Voltage Variations Research Articles

Research on the Reliability of Threshold Voltage Based on GaN High-Electron-Mobility Transistors.

With the development of high-voltage and high-frequency switching circuits, GaN high-electron-mobility transistor (HEMT) devices with high bandwidth, high electron mobility, and high breakdown voltage have become an important research topic in this field. It has been found that GaN HEMT devices have a drift in threshold voltage under the conditions of temperature and gate stress changes. Under high-temperature conditions, the difference in gate contact also causes the threshold voltage to shift. The variation in the threshold voltage affects the stability of the device as well as the overall circuit performance. Therefore, in this paper, a review of previous work is presented. Temperature variation, gate stress variation, and gate contact variation are investigated to analyze the physical mechanisms that generate the threshold voltage (VTH) drift phenomenon in GaN HEMT devices. Finally, improvement methods suitable for GaN HEMT devices under high-temperature and high-voltage conditions are summarized.

Discrete control for state of charge balance in DC microgrids considering the disturbance of photovoltaics

This study examines State of Charge (SoC) balancing control in DC microgrids subject to photovoltaic (PV) fluctuations, aiming to optimize power distribution in energy storage systems influenced by PV disturbances. The proposed approach enhances both the lifespan of storage systems and microgrid stability. To mitigate voltage variation due to PV perturbation, the paper introduces an adjustment in droop control offset. Additionally, it presents a novel discrete Sliding Mode Controller (SMC) characterized by reduced parameter sensitivity, thus enhancing control responsiveness. A SoC balancing control strategy employing sliding mode control is developed to equalize SoC levels across Battery Energy Storage Systems during both charge and discharge cycles. The stability of this strategy is substantiated through the construction of a Lyapunov function. Simulations conducted in a distributed DC microgrid environment using Simulink/SimPower Systems demonstrate the efficacy of the discrete SMC and the SoC balancing algorithm, achieving uniform SoC in energy storage nodes during operation, with improved robustness against PV perturbations.

Regulating the electrical performance of contact-separation mode triboelectric nanogenerators based on double-sided groove textures

The contact-separation mode triboelectric nanogenerators (CS-TENGs) is a kind of micro/nano electromechanical power system based on the contact electrification and electrostatic induction. With the expansion of application field of the CS-TENG, regulating the electrical performance becomes essential. In this paper, simple and effective methods for the CS-TENG output regulation based on the double-sided groove textures are proposed. To do this, groove textures on both Cu contact electrode and PDMS dielectric layer are fabricated, and influences and mechanisms of the alignment angle (the angle between the direction of groove textures on the Cu electrode and that on the PDMS dielectric layer), matching condition (textures sidewall contact and non-contact) and applied pressure on the CS-TENG output are explored through output tests, contact and electrostatic simulations. It is shown that altering the alignment angle, matching condition and applied pressure of groove texture on the Cu contact electrode and PDMS dielectric layer, could simply regulate the output of CS-TENG, where changing the alignment angle is the most effective. Under low and high applied pressures, the variations of the output voltage with alignment angle from 0˚–90˚ reach to 343.8% and 297.2%, respectively, and CS-TENG at 0˚ angle outputs the maximum voltage under both pressures, while the minimum voltages under the two pressures are exhibited from different angles. The change of contact area induced by the longitudinal deformation and transverse expansion of the groove textures is the main reason for the output regulations.

Study on deterioration of mechanical properties and voltage-strength theoretical model of CFRP/ conductive ECC composites under coupling effect of anode polarization, load and erosion environment

This study aims to systematically investigate the deterioration of tensile properties, voltage variation, and voltage-strength theoretical model of CFRP/ conductive ECC composites under coupling effect of anode polarization, load and erosion environment. The effects of testing parameters including conductive ECC mixture type, electric current density, polarization time, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time were synthetically investigated. The experimental results indicated that the voltage increases approximately linearly with the increase of degradation time in the voltage-deterioration time curves. The stress-strain curve can be divided into three stages: the stress-strain linear increase stage, the strain hardening characteristic stage, and the decline stage during failure. The conductive ECC mixture type, polarization time, current density, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time all have significant effects the deterioration of tensile strength and the voltage change ratio of CFRP/ conductive ECC composite. More importantly, an innovative voltage-strength theoretical model was proposed, which can predict the relationship between voltage and material deterioration strength. The theoretical model is in good agreement not only with the experimental results of this study, but also with the results of other studies. The model proposed can be used to predict deterioration degree of materials in real time, which has very important guiding significance for impressed current cathodic protection-structural strengthening technology (ICCP-SS) technology. This study is expected to promote a more comprehensive understanding of the deterioration of mechanical properties and voltage-strength theoretical model of CFRP/conductive ECC composites for ICCP-SS technology.

Flexible Chitosan-Based Capacitive Humidity Sensors for Respiratory Monitoring.

As one of the most important human health indicators, respiratory status is an important basis for the diagnosis of many diseases. However, the high cost of respiratory monitoring makes its use uncommon. This study introduces a low-cost, wearable, flexible humidity sensor for respiratory monitoring. Solution-processed chitosan (CS) placed on a polyethylene terephthalate substrate was used as the sensing layer. An Arduino circuit board was used to read humidity-sensitive voltage changes. The CS-based sensor demonstrated capacitive humidity sensitivity, whereby the capacitance instantly increased from 10-2 to 30 nF when the environmental humidity changed from 43% to 97%. The capacitance logarithm sensitivity and response voltage change was 35.9 pF/%RH and 0.8 V in the RH range from 56% to 97%. And the voltage variation between inhalation and exhalation was ~0.5 V during normal breathing. A rapid response time of ~0.7 s and a recovery time of ~2 s were achieved during respiration testing. Breathing modes (i.e., normal breathing, rest breathing, deep breathing, and fast breathing) and tonal changes during speech could be clearly distinguished. Therefore, such sensors provide a means for economical and convenient wearable respiratory monitoring, and they have the potential to be used for daily health examinations and professional medical diagnoses.

Differential pressure sensors based on transfer-free piezoresistive layered PdSe2 thin films

Piezoresistive layered two-dimensional (2D) crystals offer intriguing promise as pressure sensors for microelectromechanical systems (MEMS) due to their remarkable strain-induced conductivity modulation. However, integration of the conventional chemical vapor deposition grown 2D thin films onto a micromachined silicon platform requires a complex transfer process, which degrades their strain-sensing performance. In this study, we present a differential pressure sensor built on a transfer-free piezoresistive PdSe2 polycrystalline film deposited on a SiN x membrane by plasma-enhanced selenization of a metal film at a temperature as low as 200 °C. Based on the resistance change and finite element strain analysis of the film under membrane deflection, we show that a 7.9 nm thick PdSe2 film has a gauge factor (GF) of −43.3, which is ten times larger than that of polycrystalline silicon. The large GF enables the development of a diaphragm pressure sensor with a high sensitivity of 3.9 × 10−4 kPa−1 within the differential pressure range of 0–60 kPa. In addition, the sensor with a Wheatstone bridge circuit achieves a high voltage sensitivity of 1.04 mV·kPa−1, a rapid response time of less than 97 ms, and small output voltage variation of 8.1 mV in the temperature range of 25 °C to 55 °C. This transfer-free and low-temperature grown PdSe2 piezoresistive thin film is promising for MEMS transducer devices.

A linearized modeling framework for the frequency selectivity in neurons postsynaptic to vibration receptors.

Vibration is an indispensable part of the tactile perception, which is encoded to oscillatory synaptic currents by receptors and transferred to neurons in the brain. The A2 and B1 neurons in the drosophila brain postsynaptic to the vibration receptors exhibit selective preferences for oscillatory synaptic currents with different frequencies, which is caused by the specific voltage-gated Na+ and K+ currents that both oppose the variations in membrane potential. To understand the peculiar role of the Na+ and K+ currents in shaping the filtering property of A2 and B1 neurons, we develop a linearized modeling framework that allows to systematically change the activation properties of these ionic channels. A data-driven conductance-based biophysical model is used to reproduce the frequency filtering of oscillatory synaptic inputs. Then, this data-driven model is linearized at the resting potential and its frequency response is calculated based on the transfer function, which is described by the magnitude-frequency curve. When we regulate the activation properties of the Na+ and K+ channels by changing the biophysical parameters, the dominant pole of the transfer function is found to be highly correlated with the fluctuation of the active current, which represents the strength of suppression of slow voltage variation. Meanwhile, the dominant pole also shapes the magnitude-frequency curve and further qualitatively determines the filtering property of the model. The transfer function provides a parsimonious description of how the biophysical parameters in Na+ and K+ channels change the inhibition of slow variations in membrane potential by Na+ and K+ currents, and further illustrates the relationship between the filtering properties and the activation properties of Na+ and K+ channels. This computational framework with the data-driven conductance-based biophysical model and its linearized model contributes to understanding the transmission and filtering of vibration stimulus in the tactile system.

Nonlinear controller for SEPIC with single variable to tune

This work proposes a systematic approach to designing a novel integral sliding mode controller (ISMC) for a single-ended primary-inductor converter (SEPIC) with only one tunable parameter where the upper and lower bounds are derived. The designed surface results in minimal chattering behaviour at the output voltage as well as at the duty cycle and allows for operating the SEPIC at a fixed switching frequency. The proposed controller can withstand up to a 70% variation in the input voltage and 100% variation on the load side, in addition to superior performance for a cold start. The proposed controller and the corresponding mathematical formulation were simulated in a Simulink environment and experimentally tested via a scaled prototype. The proposed controller performance is also compared to Type II and integral Linear-Quadratic Regulators (LQR).

A high efficient 33 level inverter for electric vehicle application using PMSM

The permanent magnet synchronous motor (PMSM) avoids commutation-related torque ripples and produces smooth torque. Its great handling capacity and better efficiency make it an excellent choice for high-demand applications. A typical PM motor drive fed with pulse width-modulated voltages may cause the motor insulation to break down if rapid voltages (dv/dt) occur across the motor terminals. Applying variable voltage with low dv/dt and implementing multiple inverter topology can solve this issue. Multilevel converters have minimal switching losses, better power quality and the ability to operate at both fundamental and higher switching frequencies. In this study, a three phase stacked multilevel inverter-based FOC driven PMSM drive design is proposed. Here, the neutral point is a capacitor intermediate point on DC side, where current is naturally balanced throughout a switching cycle. This makes it possible to use downstream batteries and even lower voltage equipment, greatly increasing efficiency, improved performance and smother control at low speed. Therefore, direct-battery-driven electric vehicles will be able to use this. A 33 level inverter-based PMSM drive was used to implement the FOC, and the simulation results were used to validate it. The Matlab/Simulink tool is used to simulate the entire system.

Programming Operations Analysis and Statistics in One Selector and One Memory Ovonic Threshold Switching + Phase‐Change Memory Double‐Patterned Self‐Aligned Structure

This study explores the reliability of a phase‐change memory (PCM) cointegrated with an ovonic threshold switching (OTS) selector (one selector and one memory [1S1R] structure) based on an innovative double‐patterned self‐aligned architecture. The variability of the threshold voltage () for both the SET and RESET states is examined, comparing different distribution models to validate the use of mean and standard deviation as viable metrics. The dispersion of is tracked under different programming conditions to provide insight into the evolution of device behavior over SET/RESET, endurance cycles, and read cycles. The PCM device is based on a “wall” structure and on Ge2Sb2Te5 alloy, while the OTS is based on a GeSbSeN alloy. The analysis focuses on the programming characteristics and SET pulse optimization, studying current control and pulse fall times. The results are based on statistical data obtained from a kb‐sized memory array. A memory window of over 2 V is achieved. The research helps understanding the DPSA architecture, and PCM + OTS in general, offering insights into their programming, variability, and reliability targeting crossbar applications.

Optoelectronic Transimpedance Converter Based on MOS Photovaricap for High Resistive Gas Sensors

The gas detectors consist of two parts: metal-oxides gas sensor and transducer. The sensing material is made of a thin semiconductor layer. The transducer is responsible for converting the change in the several physical parameters of the thin sensitive layer into a measurable signal. Due to the high output resistance of high resistive gas sensors and the low input currents of amplifiers, electrometric cascades are employed, followed by the conversion of the gas sensors small direct current into an active current signal using a mechanical modulator (dynamic capacitor) to enhance sensitivity and stability. The aim of this research is to analyze the main characteristics of a novel type of dynamic capacitor that utilizes a surface metal-oxide-semiconductor (MOS) photovaricap (PV) as the regulating element when detecting signals from high resistive gas sensors. For the creation of surface MOS PVs, samples of p-Si with varying resistivity were chosen. A thin layer of SiO2 was deposited on these samples, onto which a translucent metallic electrode was applied. Modulation of the PV capacitance was achieved by illuminating it with a gallium arsenide LED. As a result, the capacitance of the PV is changed, producing a variable voltage across the load resistor, which was then amplified and recorded. It was observed that the settling time of the useful signal is determined by two factors. The first is the RC chain composed of the load resistance of the gas sensor and the input capacitance of the PV, and the second is slow relaxation phenomena in the structure of the MOS PV that lead to the screening of the induced charge. Characteristics of the MOS PV as a dynamic capacitor and the features of the photo capacitance as a semiconductor element, in turn, determine the transimpedance conversion coefficient. The conducted research showed that MOS PVs can be applied to register small DC currents and voltages from high resistive gas sensors. In this case, ordinary narrowband or wideband amplifiers with relatively low input resistance can be used instead of electrometric amplifiers with mechanical dynamic capacitors. The considered circuit has been experimentally tested with commercial resistors.

Enhancing the understanding of bolt loosening and wave transmission in bolted lap-joint connections: a numerical and experimental study using guided Lamb waves

Bolt loosening in bolted lap-joint connections can result in catastrophic failures in industrial settings. Therefore, it is crucial to investigate these connections thoroughly and implement preventative measures. However, examining such connections requires considering multiple influencing parameters. In this study, numerical simulations were conducted using three-dimensional finite element analysis in Abaqus software to evaluate these parameters in detail. The study employed a guided wave-based structural health monitoring approach and a precise ultrasonic-guided Lamb wave propagation method. Time signals were analyzed using phase shift and transmission coefficient (TC) factors as suitable indicators. Additionally, the S0 mode of the captured waves provided a highly informative wave packet for analysis due to its specific order. Initially, various simulations were carried out to determine the optimal length of the overlapping region that would result in the most effective transmission of waves. Increasing the bolt torque and the contact friction coefficient between the two plates in the overlapping region reduces the time for waves to reach the sensor and increases the TC of the passing waves. However, the saturation state does not cause any change in the received signals. Increasing the bolt torque is more effective in facilitating wave transmission through the connections than increasing the contact friction coefficient. Furthermore, variations in excitation voltage do not affect the arrival time or TC of the waves. The continuous wavelet transformation enabled a more detailed time-frequency analysis. The results demonstrate that changes in bolt torque do not impact the wave frequencies reaching the sensors, making the frequency insensitive to bolt loosening. Ultimately, the numerical simulation results were validated through experiments on a table-top laboratory sample. This research enhances researchers’ understanding of monitoring the health status of bolted lap-joint connections by investigating the impact of various parameters on guided Lamb wave transmission through these connections.

Adaptive Hybrid NFS-MSOGIQ Control Technique for Improving Power Quality in Solar PV Distributed Generation System

A two-stage circuit configuration with 3-phase utility grid assisted solar power generation system is designed. In order to track the solar PV arrays maximum peak power (MPP), a DC boost converter with Composite Incremental Conductance (InC) MPP technique is employed in first stage. In Second stage, a grid-tied four-leg DC-AC converter, is employed to provide the solar power that was extracted into the utility grid and to enhancing power quality. An adaptive hybrid Multi-Second Order Generalized Integrator-Quadrature (MSOGI-Q) control algorithm, in conjunction with Neuro Fuzzy system (NFS) is proposed for controlling this DC-AC converter. MSOGI-Q reference current generation strategy is designed to mitigate current harmonics by retrieving the fundamental constituents from non-linear load. The Neuro Fuzzy system along with PID controller, by adjusting the voltage from dc link keeps consistent power in between AC and DC sides for varying isolation condition. To get the peak power out of a PV panel even in different environmental conditions, the composite incremental conductance algorithm is used. To upgrade the dynamic performance of voltage variation at Point of Common Coupling (PCC) a feedforward descriptor for Photovoltaic contributions has been implemented. In addition, a comparison between the proposed NFS-MSOGIQ control technique and the existing adaptive control technique is done to assess the effectiveness of the proposed adaptive control technique. The proposed adaptive control technique for the distributed generation system is designed and stimulated in MATLAB/SIMULINK and the simulation outcomes verify the effectiveness of the proposed control technique under various transition circumstances. A laboratory prototype model of the proposed system is developed for theoretical analysis and its results are found to be compliant with IEEE standards. Furthermore, THD values of voltage and current are found to be within standard limits.

Transimpedance Matrix Can Be Used to Estimate Electrode Positions Intraoperatively and to Monitor Their Positional Changes Postoperatively in Cochlear Implant Patients.

Accurate positioning of the electrode array during cochlear implant (CI) surgery is crucial for achieving optimal hearing outcomes. Traditionally, postoperative radiological imaging has been used to assess electrode position. Transimpedance matrix (TIM) measurements have also emerged as a promising method for assessing electrode position. This involves utilizing electric field imaging to create an electric distance matrix by analyzing voltage variations among adjacent electrodes. This study aimed to investigate the feasibility of using intraoperative TIM measurements to estimate electrode position and monitor postoperative changes. Retrospective cohort study. University Medical center, tertiary academic referral center. Patients undergoing CI (CI622) surgery between January 2019 and June 2022. CI electrode positions and maximal angular insertion depths (maxAID) were determined using X-ray imaging according to Stenvers' projection. The mean gradient phase (MGP) was extracted from the TIM, and a correlation between the MGP and maxAID was examined. A model was then built to estimate the maxAID using the MGP, and changes in electrode location over time were assessed using this model. Twenty-four patients were included in this study. A positive correlation between the maxAID and the MGP ( R = 0.7, p = 0.0001) was found. The established model was able to predict the maxAID with an accuracy of 27.7 ± 4.4°. Comparing intraoperative and postoperative TIM measurements, a decrease of 24.1° ± 10.7° in maxAID over time was observed. TIM measurements are useful for estimating the insertion depth of the electrode and monitoring changes in the electrode's position over time.

Perception of power quality disturbances using Fourier, Short-Time Fourier, continuous and discrete wavelet transforms

Electric power utilities must ensure a consistent and undisturbed supply of power, with the voltage levels adhering to specified ranges. Any deviation from these supply specifications can lead to malfunctions in equipment. Monitoring the quality of supplied power is crucial to minimize the impact of fluctuations in voltage. Variations in voltage or current from their ideal values are referred to as "power quality (PQ) disturbances," highlighting the need for vigilant monitoring and management. Signal processing methods are widely used for power system applications which include understanding of voltage disturbance signals and used for retrieval of signal information from the signals Different signal processing methods are used for extracting information about a signal. The method of Fourier analysis involves application of Fourier transform giving frequency information. The method of Short-Time Fourier analysis involves application of Short-Time Fourier transform (STFT) giving time–frequency information. The method of continuous wavelet analysis involves application of Continuous Wavelet transform (CWT) giving signal information in terms of scale and time where frequency is inversely related to scale. The method of discrete wavelet analysis involves application of Discrete Wavelet transform (DWT) giving signal information in terms of approximations and details where approximations and details are low and high frequency representation of original signal. In this paper, an attempt is made to perceive power quality disturbances in MATLAB using Fourier, Short-Time Fourier, Continuous Wavelet and Discrete Wavelet Transforms. Proper understanding of the signals can be possible by transforming the signals into different domains. An emphasis on application of signal processing techniques can be laid for power quality studies. The paper compares the results of each transform using MATLAB-based visualizations. The discussion covers the advantages and disadvantages of each technique, providing valuable insights into the interpretation of power quality disturbances. As the paper delves into the complexities of each method, it takes the reader on a journey of signal processing complexities, culminating in a nuanced understanding of power quality disturbances and their representations across various domains. The outcomes of this research, elucidated through energy values, 3D plots, and comparative analyses, contribute to a comprehensive understanding of power quality disturbances. The findings not only traverse theoretical domains but also find practical utility in real-world scenarios.

Electrothermal modeling of lithium-ion batteries using an artificial intelligence technique-based approach for powerwall applications

The Powerwall, an innovative home battery powered by solar energy, is gaining popularity in the United States and Australia due to its ability to provide complete power to homes and serve as a backup during electrical supply interruptions. Recently, lithium-ion (Li-ion) battery technology has received significant attention from the industry and academia, standing out for offering greater energy capacity, power density, efficiency, and lower self-discharge rate compared to other technologies such as NiCd and NiMH batteries. Initially, this research aimed to model the Li-ion cells of the Powerwall using the equivalent circuit model (ECM). However, a detailed review of the literature indicated that a data-based approach, employing Deep Learning (DL) techniques or deep neural networks, represents the state of the art in the field. DL, a subset of machine learning and part of Artificial Intelligence (AI), offers notable advantages over ECM, including: i) high precision in estimating the non-linear relationships between voltage, current, temperature, and hidden variables such as the State of Charge (SOC); ii) the ability of a single artificial neural network to model the behavior of a Li-ion cell across different temperature ranges (example: from 0°C to 40°C); and iii) overcoming the challenge of identifying ECM parameters. Therefore, with the advancement of the research, the objective was updated to investigate and develop DL models, specifically feed-forward neural networks, for estimating the SOC of lithium-ion batteries in Powerwalls. The results obtained focus on the precise estimation of the SOC of Li-ion cells, underlining the efficacy and innovation of this methodological approach.

Design of Step Voltage Regulator Based on IGBT

The introduction of distributed generation (DG) into distribution systems is expanding due to carbon neutral policies. DG with intermittent output characteristics brings frequent voltage variations in distribution systems. Generally, a step voltage regulator (SVR) is installed in the long distribution line and controls its voltage, which has limits of stable voltage regulations due to the slow tap-changing rate, switching losses, and short life span. To solve those problems, this paper proposes an IGBT-based SVR using zero-voltage switching. It is verified that the stable operation can be obtained through simulation by PSCAD/EMTDC 4.6 software and empirical experiments.

Sensing membrane voltage by reorientation of dipolar transmembrane peptides

Membrane voltage plays a vital role in the behavior and functions of the lipid bilayer membrane. For instance, it regulates the exchange of molecules across the membrane through transmembrane proteins such as ion channels. In this paper, we study the membrane voltage-sensing mechanism, which entails the reorientation of α-helices with a change in the membrane voltage. We consider a helix having a large electrical macrodipole embedded in a lipid bilayer as a model system. We performed extensive molecular dynamics simulations to study the effect of variation of membrane voltage on the tilt angle of peptides and ascertain the optimal parameters for designing such a voltage-sensing peptide. A theoretical model for the system is also developed to investigate the interplay of competing effects of hydrophobic mismatch and dipole-electric field coupling on the tilt of the peptide and further explore the parameter space. This work opens the possibility for the design and fabrication of artificial dipolar membrane voltage-sensing elements for biomedical applications.

A Wide Dynamic Range Rectifier Based on HEMT With a Variable Self-Bias Voltage

A Wide Dynamic Range Rectifier Based on HEMT With a Variable Self-Bias Voltage

A Method to Compute Frequency Domain Models Based on Direction-Dependent Derivative of the Variation of Voltage and Current Phasors

Harmonic pollution and other potential problems are increasing due to the rising demand for Power Electronic devices in low-voltage distribution systems. The adequate modeling of the harmonic characteristics of these devices is essential for assessing their impact. Frequency Domain Models (FDMs) are based on either matrix or tensor definitions, and different methods have been proposed to compute those models' parameters. This paper proposes a method to compute matrix or tensor-based FDMs by exploiting the nonholomorphic properties of complex functions. Thus, the direction-dependent derivative of the variation of voltage-current phasors is optimized over measurements set. By proving that tensor and matrix-based models are equivalent, it is guaranteed that the method can be applied to compute both models. The Proposed and Tensorial Parametrization methods are compared using the power of the error signal as a percentage of the power of the current signal achieving a one-digit reduction in a proportion of 4:1.