Voltage Spikes Research Articles

Low voltage ride through enhancement of a permanent magnet synchronous generator based wind energy conversion system in an islanded microgrid: A dynamic matrix controlled virtual DC machine

In an isolated microgrid, the wind energy conversion system based on direct-drive permanent magnet synchronous generator may experience fluctuations in the DC bus voltage due to wind variations and grid voltage drop, thereby compromising system reliability. To address this issue, the scheme of the supercapacitor energy storage system is proposed. The existing double closed-loop PID control, which cannot provide inertia support, has shortcomings such as difficult parameter setting and slow dynamic response. To solve this problem, the dynamic-matrix-control based predictive control for a virtual DC machine method is proposed. Firstly, the concept of virtual DC machine control is firstly introduced in supercapacitor energy storage system. Secondly, according to the unit step response of virtual DC machine, the prediction model of virtual DC machine is established. Finally, the desired torque increment reference of virtual DC machine is calculated by the dynamic-matrix-control controller to change the input torque reference. Hardware-in-the-loop experiment verifies the effectiveness of the proposed method: Compared with traditional double closed-loop PID control, the maximum voltage fluctuation is reduced by 67.9 % under random wind fluctuation and the inhibition effect on DC voltage surge and plunge when fault occurs in the power grid is increased by 61.4 % and 57.9 %.© 2017 Elsevier Inc. All rights reserved.

Experimental Approach for Reliability Analysis of Medium-Power Zener Diodes under DC Switching Surge Degradation

This study investigated the reliability of Zener diodes subjected to a gradually increasing DC switching surge amplitude with delay internals between surges to avoid thermal degradation from different manufacturers with similar specifications. The analysis involved applying occasional 3 ms direct current (DC) switching surges with a gradual increasing surge voltage, followed by a constant current test to verify device functionality for three different selected manufacturer 5.1 V Zener diodes. This experimental approach was used to identify the maximum surge current that each Zener diode could handle before failing to clamp the surge voltage at the specified Zener reference voltage. Statistical analysis revealed significant differences in the maximum average surge current between different manufacturers. The maximum average surge current findings just before failure were 1.98 A, 3.18 A, and 3.33 A, respectively, and associated 95% confidence interval ranges can be used as a reliable metric to compare Zener diode population reliability against occasional DC switching surges. The findings revealed variations in the DC switching surge current handling capabilities between Zener diodes from different manufacturers with similar electrical specifications. The statistically measured maximum average surge current just before device failure can be considered an effective metric to compare the reliability of Zener diodes against DC switching surge degradation.

Thermal and electric field driven rf breakdown precursor formation on metal surfaces

The phenomenon of electric breakdown poses serious challenges to the design of devices that operate in high electric field environments. Experimental evidence points toward breakdown events that are accompanied by elevated temperatures and dark current spikes, which is attributed to high-asperity nanostructure formation that enhances the local electric field and triggers a runaway process. However, the exact mechanistic origin of such nanostructures under typical macroscopic operational conditions of electric field and magnetic-field-mediated heating remains poorly understood. In this work, we simulate the evolution of a copper surface under the combined action of the electric fields and elevated temperatures. Using a mesoscale curvature-driven surface evolution model, we show how a copper surface can undergo a type of dynamical instability that naturally leads to the formation of sharp asperities in realistic experimental conditions. Exploring the combined effect of fields and temperature rise, we identify the critical regimes that allow for the formation of breakdown precursors. The results show that thermoelastic stresses, while not essential, can significantly lower the critical electric field required for runaway surface instability, which is consistent with experimental observations that thermal effects can increase breakdown rates. Published by the American Physical Society 2024

Interleaved High Voltage Gain DC-DC Converter with Winding-Cross-Coupled Inductors and Voltage Multiplier Cells for Photovoltaic Systems

An interleaved high voltage gain DC-DC converter with winding-cross-coupled inductors (WCCIs) and voltage multiplier cells is proposed for photovoltaic systems. The converter configuration is based on the interleaved boost converter integrating the diode-capacitor clamp circuits, the winding-cross-coupled inductors, and voltage multiplier cells to increase the voltage gain and reduce the semiconductor voltage stresses. The equal current sharing of two phases is achieved with the help of the winding-cross-coupled inductors. The converter achieves high voltage gain while operating at a proper duty ratio. The low-voltage-rated MOSFETs with low on-resistance are available to reduce the conduction losses due to the low switch voltage stress. The leakage energy of the coupled inductors is recycled such that the voltage spikes on the power switches are avoided. The input current ripple is decreased due to the interleaved operation. The operating principle and steady-state analysis of the proposed converter are proposed in detail. The design guidelines of the proposed converter are given. In addition, the closed-loop controlled system of the proposed converter is designed to diminish the effect of the variations in input voltage and load on the output voltage. Finally, the experimental results of a 1000 W converter prototype with 36 V input and 400 V output are given to validate the theoretical analysis and the converter performance.

Synaptic properties of GaOx-based memristor with amorphous GaOx deposited by RF magnetic sputtering

GaOx devices have been extensively explored for applications such as power devices and solar blind detectors, based on their wide bandgap. In this study, we investigated the synaptic properties of the amorphous gallium oxide (a-GaOx)- based memristor with a W/WOx/a-GaOx/ITO structure, in which a-GaOx are deposited by RF magnetic sputtering at ambient temperature. The structure and components of a-GaOx are characterized by XRD, XPS, SEM, and EDS. The electrical test indicates that W/WOx/a-GaOx is ohmic due to the thin WOx layer with a high concentration of oxygen vacancies. Consequently, the synaptic characteristics of the W/WOx/a-GaOx/ITO memristor depend on both the a-GaOx layer itself and the a-GaOx/ITO junction. The fitting results indicate that the a-GaOx/ITO junction is Schottky with unidirectional conductive properties. However, the elevated defect density results in a larger current for the reverse-biased a-GaOx/ITO junction. Moreover, adjusting the thickness of a-GaOx allows the device to achieve almost symmetrical forward and reverse currents. We have successfully observed typical synaptic characteristics in W/WOx/a-GaOx/ITO when stimulated by consecutive spike signals. Clearly, through careful design considerations regarding the structure and parameters, we have realized superior synaptic performance in a-GaOx-based memristors. This achievement shows that amorphous GaOx has great potential applications in neuromorphic computation chips for artificial intelligence or the Internet of Things in the future.

A Partial Active Gate Control for Improvement of a Trade-Off Relation Between Surge Voltage and Efficiency in a Three-Phase Inverter

A Partial Active Gate Control for Improvement of a Trade-Off Relation Between Surge Voltage and Efficiency in a Three-Phase Inverter

Variation of (001) surface structures of strontium titanate single crystals caused by flash event under direct/alternative current electric fields

Flash events, which are electric power spikes occurring under an electric field and temperature above the threshold, can significantly accelerate mass diffusion over short periods of time. This study investigated the surface structure of the (001) surface of strontium titanate single-crystal treated by flash events caused by direct current (DC) and alternating current (AC) electric fields from a viewpoint of surface-related mass diffusion. The surface structuring caused by flash events was significantly different among DC and AC electric fields. The DC-flash event destabilized surface steps, causing them to wander and form surface mounds with a height of several tens of nanometers. In addition, numerous two-dimensional (2D) nuclei with a size of several nanometers are formed on the terraces. In contrast, the AC-flash event stabilized surface steps without the formation of surface mounds, causing them nearly straight with uniform terrace width at approximately 500 nm. 2D nuclei with a size of a few 10 nm were formed at the step edges with round shapes. Both methods were confirmed as evidenced by the formation of two-dimensional nuclei on the surface after the flash events, to enhance surface-related mass diffusion.

Advanced iontronic spiking modes with multiscale diffusive dynamics in a fluidic circuit

Fluidic iontronics is emerging as a distinctive platform for implementing neuromorphic circuits, characterised by its reliance on the same aqueous medium and ionic signal carriers as the brain. Drawing upon recent theoretical advancements in both iontronic spiking circuits and in dynamic conductance of conical ion channels, which form fluidic memristors, we expand the repertoire of proposed neuronal spiking dynamics in iontronic circuits. Through a modelled circuit containing channels that carry a bipolar surface charge, we extract phasic bursting, mixed-mode spiking, tonic bursting, and threshold variability, all with spike voltages and frequencies within the typical range for mammalian neurons. These features are possible due to the strong dependence of the typical conductance memory retention time on the channel length, enabling timescales varying from individual spikes to bursts of multiple spikes within a single circuit. These advanced forms of neuronal-like spiking support the exploration of aqueous iontronics as an interesting platform for neuromorphic circuits.

ВПЛИВ ДИСКРЕТНОГО ХАРАКТЕРУ СИГНАЛУ ШВИДКОСТІ НА ПРОЦЕСИ КЕРУВАННЯ МОМЕНТОМ ВЕКТОРНО-КЕРОВАНОГО АСИНХРОННОГО ДВИГУНА

The paper presents the investigation of the impact of the discrete character of the measured by incremental encoder speed signal on the induction motor torque vector control in traction electrical drive. The study is based on mathemati-cal simulations for a direct vector flux-torque control system which provides direct asymptotic field-orientation, asymp-totic flux-torque trajectory tracking, and asymptotic decoupling of the torque and flux subsystems. The parameters of the induction motor and encoder used in the study correlate with used in the real traction electromechanical systems of trolleybuses. It is shown that introduction of first order filter in the speed measurement channel reduces the induction motor’s current and torque spikes, but leads to an error in torque control and degradation of the rotor flux field-orientation conditions. Combined utilization of filtered and unfiltered speed signal is proposed in order to avoid this disadvantage. Ref. 7, fig. 6.

Dual-Coupled-Inductor-Based High-Step-Up Boost Converter with Active-Clamping and Zero-Voltage Switching

Many applications, such as photovoltaic systems, uninterruptible power supplies, and automobile headlamps, need a high step-up DC–DC converter without isolation. The conventional boost converter has the advantages of simple topology and easy control. However, it has some shortcomings, such as insufficient step-up voltage ratio and poor efficiency when operating at large duty-cycle conditions. One of the popular topologies used to overcome these problems is the coupled-inductor boost converter. It utilizes the turn ratio of the coupled inductor to realize a higher step-up voltage ratio. The drawback is that the leakage inductance of the coupled inductor causes a huge voltage spike when the power switches are turned off. Moreover, because coupled inductors are characterized by their large volume and high profile, a conventional coupled-inductor boost converter is unsuited for photovoltaic systems, such as the solar microinverter. This study proposes a novel high-step-up boost converter to solve these problems. This proposed converter uses dual coupled inductors instead of the conventional coupled-inductor boost converter. The secondary side of the coupled inductor is connected in series to increase the step-up voltage ratio. The proposed converter utilizes active clamping to achieve zero-voltage switching (ZVS) for suppressing voltage spike and improving conversion efficiency. In addition, low-profile designs can be fulfilled easily for solar microinverters. The proposed converter and its control method are introduced. The operation principle, circuit characteristics, and circuit analysis are presented. A prototype converter with 300 W output power 25–40 VDC input voltage and 200 VDC output voltage was tested. All functions, including high step-up voltage ratio, ZVS, and active clamping, were achieved, and the highest efficiency was around at 94.7%.

Screening of place cell and analysis of its influencing factors for pigeons

Place cell with location tuning characteristics play an important role in brain spatial cognition and navigation, but there is relatively little research on place cell screening and its influencing factors. Taking pigeons as model animals, the screening process of pigeon place cell was given by using the spike signal in pigeon hippocampus under free activity. The effects of grid number and filter kernel size on the place field of place cells during the screening process were analyzed. The results from the real and simulation data showed that the proposed place cell screening method presented in this study could effectively screen out place cell, and the research found that the size of place field was basically inversely proportional to the number of grids divided, and was basically proportional to the size of Gaussian filter kernel in the overall trend. This result will not only help to determine the appropriate parameters in the place cell screening process, but also promote the research on the neural mechanism of spatial cognition and navigation of birds such as pigeons.

PLC Based Transformer Protection from Over Voltage and Under Voltage

A PLC (Programmable Logic Controller) based transformer protection system is an electronic system designed to protect industrial transformers from various electrical faults and abnormalities. The system utilizes sensors to detect electrical parameters such as voltage, current, and temperature and uses a PLC to process the data and control the transformer's operation. The protection system can be programmed to detect faults such as overload, overvoltage, undervoltage, phase loss, phase reversal, and over-temperature conditions. Once a fault is detected, the PLC will automatically shut down the transformer to prevent further damage. The system provides reliable and accurate protection to the transformer, reducing the risk of costly downtime and repairs. Transformer protection from over and under voltages is a critical aspect of any transformer control system. Overvoltage can damage the transformer's insulation, bearings, and winding, while undervoltage can cause the transformer to stall or overheat. To protect the transformer from these conditions, various protection devices can be employed, including overload relays, circuit breakers, and voltage monitors. To protect against overvoltage, a voltage monitor can be installed, which will detect any voltage spikes or surges and trigger an alarm or shut down the transformer if the voltage exceeds a predetermined threshold. Similarly, an undervoltage relay can be used to protect the transformer from low voltage conditions. The undervoltage relay will monitor the voltage levels and shut down the transformer if the voltage drops below a certain level.. Key Words:-PLC (Programmable Logic Controller), SMPS, Voltage Controlled Relay, LED indicators, Transformer and Dimmer.

Single-unit data for sensory neuroscience: Responses from the auditory nerve of young-adult and aging gerbils

This dataset was collected to study the functional consequences of age-related hearing loss for the auditory nerve, which carries acoustic information from the periphery to the central auditory system. Using high-impedance glass electrodes, raw voltage traces and spike times were recorded from more than one thousand single fibres of the auditory nerve of young-adult, middle-aged, and old Mongolian gerbils raised in a quiet environment. The dataset contains not only responses to simple acoustic stimuli to characterize the fibres, but also to more complex stimuli, such as speech logatomes in background noise and Schroeder-phase stimuli. A software toolbox is provided to search through the dataset, to plot various analysed outcomes, and to give insight into the analyses. This dataset may serve as a valuable resource to test further hypotheses about age-related hearing loss. Additionally, it can aid in optimizing available computational models of the auditory system, which can contribute to, or eventually even fully replace, animal experiments.

Utilizing Ragone framework for optimized phase change material-based heat sink design in electronic cooling applications

This study explores the latent thermal energy storage potential of an organic phase change material with porous copper foam and its applicability in electronic cooling under varying heat load conditions. The organic phase change material, n-eicosane, is known for its inherently low thermal conductivity of 0.15 W/mK, rendering it vulnerable during power spikes despite its abundant latent heat energy for phase transition from solid to liquid. Porous copper foams are often integrated into n-eicosane to enhance the composite's thermal conductivity. However, the volume fraction of the phase change material in the porous foam that optimally improves the thermal performance can be dependent on the boundary condition, the cut-off temperature, and the thickness. A finite difference numerical model was developed and utilized to ascertain the energy consumption for the composite of n-eicosane with two kinds of porous copper foam with varying porosity under different heat rates, cut-off temperatures, and thickness. In addition, the results are compared with a metallic phase change material (gallium), a material chosen with a similar melting point but significantly high thermal conductivity and volumetric latent heat. For validation of the numerical model and to experimentally verify the effect of boundary condition (heat rate), experimental investigation was performed for n-eicosane and high porosity copper foam composite at varying heat rates to observe its melting and solidification behaviors during continuous operation until a cut-off temperature of 70 °C is reached. Experiments reveal that heat rate influences the amount of latent energy storage capability until a cutoff temperature is reached. For broad comparison, the numerical model was used to obtain the accessed energy and power density and generate thermal Ragone plots to compare and characterize pure gallium and n-eicosane - porous foam composite with varying volume fractions, cutoff temperature, and thickness under volumetric and gravimetric constraints. Overall, the proposed framework in the form of thermal Ragone plots effectively delineates the optimal points for various combinations of heat rate, cut-off point, and aspect ratio, affirming its utility for comprehensive design guidelines for PCM-based composites for electronic cooling applications

Hardware Implementation of a Fully Functional Stochastic p‐STT Neuron for Probabilistic Computing

AbstractA stochastic binary neuron is developed for probabilistic computing using a perpendicular spin‐transfer torque (p‐STT) neuron device and its associated peripheral circuits. The p‐STT neuron device, featuring a 300‐nm‐diameter pillar structure and a perpendicular magnetic‐tunnelling‐junction spin valve, is fabricated to exhibit stochastic switching behavior characterized by a sigmoidal function. The stochastic switching mechanism is influenced by the presence of defect sites within the device. The hardware implementation encompasses the construction of the neuron peripheral circuit, including the fire‐spike generation, sensing amplifier, and reset circuit, using a 28‐nm‐design‐rule complementary metal‐oxide‐semiconductor (C‐MOSFET) process. This hardware realization also demonstrates stochastic switching behavior with a sigmoidal function. However, a slight shift toward higher input voltage spike amplitudes is observed compared to the p‐STT neuron device alone, owing to voltage drop within the peripheral circuit. Furthermore, the software‐based investigation focuses on validating the feasibility of a spiking neural network. The temporal correlation detection is estimated using the stochastic switching probability derived from the hardware implementation, indicating successful synchronization between the correlated input neuron and the output p‐STT neuron.

Integrating Image Perception and Time‐to‐First‐Spike Coding in MoS2 Phototransistors for Spiking Neural Network

AbstractHuman vision system remains alert for dangers and adopts high‐speed and low‐power coding methods to convert the image information to spike signals. To meet the demand for danger alert in machine vision, it is important to design intelligent sensors to integrate the functions of image perception and high‐efficiency coding for high‐priority analysis. Inspired by the human visual system, a MoS2 phototransistor is introduced on SiNx substrate enabling simultaneous image perception and time‐to‐first‐spike (TTFS) coding. The device demonstrates exceptional performance in encoding 3‐bit grayscale images, achieving a low mean squared error of 0.008 and a high structural similarity index of 0.9784. Spiking neural networks (SNN) with TTFS coding achieve high recognition accuracy (98.86%) while reducing spike count by 75%. The device array also perceives motion direction and object states by converting data temporally. This work establishes a hardware foundation to promote the performance of SNNs in efficiently identifying crucial information.

Increasing the Sensitivity of pH Glass Electrodes with Constant Potential Coulometry at Zero Current.

It has recently become possible to increase the sensitivity of ion-selective electrodes (ISEs) by imposing a constant cell potential, allowing one to record current spikes with a capacitor placed in series in the circuit. The approach requires a transient current to pass through the measurement cell, which unfortunately may introduce measurement errors and additionally excludes the use of high-impedance indicator electrodes, such as pH glass electrodes. We present here an electronic circuit that overcomes these limitations, where the cell is measured at zero current in combination with a voltage follower, and the current spike and capacitor charging occur entirely within the instrument. The approach avoids the need for a counter electrode, and one may use any electrode useful in potentiometry regardless of its impedance. The characteristics of the circuit were found to approach ideality when evaluated with either an external potential source or an Ag/AgCl electrode. The current may be linearized and extrapolated to further reduce the measurement time. The circuit is further tested with the most common yet very challenging electrode, the pH glass electrode. A precision of 64 μpH was obtained for 0.01 pH change up to 0.05 from a reference solution. Similar pH changes were also measured reliably further away from the reference solution (0.5-0.55) and resulted in a precision of 377 μpH. The limitations of this experimental setup were explored by performing pH calibrations within the measuring range of the probe.

Ultralow Power Electronic Analog of a Biological Fitzhugh-Nagumo Neuron.

Here, we introduce an electronic circuit that mimics the functionality of a biological spiking neuron following the Fitzhugh-Nagumo (FN) model. The circuit consists of a tunnel diode that exhibits negative differential resistance (NDR) and an active inductive element implemented by a single MOSFET. The FN neuron converts a DC voltage excitation into voltage spikes analogous to biological action potentials. We predict an energy cost of 2 aJ/cycle through detailed simulation and modeling for these FN neurons. Such an FN neuron is CMOS compatible and enables ultralow power oscillatory and spiking neural network hardware. We demonstrate that FN neurons can be used for oscillator-based computing in a coupled oscillator network to form an oscillator Ising machine (OIM) that can solve computationally hard NP-complete max-cut problems while showing robustness toward process variations.

Overshoot‐Suppressed Memristor Crossbar Array with High Yield by AlOx Oxidation for Neuromorphic System

AbstractThere is a need to design a hardware synapse array appropriate for enhancing the efficiency of neuromorphic computing systems while minimizing energy consumption. This study introduces a memristor device with an AlOx overshoot suppression layer (A‐OSL) to achieve a self‐compliance effect. By optimizing each cell within the 16 × 16 crossbar array, synaptic devices are successfully fabricated with reliable characteristics and 3‐bit multilevel capabilities. In addition, the oxygen composition of TiOx and the annealing conditions are optimized to reduce the forming voltage and minimize the variation in the switching voltage. As a result, stable forming‐free characteristics are obtained through A‐OSL insertion, a reduction in forming voltage, and TiOx oxygen composition optimization. Also, target weights are accurately transferred to the A‐OSL memristor crossbar array and conducted the inference process by applying spike signals to the array following the designated time step. The spiking neural network (SNN) is demonstrated by measuring vector‐matrix multiplication (VMM) of the 16 × 16 crossbar array. The VMM results exhibit a classification accuracy of 90.80% for the MNIST dataset, which is close to the accuracy achieved by software‐based approaches, amounting to 91.85%.

Harnessing nonlinear conductive characteristic of TiO2/HfO2 memristor crossbar for implementing parallel vector–matrix multiplication

Memristor crossbar arrays are expected to achieve highly energy-efficient neuromorphic computing via implementing parallel vector–matrix multiplication (VMM) in situ. The similarities between memristors and neural synapses offer opportunities for realizing hardware-based brain-inspired computing, such as spike neural networks. However, the nonlinear I–V characteristics of the memristors limit the implementation of parallel VMM on passive memristor crossbar arrays. In our work, we propose to utilize differential conductance as a synaptic weight to implement linear VMM operations on a passive memristor array in parallel. We fabricated a TiO2/HfO2 memristor crossbar array, in which differential-conductance-based synaptic weight exhibits plasticity, nonvolatility, multi-states, and tunable ON/OFF ratio. The noise-dependent accuracy performance of VMM operations based on the proposed approach was evaluated, offering an optimization guideline. Furthermore, we demonstrated a spike neural network circuit capable of processing small spiking signals through the differential-conductance-based synapses. The experimental results showcase effective space-coded and time-coded spike pattern recognition. Importantly, our work opens up new possibilities for the development of passive memristor arrays, leading to increased energy and area efficiency in brain-inspired chips.