Circuit Parameters Research Articles

Electromagnetic frequency prediction pattern for electrical circuited shell based on FSTT theory using electromagnetic wave prediction method

This research focuses on electromagnetic analysis of electrical circuited shell to predict possible failure using wave prediction method. The equation is established considering axial and lateral hydrostatic pressure based on first order shear deformation theory of shell motion using the wave propagation approach and classic Flügge shell equations. For validation of accuracy of this research method, a comparison carried out with experimental data. With this method the effects of circuit parameters as well as different t power-law exponent on the frequencies are investigated. The results showed fantastic agreement between the present method and experimental ones.

Modeling and Analyzing of CMOS Cross-Coupled Differential-Drive Rectifier for Ultra-Low-Power Ambient RF Energy Harvesting

This paper models and analyzes the Complementary Metal Oxide Semiconductor (CMOS) cross-coupled differential-drive (CCDD) rectifier for Ultra-Low-Power ambient radio-frequency energy harvesters (RFEHs) working in the subthreshold region. In this paper, two closed-form equations of CCDD rectifier output voltage and input resistance in the subthreshold region were derived based on BSIM4 models of NMOS and PMOS. The model give insight to specify circuit parameters according to different inputs, transistor sizes, threshold voltages, numbers of stages, load conditions and compensation voltages, which can be used to optimize the rectifier circuit. There is a good agreement between the simulation results and these models, and these models have a maximum deviation of 10% in comparison with the simulation results in the subthreshold region. The measurement results of a single-stage CCDD rectifier reported in a previous paper were adopted to verify the model. The output voltage and input resistance predicted by these models provide excellent consistency with corresponding measurement results. The model can be employed to optimize the CCDD rectifier without expensive calculation in the design stage.

Vibration Suppression and Energy Harvesting of Nonlinear Energy Sink-Based Piezoelectric System with Combined Damping and Bistability Properties for Nonlinear Oscillator

Nonlinear energy sink (NES) as a new type of dynamic absorber has received widespread attention due to its broadband vibration suppression capability, but it has a certain requirement of energy triggering threshold. In this work, a bistable NES-based piezoelectric system with combined damping (BCPNES) and low threshold requirement is proposed. Electromechanical-coupled equations for the nonlinear oscillator coupled with BCPNES (NO-BCPNES) are established. The vibration suppression and vibration energy harvesting performance for the coupled system are investigated numerically and analytically. The frequency–energy plots of the conservative system are investigated using the complex-variable averaging method and the electromechanical decoupling method. The influence of circuit parameters on the target energy transfer threshold and harvested energy is discussed through the equivalent stiffness and damping of the circuit. The vibration suppression performance and the target energy transfer characteristics are analyzed in terms of the time–history response, the time–frequency response and the slowly varying dynamic flow, respectively. The results show that the electromechanical coupling coefficient affects the skeleton curve of frequency–energy plots in the form of equivalent stiffness. The NO-BCPNES system exhibits higher energy dissipation performance and better targeted energy transfer form under various excitations. From the phase perspective, NES-based piezoelectric system achieves vibration suppression of the main structure through the phase locking phenomenon. The mechanism of the influence of piezoelectric device parameters on the energy harvesting performance of the systems is clarified.

Complex dynamics in an atmospheric pressure glow discharge in helium: transition from stationary to periodic oscillatory, and fully chaotic states

Abstract This work deals with the numerical study of spontaneous temporal oscillations in an atmospheric pressure glow discharge (APGD) in helium. The transition of helium APGD from stationary to periodic oscillatory state through the Hopf bifurcation, and further from periodic to chaotic oscillations through period-doubling bifurcations is explored. The choice of the discharge and external electric circuits parameters is guided by the relevant experiments. The ballast resistance and supply voltage of the external circuit play the role of control parameters. The method is based on the stability analysis of stationary states of the discharge. 

The stability diagram predicting parameter regimes at which stable and oscillatory states of the APGD can be expected is obtained. The effects of the discharge parameters (such as the gas gap, secondary electron emission coefficients, and capacitance in the external electric circuit) on the bifurcation curves are identified. 

The Lorenz map and corresponding period-doubling bifurcation diagram characterizing transition to chaotic oscillations in helium APGD with an increase in the control parameter are derived. The value of the capacitance in the external circuit plays a critical role in the dynamical behavior of the discharge. Decreasing its value contributes to the dissipation/damping of the system, whereas increasing it enhances the irregular behavior of the system.

Random Natural Gradient

Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. An important bottleneck is the classical optimization loop, where the multiple local minima and the emergence of barren plateaux make these approaches less appealing. To improve the optimization the Quantum Natural Gradient (QNG) method \cite{stokes2020quantum} was introduced – a method that uses information about the local geometry of the quantum state-space. While the QNG-based optimization is promising, in each step it requires more quantum resources, since to compute the QNG one requires O(m2) quantum state preparations, where m is the number of parameters in the parameterized circuit. In this work we propose two methods that reduce the resources/state preparations required for QNG, while keeping the advantages and performance of the QNG-based optimization. Specifically, we first introduce the Random Natural Gradient (RNG) that uses random measurements and the classical Fisher information matrix (as opposed to the quantum Fisher information used in QNG). The essential quantum resources reduce to linear O(m) and thus offer a quadratic "speed-up", while in our numerical simulations it matches QNG in terms of accuracy. We give some theoretical arguments for RNG and then benchmark the method with the QNG on both classical and quantum problems. Secondly, inspired by stochastic-coordinate methods, we propose a novel approximation to the QNG which we call Stochastic-Coordinate Quantum Natural Gradient that optimizes only a small (randomly sampled) fraction of the total parameters at each iteration. This method also performs equally well in our benchmarks, while it uses fewer resources than the QNG.

Generation of low-temperature plasma by pulse-width modulated signals and monitoring of the interaction thereof with the surface of objects

Abstract The article discusses the use of pulse-width modulation signals to generate low-temperature at-mospheric plasma in an inert gas environment. The results of studies of the energy consumption of a low-temperature plasma generation system depending on the duty rate, as well as the pulse repetition rate, are presented. The operating modes of the system have been established, in which a minimum of energy consumption is achieved. The issues of evaluating the interaction of plasma with objects based on the analysis of changes in signal parameters in the high-voltage circuit of the generator are also considered.

Total harmonic distortion estimation in piezoelectric micro-electro-mechanical-system loudspeakers via a lumped elements approach

In the context of the increasing trend towards miniaturization required by new wireless audio devices, piezoelectric micro-electro-mechanical-system (MEMS) loudspeakers are getting extensive attention. Finite Element Methods (FEM) and Lumped Element Methods (LEM) models able to accurately predict their linear response have been recently proposed in the literature. However, a nonlinear model able to predict the Total Harmonic Distortion (THD) of theses types of devices is to date not available. In this paper we present a FEM- assisted lumped-parameters equivalent circuit accounting for piezoelectric hysteresis which demonstrates good agreement with experimental THD results carried out on piezoelectric MEMS loudspeakers prototypes fabricated by STMicroelectronics. The nonlinear electro-mechanical domain is simulated through a Reduced Order Model (ROM) which considers as basis function the pre-stressed undamped actuated mode of the device computed via FEM, to simulate loudspeaker diaphragms of arbitrarily complex geometry. The parameters of the acoustical circuit are instead derived through analytical formulas.

Hysteresis and self-oscillations in an artificial memristive quantum neuron

We theoretically study an artificial neuron circuit containing a quantum memristor in the presence of relaxation and dephasing. The charge transport in the quantum element is realized via tunneling of a charge through a quantum particle which shuttles between two terminals—a functionality reminiscent of classical diffusive memristors. We demonstrate that this physical principle enables hysteretic behavior in the current-voltage characteristics of the quantum device. In addition, being used in an artificial neural circuit, the quantum switcher is able to generate self-sustained current oscillations. Our analysis reveals that these self-oscillations are triggered only in quantum regimes with a moderate rate of relaxation, and cannot exist either in a purely coherent regime or at a very high decoherence. We investigate the hysteresis and instability leading to the onset of current self-oscillations and analyze their properties depending on the circuit parameters. Our results provide a generic approach to the use of quantum regimes for controlling hysteresis and generating self-oscillations. Published by the American Physical Society 2024

Simulation-based effective comparative analysis of neuron circuits for neuromorphic computation systems

The spiking neural networks (SNN) which are inspired by the human brain offers wider scope for application in the growth of neuromorphic computing systems due to their brain level computational capabilities, reduced power consumption, minimal data movement cost, and among other advantages. Spike-based neurons and synapses are the essential building blocks of SNN, and their efficient implementation is vital to its performance enhancement. In this regard, the design and implementation of spiking neurons have been the major focus among the researchers. In this paper, functioning of different leaky integrate fire (LIF)-based spiking neuron circuits like frequency adaptable CMOS-based LIF, resistor-capacitor-based (RC) LIF, and volatile memristor-based LIF are subjected to comparison. The work mainly focuses on revealing analysis of spike duration and amplitude, number of spikes produced during excitation period, threshold operation, field of application, and various other significant parameters of aforementioned neuron circuits. Extensive simulations of these circuits are carried out utilizing the Cadence Virtuoso simulation environment in order to validate their behavior. Further, a brief comparative analysis is executed considering into account the attributes like circuit complexity, supply voltage, firing rate, membrane capacitance, nature of input/output, refractory mechanism, and energy consumption per spike. This work seeks to assist researchers in selecting an appropriate LIF model to efficiently construct memristors and/or non-memristors based SNN for certain application.

Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions

With the rapid development of the new energy sector and lithium-ion (Li-ion) battery technologies, using Li-ion batteries with high energy density and high discharge rate to form the primary energy subsystem can further improve the compactness and miniaturization level of pulsed power systems. In traditional electric power systems, Li-ion batteries normally operate under the discharge condition of low current and long time. However, as the main power source of pulsed power systems, it is required that Li-ion batteries should have the capability for high-rate pulse discharge. To ensure the safe and reliable operation of the battery energy storage system, it is necessary to conduct the parameter identification of the Li-ion battery model to establish an accurate pulse discharge model under such working conditions. This paper focuses on the discharge characteristics of a cylindrical high-rate single Li-ion battery with a capacity of 3 Ah. At a 20 C rate, the discharge data were obtained when the pulse repetition frequency was 10 Hz and the duty cycle was 90%. By using the mathematical expressions of the Thevenin equivalent circuit model, the recursive relationship of the circuit parameters was obtained, and the parameter identification of the battery model was conducted based on the experimental data by using the genetic algorithm. The results show that the fitting accuracy of the parameter identification reaches 0.9995, indicating the high precision of the model for the Li-ion battery. This work provides a significant reference for the modeling and parameter identification of Li-ion batteries under high-rate pulse discharge conditions.

РАЗРАБОТКА ПРОГРАММЫ РАСЧЕТА ПАРАМЕТРОВ СХЕМЫ ЗАМЕЩЕНИЯ ТРЕХФАЗНОГО АСИНХРОННОГО ЭЛЕКТРОДВИГАТЕЛЯ

The article is devoted to developing a program for calculating the parameters of a T-shaped equivalent circuit of three-phase asynchronous electric motors. The relevance of this work is due to the need to obtain reliable results of computer simulation modelling of electric drive systems in software packages. The aim of the study is to implement in a convenient software interface an analytical technique for calculating the parameters of an asynchronous motor equivalent circuit with minimal deviations from the catalogue data. For the software calculation of the equivalent circuit parameters the paper considers analytical approximation and iterative counting techniques, since they do not require experiments on industrial electrical equipment. A comparative analysis of such techniques is performed using the example of a three-phase asynchronous motor brand BA280S4 with a power of 110 kW. The results of the compar-ative analysis show that the highest reliability of the mechanical and electromechanical characteristics is achieved in the case of using the iterative counting technique with minimizing the objective function of the sum of the weighted squares of the deviations of the control point values from the catalogue data. The authors implement the program for calculating the equivalent circuit parameters according to the selected calculation method in the Embarcadero Delphi environment. The reliable values of the electric motor parameters calculated by the program will allow for computer to model electric drive systems that best matches real objects.

IGZO TFT Backplane Integration for µLED Flat-Panel Display

The focus of this work is the process integration of Indium Gallium Zinc Oxide (IGZO) transistors as a µLED backplane for row/column addressing. A single pixel is composed of a µLED driven by an arrangement of two transistors and a storage capacitor. The pixels are then arrayed on a glass substrate to support active-matrix control of monochrome and full color (RGB) displays from 1x1cm (50 x 50 pixels) up to 7.6 x 7.6 cm (380 x 380 pixels). Optimization of circuit parameters considering size and scan frequency was modeled using existing TFT and µLED electrical device compact models. New process parameters and procedures were determined for the proper integration of µLEDs in an existing TFT fabrication process. Red, green, and blue µLED devices were fabricated at Tyndall National Institute on native substrates and were transferred to TFT pixels using an X-Display MTP-1003 micro-transfer printer. The performance of individual test cells was assessed using an Agilent B1500, revealing a voltage transfer characteristic indicating the ability to modulate and control µLED current.

Feedback-based quantum algorithms for ground state preparation

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one class of ground state algorithms that has received significant attention in recent years. These algorithms utilize a hybrid quantum-classical computing framework to prepare ground states on quantum computers. However, this requires solving a classical optimization problem that can become prohibitively expensive in high dimensions. Here, we develop formulations of feedback-based quantum algorithms for ground state preparation that can be used to address this challenge for two broad classes of Hamiltonians: Fermi-Hubbard Hamiltonians, and molecular Hamiltonians represented in second quantization. Feedback-based quantum algorithms are optimization-free; in place of classical optimization, quantum circuit parameters are set according to a deterministic feedback law derived from quantum Lyapunov control principles. This feedback law guarantees a monotonic improvement in solution quality with respect to the depth of the quantum circuit. A variety of numerical illustrations are provided that analyze the convergence and robustness of feedback-based quantum algorithms for these problem classes. Published by the American Physical Society 2024

A Novel Spotted Hyena Optimizer for the Estimation of Equivalent Circuit Model Parameters in Li-Ion Batteries

Li-ion batteries possess significant advantages like large energy density, fast recharge, and high reliability; hence, they are widely adopted in electric vehicles, portable electronics, and military and aerospace applications. Albeit having their merits, accurate battery modeling is subjected to problems like prior information on internal chemical reactions, complexity in problem formulation, a large number of unknown parameters, and the need for extensive experimentation. Hence, this article presents a reliable Spotted Hyena Optimizer (SHO) to determine the equivalent circuit parameters of lithium-ion (Li-ion) batteries. The methodology of the SHO is derived from the living and hunting tactics of spotted hyenas, and it is efficiently applied to solve the battery parameter estimation problem. Nine unknown battery model parameters of a Samsung INR 18650-25R are determined using this method. The model parameters estimated are endorsed for five different datasets with various discharge current values. Further, the effect of parameter range and its selection is also emphasized. Secondly, for validation, various performance metrics such as Integral Squared Error, mean best, mean worst, and Standard Deviation are evaluated to authenticate the superiority of the proposed parameter extraction. From the computed results, the SHO algorithm is able to explore the search area up to 89% in the case of larger search ranges. The chosen model and range of the SHO precisely predict the behavior of the proposed Li-ion battery, and the results are in accordance with the catalog data.

An Enhanced LPRAFF with Tri-State Inverter Embedded Non-Clock Gating via the CT-GWO Algorithm

Since a long time ago, it has been understood how radiation affects digital circuits, particularly those using the Complementary Metal Oxide Semiconductor (CMOS) model. Total Ionisation Dose (TID) and Single Event Effects (SEE) are the two most significant radiation effects. Depending on the gate input count, the complexity of the circuit will rise, which will worsen the radiation and raise the cumulative dose levels. The incremental dose level affects the circuit parameter failure, which affects how well the logic design functions. Many authors concentrate on minimising the effects of radiation while preventing function loss, but these extra efforts use excess energy. To improve the efficiency of the Low Power Radiation Aware (LPRA) circuit, this paper introduces optimisation concepts in a Flip Flop (FF) architecture named Chaos Theory-based Grey Wolf Optimised FF (CT-GWOFF). First, compute each component's radiation response using a physics-based modelling strategy. To minimise undesirable latches and disable the inverter chain when the input data remain constant, a tri-state inverter, incorporating a non-clocked gating mechanism, is provided. This prevents repeated transitions of delayed clock signals. Moreover, the proposed model is implemented in FFs for simulation purposes, making it more cognizant of radiation effects and power consumption. Using the HSPICE tool, the performance of the suggested circuit design is evaluated at the 16 nm CMOS Predictive Technology Model (PTM).

Influence of the Bias Voltage on Effective Electron Velocity in AlGaN/GaN High Electron Mobility Transistors.

The small-signal S parameters of the fabricated double-finger gate AlGaN/GaN high electron mobility transistors (HEMTs) were measured at various direct current quiescent operating points (DCQOPs). Under active bias conditions, small-signal equivalent circuit (SSEC) parameters such as Rs and Rd, and intrinsic parameters were extracted. Utilizing fT and the SSEC parameters, the effective electron velocity (νe-eff) and intrinsic electron velocity (νe-int) corresponding to each gate bias (VGS) were obtained. Under active bias conditions, the influence mechanism of VGS on νe-eff was systematically studied, and an expression was established that correlates νe-eff, νe-int, and bias-dependent parasitic resistances. Through the analysis of the main scattering mechanisms in AlGaN/GaN HEMTs, it has been discovered that the impact of VGS on νe-eff should be comprehensively analyzed from the aspects of νe-int and parasitic resistances. On the one hand, changes in VGS influence the intensity of polar optical phonon (POP) scattering and polarization Coulomb field (PCF) scattering, which lead to changes in νe-int dependent on VGS. The trend of νe-int with changes in VGS plays a dominant role in determining the trend of νe-eff with changes in VGS. On the other hand, both POP scattering and PCF scattering affect νe-eff through their impact on parasitic resistance. Since there is a difference in the additional scattering potential corresponding to the additional polarization charges (APC) between the gate-source/drain regions and the region under the gate, the mutual effects of PCF scattering on the under-gate electron system and the gate-source/drain electron system should be considered when adjusting the PCF scattering intensity through device structure optimization to improve linearity. This study contributes to a new understanding of the electron transport mechanisms in AlGaN/GaN HEMTs and provides a novel theoretical basis for improving device performance.

A Novel Single-Stage Boost Single-Phase Inverter and Its Composite Control Strategy to Suppress Low-Frequency Input Ripples

Low-frequency pulsating ripples exist on the input side of a single-phase inverter, which bring some adverse effects and harm to the inverter and photovoltaic power generation system. In order to suppress the low-frequency pulsating ripple and reduce the filter circuit parameters, a novel single-stage boost single-phase inverter is proposed, which can suppress low-frequency ripple. And a three-closed-loop compound control strategy that can suppress input low-frequency ripples under the limitation of an energy storage inductor current and buffer capacitor voltage is proposed. The circuit topology, control strategy, key circuit parameters design, system modeling, and simulation of the inverters are deeply analyzed and studied. Simulation and experimental results show that the inverter has a good ability to suppress input low-frequency ripples.

SQuADDS: A validated design database and simulation workflow for superconducting qubit design

We present an open-source database of superconducting quantum device designs that may be used as the starting point for customized devices. Each design can be generated programmatically using the open-source Qiskit Metal package, and simulated using finite-element electromagnetic solvers. We present a robust workflow for achieving high accuracy on design simulations. Many designs in the database are experimentally validated, showing excellent agreement between simulated and measured parameters. Our database includes a front-end interface that allows users to generate ``best-guess'' designs based on desired circuit parameters. This project lowers the barrier to entry for research groups seeking to make a new class of devices by providing them a well-characterized starting point from which to refine their designs.

Monitoring the Dilution of Buffer Solutions with Different pH Values above and below Physiological pH in Very Small Volumes.

The accurate determination of the post-dilution concentration of biological buffers is essential for retaining the necessary properties and effectiveness of the buffer to maintain stable cellular environments and optimal conditions for biochemical reactions. In this work, we introduce a silicon-based impedance chip, which offers a rapid and reagent-free approach for monitoring the buffer concentrations after dilution with deionized (DI) water. The impedance of the impedance chip is measured, and the impedance data are modeled using a multiparameter equivalent circuit model. We investigated six aqueous biological buffers with pH values above and below the physiological pH for most tissues (pH ~ 7.2-7.4) following dilution with DI water by factors of 2.0, 10.0, 20.0, 100.0, and 200.0. The impedance measurement is then performed for the frequency spectrum of 40 Hz to 1 MHz. From the interpretation of the impedance measurement using the multiparameter equivalent circuit model, we report a buffer-sensitive equivalent circuit parameter RAu/Si of the silicon-based impedance chip showing a linear trend on a logarithmic scale with the buffer concentration change after dilution. The parameter RAu/Si is independent of the buffer pH and the added volume. The results demonstrate the efficacy of the silicon-based impedance chip as a versatile tool for precise post-dilution concentration determination of diverse biologically relevant buffers. The presented impedance chip offers rapid, accurate, and reliable monitoring, making it highly suitable for integration into automated liquid-handling systems to enhance the efficiency and precision of biological and chemical processes.

State of Charge Estimation of Lithium-Ion Batteries Based on Fractional-Order Model with Mul-ti-Innovations Dual Cubature Kalman Filter Method

An accurate estimation of the lithium battery’s state of charge (SOC) is critical. The article proposes a dual fractional order multi-innovations cubature Kalman filter (DFOMICKF) algorithm for estimating lithium battery SOC. The algorithm adopts the idea of multiple time scales, where one of the FOMICKF is used to identify the circuit model parameters online in the macro time scale. Another FOMICKF is used to estimate the SOC in the micro time scale, and the circuit parameters updated online in real-time are passed into the estimation of the SOC filter to form an online joint estimation method of SOC and circuit parameters. Finally, multiple algorithms of DFOMICKF, FOMICKF, FOCKF, and CKF are compared and experimented under different working conditions to compare and analyze the estimated SOC errors. It is verified that the proposed algorithm can solve the problems of inaccuracy, poor convergence, and poor robustness of the traditional Kalman filtering algorithm for estimating SOC, which has good research value.