Search Results (307)

Inverters are widely applied in aviation, distributed power grids, and vehicles, where their health status directly impacts the stable operation of entire systems. Existing health assessment methods suffer from poor real-time performance, require additional measurement circuits, and are prone to misjudgment, while failing to adequately address slow degradation behaviors during inverter operation. To address these challenges, this study proposes an inverter health assessment method based on an improved D-S evidence theory. First, based on the practical requirements of subway auxiliary inverters, 13 key evaluation indicators were selected. Subjective weights were obtained using the Analytic Hierarchy Process (AHP), while objective weights were derived through the Critic method, credibility, and falsity weighting. These were then fused using game theory to obtain composite weights. Next, after data normalization, a ridge-type membership function was employed to describe health state uncertainty. Finally, the improved D-S evidence theory integrates multi-source information to achieve online health status assessment. Experimental validation demonstrates that this method effectively evaluates the impact of IGBT failures, sensor malfunctions, and capacitor–inductor degradation on the inverter. It exhibits strong robustness under DC voltage fluctuations and load variations, enabling real-time output of health scores and grades to provide a reliable basis for maintenance decisions. Full article

The increasing adoption of electric vehicles (EVs) demands highly efficient bidirectional DC–DC converters capable of seamless energy transfer between the grid and vehicle batteries. This paper introduces a Fixed-Frequency Dual-Active-Bridge (DAB) resonant converter featuring four degrees of freedom, achieved through a combination of triple phase-shift (TPS) modulation and a current-controlled variable inductor (VI). The proposed control strategy aims to minimize conduction and switching losses by simultaneously managing reactive power, RMS current, and soft-switching conditions across wide variations in voltage and power. Unlike conventional phase-shift or variable-frequency modulations, the fixed-frequency operation maintains full zero-voltage switching (ZVS) for the two bridges, and zero-current switching (ZCS) in the bridge that is receiving energy, enhancing overall system reliability and control simplicity. The proposed converter is validated through simulations and experimental results from a SiC MOSFET-based 14 kW prototype operating at 122 kHz, demonstrating peak efficiencies above 97% under both charging and discharging modes. The experimental results confirm that the proposed DAB topology and modulation scheme significantly improve efficiency and controllability, making it a promising solution for next-generation on-board chargers and vehicle-to-grid (V2G) applications. Full article

Multi-agent systems are widely used in modern power systems, but they face challenges such as low data utilization, stringent triggering conditions, and poor environmental adaptability. This study proposes a multi-agent event-triggered control method based on the Proximal Policy Optimization (PPO) policy gradient algorithm. By maximizing the cumulative reward, the agents are driven to learn adaptive triggering strategies, which reduces communication frequency while ensuring system stability. A multi-agent reinforcement learning model is constructed, and the training results show that both the single-episode reward and the average reward significantly increase with the number of training episodes, thus verifying the effectiveness of the algorithm. Based on Lyapunov stability and LaSalle’s invariance principle, an event-triggering threshold is designed using an exponential decay function. Moreover, the sequential decision-making process under uncertain environments is described using the Markov decision process. In the case study with six agents, the triggering conditions effectively constrain the error growth and ensure system stability. The method is further extended to a 33-node power system, where each node is regarded as an agent to simulate voltage fluctuations under load variations. Compared with periodic sampling control, the event-triggered control exhibits faster convergence speed, higher steady-state accuracy, and stronger anti-interference capability, thus confirming its superiority in complex power systems. Full article

Wire electrical discharge machining (WEDM) is widely used for the precision cutting of difficult-to-machine materials, including nickel-based superalloys. Wire electrode wear, however, remains a practical limitation, because it affects process stability, wire consumption, and machining cost. This work examines the wear behaviour of a gamma-phase Cu₅Zn₈-coated copper-core wire electrode (Elecut X, ø 0.25 mm) during the WEDM of Inconel 718 using direct gravimetric measurement. A 3³ full factorial experiment was carried out with three electrical parameters: pulse-on time (A), pulse-off time (B), and servo reference voltage (Aj). The discharge process was monitored with an oscilloscope so that measurements only started after the programmed pulse-off time had been reached. Electrode wear was evaluated as the mass loss Δm of 4 m wire segments after 5 min cutting intervals on a Charmilles Robofil 310 machine, and factor significance was assessed by analysis of variance (ANOVA). Pulse-on time was the dominant factor, accounting for 88.45% of the total variation in Δm, followed by servo reference voltage and pulse-off time. SEM/EDS examination showed material transfer from the Inconel 718 workpiece to the worn electrode surface, with local nickel content reaching 16.84 wt.% on the frontal face of the most worn sample. The results provide a quantitative basis for reducing wire consumption during the WEDM of Inconel 718 while recognising the trade-off with cutting productivity. Full article

Although compression therapy is widely used to improve wound healing, selecting the appropriate pressure remains a challenge in clinical practice. This work proposes an intelligent patch integrated into a bandage that allows for the simultaneous monitoring of the applied pressure and wound condition using Near-Field Communication (NFC). The proposed patch integrates a force-sensitive resistive sensor to measure pressure and a capacitive sensor to detect wound exudate through capacitance variations. Capacitance is obtained by analyzing the delay in the stepwise response of the sensor, while resistance is measured from the voltage drop across a resistive divider, which is read by a microcontroller’s analog-to-digital converter. The system is powered wirelessly through NFC energy harvesting, triggered by a mobile device that acts as a reader. The NFC module can be moved away after measurement to improve patient comfort or remain integrated into the dressing for periodic monitoring. Experimental results demonstrate pressure measurements up to 140 mmHg and exudate detection up to 200 $\mathsf{\mu }$L, confirming the feasibility of battery-free NFC smart bandages for therapeutic monitoring based on wound compression. Full article

Lithium-ion batteries (LIBs) are widely used in the electric bicycle/vehicle sector, but fire accidents frequently caused by thermal runaway of LIBs have become a severe public concern. From a reverse perspective of safety engineering, investigation of fire accidents based on the historical data recorded by the Battery Management System (BMS) and exploration of the causes of thermal runaway can enhance the safety of LIBs and electric bicycles/vehicles. This study aims to provide support for fire investigation through the analysis of the BMS. By conducting electrical, thermal and mechanical abuse experiments, the variations of the electrothermal parameters involving voltage, current and temperature are examined. The results reveal that these electrothermal parameters exhibit unique time-sequential inter-relationships under each specific abuse mode. A secured relationship can be solidified between the variation features of the electrothermal parameters and the specific cause of thermal runaway, i.e., whether the abuse mode is electrical, thermal or mechanical abuse. Such peculiar time-series variations or inter-relationships can be used for post hoc fire investigation to trace the fire reasons. Based on the findings of this study, a real fire case was analyzed to validate the feasibility of the proposed tracing method by means of BMS analysis. The resultant fire reason confirmed the one given by the authority, thus validating the effectiveness of the fire investigation method. Full article

This work presents a comprehensive analysis of a Palladium (Pd)-gated graphene nanoribbon field-effect transistor (GNRFET) as a high-sensitivity potential hydrogen sensor under idealized conditions, focusing on the structural and environmental control of multimetric sensitivity. Hydrogen adsorption is modeled through pressure-dependent work-function modulation and interface coverage, including competition with oxygen. For hydrogen gas at a pressure of $P_{{\mathrm{H}}_2}={10}^{-6}$ Torr without O₂, the sensor exhibits a maximum threshold voltage sensitivity of about 300 mV, which is reduced to roughly 40 mV under an oxygen partial pressure of 152 Torr, quantifying the impact of background gas on response. Band diagrams, transmission spectra, local density of states, and transfer characteristics are examined over wide ranges of H₂ pressure, temperature, gate length, and nanoribbon width. Sensitivity is evaluated using drain current change, threshold voltage shift, and average subthreshold swing variation. Results showed that the sensitivity based on current is high for ultralow hydrogen pressures, whereas it is low in higher levels of pressure compared to the sensitivity based on subthreshold. Also, uncertainty analysis revealed that the threshold voltage metric remains largely geometry-independent and thus tolerant to fabrication variations. Full article

Direct power control (DPC) is widely recognized for its simplicity and fast dynamic response; however, conventional implementations based on hysteresis comparators suffer from critical limitations, including variable switching frequency and pronounced active power oscillations, which hinder their applicability in renewable and hybrid energy systems. To address these challenges, this study proposes a fractional-order predictive DPC strategy incorporating a fractional-order proportional–integral (FOPI) regulator to enhance dynamic performance and robustness. The proposed method is systematically evaluated against both a conventional proportional–integral-based DPC (PI-DPC) and existing fractional-order DPC approaches under identical operating conditions using MATLAB simulations. The results demonstrate that the proposed controller achieves a stabilized switching frequency while significantly improving DC-link voltage performance. Specifically, the proposed method reduces voltage ripples to 0.027 V compared to 0.094 V and 0.104 V for PI-DPC and FOPI-FOPI-DPC with space vector modulation (SVM), corresponding to improvements of 71.27% and 74.03%, respectively. The overshoot is also reduced to 0.75%, outperforming PI-DPC (1.25%) and FOPI-FOPI-DPC-SVM (1%), with improvements of 40% and 25%. In terms of dynamic response, the proposed approach achieves a fast response time of 0.06 s, representing a 40% improvement over PI-DPC, while maintaining comparable performance with other fractional-order methods. Additionally, the steady-state error is reduced to 0.04 V, achieving improvements of 60% and 50% compared to PI-DPC and FOPI-FOPI-DPC-SVM, respectively. Although the settling time shows marginal variation, the overall system exhibits enhanced stability and robustness. These outcomes highlight the effectiveness of integrating fractional-order control with predictive strategies, offering a robust and practically viable solution for real-world hybrid power systems that integrate renewable generation and energy storage. Full article

This work presents a reliability-oriented design methodology for LC oscillators, focusing on Colpitts configurations implemented by a bipolar transistor. A nonlinear steady-state analytical framework is used as a practical design tool to determine the resonant tank parameters, loop gain conditions, and the dependence of oscillation amplitude on the operating conditions. Based on this analysis, a systematic sizing procedure is developed, in which the LC tank is designed and statistically characterized prior to amplifier and bias selection. The influence of component tolerances, temperature variation, supply voltage deviation, and load changes is quantified through statistical Monte Carlo analysis. To overcome the amplitude instability observed in the classical Colpitts topology, an automatic gain control (AGC) block is introduced that directly regulates the transistor transconductance, eliminating the need for individual amplitude adjustment. The simulation results demonstrate that, while the conventional Colpitts oscillator exhibits output amplitude variations of approximately ±30% under realistic parameter deviations, the proposed AGC-enhanced design limits worst-case amplitude variation to within ±10% using only standard tolerance components. A hardware prototype was developed to experimentally validate the methodology over wide variations in resonant tank parameters, amplifier bias conditions, and external load. The combined analytical, statistical, and experimental results confirm that the proposed approach simplifies the design process, improves robustness, and enables predictable, trimming-free oscillator operation suitable for mass-produced electronic systems. Full article

A dual-mode variable gain amplifier (VGA) with a wide-dynamic-range is proposed in this paper. The VGA is designed in a 0.18 μm CMOS process, and it has a body-driven variable load cell and binary gain array structure to implement both the digitally stepped programmable gain amplifier (PGA) mode and the analog-controlled VGA mode. This design removes additional digital conversion modules when integrated into an automatic gain control (AGC) loop, which simplifies the whole system architecture significantly. The design is also able to address several limitations of conventional VGAs, such as a single control mode, low AGC compatibility, and a narrow gain range. The simulation results after post-layout indicate that at PGA mode, the design has an ultra-wide gain band of −0.03 to 126.9 dB with a constant gain step of 1 dB. And in VGA mode, it allows smooth, continuous gain adjustment over a large range of −25.3 dB to 187.4 dB. The bandwidth of −3 dB is more than 45 MHz in both modes. The whole VGA uses 1.026 mW and has a core size of 0.011 mm². The output 1-dB compression point (OP1dB) was −1.57 dBm at minimum gain in the PGA mode and −4.02 dBm in the VGA mode. Besides, PVT analysis, Monte Carlo simulations and AGC system-level verification are evident enough to prove that the suggested VGA has high immunity to PVT (Process, Voltage, Temperature) variations, stable processes and high practicality in engineering applications. Full article

Underwater explosion bubbles generate intense pressure pulses and high-speed re-entrant jets during their expansion and collapse processes, posing significant threats to ships and submerged structures. In practical engineering, plate-like structures with different orientations are widely encountered; therefore, investigating the influence of boundary orientation on bubble dynamics is of great importance. In this study, underwater electrical explosion experiments were conducted using a capacitor discharge voltage of 300 V, with stand-off distances ranging from 1 mm to 30 mm. Two typical boundary configurations were established, namely a vertical plate and a horizontal plate. High-speed imaging was employed to capture the complete bubble evolution process, while coupled Eulerian–Lagrangian (CEL) simulations were performed to analyze bubble dynamics and structural response. The results indicate that, under the vertical plate condition, the maximum bubble diameter decreases monotonically with increasing stand-off distance, whereas the oscillation period exhibits a non-monotonic variation. At a stand-off distance of 5 mm, the maximum bubble diameter in the vertical plate configuration is 40.3% larger than that in the horizontal plate configuration. The reflected shock wave from the elastic boundary modifies the surrounding pressure field, thereby influencing the evolution of the bubble interface. In the presence of a vertical elastic plate, the bubble exhibits a centroid displacement during the expansion phase, and a re-entrant jet directed toward the boundary forms during collapse. In contrast, under the horizontal elastic plate condition, the bubble maintains a nearly axisymmetric evolution, and the re-entrant jet develops along the vertical direction. As the standoff distance between the plate and the charge center increases, the boundary effect gradually weakens, and the bubble morphology approaches that under free-field conditions. This study provides experimental evidence for understanding bubble–structure interaction (BSI) between underwater explosion bubbles and ship plate structures, and offers valuable insights for blast-resistant design of naval structures and the evaluation of underwater explosion loads. Full article

This paper presents a flipped-voltage-follower low-dropout regulator (FVF-LDO) for power supply rejection enhancement and low-power operation in CMOS transimpedance amplifiers for optical receiver applications. The proposed FVF-LDO ensures high stability and reliable regulation over a wide range of load conditions by employing a flipped-voltage follower for fast local feedback and improved power supply rejection, while a super-source follower enhances the transient response through increased current-driving capability. A bandgap reference with a 3-bit trimming DAC is adopted to compensate process variations and support stable LDO operations, achieving a temperature coefficient of 19.6 ppm/°C over a wide range of −25 °C to 125 °C. The FVF-LDO exhibits a 101 mV undershoot under a 100 µA-to-10 mA load step with a 100 ns edge time. When applied to an optoelectronic inverter-based active-feedback transimpedance amplifier (TIA), the regulated supply improves the power supply rejection ratio (PSRR) from −6 dB to −38.3 dB. The proposed optoelectronic TIA realized in a 180 nm CMOS process achieves 67 dBΩ transimpedance gain, 869 MHz bandwidth, 66 dB dynamic range, 6.68 pA/√Hz input-referred noise current spectral density, and 4.68 mW power consumption from a single 1.8 V supply. The proposed TIA chip occupies a core area of 940 × 162 µm². Full article

With the increasing demand for high speed and high-precision motion control in CNC machine tools, permanent magnet linear synchronous motors (PMLSMs) have been widely adopted in feed drive systems due to their excellent dynamic performance and positioning accuracy. However, existing model predictive current control (MPCC) variants still face challenges regarding high computational overhead and strong dependency on accurate motor parameters, which limit their industrial applicability. To address these issues, this paper proposes an adaptive recursive MPCC for PMLSM drives based on the Cartesian distance minimization principle. An adaptive recursive prediction scheme that is inspired by the feedback structure of recurrent architectures is first introduced. By cyclically utilizing the previously sampled current to predict the next period’s state, the strategy effectively decouples the control law from inductance variations. The dependence on resistance is further mitigated by analyzing the correlation between the ideal current vector and voltage vector deviations. Second, the selection of the optimal voltage vector is transformed into a geometric problem: minimizing the Cartesian distance between the reference voltage and 19 candidate deviations within a proposed virtual voltage vector hexagon. To minimize the computational burden, the vector space is partitioned into eight regions, allowing the optimal candidate to be selected from only two pre-derived deviations. The experimental results demonstrate that the proposed method significantly outperforms existing MPCC benchmarks. Specifically, the execution time is reduced by 63.6%. Under severe parameter mismatch, the current THD is reduced from 14.82% to 6.35%, and the thrust ripple is improved from 12.06 N to 5.25 N, validating its superior robustness and efficiency. Full article

This paper presents an adaptive talkative power (TP) framework that enables simultaneous high-efficiency power transfer and reliable data communication under time-varying load conditions. A high-frequency TP-based bidirectional boost converter employing a SiC-based zero voltage switching–quasi square wave (ZVS-QSW) topology is proposed, incorporating closed-loop online efficiency optimization. Data transmission is realized through adaptive switching-frequency modulation at the transmitter, allowing information encoding while preserving optimal power transfer efficiency. To support reliable data detection under unknown and non-constant load conditions, an adaptive receiver architecture is developed that extracts information from output voltage ripple variations induced by frequency modulation. Owing to the nonlinear and complex nature of the ripple characteristics, a supervised machine-learning-based classification approach is employed for data detection, eliminating the need for prior knowledge of converter parameters and overcoming the limitations of conventional maximum-likelihood detection methods. The proposed system is validated through real-time simulations using a dSPACE MicroLabBox system in conjunction with MATLAB/Simulink R2025b. Simulation results demonstrate power transfer efficiencies approaching 98% while enabling reliable and efficient data transmission across a wide range of operating conditions, including varying conversion ratios and dynamic load variations, thereby confirming the effectiveness and robustness of the proposed TP-based power and data transmission scheme. Full article

Weak alternating electric fields are widely used in neuromodulation techniques such as transcranial alternating current stimulation (tACS), yet the precise biophysical mechanisms underlying neuronal responses remain incompletely understood. Current computational models often neglect the electrical properties of the extracellular microenvironment, limiting their predictive accuracy. Motivated by experimentally observed frequency-dependent modulation of neuronal activity, we developed a two-compartment model of hippocampal CA3 pyramidal neurons in which extracellular resistance is explicitly parameterized and systematically examined as a key factor influencing neuronal response properties under external electric fields. Within a dual-compartment Hodgkin–Huxley framework, the neuron is divided into a “soma–basal dendrite unit” and an “apical dendrite unit,” accounting for voltage polarization induced by external fields. Using phase-locking ratio curves and three-dimensional parameter response surface, we systematically characterized neuronal sensitivity to field parameters and examined how potassium equilibrium potential ($V_K$) and extracellular resistance ($R_{\mathrm{out}}$) modulate these responses. Our results demonstrate that increasing $R_{\mathrm{out}}$ enhances neuronal responsiveness to external fields, while $V_K$ variations primarily regulate intrinsic excitability. These findings provide mechanistic insights into the frequency-dependent modulation of neuronal responses under weak electric fields, consistent with phenomena observed in biological neural systems, and provide a mechanistic and theoretical framework for understanding the joint effects of electric field amplitude and frequency on neuronal sensitivity to weak electric fields, which may help inform future neuromodulation strategies. Full article