Search Results (850)

Gallium nitride high electron mobility transistors (GaN HEMTs), characterized by their extremely high switching speeds and superior high-frequency performance, have demonstrated significant advantages, and gained extensive applications in fields such as aerospace and high-power-density power supplies. However, their unique internal architecture renders these devices highly sensitive to circuit parasitic parameters. Conventional circuit design methodologies often induce severe issues such as overshoot and high-frequency oscillations, which significantly constrain the realization of their high-frequency performance. To solve this problem, this paper investigates the nonlinear dynamic behavior of GaN HEMTs during switching transients by establishing an equivalent impedance model. Based on this model, a detailed analysis is implemented to elucidate the mechanism by which RC Snubber circuits influence the system’s resonance frequency and the amplitude at the resonant frequency. Through this analysis, an optimal RC Snubber circuit parameter is derived, enabling effective suppression of high-frequency oscillations during the switching transient of GaN HEMT. Experimental results demonstrate that the proposed design achieves a maximum reduction of 40% in voltage overshoot, shortens the ringing time to one-twentieth of the original value, and suppresses noise by 20 dB in the high-frequency range of 20 MHz to 30 MHz, thereby significantly enhancing the stability and reliability of circuit operation. Additionally, considering the heat dissipation requirements in high power density scenarios, this work optimizes the layout of devices, and heat sinks to maintain operational temperatures within safe limits, further mitigating the impact of parasitic parameters on overall system performance. Full article

In order to solve the problems of mass transfer polarization spatiotemporal distribution variations, uncontrollable regulation error, and accelerated capacity decay caused by ion crossover in high-power vanadium liquid flow batteries (VFBs), a three-dimensional battery model with a flow-type flow field based on the three-dimensional transient COMSOL Multiphysics^® 6.1 numerical modeling method was developed in this study. The model combines the ion transmembrane migration equation with the mass transfer polarization theory, constructs an objective function to quantify the regulation error, and is validated by multifluid-field structural simulations. The results indicate the following: (1) Ion crossover induces a 3–5% electrolyte concentration deviation and a current density distribution bias reaching 11%; (2) The intensity of mass transfer polarization exhibits a linear increase with the flow rate difference between the positive and negative electrodes; (3) Ion crossover significantly degrades system performance, causing Coulombic efficiency (CE) and Energy efficiency (EE) to decrease by 1.1% and 1.5%, respectively. This research demonstrates that unlike conventional flow field optimization, our strategy quantifies the regulation error by directly compensating for the ΔQ caused by ion crossing, and further regulation minimizes the effect, providing a theoretical basis for mass transfer intensification and capacity recovery in flow batteries. Full article

This paper proposes an enhanced Model Predictive Direct Speed Control (MPDSC) framework for Permanent Magnet Synchronous Motor (PMSM) drives, integrating duty ratio optimization and load torque disturbance compensation to significantly improve both transient and steady-state performance. Traditional finite-control-set MPC strategies, which apply a single voltage vector per sampling interval, often suffer from steady-state ripples, elevated total harmonic distortion (THD), and high computational complexity due to exhaustive switching evaluations. The proposed approach addresses these limitations through a novel dual-stage cost function structure: the first cost function optimizes dynamic response via predictive control of speed error, while the second adaptively minimizes torque ripple and harmonic distortion by adjusting the active–zero voltage vector duty ratio without the need for manual weight tuning. Robustness against time-varying disturbances is further enhanced by integrating a real-time load torque observer into the control loop. The scheme is validated through both MATLAB/Simulink R2020a simulations and real-time experimental testing on a dSPACE 1202 rapid control prototyping platform across small- and large-scale PMSM configurations. Experimental results confirm that the proposed controller achieves a transient speed deviation of just 0.004%, a steady-state ripple of 0.01 rpm, and torque ripple as low as 0.0124 Nm, with THD reduced to approximately 5.5%. The duty ratio-based predictive modulation ensures faster settling time, improved current quality, and greater immunity to load torque disturbances compared to recent duty-ratio MPC implementations. These findings highlight the proposed DR-MPDSC as a computationally efficient and experimentally validated solution for next-generation PMSM drive systems in automotive and industrial domains. Full article

Objectives: Retinitis pigmentosa (RP) is commonly initiated by rod photoreceptor degeneration due to genetic mutations, followed by secondary cone loss and progressive blindness. Preserving rod function during the earlier stages of RP is a key therapeutic goal, as rod survival supports cone maintenance and delays vision loss. In this study, we investigated the therapeutic potential of transient knockdown of retinoid-related orphan receptor beta (RORB) using a cell-penetrating asymmetric small interfering RNA (cp-asiRORB) in Rho^P23H mice, a model of autosomal dominant RP. While the role of RORB in the adult retina remains unclear, prior studies of related nuclear receptors suggest potential involvement in proteostasis. Based on this, we hypothesized that persistent RORB expression may influence photoreceptor homeostasis under degenerative stress. Methods: We first optimized the cp-asiRORB design to enhance gene silencing and cellular uptake. In vitro studies were conducted under proteotoxic stress. In vivo studies involved intravitreal administration of cp-asiRORB in Rho^P23H mice. Furthermore, single-cell RNA sequencing of rod photoreceptors was performed. Results: In vitro studies demonstrated that RORB knockdown improved cell viability, reduced apoptosis, and diminished aggresome formation under proteotoxic stress. Intravitreal administration of cp-asiRORB in Rho^P23H mice effectively reduced RORB expression in the retina, leading to improved photoreceptor survival and preserved visual function. Single-cell RNA sequencing revealed upregulation of proteasomal subunit genes in cp-asiRORB-treated eyes, indicating enhanced proteostasis. Conclusions: Together, these results demonstrate that transient suppression of RORB mitigates proteotoxic stress and slows RP progression, highlighting a novel RNAi-based therapeutic strategy for retinal degeneration. Full article

This article presents a gear selection methodology for electric vehicle powertrains employing two identical Permanent Magnet Synchronous Machines (PMSMs) arranged in a twin-drive configuration. Both machines are coupled through a shared output shaft and operate with coordinated torque–speed characteristics, enabling efficient utilization of the available gear stages. The proposed approach establishes a control-oriented drivetrain framework that incorporates mechanical dynamics together with real-time thermal states and loss mechanisms. Unlike conventional strategies, which rely mainly on static or speed-based shifting rules, the method integrates detailed thermal and electromagnetic loss modeling directly into the gear-shifting logic. By accounting for the dynamic thermal behavior of PMSMs under variable load conditions, the strategy aims to reduce cumulative drivetrain losses, including electromagnetic, thermal, and mechanical, while maintaining high efficiency. The methodology is implemented in a MATLAB/Simulink R2024a and LabVIEW 2024Q2 co-simulation environment, where thermal feedback and instantaneous efficiency metrics dynamically guide gear selection. Simulation results demonstrate measurable improvements in energy utilization, particularly under transient operating conditions. The resulting efficiency maps are broader and flatter, as the motors’ operating points are continuously shifted toward zones of optimal performance through adaptive gear ratio control. The novelty of this work lies in combining real-time loss modeling, thermal feedback, and coordinated gear management in a twin-motor system, validated through experimentally motivated efficiency maps. The findings highlight a scalable and dynamic control framework suitable for advanced electric vehicle architectures, supporting intelligent efficiency-oriented drivetrain strategies that enhance sustainability, thermal management, and system performance across diverse operating conditions. Full article

The integration of multiple renewable and storage units in electric vehicle (EV) hybrid energy systems presents significant challenges in stability, dynamic response, and disturbance rejection, limitations often encountered with conventional sliding mode control (SMC) and super-twisting SMC (STSMC) schemes. This paper proposes a condition-based integral terminal super-twisting sliding mode control (CBITSTSMC) strategy, with gains optimally tuned using an improved gray wolf optimization (I-GWO) algorithm, for coordinated control of a multi-source DC–DC converter system comprising photovoltaic (PV) arrays, fuel cells (FCs), lithium-ion batteries, and supercapacitors. The CBITSTSMC ensures finite-time convergence, reduces chattering, and dynamically adapts to operating conditions, thereby achieving superior performance. Compared to SMC and STSMC, the proposed controller delivers substantial reductions in steady-state error, overshoot, and undershoot, while improving rise time and settling time by up to 50%. Transient stability and disturbance rejection are significantly enhanced across all subsystems. Controller-in-the-loop (CIL) validation on a Delfino C2000 platform confirms the real-time feasibility and robustness of the approach. These results establish the CBITSTSMC as a highly effective solution for next-generation EV hybrid energy management systems, enabling precise power-sharing, improved stability, and enhanced renewable energy utilization. Full article

In deep-sea oil and gas development scenarios, deep-sea dual-channel connectors often face the risk of seal failure due to internal and external temperature difference loads. To address this issue, this paper systematically establishes equivalent heat transfer models for the key parts of the connector based on the third-type boundary condition. On this basis, the quantitative correlation between the equivalent thermal conductivity, composite heat transfer coefficient and temperature of each part is explored. Using the finite element numerical simulation method, the transient temperature field of the connector under three working conditions (heating, cooling and temperature shock) is simulated and analyzed, revealing the temperature distribution characteristics and temperature change trends of the maximum temperature difference of each key component of the connector; combined with thermal–structural coupling simulation, the temperature field is converted into static load, to determine the behavior of the contact stress on the sealing surface under different temperature–pressure coupling working conditions; in addition, by placing the test prototype in a high-low temperature cycle chamber, the seal performance tests under pressurized and non-pressurized working conditions are carried out to verify the reliable sealing performance of the connector under variable temperature conditions. The results of this paper provide comprehensive theoretical support and an experimental basis for the thermodynamic optimization design of deep-sea connectors and the improvement of the reliability of the sealing system. Full article

The aviation wet clutch, as an indispensable component in helicopters, is particularly vulnerable to performance deterioration due to temperature rises, especially in high-power-density and high-torque conditions. Consequently, a comprehensive thermal-fluid-dynamic model, coupled with a dynamic model considering the spline friction and split spring and a thermal model considering the heat transfer parameters in friction pair gaps, was proposed in this work. The effects of operating parameters on the transient thermal behaviors of friction discs were investigated. A rise in rotation speed from 2000 rpm to 2400 rpm facilitates a 10.1% increase in the maximum temperature of the friction discs. An increase in control oil pressure from 1.5 MPa to 1.9 MPa rises the maximum temperature of the friction disc by 19.4%. Moreover, increased lubrication oil flow not only depresses the maximum temperature of the friction disc by 14.5% but also significantly narrows the temperature gradient by 16.7% and improves the temperature field uniformity. Therefore, reasonably increasing lubricant oil flow and decreasing control oil pressure can effectively reduce temperature rises and improve the temperature field uniformity. These results contribute to designing and developing optimal control strategies to enhance the comprehensive performance of helicopter transmission. Full article

Traditional noise reduction methods often struggle to balance noise suppression with the preservation of transient features in acceleration signals, especially when dealing with high-speed transient data. This study proposes a novel noise reduction method combining ensemble empirical mode decomposition (EEMD), sample entropy (SE), and improved wavelet threshold denoising (IWTD) to address the issue. The method utilizes EEMD to decompose the signal into intrinsic mode functions (IMFs) and a residual term. By setting an SE threshold (SE = 0.3), it effectively differentiates noise-dominated components from those containing significant transient features. IWTD is then applied to the noise-dominated components, and the processed components are reconstructed to yield the denoised signal. A baseline signal is generated in the lab, and noise is added to create the test set. The results show that this method achieves optimal noise reduction performance. Its effectiveness is validated through the output signal-to-noise ratio, root mean square error, and correlation coefficient. Overall, this method enhances noise reduction performance while preserving transient features. The method has been validated using real multi-layer penetration acceleration signals, supporting subsequent penetration layer identification and inversion analysis of the penetration process. Full article

Purpose: We evaluated the feasibility of individualized sodium bicarbonate (NaHCO₃) supplementation and its physiological effects on simulated artistic swimming duet performance, including blood buffering responses, perceived exertion, gastrointestinal (GI) tolerance, and performance scores. Methods: Seventeen (n = 17) elite adolescent female artistic swimmers completed an initial trial to determine individual time-to-peak blood bicarbonate concentration (Part 1). Subsequently, a subset (n = 7) completed a randomized, double-blind, crossover intervention (Part 2), performing competition duet routines (4 min) after ingesting either 0.3 g/kg NaHCO₃ or a placebo timed to their individual alkalosis peak. Blood gas and lactate samples were taken pre- and post-performance. Performance was scored by blinded FINA adjudicators. GI discomfort was assessed before and after each routine. Results: Peak blood bicarbonate occurred at 52 ± 9 min post-ingestion, with a mean increase of 6.7 ± 1.8 mmol/L (g = 5.03). In Part 2 (n = 7), NaHCO₃ significantly elevated pre- and post-performance pH (7.46 ± 0.02 vs. 7.37 ± 0.01; 7.34 ± 0.02 vs. 7.26 ± 0.03), HCO₃⁻ (29.5 ± 0.9 vs. 22.4 ± 0.4 mmol/L; 21.5 ± 1.2 vs. 15.7 ± 1.5 mmol/L), and base excess (5.9 ± 0.6 vs. −2.9 ± 0.5 mmol/L; −4.3 ± 0.8 vs. −10.3 ± 1.1 mmol/L) compared to the placebo (all p < 0.05, g = 3.99–14.93). Post-performance lactate was higher (9.3 ± 1.0 vs. 8.4 ± 0.9 mmol/L, g = 0.89), while rating of perceived exertion (RPE) was lower (12.9 ± 0.7 vs. 14.4 ± 0.7, p < 0.05, g = −2.14). Propulsion improved (6.66 ± 0.16 vs. 6.52 ± 0.20, g = 0.85), with no change in execution. Mild gastrointestinal symptoms were transiently elevated with NaHCO₃. Conclusions: Individualized NaHCO₃ dosing is a feasible and effective ergogenic strategy for artistic swimmers, enhancing systemic alkalosis and perceptual tolerance while preserving technical execution. These findings support the sport-specific integration of NaHCO₃ to optimize anaerobic performance elements in high-level artistic swimming. Full article

In the research of triboelectric nanogenerators (TENGs), most attention has been paid to material modification, structural design, and power management. Little study has been performed on the transient process of TENGs, although the capacitance characteristics of TENGs are well known. In this work, the transient process of contact-mode TENGs was studied by the infinite-plate model and verified by experimental tests. The results showed that TENGs exhibited a much higher output in the transient process than that in the steady state. Within the transient process, the transfer charge gradually grew to a maximum value, while the output current and power decreased. A formula to calculate the duration of the transient process was derived by Fourier expansion. This work also demonstrated an interesting transformation process of the Q-V curve in the transient process. Furthermore, the transient phenomenon was verified clearly in a contact-mode TENG sample fabricated by copper and polytetrafluoroethylene (PTFE) films through experimental tests. These results are useful for performance optimization of TENGs in applications. Full article

A novel long-lasting luminescent composite material based on the (Ca,Sr)-Al-O system was synthesized using a solution combustion method. (Ca,Sr)₃Al₂O₆ is the primary phase, with SrAl₂O₄ as a controllable secondary phase. Compared to conventional single-phase SrAl₂O₄ phosphors, the introduction of a calcium-rich hexaaluminate matrix creates additional defects and a specific trap distribution at the composite interface, significantly improving carrier storage and release efficiency. Eu²⁺ + Nd³⁺ synergistic doping enables precise control of the trap depth and number. Under 365 nm excitation, Eu²⁺ emission is located at ~515 nm, with Nd³⁺ acting as an effective trap center. Under optimal firing conditions at 700 °C (Eu²⁺ = 0.02, Nd³⁺ = 0.003), the afterglow lifetime exceeds 30 s. Furthermore, The (Ca,Sr)₃Al₂O₆ host stabilizes the lattice and optimizes defect states, while synergizing with the SrAl₂O₄ secondary phase to improve the afterglow performance. This composite phosphor exhibits excellent dual-mode anti-counterfeiting properties: long-lasting green emission under 365 nm excitation and transient blue-violet emission under 254 nm excitation. Based on this, a screen-printing ink was prepared using the phosphor and ethanol + PVB, enabling high-resolution QR code printing. Pattern recognition and code verification can be performed both in the UV on and off states, demonstrating its great potential in high-security anti-counterfeiting applications. Compared to traditional single-phase SrAl₂O₄ systems, this study for the first time constructed a composite trap engineering of the (Ca,Sr)₃Al₂O₆ primary phase and the SrAl₂O₄ secondary phase, achieving the integration of dual-mode anti-counterfeiting functionality with a high-resolution QR code fluorescent ink. Full article

Cities need photovoltaic (PV) systems to meet climate-neutral goals, yet dense urban forms and variable weather limit their output. This review synthesizes how machine learning (ML) models capture both static factors (orientation, roof, and façade geometry) and dynamic drivers (irradiance, transient shading, and meteorology) to predict and optimize urban PV performance. Following PRISMA 2020, we screened 111 records and analyzed 61 peer-reviewed studies (2020–2025), eight Horizon-Europe projects, as well as market reports. Deep learning models—mainly artificial and convolutional neural networks—typically reduce the mean absolute error by 10–30% (median ≈ 15%) compared with physical or empirical baselines, while random forests support transparent feature ranking. Short-term irradiance variability and local shading are the dominant dynamic drivers; roof shape and façade tilt lead the static set. Industry evidence aligns with these findings: ML-enabled inverters and module-level power electronics increase the measured annual yields by about 3–15%. A compact meta-analysis shows a pooled correlation of r ≈ 0.966 (R² ≈ 0.933; 95% CI 0.961–0.970) and a pooled log error ratio of −0.16 (≈15% relative error reduction), with moderate heterogeneity. Key gaps remain, such as limited data from equatorial megacities, sparse techno-economic or life-cycle metrics, and few validations under heavy soiling. We call for open datasets from multiple cities and climates, and for on-device ML (Tiny Machine Learning) with uncertainty reporting to support bankable, city-scale PV deployment.” Full article

This review paper deals with Triply Periodic Minimal Surfaces (TPMS) and lattice structures as a new generation of heat exchangers. Especially, their manufacturing is becoming feasible with technological progress. While some intricate structures are fabricated, challenges persist concerning manufacturing limitations, cost-effectiveness, and performance under transient operating conditions. Studies reported that these complex geometries, such as diamond, gyroid, and hexagonal lattices, outperform traditional finned and porous materials in thermal management, particularly under forced and turbulent convection regimes. However, TPMS necessitates the optimization of geometric parameters such as cell size, porosity, and topology stretching. The complex geometries enhance uniform heat exchange and reduce thermal boundary layers. Moreover, the integration of high thermal conductivity materials (e.g., aluminum and silver) and advanced coolants (including nanofluids and ethylene glycol mixtures) further improves performance. However, the drawback of complex geometries, confirmed by both numerical and experimental investigations, is the critical trade-off between heat transfer performance and pressure drop. The potential of TPMS-based heatsinks transpires as a trend for next-generation thermal management systems, besides identifying key directions for future research, including design optimization, Multiphysics modeling, and practical implementation. Full article

A newly developed hybrid maximum power point tracker (MPPT) utilizes a modified simulated annealing (SA) algorithm in conjunction with an adaptive hill climbing (HC) technique to optimize the extraction of the maximum power point (MPP) from photovoltaic (PV) systems. This innovative MPPT improves the ability to harvest maximum power from the PV system, particularly under rapidly fluctuating weather conditions and in situations of partial shading. The controller combines the rapid local search abilities of HC with the global optimization advantages of SA, which has been modified to retain and retrieve the maximum power achieved, thus ensuring the extraction of the global maximum. Furthermore, an adaptive HC algorithm is implemented with a variable step size adjustment, which accelerates convergence and reduces steady-state oscillations. Additionally, an offline SA algorithm is utilized to fine-tune the essential parameters of the proposed controller, including the maximum and minimum step sizes for duty cycle adjustments, initial temperature, and cooling rate. Simulations performed in Matlab/Simulink, along with experimental validation using Imperix-Opal-RT, confirm the effectiveness and robustness of the proposed controller. In the scenarios that were tested, the suggested HC–SA reached the global maximum power point (GMPP) of approximately 600 W in about 0.05 s, whereas the traditional HC stabilized at a local maximum close to 450 W, and the fuzzy-logic MPPT attained the GMPP at a slower rate, taking about 0.2 s, with a pronounced transient dip before settling with a small steady-state ripple. These findings emphasize that, under the operating conditions examined, the proposed method reliably demonstrates quicker convergence, enhanced tracking accuracy, and greater robustness compared with the other MPPT techniques. Full article