is derived by applying the principle of stationary phase and determining the azimuth stationary phase point via series reversion. Finally, imaging is achieved by azimuth compression, range cell migration correction, and secondary range compression. Simulation results demonstrate that the proposed algorithm achieves well-focused images while maintaining computational efficiency. Full article

The increasing integration of wind power reduces the equivalent inertia of power systems, leading to lower frequency nadirs and higher rate of change of frequency following disturbances. In Type-4 wind turbine systems, conventional maximum power point tracking (MPPT) may counteract the additional inertial power command during frequency support and cause secondary frequency dips during rotor-speed recovery. To address these issues, this paper proposes a virtual-inertia rate-of-change-of-frequency (VI-RoCoF) frequency-modulated Andronov-Hopf oscillator (AHO)-based adaptive inertia enhancement method together with an adaptive MPPT coordination strategy. The proposed method constructs a frequency-support demand from frequency deviation and VI-filtered RoCoF and embeds it into the instantaneous angular-frequency evolution of the AHO. Different from a conventional linear virtual-inertia controller that directly converts frequency-deviation and RoCoF signals into an algebraic power command, the proposed method realizes the additional support through a bounded limit-cycle frequency-forming process, thereby preserving phase continuity and nonlinear amplitude self-regulation during frequency modulation. Meanwhile, the adaptive MPPT strategy adjusts the power reference in stages to suppress the counteractive effect of conventional MPPT on inertial support and to ensure a smooth transition back to maximum power point tracking. Theoretical analysis shows that the proposed modulation maintains the limit-cycle stability of the AHO under bounded control constraints while improving the equivalent inertia and damping characteristics of the system. Simulation results, including both averaged-model and switching-level SPS simulations, demonstrate that, compared with conventional AHO-based, fixed-inertia AHO-based, and linear VI-RoCoF benchmark schemes without AHO dynamics, the proposed AHO-MPPT coordinated control strategy increases the frequency nadir, reduces the peak RoCoF, improves recovery-stage frequency dynamics, mitigates secondary frequency dips, maintains bounded AHO internal variables, and preserves DC-link voltage stability. Full article

High-frequency link inverters (HFLI) inherently suffer from voltage ringing, and the issue becomes more severe under non-unity power factor loads. Although active clamping circuits can effectively suppress the voltage ringing, they cause severe distortion in the output voltage and current waveforms under such loads. To address this problem, this paper proposes an improved modulation strategy with leakage energy feedback for active-clamped high-frequency link inverters (ACHFLI). In the proposed strategy, two secondary-side MOSFETs achieve zero-current switching (ZCS) turn-off, while the other two MOSFETs operate at low frequency throughout the entire line cycle. By feeding the leakage inductance energy back to the primary side, the voltage balance of the clamping capacitor can be better maintained under non-unity power factor loads, thereby mitigating the waveform distortion in the output voltage and current during the intervals when their polarities are opposite. A prototype with 48 V_in input, 110 V_o output, and 300 W rated power was built to verify the proposed strategy. Experimental results show that the modulation strategy alleviates the waveform distortion when the voltage and current have opposite polarities, and the total harmonic distortion (THD) of the output voltage is reduced by a maximum of 2.74%. Full article

In multi-coil, multi-load magnetically coupled resonant wireless power transfer (MCR–WPT) systems, the non-negligible cross-coupling among multiple resonators, including the transmitter (Tx), receiver 1 (Rx1), and receiver 2 (Rx2), introduces complex frequency-splitting behavior through the Tx–Rx1, Tx–Rx2, and Rx1–Rx2 coupling paths, severely constraining transmission efficiency and operational stability. In practical multi-receiver WPT applications, receiver-side cross-coupling is often unavoidable and may shift the maximum-power and maximum-efficiency points away from the designed resonant frequency. Clarifying this mechanism is therefore important for coil arrangement, impedance matching, and stable multi-load power delivery. This paper establishes an equivalent circuit model to derive analytical expressions for input impedance, load power, and efficiency. Based on this framework, the formation mechanism of frequency splitting under concurrent coupling paths is systematically investigated. The results indicate that dominant coupling paths dictate the positions and magnitudes of primary split peaks, while cross-coupling between receivers induces local modal reconfiguration and energy redistribution, leading to secondary or minor characteristic peaks. Both simulation and experimental results demonstrate that the coupling coefficient primarily governs the frequency-splitting trajectory, whereas load resistance predominantly modulates peak amplitudes. For $k=0.520$, the split-frequency peaks in the two-coil benchmark occur at $64.6 \mathrm{kHz}$ and $103.8 \mathrm{kHz}$, showing good agreement with the calculated modal frequencies. In the tri-coil dual-load system, pronounced power peaks around $63 \mathrm{kHz}$ and $112 \mathrm{kHz}$ further confirm the shift of the maximum-power transfer points under asymmetric coupling and loading conditions. Furthermore, under strong-coupling conditions, the maximum power transfer point shifts from the nominal resonant frequency toward the system’s inherent modal frequencies. This study elucidates the evolution of frequency splitting in tri-coil dual-load systems, providing a theoretical foundation for parameter optimization in multi-node WPT networks. Full article

The Four-Switch Buck-Boost (FSBB) converter has been widely used in airborne secondary power systems in recent years because of its excellent wide voltage regulation capability, its soft-switching characteristics and the fact that its polarity of input and output voltages are the same. However, when the FSBB converter adopts the quadrilateral modulation strategy to realize Zero-Voltage Switching (ZVS), its negative current, inductance parameters, and several time state variables all affect the efficiency of the converter. Aiming at the above problems, this paper proposes a fixed frequency control strategy for the sub-peak current, which reduces the number of sampling circuits and can calculate the control variables in real time by sampling only the input voltage and output voltage. Finally, a 500 W experimental prototype with a switching frequency of 200 kHz is built to verify the proposed control strategy. The experimental results show that the FSBB converter achieves a peak efficiency of 97.2% and operates stably under a wide input voltage range. Full article

Automatic modulation classification (AMC) is a critical enabler of cognitive radio (CR) systems, allowing secondary users to identify primary user modulation schemes and adapt transmission parameters in real time. Traditional AMC approaches, based on likelihood functions or hand-crafted features, suffer from degraded performance under low signal-to-noise ratio (SNR) conditions and realistic channel impairments. In this paper, we propose MS-SENet (Multi-Scale Squeeze–Excitation Network), a novel deep-learning architecture that integrates multi-scale convolutional feature extraction, squeeze-and-excitation channel attention, residual learning, bidirectional long short-term memory (BiLSTM) temporal modelling, and global attention pooling into a unified framework for robust AMC. The multi-scale convolution module employs parallel branches with kernel sizes of 3, 5, and 7 to capture both fine-grained phase transitions and coarse envelope patterns from raw in-phase/quadrature (I/Q) signal samples. Squeeze–excitation residual blocks perform channel-wise feature recalibration, enabling the network to emphasize informative feature maps while suppressing less relevant ones. A bidirectional LSTM layer models temporal dependencies across the signal sequence, and a global attention pooling mechanism performs weighted temporal aggregation prior to classification. We present a comprehensive taxonomy of deep-learning architectures for AMC organised along five axes—input representation, feature extraction, temporal modelling, regularization strategy, and architectural complexity—and conduct a rigorous comparative evaluation against ten baseline architectures on a RadioML-style synthetic dataset (110,000 samples, 11 modulation classes, and 20 SNR levels from −20 to +18 dB). The experimental results demonstrate that MS-SENet achieves a mean classification accuracy of 87.9% at SNR ≥ 0 dB (the average of the medium and high SNR regime averages: 86.06% for 0 ≤ SNR < 10 dB and 89.68% for SNR ≥ 10 dB) while maintaining a compact footprint of approximately 406 K parameters, making it suitable for deployment on resource-constrained edge devices. We further analyze the robustness of the proposed architecture to multipath fading, carrier frequency offset, and sample rate offset, confirming its resilience under practical operating conditions. MS-SENet is an architecture designed for automatic modulation classification of I/Q signals and is not related to the homonymous architecture for speech emotion recognition. Full article

Negative air ions (NAIs) are key ecological indicators of atmospheric cleanliness and forest ecosystem service functions, particularly in the context of forest wellness and ecotourism. However, long-term, high-frequency observations of NAIs across broad spatial scales remain scarce, limiting our understanding of its regional spatiotemporal dynamics and environmental controls. Here, we present a six-year (2018–2023) continuous, hourly monitoring dataset of NAI concentrations from 60 fixed forest sites across Zhejiang Province, a typical subtropical humid region in southeastern China. The provincial mean NAI concentration over the study period was 1672 ions·cm⁻³, with a pronounced “high around the periphery, low in the center” spatial pattern, with the mountainous southwestern areas consistently showing the highest concentrations and the central Jinqu Basin the lowest. On diurnal scales, NAIs exhibited a bimodal pattern with primary peaks at 7:00 and secondary peaks at 16:00, rather than a simple daytime–nighttime dichotomy. Seasonal dynamics showed significantly higher NAI in summer than in autumn and winter; however, the summer–winter difference was only ~25%, much smaller than the ratios reported for temperate regions. Interannually, NAI concentrations increased from 2018 to 2023 (average annual increase of 158 ions·cm⁻³), peaking during the 2020–2022 period, when anthropogenic emissions were substantially reduced. Using linear mixed-effects models, we identified relative humidity as the dominant positive driver of NAI variability, followed by wind speed as a negative modulator, and precipitation playing a minor role. These findings reveal the multi-scale spatiotemporal dynamics of NAIs in subtropical forests and underscore the overriding control of humidity over ion persistence. Our study provides a robust regional benchmark for background NAI levels in humid subtropical climates and offers direct scientific support for forest-based health resource planning and air quality assessment. Full article

Objectives: Karting imposes high neuromuscular demands on the forearm during dynamic steering, gripping and braking. This study examined whether a single high-velocity, low-amplitude (HVLA) manipulation of the elbow acutely modified surface EMG_RMS amplitude and EMG median frequency responses during standardized isometric forearm testing after simulated karting load, rather than EMG activity during dynamic driving itself. Methods: In this randomized, sham-controlled, within-subject trial, 15 drivers completed a single-session within-participant protocol in which one upper limb was randomly allocated to receive elbow HVLA manipulation (manipulated limb) and the contralateral limb received a standardized sham procedure (sham limb) involving therapist contact and low-grade oscillatory movement without end-range pre-tension or thrust. Drivers completed two 8 min simulated races separated by the allocated manual procedure. Surface electromyography (EMG) from four forearm muscles was collected outside the karting task during standardized laboratory-based isometric forearm contractions at baseline, after race 1, post-intervention, and after race 2. EMG was not recorded during real-time steering, braking, vibration exposure or competitive driving. The extensor carpi radialis (ECR) was specified as the principal muscle of interest because the HVLA technique pre-tensioned the common extensor origin and radial wrist extensors. The primary outcome was ECR mean EMG_RMS amplitude, expressed in µV, across the four measurement time points; the primary statistical test was the condition × time interaction. ECR maximal EMG_RMS amplitude and ECR median frequency were treated as secondary outcomes, whereas ECU, FCR, and FCU outcomes were treated as exploratory anatomical specificity outcomes. Mixed-model ANOVAs compared maximal and mean EMG amplitudes and median frequency between manipulated and sham limbs, treating limb condition and time as repeated within-participant factors. Results: For the primary outcome, ECR mean EMG_RMS amplitude showed a main effect of condition (p = 0.023) and a condition × time interaction (p < 0.001). As a secondary amplitude outcome, ECR maximal EMG_RMS amplitude showed a main effect of time (p = 0.009) and a condition × time interaction (p < 0.001), with higher post-manipulation values in the manipulated limb. No consistent limb-condition effects were found for the other muscles, and EMG median frequency showed only modest time-related changes (p = 0.031) without between-condition differences. Conclusions: A single-elbow manipulation produced short-lived, muscle-specific increases in ECR activation after simulated racing, whereas broader neuromuscular changes were not evident. These findings indicate only transient modulation of ECR surface EMG amplitude in a small sample of screened karting drivers and do not demonstrate improved recovery, neuromuscular efficiency, sport performance, or injury prevention. Because EMG was assessed during standardized isometric contractions rather than during dynamic steering, braking, vibration exposure or competitive racing, the findings should not be interpreted as direct evidence of altered neuromuscular behaviour during actual kart driving. Larger studies including force, performance, clinical, fatigue-specific and dynamic driving EMG outcomes are required. Full article