Search Results (1,276)

A novel reduced-component multilevel inverter (MLI) topology is presented to overcome the limitations of conventional multilevel inverters, such as high switching losses, complex modulation, and excessive semiconductor usage. The proposed triple-source cross-connected configuration minimizes conduction paths and reduces voltage stress across switching devices to approximately 45% of the total DC-link voltage. A hybrid carrier-less pulse-width modulation (PWM) strategy, derived from the equal-area criterion, was developed to generate switching pulses without the need for carriers or reference signals. Analytical and experimental analyses demonstrated a significant improvement in power quality, achieving a total harmonic distortion (THD) of 4.3%, compared with 8.2% in conventional PWM schemes, while enhancing the conversion efficiency from 91.5% to 95.2%. Simulation and hardware validation in a nine-level prototype confirmed the superior efficiency, low harmonic distortion, and compactness of the proposed inverter, making it well-suited for renewable energy integration, electric vehicles, and medium-power industrial systems. Full article

This study presents the development of a buck–boost converter for application in unmanned guided vehicles (UGVs). The converter was designed with its input connected to a lithium iron phosphate battery pack and its output connected to an inverter. This configuration enabled the inverter, which powered the drive motor, to receive a stable DC voltage, thereby mitigating the effects of battery voltage fluctuations and enhancing the overall system stability. A pulse-width modulation (PWM) controller was employed to regulate the developed buck–boost converter. During the transition from buck mode to buck–boost mode, both power MOSFETs were simultaneously turned on; however, the datasheet of the PWM controller did not provide operational details or characteristic curve analysis for this mode. Therefore, this study derived the relationship between voltage gain and duty cycle ratio for the transition mode. To analyze the input voltage versus duty cycle characteristics, the linear equation was employed. This analytical model was adjusted to meet different converter specifications developed for experimental validation. Furthermore, the external-connect test capacitor method was used to extract the equivalent parasitic inductance and capacitance present in the practical circuit of the buck–boost converter. Based on these parameters, a snubber circuit was designed and connected across the drain–source terminals of the power MOSFETs to suppress voltage spikes occurring at the junctions. Finally, the developed buck–boost converter prototype was installed on an unmanned guided vehicle to convert the power from the lithium battery pack into the input power required by two inverters. A computer host was used to control the motor speed. By measuring the output voltage and current of the buck–boost converter, its electrical functionality and performance specifications were verified. The dimensions of the developed UGV chassis prototype were 40 cm in length, 45 cm in width, and 18.3 cm in height. Full article

With the rapid deployment of artificial intelligence (AI) data centers, demand for optical modules surges—alongside faster upgrades and stricter low-power requirements. However, traditional optical driver integrated circuits (ICs) rely on device-specific customization, which lengthens driver design cycles, delays module deployment, and raises costs, becoming a bottleneck for optical module evolution. To address these issues, this work proposes a unified optical transmitter electronic integrated circuit (EIC) design approach featuring synergistic driver-laser/modulator co-design and a versatile output driver (VOD). The VOD can be configured into three output impedance states (open-drain, differential 50-$\Omega$, or differential 100-$\Omega$), enabling it to drive various optical devices like distributed feedback lasers (DFBs), vertical-cavity surface-emitting lasers (VCSELs), electro-absorption modulated lasers (EMLs), and Mach-Zehnder modulators (MZMs) with a single design, minimizing device-specific customization. Meanwhile, its power consumption is also adjustable to maximize the power efficiency. The proposed design approach demonstrates the potential to address the critical interoperability, cost, and power challenges faced by AI data centers, providing a scalable template for next-generation coherent and 4-level pulse amplitude modulation systems and facilitating rapid deployment. Full article

A sustainable non-lithium battery is proposed, integrated with renewables to cater for the intermittency and differences between daily supply and demand. A room temperature sodium–sulfur (RT Na-S) battery presented in this study offers a promising energy density of 177 Wh/kg of the pouch cell. A framework is introduced for the design of an RT Na-S battery system, alone and combined with a supercapacitor, and its operating schedule for two case studies: (a) a photovoltaic (PV) system for a household and (b) a wind turbine for an industrial site. Daily power supply and demand profiles are included in both cases. In the first design step, the required mass and volume of the battery cells are determined. In the second step, the system architecture is designed, and simulations of the renewable-energy storage system–demand are carried out for four consecutive days. An RT Na-S battery–supercapacitor system is recommended in association with the wind turbine that involves high frequency and high power pulses, where the supercapacitor caters for power exceeding 0.1 C. A standalone RT Na-S battery is recommended for the PV system. The simulations predicted that each storage system covered all the net power and energy demands without any contributions from the grid. Full article

Ytterbium-doped femtosecond fiber lasers are widely used in scientific research, industrial processing, and other fields due to their high quantum efficiency, wide gain bandwidth, and compact structure. This article addresses the problems of low processing efficiency and difficulty in increasing the average power of femtosecond lasers. A high repetition rate fiber chirped pulse amplification system is built, which uses a high repetition rate Figure-9 fiber laser as the seed source and an acousto-optic modulator (AOM) to shape the dense pulse train in the time domain. The main amplification stage uses a large mode field ytterbium-doped fiber to achieve full fiberization of the amplification system, and a volume grating (VBG) is selected as the pulse compressor to make the laser system highly integrated. When the repetition rate is 67.5 MHz, the compressed output laser has an average power of 20.5 W, a pulse width of 447 fs, a pulse train energy of 750 μJ, a spot ellipticity of 0.96, and a beam quality M² better than 1.4 ($M_x^2=1.33$, $M_y^2=1.16$). Full article

The dual-pulse heterodyne demodulation distributed acoustic sensing (HD-DAS) system has superior performance but is fundamentally limited by the short sensing range, which poses a significant obstacle to its application in long-distance monitoring. This paper proposes and experimentally demonstrates a novel binary-tree structure DAS (BTS-DAS) aimed at overcoming this critical limitation. By physically decoupling the long-distance transmission fiber from the final sensing part, this structure effectively expands the system’s remote sensing capability without compromising the high pulse repetition rate for high-performance measurement. We identified modulation instability (MI), rather than stimulated Brillouin scattering (SBS), as the dominant nonlinear noise source in the extended fiber chain. Through careful power management, we established an optimal launch power window. The practical feasibility of the system was verified during on-site testing, where vibrations were successfully detected over a 10 km transmission link with sensing occurring in the 250 m sensing fiber segment, achieving a low background noise of −59.79 dB ref rad/$\sqrt{\mathrm{Hz}}$. This work presents a robust and scalable solution for long-range, high-performance acoustic sensing. Full article

As the primary discharge channel for fault currents, substation grounding grids are crucial for ensuring the safe and stable operation of power systems. Due to its non-destructive and efficient nature, the pulsed eddy current (PEC) method has become a research hotspot in grounding grid detection in recent years. However, during the detection process, the signal is severely interfered with by substation noise, seriously affecting data quality and interpretation accuracy. To address the problem of suppressing both power frequency and random noise, this paper proposes a composite denoising method that combines bipolar cancellation, minimum noise fraction (MNF), and mask-guided self-supervised denoising. First, based on the periodic characteristics of power frequency noise, a bipolar pulse excitation and differential averaging process is designed to effectively filter out power frequency interference. Subsequently, an MNF algorithm is introduced to identify and reconstruct random noise, improving signal purity. Furthermore, a mask-guided self-supervised denoising model is constructed, using a segmentation convolutional neural network to extract signal-noise masks from noisy data, achieving refined suppression of residual noise. Comparative experiments with simulation and actual substation noise data show that the proposed method outperforms existing typical noise reduction algorithms in terms of signal-to-noise ratio improvement and waveform fidelity, significantly improving the availability and interpretation reliability of pulsed eddy current data. Full article

This study presents a pulse generator employing a saturable pulse transformer (SPT) in conjunction with a fast recovery diode, integrated within an all-solid-state pulse-forming network (PFN). The saturation inductance of the SPT serves as a component of the initial LC section of the PFN, thereby contributing to the preservation of output waveform integrity. The secondary energy storage capacitor is charged through the primary circuit and the SPT, subsequently discharging into the load under the regulation of the SPT. An increase in the SPT’s transformation ratio corresponds to a rise in its saturated inductance, which in turn prolongs the pulse rise time. To mitigate this effect, a fast recovery diode is incorporated to sharpen the pulse front. Specifically, upon saturation of the SPT, current reverses through the fast recovery diode, effectively short-circuiting the load. When the inductor current attains a predetermined threshold, the diode reverts to reverse cut-off and rapidly switches off, enabling the PFN to discharge swiftly into the load and generate a high-voltage pulse characterized by a rapid rising edge. Furthermore, augmenting the number of secondary windings on the SPT—each connected to a PFN module—and arranging multiple PFNs in series facilitates an increase in output voltage. Experimental evaluations demonstrated that a three-stage PFN pulse generator attained a peak voltage of −16.9 kV on an 80 Ω matched load, with pulse currents exceeding 200 A while maintaining a 19 ns front edge. These results indicate that the proposed approach is effective for producing high-voltage, narrow pulses with rapid rise times. Additionally, the pulse power generator is capable of delivering repetitive pulses of −16.9 kV at a frequency of 20 kHz in burst mode. Full article

This work presents the development and experimental validation of a low-cost, piezoelectret-based energy harvesting system integrated into a custom insole, as a promising alternative for future self-powered wearable electronics. The design utilizes eight thermoformed Teflon piezoelectrets, strategically positioned in high-impact regions (heel and forefoot), to convert footstep-induced mechanical motion into electrical energy. The sensors, fabricated using Fluorinated Ethylene Propylene (FEP) and Polytetrafluoroethylene (PTFE) layers via thermal pressing and aluminum sputtering, were connected in parallel to enhance signal consistency and robustness. A solenoid-actuated mechanical test rig was developed to simulate human gait under controlled conditions. The system consistently produced voltage pulses with peaks up to 13 V and durations exceeding ms, even under limited-force loading (10 kgf). Signal analysis confirmed repeatable waveform characteristics, and a Delon voltage multiplier enabled partial conversion into usable DC output. While not yet optimized for maximum efficiency, the proposed setup demonstrates the feasibility of using piezoelectrets for energy harvesting. Its simplicity, scalability, and low cost support its potential for future integration in applications such as fitness tracking, health monitoring, and GPS ultimately contributing to the development of autonomous, self-powered smart footwear systems. It is important to emphasize that the present study is a proof-of-concept validated exclusively under controlled laboratory conditions using a mechanical gait simulator. Future work will address real-time insole application tests with human participants. Full article

We present a photoacoustic spectroscopy (PAS)-based method using a laser Doppler vibrometer (LDV) for real-time detection of laser-induced damage (LID) in optical components. By measuring audible frequency surface vibrations, the method enables remote, non-contact, and sensitive detection. Experiments with various dielectric optics (slide glass and single-layer coatings) and pulse durations (7 ns and 360 ps) of an Nd:YAG laser (wavelength of 1064 nm) showed detection accuracy comparable to microscopy. Vibration spectra correlated with natural modes calculated by finite element modeling, and vibrations according to the detecting location were observed. The method remained effective under typical mounting conditions, demonstrating its practical applicability. This PAS-LDV approach offers a promising tool for in situ monitoring of LID in high-power laser systems. Full article

(Bi_0.5Na_0.5)TiO₃-based lead-free ferroelectric ceramics are among the most extensively researched energy storage materials today. In this paper, (1 − x)Bi_0.46Sr_0.06Na_0.5TiO_3−xCaTiO₃ ceramics were synthesized through a solid-phase sintering method by synergistically adjusting CaTiO₃ components after introducing Sr²⁺ at the A-site. The XRD patterns revealed that all samples formed a single perovskite solid solution, with the 111 and 200 peaks shifting to higher levels as the CaTiO₃ increased, indicating a gradual decrease in cell volume. The SEM images exhibited dense crystals without any apparent porosity, which were formed by the different components of the ceramics. Through energy storage, dielectric, and charge–discharge performance tests, it was found that with a 10%mol CaTiO₃ addition, the samples obtained a maximum breakdown field strength of 260 kV/cm and corresponding saturation polarization strength of 32.80 μC/cm² and thereby exhibited a reversible energy storage density valued 3.52 J/cm³. In addition, the dielectric constant varied by less than 10% within the temperature range of 63.7 °C to 132.7 °C and presented good frequency (10–250 Hz) stability at 180 kV/cm. Moreover, the ceramics demonstrated a maximum current density reaching 349.58 A/cm² and a maximum power density of 18.90 MW/cm³ for their charge–discharge performance, all of which makes them suitable for pulse system applications. Full article

The global adoption of solar-powered streetlights has grown significantly, driven by their cost-effectiveness and potential to reduce dependence on fossil fuels associated with conventional street lighting. Battery storage represents a substantial portion of the total capital cost in solar-powered streetlight systems. Therefore, selecting an efficient charge regulator is crucial to protect battery lifespan and reduce energy losses. In this context, the choice of an appropriate charge regulator plays a vital role in enhancing system reliability and overall performance. This study presents a practical approach for evaluating three commercially available 6 A-rated Pulse Width Modulation (PWM) solar charge regulators intended for recharging lead-acid batteries in a proposed 12 V off-grid solar photovoltaic (PV) street lighting system. The regulators were evaluated concurrently in separate circuits, each experiencing similar meteorological conditions, including similar temperature and solar irradiance. The measured data for each regulator were acquired using LabVIEW-based virtual instruments. The performance comparison was conducted using the Linear Regression Algorithm (LRA) to support decision-making. Based on the analysis, the most suitable PWM charge regulator was identified as the one offering the best charging performance due to low internal losses. Hence, solar battery charge regulators with identical load current ratings do not necessarily deliver equivalent charge/discharge performance. Full article

Large-scale lithium-ion energy storage systems (ESSs) are indispensable for renewable energy integration and grid support, yet ensuring long-term reliability under field conditions remains challenging. This study investigates degradation trends in a 50 MW-class ESS deployed on Jeju Island, South Korea, focusing on two indicators: direct current internal resistance (DCIR) and state-of-health (SOH). Annual round-trip (capacity) and hybrid pulse power characterization (HPPC) tests conducted from 2023 to 2025 quantified capacity fade and resistance growth. A polynomial-regression-based temperature compensation was applied—compensating DCIR to 23 °C and SOH to 30 °C—which reduced environmental scatter and clarified year-to-year degradation trends. Beyond mean shifts, intra-bank variability increased over time, indicating rising internal imbalance. A focused case study (Bank 03-01) revealed concurrent SOH decline and DCIR escalation localized near specific racks; spatial maps linked this hotspot to heating, ventilation, and air conditioning (HVAC)-driven airflow asymmetry and episodic fan operation. These findings underscore the importance of combining temperature compensation, variability-based diagnostics, and spatial visualization in field ESS monitoring. The proposed methodology provides practical insights for the early detection of abnormal degradation and supports lifecycle management of utility-scale ESSs under real-world conditions. Full article

Synthetic Aperture Radar (SAR) onboard satellites provides high-resolution Earth imaging independent of weather conditions. SAR data are acquired by an aircraft or satellite and sent to a ground station to be processed. However, for novel applications requiring real-time analysis and decisions, onboard processing is necessary to escape the limited downlink bandwidth and latency. One such application is real-time target recognition, which has emerged as a decisive operation in areas such as defense and surveillance. In recent years, deep learning models have improved the accuracy of target recognition algorithms. However, these are based on optical image processing and are computation and memory expensive, which requires not only processing the SAR pulse data but also optimized models and architectures for efficient deployment in onboard computers. This paper presents a fast and accurate target recognition system directly on raw SAR data using a neural network model. This network receives and processes SAR echo data for fast processing, alleviating the computationally expensive DSP image generation algorithms such as Backprojection and RangeDoppler. Thus, this allows the use of simpler and faster models, while maintaining accuracy. The system was designed, optimized, and tested on low-cost embedded devices with low size, weight, and energy requirements (Khadas VIM3 and Raspberry Pi 5). Results demonstrate that the proposed solution achieves a target classification accuracy for the MSTAR dataset close to 100% in less than 1.5 ms and 5.5 W of power. Full article

Power electronic devices for AC/DC and AC/AC conversion are, nowadays, widely distributed in electrified transportation and industrial applications, which can determine significant deviation in supply voltage waveform from the AC sinusoidal and promote insulation extrinsic aging mechanisms as partial discharges (PDs). PDs are one of the most harmful processes as they are able to cause accelerated extrinsic aging of electrical insulation systems and are the cause of premature failure in electrical asset components. PD phenomenology under pulse width modulated (PWM) voltage waveforms has been dealt with in recent years, also through some IEC/IEEE standards, but less work has been performed on PD harmfulness under AC distorted waveforms containing voltage harmonics and notches. On the other hand, these voltage waveforms can often be present in electrical assets containing conventional loads and power electronics loads/drives, such as for ships or industrial installations. The purpose of this paper is to provide a contribution to this lack of knowledge, focusing on PD sensing and phenomenology. It has been shown that PD patterns can change considerably with respect to those known under sinusoidal AC when harmonic voltages and/or notches are present in the supply waveform. This can impact PD typology identification, which is based on features related to PD pattern-based physics. The adaptation of identification AI algorithms used for AC sinusoidal voltage as well as distorted AC waveforms is discussed in this paper, showing that effective identification of the type of defects generating PD, and thus of their harmfulness, can still be achieved. Full article