Search Results (4,594)

Modular multilevel converters (MMCs) are widely used in power-conversion applications, including distributed energy storage integration, because of their scalability, high efficiency, and reduced harmonic distortion. Integrating battery storage systems into MMC submodules using dual active bridge (DAB) converters provides electrical isolation and reduces voltage stress, harmonics, and common-mode issues. However, voltage fluctuations due to the battery state of charge can compromise the zero-voltage switching (ZVS) operation of a DAB and increase the reactive power circulation, leading to higher losses and reduced system performance. To address these challenges, this study investigated an active control strategy for submodule voltage regulation in an MMC with DAB-based battery integration. Assuming single-phase-shift modulation, two control strategies were evaluated. The first strategy regulated the DAB voltage on one side to match the battery voltage on the other, scaled by the high-frequency transformer turns ratio, which facilitated the ZVS operation and reduced the reactive power. The second strategy optimized this voltage to minimize the total power-conversion losses. The proposed control strategies improved the efficiency, particularly at low power levels, achieving several percentage points of improvement compared to maintaining a constant voltage. Full article

Dynamic wireless charging systems have emerged as a promising solution to extend the driving range of electric vehicles by enabling energy transfer while the vehicle is in motion. However, the segment-based charging lane structure introduces challenges such as pulsation of the output power and the need for precise switching control of the transmitting segments. This paper proposes a position-sensorless control method for managing transmitting lines in a dynamic wireless charging system. The proposed approach uses a segmented charging lane structure combined with two receiving coils and LCC compensation circuits on both the transmitting and receiving sides. Based on theoretical analysis, the study determines the optimal switching positions and signals to reduce the current fluctuation. To validate the proposed method, a dynamic wireless charging system prototype with a power rating of $3kW$ was designed, constructed, and tested in a laboratory environment. The results demonstrate that the proposed position-sensorless control method effectively mitigates power fluctuations and enhances the stability and efficiency of the wireless charging process. Full article

This paper proposes a novel control strategy for a dual-stage grid-connected solar photovoltaic (PV) system designed to ensure reliable and efficient operation under unstable grid conditions. The strategy incorporates a Phase-Locked Loop (PLL)-based positive sequence estimator for accurate detection of grid voltage disturbances, including sags, swells, and fluctuations in solar irradiance. A dynamic DC-link voltage regulation mechanism is employed to minimize converter power losses and enhance the performance of the Voltage Source Converter (VSC) under weak grid scenarios. The control scheme maintains continuous maximum power point tracking (MPPT) and unity power factor (UPF) operation, thereby improving overall grid power quality. The proposed method is validated through comprehensive simulations and real-time hardware implementation using the OPAL-RT OP4510 platform. The results demonstrate compliance with IEEE Standard 519, confirming the effectiveness and robustness of the proposed strategy. Full article

Deep drilling and horizontal wells, as important means of unconventional oil and gas development, face problems with the high energy consumption but low removal efficiency of traditional well washing equipment, the uneven cleaning of horizontal well intervals, and an insufficient degree of automation. This paper proposes a novel hydraulic drive well washing device which consists of two main units. The wellbore cleaning unit comprises a hydraulic drive cutting–flushing module, a well cleaning mode-switching module, and a filter storage module. The unit uses hydraulic and mechanical forces to perform combined cleaning to prevent mud and sand from settling. By controlling the flow direction of the well washing fluid, it can directly switch between normal and reverse washing modes in the downhole area, and at the same time, it can control the working state of corresponding modules. The assembly control unit includes the chain lifting module and the arm assembly module, which can lift and move the device through the chain structure, allow for the rapid assembly of equipment through the use of a mechanical arm, and protect the reliability of equipment through the use of a centering structure. The device converts some of the hydraulic power into mechanical force, effectively improving cleaning and plugging removal efficiency, prolonging the downhole continuous working time of equipment, reducing manual operation requirements, and comprehensively improving cleaning efficiency and energy utilization efficiency. Full article

Real-time wildlife monitoring on edge devices poses significant challenges due to limited power, constrained bandwidth, and unreliable connectivity, especially in remote natural habitats. Conventional object detection systems often transmit redundant data of the same animals detected across multiple consecutive frames as a part of a single event, resulting in increased power consumption and inefficient bandwidth usage. Furthermore, maintaining consistent animal identities in the wild is difficult due to occlusions, variable lighting, and complex environments. In this study, we propose a lightweight hybrid tracking framework built on the YOLOv8m deep neural network, combining motion-based Kalman filtering with Local Binary Pattern (LBP) similarity for appearance-based re-identification using texture and color features. To handle ambiguous cases, we further incorporate Hue-Saturation-Value (HSV) color space similarity. This approach enhances identity consistency across frames while reducing redundant transmissions. The framework is optimized for real-time deployment on edge platforms such as NVIDIA Jetson Orin Nano and Raspberry Pi 5. We evaluate our method against state-of-the-art trackers using event-based metrics such as MOTA, HOTA, and IDF1, with a focus on detected animals occlusion handling, trajectory analysis, and counting during both day and night. Our approach significantly enhances tracking robustness, reduces ID switches, and provides more accurate detection and counting compared to existing methods. When transmitting time-series data and detected frames, it achieves up to 99.87% bandwidth savings and 99.67% power reduction, making it highly suitable for edge-based wildlife monitoring in resource-constrained environments. Full article

Dual-active bridge (DAB) converters have emerged as a preferred topology in electric vehicle charging and energy storage applications, owing to their structurally symmetric configuration and intrinsic galvanic isolation capabilities. However, conventional triple-phase shift (TPS) control strategies face significant challenges in maintaining high efficiency across ultra-wide output voltage and load ranges. To exploit the inherent structural symmetry of the DAB topology, a symmetric optimization strategy based on triple-phase shift (SOS-TPS) is proposed. The method specifically targets the forward buck operating mode, where an optimization framework is established to minimize the root mean square (RMS) current of the inductor, thereby addressing both switching and conduction losses. The formulation explicitly incorporates zero-voltage switching (ZVS) constraints and operating mode conditions. By employing the Karush–Kuhn–Tucker (KKT) conditions in conjunction with the Lagrange multiplier method (LMM), the refined control trajectories corresponding to various power levels are analytically derived, enabling efficient modulation across the entire operating range. In the medium-power region, full-switch ZVS is inherently satisfied. In the low-power operation, full-switch ZVS is achieved by introducing a modulation factor λ, and a selection principle for λ is established. For high-power operation, the strategy transitions to a conventional single-phase shift (SPS) modulation. Furthermore, by exploiting the inherent symmetry of the DAB topology, the proposed method reveals the symmetric property of modulation control. The modulation strategy for the forward boost mode can be efficiently derived through a duty cycle and voltage gain mapping, eliminating the need for re-derivation. To validate the effectiveness of the proposed SOS-TPS strategy, a 2.3 kW experimental prototype was developed. The measured results demonstrate that the method ensures ZVS for all switches under the full load range, supports ultra-wide voltage conversion capability, substantially suppresses RMS current, and achieves a maximum efficiency of 97.3%. Full article

Intelligent monitoring and fault diagnosis of PV grid-connected inverters are crucial for the operation and maintenance of PV power plants. However, due to the significant influence of weather conditions on the operating status of PV inverters, the accuracy of traditional fault diagnosis methods faces challenges. To address the issue of open-circuit faults in power switching devices, this paper proposes a multi-dimensional feature perception network. This network captures multi-scale fault features under complex operating conditions through a multi-dimensional dilated convolution feature enhancement module and extracts non-causal relationships under different conditions using convolutional feature fusion with a Transformer. Experimental results show that the proposed network achieves fault diagnosis accuracies of 97.3% and 96.55% on the inverter dataset and the generalization performance dataset, respectively. Full article

Traffic-related pollutants remain a challenging global issue, with significant policy implications. Within the European Union, Romania has the highest yearly societal cost per capita due to air pollution, which kills 29,000 Romanians every year, whereas the health and economic costs are also significant. In this context, municipal authorities in the country, particularly in high-density areas, should place a strong focus on mitigating air pollution. In particular, the capital city, Bucharest, ranks among the most congested cities in the world while registering the highest pollution index in Romania, with traffic pollution responsible for two-thirds of its air pollution. Consequently, studies that assess and model pollution trends are paramount to inform local policy-making processes and assist pollution-mitigation efforts. In this paper, a generalized additive modeling (GAM) framework is employed to model hourly concentrations of nitrogen dioxide (NO₂), i.e., a relevant traffic-pollution proxy, at a busy urban traffic location in central Bucharest, Romania. All models are developed on a wide, fine-granularity dataset spanning January 2017–December 2022 and include extensive meteorological covariates. Model robustness is assured by switching between the generalized additive model (GAM) framework and the generalized additive mixed model (GAMM) framework when the residual autoregressive process needs to be specifically acknowledged. Results indicate that trend GAMs explain a large amount of the hourly variation in traffic pollution. Furthermore, meteorological factors contribute to increasing the models’ explanation power, with wind direction, relative humidity, and the interaction between wind speed and the atmospheric pressure emerging as important mitigators for NO₂ concentrations in Bucharest. The results of this study can be valuable in assisting local authorities to take proactive measures for traffic pollution control in the capital city of Romania. Full article

This paper presents a stochastic analysis of a two-unit cold standby system incorporating imperfect switching mechanisms. Each unit operates in one of three states: normal, partial failure, or total failure. Employing Markov processes, the study evaluates system reliability by examining the mean time to failure (MTTF) and steady-state availability metrics. Failure and repair times are assumed to follow exponential distributions, while the switching mechanism is modeled as either perfect or imperfect. The results highlight the significant influence of switching reliability on both MTTF and system availability. This analysis is crucial for optimizing the performance of complex systems, such as thermal power plants, where continuous and reliable operation is imperative. The study also aligns with recent research trends emphasizing the integration of preventive maintenance and advanced reliability modeling approaches to enhance overall system resilience. Full article

In advanced Complementary Metal-Oxide-Semiconductor (CMOS) technologies, where diminished feature sizes amplify radiation-induced soft errors, the optimization of fault-tolerant circuit designs requires detailed transistor-level analysis of reliability–performance trade-offs. As a fundamental building block in digital systems and critical data paths, the 2:1 multiplexer, widely used in data-path routing, clock networks, and reconfigurable systems, provides a critical benchmark for assessing radiation-hardened design methodologies. In this context, this work aims to analyze the power consumption, area overhead, and delay of 2:1 multiplexer designs under transient fault conditions, employing the CMOS and Differential Cascode Voltage Switch Logic (DCVSL) logic styles and mitigation strategies. Electrical simulations were conducted using 32 nm high-performance predictive technology, evaluating both the original circuit versions and modified variants incorporating three mitigation strategies: transistor sizing, D-Cells, and C-Elements. Key metrics, including power consumption, delay, area, and radiation robustness, were analyzed. The C-Element and transistor sizing techniques ensure satisfactory robustness for all the circuits analyzed, with a significant impact on delay, power consumption, and area. Although the D-Cell technique alone provides significant improvements, it is not enough to achieve adequate levels of robustness. Full article

Background: Spinal muscular atrophy type 1 (SMA1) is a severe neuromuscular disorder characterized by progressive muscle weakness and atrophy, including the muscles of the oral cavity and esophagus. Eosinophilic esophagitis (EoE), a chronic, allergic disease, presents with eosinophilic infiltration of the esophagus, leading to esophageal dysmotility. Feeding difficulties may occur in both conditions. So far, the coexistence of EoE and SMA1 has not been described; we present the first such case. Case presentation: The patient was a girl with SMA1 diagnosed shortly after birth, treated with nusinersen and onasemnogene abeparvovec, and fed a standard industrial diet through a gastrostomy. In her second year of life, she developed increasing symptoms: distress during feeding, regurgitation, vomiting, and weight loss. She was treated with proton pump inhibitors without clinical improvement. Gastroscopy was performed, revealing superficial epithelial damage with bleeding in the proximal esophagus. Histopathology showed chronic inflammation with up to 150 eosinophils per high-power field, microabscesses, spongiosis, and basal layer hypertrophy. The girl was diagnosed with EoE. Her diet was switched from a standard industrial formula to an amino acid-based formula, which led to marked clinical improvement, the resolution of symptoms, and appropriate weight gain. Conclusions: This case report highlights the challenges of diagnosing EoE in SMA1 patients and emphasizes the need for multidisciplinary approaches and further investigation of allergic manifestations in SMA1 patients. Full article

Under the “dual carbon” goals and rapid clean energy development, power grids face challenges including rapid load growth, uneven power flow distribution, and limited transmission capacity. This paper proposes a novel FACTS device with fault tolerance and switchable topology that maintains power flow control over multiple lines during N-1 faults, enhancing grid safety and economy. The paper establishes a steady-state mathematical model based on additional virtual nodes and provides power flow calculation methods to accurately reflect the device’s control characteristics. An entropy-weighted TOPSIS method was employed to establish a quantitative evaluation system for assessing the grid performance improvement after FACTS device integration. To address interaction issues among multiple flexible devices, an optimization planning model considering th3e coordinated effects of UPFC and VSC-HVDC was constructed. Multi-objective particle swarm optimization obtained Pareto solution sets, combined with the evaluation system, to determine the optimal configuration schemes. Considering wind power uncertainty and fault risks, we propose a system-level coordinated operation strategy. This strategy constructs probabilistic risk indicators and introduces topology switching control constraints. Using particle swarm optimization, it achieves a balance between safety and economic objectives. Simulation results in the Jiangsu power grid scenarios demonstrated significant advantages in enhancing the transmission capacity, optimizing the power flow distribution, and ensuring system security. Full article

With their superior switching speed, GaN high-electron-mobility transistors (HEMTs) enable high power density, reduce energy losses, and increase power efficiency in a wide range of applications, such as power electronics, due to their high breakdown voltage. GaN-HEMT devices are subject to long-term reliability due to the self-heating effect and lattice mismatch between the SiC substrate and the GaN. Depletion-mode GaN HEMTs are utilized for radio frequency applications, and this work investigates three wide-bandgap (WBG) GaN HEMT fixed-frequency oscillators with output buffers. The first GaN-on-SiC HEMT oscillator consists of an HEMT amplifier with an LC feedback network. With the supply voltage of 0.8 V, the single-ended GaN oscillator can generate a signal at 8.85 GHz, and it also supplies output power of 2.4 dBm with a buffer supply of 3.0 V. At 1 MHz frequency offset from the carrier, the phase noise is −124.8 dBc/Hz, and the figure of merit (FOM) of the oscillator is −199.8 dBc/Hz. After the previous study, the hot-carrier stressed RF performance of the GaN oscillator is studied, and the oscillator was subject to a drain supply of 8 V for a stressing step time equal to 30 min and measured at the supply voltage of 0.8 V after the step operation for performance benchmark. Stress study indicates the power oscillator with buffer is a good structure for a reliable structure by operating the oscillator core at low supply and the buffer at high supply. The second balanced oscillator can generate a differential signal. The feedback filter consists of a left-handed transmission-line LC network by cascading three unit cells. At a 1 MHz frequency offset from the carrier of 3.818 GHz, the phase noise is −131.73 dBc/Hz, and the FOM of the 2nd oscillator is −188.4 dBc/Hz. High supply voltage operation shows phase noise degradation. The third GaN cross-coupled VCO uses 8-shaped inductors. The VCO uses a pair of drain inductors to improve the Q-factor of the LC tank, and it uses 8-shaped inductors for magnetic coupling noise suppression. At the VCO-core supply of 1.3 V and high buffer supply, the FOM at 6.397 GHz is −190.09 dBc/Hz. This work enhances the design techniques for reliable GaN HEMT oscillators and knowledge to design high-performance circuits. Full article

This study presents a Variational Autoencoder (VAE)-based framework for the unsupervised mechanical fault diagnosis of high-voltage isolation switches. By analyzing voltage and current signals to compute instantaneous power sequences, the method detects anomalies through reconstruction errors. Experimental results from both laboratory and real-world datasets demonstrate that the VAE model outperforms traditional methods, offering high diagnostic accuracy and robustness without the need for labeled data or manual feature extraction. This approach provides an effective solution for the real-time monitoring and predictive maintenance of high-voltage switchgear. Full article

The stable operation of micromachine systems relies on reliable power management, where DC-DC converters provide energy with high efficiency to extend operational endurance. However, these converters also constitute significant electromagnetic interference (EMI) sources that may interfere with the normal functioning of micro-electromechanical systems. This paper proposes a boost converter utilizing Pulse Width Modulation (PWM) with peak current mode control to address the EMI issues inherent in the switching operation of DC-DC converters. The converter incorporates a Hybrid Spread Spectrum (HSS) technique to effectively mitigate EMI noise. The HSS combines a 1.2 MHz pseudo-random spread spectrum with a 9.4 kHz triangular periodic spread spectrum. At a standard switching frequency of 2 MHz, the spread spectrum range is set to ±7.8%. Simulations conducted using a 0.5 μm Bipolar Complementary Metal-Oxide-Semiconductor Double-diffused Metal-Oxide-Semiconductor (BCD) process demonstrate that the HSS technique reduces EMI around the switching frequency by 12.29 dBμV, while the converter’s efficiency decreases by less than 1%. Full article