Search Results (38)

This study presents the design, real-time implementation, and full-scale experimental validation of a rule-based Energy Management Strategy (EMS) for a dual-stack Fuel Cell Hybrid Electric Vehicle (FCHEV) developed on a Jeep Wrangler platform. Unlike previous studies, predominantly focused on simulation-based analysis or single-stack architectures, this work provides comprehensive vehicle-level experimental validation of a deterministic real-time EMS applied to a dual fuel cell system in an SUV-class vehicle. The control algorithm, deployed on a National Instruments CompactRIO embedded controller, ensures deterministic real-time energy distribution and stable hybrid operation under dynamic load conditions. Simulation analysis conducted over eight consecutive WLTC cycles shows that both fuel cell stacks operate predominantly within their optimal efficiency range (25–35 kW), achieving an average DC efficiency of 68% and a hydrogen consumption of 1.35 kg/100 km under idealized conditions. Experimental validation on the Wrangler FCHEV demonstrator yields a hydrogen consumption of 1.67 kg/100 km, corresponding to 1.03 kg/100 km·m² after aerodynamic normalization (Cd·A = 1.624 m²), reflecting real-world operating constraints. The proposed EMS promotes fuel-cell durability by reducing current cycling amplitude and maintaining operation within high-efficiency regions for the majority of the driving cycle. By combining deterministic real-time embedded control with vehicle-level experimental validation, this work strengthens the link between EMS design and practical deployment and provides a scalable reference framework for future hydrogen powertrain control systems. Full article

Rydberg atoms are neutral atoms excited to high principal quantum number states, which endows them with exaggerated properties such as large electric dipole moments, long lifetimes, and extreme sensitivity to external electromagnetic fields. These characteristics form the foundation of Rydberg atom-based sensors, an emerging class of quantum devices capable of optically detecting electric fields across frequencies from DC to the terahertz regime. Rydberg-based electrometry operates through both Autler–Townes (AT) splitting of resonant Rydberg transitions and Stark-shift measurements for high-frequency or far-detuned fields, enabling broadband field sensing from DC to the THz regime. Using ladder-type electromagnetically induced transparency (EIT) and AT splitting, these sensors enable non-invasive, SI-traceable measurements of field amplitude, frequency, phase, and polarization. Recent developments have demonstrated broadband electric field probes, voltage calibration standards, and compact RF receivers based on thermal vapor cells and integrated photonic architectures. Furthermore, innovations in multi-photon EIT, superheterodyne readout, and multi wave mixing have expanded the dynamic range and bandwidth of Rydberg-based electrometry. Despite challenges related to environmental perturbations, linewidth broadening, and laser stabilization, ongoing advances in atomic control, hybrid photonic integration, and EIT-based readout promise scalable, chip-compatible sensors. This review summarizes the physical principles, experimental progress, and emerging applications of Rydberg atom-based sensing, emphasizing their potential for next generation quantum metrology, wireless communication, and precision field mapping. Full article

Computational analysis using PSpice has become an indispensable tool for evaluating power electronics circuits, as it allows accurate simulation of transient effects, ripple, and component dynamics, enabling reliable assessment of complex topologies before physical implementation. In single-phase systems, electrolytic components are commonly used due to their high energy density, which helps mitigate low-frequency ripple caused by power oscillations between the DC and AC sides. However, these components have a limited lifespan, which compromises the system’s long-term reliability. This work proposes and evaluates the Stacked Switched Capacitor (SSC) topology as a power decoupling technique, implemented within a 200 W Cuk converter. The proposed SSC design enables a substantial reduction in required capacitance, replacing a conventional 600 μF capacitor with only three 36 μF capacitors, while maintaining voltage stability and output power performance. Simulation results show a high efficiency of 94% and a DC-link energy of 0.992 J, confirming the SSC’s ability to effectively mitigate voltage ripple at twice the grid angular frequency (2ω, rad/s) without compromising system durability. Comparative analysis with conventional decoupling strategies demonstrates that the SSC topology offers a compact, efficient, and reliable alternative, reducing the number of required passive components and switching devices. These results provide a strong basis for further exploration of SSC-based designs in space- and cost-constrained single-phase DC-AC applications. Full article

Neuromorphic circuits emulate the brain’s massively parallel, energy-efficient, and robust information processing by reproducing the behavior of neurons and synapses in dense networks. Memristive technologies have emerged as key enablers of such systems, offering compact and low-power implementations. In particular, locally active memristors (LAMs), with their ability to amplify small perturbations within a locally active domain to generate action potential-like responses, provide powerful building blocks for neuromorphic circuits and offer new perspectives on the mechanisms underlying neuronal firing dynamics. This paper introduces a novel second-order locally active memristor (LAM) governed by two coupled state variables, enabling richer nonlinear dynamics compared to conventional first-order devices. Even when the capacitances controlling the states are equal, the device retains two independent memory states, which broaden the design space for hysteresis tuning and allow flexible modulation of the current–voltage response. The second-order LAM is then integrated into a FitzHugh–Nagumo neuron circuit. The proposed circuit exhibits oscillatory firing behavior under specific parameter regimes and is further investigated under both DC and AC external stimulation. A comprehensive analysis of its equilibrium points is provided, followed by bifurcation diagrams and Lyapunov exponent spectra for key system parameters, revealing distinct regions of periodic, chaotic, and quasi-periodic dynamics. Representative time-domain patterns corresponding to these regimes are also presented, highlighting the circuit’s ability to reproduce a rich variety of neuronal firing behaviors. Finally, two unknown system parameters are estimated using the Aquila Optimization algorithm, with a cost function based on the system’s return map. Simulation results confirm the algorithm’s efficiency in parameter estimation. Full article

This research explores a phase-shift-based discontinuous PWM method used for 24 V battery-powered onboard micro inverters, which are critical for thermally limited applications like micromachines, where efficient heat dissipation and compact size are paramount. Discontinuous pulse width modulation (DPWM) reduces switching losses by clamping the phase voltage to the DC bus in order to improve inverter efficiency. Due to the change in power factor at different operating points from motors or the inductor load, the use of only one DPWM method cannot achieve the optimal efficiency of a three-phase voltage source inverter (3ph-VSI). This paper proposes a generalized DPWM method with a continuously adjustable phase shift angle, which extends the six traditional DPWM methods to any type. According to different power factors, the proposed DPWM method is divided into five power factor angle intervals, namely [−90°, −60°], [−60°, −30°], [−30°, 30°], [30°, 60°], and [60°, 90°], and automatically adjusts the phase shift angle to the optimal-efficiency DPWM mode. The power factor is calculated by means of the Synchronous Reference Frame Phase-Locked Loop (SRF-PLL) method. The switching losses and harmonic characteristics of the proposed DPWM are analyzed, and finally, a 24 V onboard 3ph-VSI experimental platform is built. The experimental results show that the efficiency of DPWM methods can be improved by 3–6% and the switching loss can be reduced by 40–50% under different power factors. At the same time, the dynamic performance of the proposed algorithm with a transition state is verified. This method is particularly suitable for miniaturized inverters where efficiency and thermal management are critical. Full article

This work presents a low-power photoplethysmography (PPG) readout integrated circuit (IC) that achieves a wide dynamic range (DR) through the direct integration of a voltage-controlled oscillator (VCO)-based quantizer into the photodiode driver. Conventional PPG readout circuits rely on either transimpedance amplifier (TIA) or light-to-digital converter (LDC) topologies, both of which require auxiliary DC suppression loops. These additional loops not only raise power consumption but also limit the achievable DR. The proposed design eliminates the need for such circuits by embedding a linear regulator with a mirroring scale calibrator and a time-domain quantizer. The quantizer provides first-order noise shaping, enabling accurate extraction of the AC PPG signal while the regulator directly handles the large DC current component. Post-layout simulations show that the proposed readout achieves a signal-to-noise-and-distortion ratio (SNDR) of 40.0 dB at 10 µA DC current while consuming only 0.80 µW from a 2.5 V supply. The circuit demonstrates excellent stability across process–voltage–temperature (PVT) corners and maintains high accuracy over a wide DC current range. These features, combined with a compact silicon area of 0.725 mm² using TSMC 250 nm bipolar–CMOS–DMOS (BCD) process, make the proposed IC an attractive candidate for next-generation wearable and biomedical sensing platforms. Full article

The transition toward more electric aircraft (MEA) and all-electric aircraft (AEA) has driven the adoption of high-voltage DC (HVDC) electrical architectures to meet increasing power demands while reducing weight and enhancing overall efficiency. However, HVDC systems introduce new challenges, particularly concerning insulation reliability and the detection of in-flight series arc faults. This paper presents the design and evaluation of a capacitive sensor specifically developed to detect series arc faults in HVDC electrical systems for aerospace applications. A model of the sensor is proposed and validated through both simulations and experimental measurements using a step response test. The results show excellent agreement between the model and the physical setup. After validating the capacitive coupling value and its response to high-frequency signals, series arcs were generated in the laboratory to evaluate the sensor’s performance under realistic operating conditions, which involve different signal dynamics. The results are highly satisfactory and confirm the feasibility of using capacitive sensing for early arc detection, particularly aligned with the stringent requirements of more electric aircraft (MEA) and all-electric aircraft (AEA). The proposed sensor thus enables non-intrusive detection of series arc faults in compact, lightweight, and safety-critical environments. Full article

This article presents a hybrid fault diagnosis framework for DC–DC converters in photovoltaic (PV) systems, combining digital twin (DT) modelling and detection with machine learning anomaly classification. The proposed method addresses both hardware faults such as open and short circuits in insulated-gate bipolar transistors (IGBTs) and diodes and sensor-level false data injection attacks (FDIAs). A five-dimensional DT architecture is employed, where a virtual entity implemented using FMI-compliant FMUs interacts with a real-time emulated physical plant. Fault detection is performed by comparing the real-time system behaviour with DT predictions, using dynamic thresholds based on power, voltage, and current sensors errors. Once a discrepancy is flagged, a second step classifier processes normalized time-series windows to identify the specific fault type. Synthetic training data are generated using emulation models under normal and faulty conditions, and feature vectors are constructed using a compact, interpretable set of statistical and spectral descriptors. The model was validated using OPAL-RT Hardware in the Loop emulations. The results show high classification accuracy, robustness to environmental fluctuations, and transferability across system configurations. The framework also demonstrates compatibility with low-cost deployment hardware, confirming its practical applicability for fault diagnosis in real-world PV systems. Full article

This paper focuses on improvement effects on soil foundations under dynamic compaction (DC). Firstly, a confocal ellipsoidal densification model (CEDM) composed of a heavy compacted zone (HCZ) and a weak compacted zone (WCZ) was proposed to describe the subarea characteristic of an improvement range. Next, based on a confocal assumption of HCZ and WCZ ellipses, a mass balance equation considering changes in soil dry density in different compacted zones was established for solving the ellipsoidal parameters. Then, a designed laboratory test was conducted and a two-dimensional (2D) finite element model (FEM) established. The simulated crater depth and dynamic stress agreed well with testing results, confirming that the established FEM could be used for investigating the DC process. Finally, the applicability of the solution procedure for the proposed CEDM was verified. The predicted HCZ and WCZ were in close agreement with the simulated results, indicating that the proposed CEDM could be used for estimating the soil improvement range. With increases in tamping times, the HCZ ellipse moved down in the vertical direction without volumetric expansion, while the WCZ ellipse expanded along the depth and lateral directions. These findings may offer some guidelines for research into improvement effects on soil foundation under DC. Full article

This study aims to evaluate the accuracy of different dynamic compaction (DC) load equivalent conversion methods in DC vibration calculations. It also investigates the effect of vibration isolation treatments on the vibration reduction performance of loess foundations, with the goal of optimizing vibration control during DC construction. Five classical methods were used to convert the DC loads into time-dependent surface loads, which were subsequently fed into Plaxis’s dynamic multiplier table for the numerical implementation of DC tests. By comparing the numerical simulation results with in situ monitoring data from a loess site, the accuracy of the five DC load equivalent conversion methods was evaluated. The momentum theorem method was identified as the most precise for both vibration velocity and settlement. Subsequently, the momentum theorem method was utilized to investigate the influence of depth and distance of vibration isolation trench, as well as the properties of vibration isolation materials on vibration reduction effect. It is indicated that the optimal depth for the vibration isolation trench of the loess site is 2 m, beyond which the improvement in vibration reduction effects is not notable. The excavation distance of the vibration isolation trench should be set as close as possible to the boundary of the construction site to achieve the best vibration reduction effect. As for the properties of vibration isolation materials, it is shown that the unit weight and damping ratio of the filling material have a significant effect on the vibration reduction effect, while the influence of the shear strength of the filling material is negligible. Besides the vibrating reduction influence of filling materials, utilizing spring dampers has a better vibration reduction effect. Increasing the stiffness of the spring dampers and reducing their spacing can significantly enhance the vibration reduction effect. In practical engineering applications, it is essential to consider both the effects and economic costs to select the optimal vibration reduction treatment and its parameters. This study provides a scientific basis for vibration control during DC construction, contributing to ensuring construction safety and efficiency while minimizing the impact on the surrounding environment. Full article

The quality inspection of potato seed tubers is pivotal for their effective segregation and a critical step in the cultivation process of potatoes. Given the dearth of research on intelligent tuber-cutting machinery in China, particularly concerning the identification of bud eyes and defect detection, this study has developed a multi-target recognition approach for potato seed tubers utilizing deep learning techniques. By refining the YOLOv5s algorithm, a novel, lightweight model termed DCS-YOLOv5s has been introduced for the simultaneous identification of tuber buds and defects. This study initiates with data augmentation of the seed tuber images obtained via the image acquisition system, employing strategies such as translation, noise injection, luminance modulation, cropping, mirroring, and the Cutout technique to amplify the dataset and fortify the model’s resilience. Subsequently, the original YOLOv5s model undergoes a series of enhancements, including the substitution of the conventional convolutional modules in the backbone network with the depth-wise separable convolution DP_Conv module to curtail the model’s parameter count and computational load; the replacement of the original C3 module’s Bottleneck with the GhostBottleneck to render the model more compact; and the integration of the SimAM attention mechanism module to augment the model’s proficiency in capturing features of potato tuber buds and defects, culminating in the DCS-YOLOv5s lightweight model. The research findings indicate that the DCS-YOLOv5s model outperforms the YOLOv5s model in detection precision and velocity, exhibiting superior detection efficacy and model compactness. The model’s detection metrics, including Precision, Recall, and mean Average Precision at Intersection over Union thresholds of 0.5 (mAP1) and 0.75 (mAP2), have improved to 95.8%, 93.2%, 97.1%, and 66.2%, respectively, signifying increments of 4.2%, 5.7%, 5.4%, and 9.8%. The detection velocity has also been augmented by 12.07%, achieving a rate of 65 FPS. The DCS-YOLOv5s target detection model, by attaining model compactness, has substantially heightened the detection precision, presenting a beneficial reference for dynamic sample target detection in the context of potato-cutting machinery. Full article

Benefitting from a large bandwidth and compact configuration, a time-domain pulse-shaping (TPS) system provides possibilities for generating broadband radio frequency (RF) arbitrary waveforms based on the Fourier transform relationship between the input–output waveform pair. However, limited by the relatively low sampling rate and bit resolution of an electronic arbitrary-waveform generator (EAWG), the diversity and fidelity of the output waveform as well as its reconfiguration rate are constrained. To remove the EAWG’s limitation and realize dynamic real-time reconfiguration of RF waveforms, we propose and demonstrate a novel approach of RF arbitrary-waveform generation based on an improved TPS system with an integrated dual parallel Mach–Zehnder modulator (DPMZM) and multi-tone inputs. By appropriately adjusting the DC bias voltages of DPMZM and the power values, as well as the center frequencies of the multi-tone inputs, any desired RF arbitrary waveform can be generated and reconfigured in real time. Proof-of-concept experiments on the generation of different user-defined waveforms with a sampling rate up to 27 GSa/s have been successfully carried out. Furthermore, the impact of modulation modes and higher-order dispersion on waveform fidelity is also discussed in detail. Full article

Dynamic compaction (DC) represents a cost-effective method for reinforcing subgrade and is particularly suited to treating large-scale building subgrade. Nevertheless, the effect of DC reinforcement on high groundwater level (HGL) subgrade remains uncertain due to the lack of clarity surrounding the energy transfer mechanism of DC in HGL subgrade. In this paper, an outdoor model test of HGL subgrade was conducted based on the DC method. The temporal evolution of the internal transverse and vertical dynamic stresses in soil under different water levels, energy levels, and tamper weight conditions was monitored, and the DC mechanism of HGL subgrade was described from the perspectives of the dynamic stress waveform, peak development, and attenuation. On this basis, a novel methodology for assessing the extent of subgrade reinforcement through the utilization of impulses was put forth, thereby facilitating a more precise evaluation. The results showed that the HGL is obstructive in DC energy transfer. The peak dynamic stress, depth of impact and maximum impulse per unit area were markedly diminished when tamping the water surface. The study results also recommend that construction could expand the application range of the DC method and provide engineering suggestions for the selection of construction parameters and subsequent building construction. Full article

Dynamic compaction is a method of ground reinforcement that uses the huge impact energy of a free-falling hammer to compact the soil. This study presents a DC method for strengthening coral reef foundations in the reclamation area of remote sea islands. Pilot tests were performed to obtain the design parameters before official DC operation. The standard penetration test (SPT), shallow plate-load test (PLT), and deformation investigation were conducted in two improvement regions (A₁ and A₂) with varying tamping energies. During the deformation test, the depth of the tamping crater for the first two points’ tamping and the third full tamping was observed at two distinct sites. The allowable ground bearing capacity at two disparate field sites was at least 360 kPa. The reinforcement depths were 3.5 and 3.2 m in the A₁ and A₂ zones, respectively. The DC process was numerically analyzed by the two-dimensional particle flow code, PFC2D. It indicated that the reinforcement effect and effective reinforcement depth were consistent with the field data. The coral sand particles at the bottom of the crater were primarily broken down in the initial stage, and the particle-crushing zone gradually developed toward both sides of the crater. The force chain developed similarly at the three tamping energies (800, 1500, and 2000 kJ), and the impact stress wave propagated along the sand particles primarily in the vertical direction. Full article

The cruise industry is obliged by economic and environmental initiatives to pursue fuel-efficient solutions and lower ship exhaust emissions. The medium voltage DC (MVDC) distribution with intelligent power management has become a concept for next-generation onboard power systems as its energy-saving feature is to eliminate the frequency constraint and simultaneously optimize engine loads and speed in response to load variations. The incentive for this transition lies on one hand in the fuel efficiency consideration and the reduction of power losses from serial conversion stages. On the other hand, the DC-based technology has been conceived as high-power density design, thus significantly increasing the payload. This study investigates such potential benefits focusing exclusively on large cruise vessels. A highly representative model of the integrated power platform that incorporates all dynamic interactions from the ship hull and essential machinery typically installed on board cruise ships is proposed. The power management strategy also takes account of actual sea conditions and real-time operation requirements. The simulation results demonstrate that the optimization-based MVDC system is able to maximize the opportunity of search agents in finding optimum fuel efficiency areas throughout the scenario time. An analysis of the system structure weight and space reduction of the MVDC architecture is also performed through the utilization of more compact electrical distribution devices and very high power-dense combustion turbines. Full article