Voltage Variance Research Articles

Impact of imperfect homodyne detection on measurements of vacuum states shot noise

The secret key rate of a continuous variables quantum key distribution system (CV-QKD) depends highly on the loss and excess noise of the quantum channel. A proper modelling of the quantum channel is essential to detect and prevent an eavesdropping attack. In CV-QKD, homodyne detection is widely used to measure the quadratures of the modulated optical signal. Nevertheless, the homodyne detector (HD) can be a source of noise for the CV-QKD system. In this paper, a HD is modelled considering intrinsic imperfections. Moreover, an improved method is proposed to obtain mean, variance and auto-covariance functions for estimation of the HD performance, considering ideal and unbalanced HD operation modes with ideal and non-ideal local oscillator pulse intensity functions being compared. The imbalance of the HD leads to non-zero mean output and a quadratic relation of voltage variance. Despite that, the rebalance of the system was attained with the cost of lowering the system voltage output intensity.

Flexible CMOS chip converted by a novel chip transformation process

In this Letter, the authors report a flexible CMOS chip converted by a novel chip transformation process. To realise a truly flexible CMOS chip, a two-step etching process was employed in the transformation process: (i) vapour etching to remove inter-dielectric layers followed by polymer encapsulation and (ii) plasma etching to remove the substrate of the chip. The I–V results measured after the chip transformation process show a voltage variance of <0.8% compared to the rigid chip. The bending test also revealed very small changes (0.6%) under strain conditions. Their results offer a viable route to use the foundry-fabricated CMOS chip for flexible chips; thus, a high-performance flexible chip can be realised. This technology will enable us to utilise various foundry-processed chips for future flexible applications such as health and environment monitoring, advanced mobile communication systems, and wearable electronics via a simple post-transformation process.

Reliability Analysis of an Epileptic Seizure Detector Powered by an Energy Harvester

Due to a limited lifetime of a battery, energy harvesters have been studied as alternative energy sources for implantable biomedical devices such as an implantable stimulator for epileptic seizure suppression. However, energy harvesters have weakness in providing stable power. We designed a neural recording circuit powered solely by a piezoelectric energy harvester, and applied its output to a seizure detector to analyze the reliability of the recorded signal. Performance of the seizure detector was evaluated. We found that the average time differences between with and without voltage variances were about 0.05 s under regular vibrations and about 0.07 s under irregular vibrations, respectively. The ratio of average true positive alarm period varied within about 0.02% under regular vibrations and 0.029% under irregular vibrations, respectively. The ratio of average false positive alarm period varied within about 0.004% under regular vibrations and 0.014% under irregular vibrations, respectively. This paper presents a reliability analysis of an epileptic seizure detector with a neural signal recording circuit powered by a piezoelectric energy harvester. The results showed that a supply voltage variance within ±10% could be acceptable for reliable operation of a seizure detector.

Droop-Free Distributed Control for AC Microgrids With Precisely Regulated Voltage Variance and Admissible Voltage Profile Guarantees

In this paper, we propose a droop-free distributed cooperative control with precisely regulated voltage variance and admissible voltage profile guarantees for AC microgrids. First a distributed voltage variance observer is proposed and proven to be able to converge to global voltage variance using only local measurements and information from neighboring distributed generators (DGs). A droop-free distributed control with average voltage regulator, voltage variance regulator, and relaxed reactive power regulator is then designed and shown to be able to achieve the regulation of average voltage and voltage variance and relaxed reactive power sharing in steady-state. For relaxed reactive power sharing, one special DG that could be a community-owned or utility-owned DG will not participate in reactive power sharing and this flexibility is utilized to regulate the voltage profile. The small-signal stability of the system with the proposed control is evaluated by measurement-based Prony analysis, which can also guide the control parameter selection. It is also shown that the steady-state solution of the proposed control can be obtained by solving a set of nonlinear equations, which allows more efficient evaluation of the control performance under different operating conditions and various controller settings. To validate the performance of the proposed control, extensive real-time simulation studies are performed in OPAL-RT on a four-DG test microgrid.

Influence of optimization of control factors on threshold voltage of 18 nm HfO2/TiSi2 NMOS

&lt;span&gt;This paper presents the influence of control factors as the process in development of 18 nm gate length NMOS transistor. The threshold voltage (VTH) can be minimized by optimal the control factors. Five control factors were selected through experiments. They are Adjustment VTH Implantation, Compensation Implantation, Compensation Energy Implantation, Source/Drain Implantation and Halo Implantation. While the two noise factors were introduced which are Phosphor Silicate Glass (PSG) temperature and Boron Phosphor Silicate Glass (BPSG) temperature to complete the combination with five control factors in process of Taguchi method L27 orthogonal array. The purpose of this research is to find the best value of interaction between combination controls factors and noise factors to achieve the best point of threshold voltage. In CMOS design, the threshold voltage is the benchmarking of physical parameter for determining the functional of transistor. The Virtual Wafer Fabrication SILVACO software was used to fabricate the 18 nm NMOS device. Hafnium Oxide (HfO2) and Titanium dioxide (TiO2) were utilized as the high-K materials and the Titanium Silicide (TiSi2) was utilized as metal gate. The statistics data are from the signal noise ratio (SNR) with nominal-the best (NTB) and the analysis of variance (ANOVA) of L27 orthogonal array are executed to minimize the variance of threshold voltage. The results show that the optimization and interaction method is achieved to perform the threshold voltage value with least variance is 0.3055 volts while the target value that is 0.302 ± 12.7% volts from value recommendation by the International Roadmap for Semiconductor prediction 2012.&lt;/span&gt;

Impact of balance resistor uncertainty on voltages across supercapacitors

Abstract In some applications, due to a relative low operating voltage of a supercapacitor cell, it is necessary to connect it in series to achieve a required operating voltage. However, due to the variation of supercapacitor parameters, there is a voltage imbalance across the supercapacitors connected in series, hence they should be balanced (equalized) by means of an appropriate technique. For this purpose, several active and passive balancing techniques are used. In this paper, the technique of passive voltage balancing using resistors is described. The phenomenon and the physical cause of voltage imbalance on supercapacitor (SC) cells are explained in detail. The paper gives a mathematical model that accurately describes voltage balancing using resistors. An uncertainty analysis was introduced to describe the expected voltage variation of supercapacitors before and after passive voltage balancing using resistors. All relevant expressions which determine the expected voltage variation before and after implementation of voltage balancing are derived. The derived expressions allow determination of voltage variance and uncertainty on SCs in the most unfavorable case of voltage imbalance. Based on the presented theory and derived expressions, the guidelines in the implementation of passive techniques for voltage balancing using resistors are given.

Confidence Level Optimization of DG Piecewise Affine Controllers in Distribution Grids

Distributed generators (DGs) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws with dead-band terms. Their settings are usually tuned using a decentralized method which uses local data and optimizes only the DG node behavior. It is shown that when short-term forecasts of stochastic powers are Gaussian and the grid model is assumed to be linear, nodes voltages can either be approximated by Gaussian or sums of truncated Gaussian variables. In the latter case, the voltages probability density functions (pdf) that are needed to compute the overvoltage risks or DG control effort are less straightforward than for normal distributions. These pdf are used into a centralized optimization problem which tunes all DGs control parameters. The objectives consist in maximizing the confidence levels for which voltages and powers remain in prescribed domains and minimizing voltage variances and DG efforts. Simulations on a real distribution grid model show that the truncated Gaussian representation is relevant and that control parameters can easily be updated even when extra DGs are added to the grid. The DG reactive power can be reduced down to 50% or node voltages variances can be reduced down to 30%.

Mitigating the Risk of Voltage Collapse Using Statistical Measures From PMU Data

With the continued deployment of synchronized phasor measurement units (PMUs), high sample rate data are rapidly increasing the real time observability of power systems. Prior research has shown that the statistics of these data can provide useful information regarding network stability, but it is not yet known how this statistical information can be actionably used to improve power system stability. To address this issue, this paper presents a method that gauges and improves the voltage stability of a system using the statistics present in PMU data streams. Leveraging an analytical solver to determine a range of “critical” bus voltage variances, the presented methods monitor raw statistical data in an observable load pocket to determine when control actions are needed to mitigate the risk of voltage collapse. A simple reactive power controller is then implemented, which acts dynamically to maintain an acceptable voltage stability margin within the system. Time domain simulations on 3-bus and 39-bus test cases demonstrate that the resulting statistical controller can outperform more conventional feedback control systems by maintaining voltage stability margins while loads simultaneously increase and fluctuate.

Transmission of temporally correlated spike trains through synapses with short-term depression.

Short-term synaptic depression, caused by depletion of releasable neurotransmitter, modulates the strength of neuronal connections in a history-dependent manner. Quantifying the statistics of synaptic transmission requires stochastic models that link probabilistic neurotransmitter release with presynaptic spike-train statistics. Common approaches are to model the presynaptic spike train as either regular or a memory-less Poisson process: few analytical results are available that describe depressing synapses when the afferent spike train has more complex, temporally correlated statistics such as bursts. Here we present a series of analytical results—from vesicle release-site occupancy statistics, via neurotransmitter release, to the post-synaptic voltage mean and variance—for depressing synapses driven by correlated presynaptic spike trains. The class of presynaptic drive considered is that fully characterised by the inter-spike-interval distribution and encompasses a broad range of models used for neuronal circuit and network analyses, such as integrate-and-fire models with a complete post-spike reset and receiving sufficiently short-time correlated drive. We further demonstrate that the derived post-synaptic voltage mean and variance allow for a simple and accurate approximation of the firing rate of the post-synaptic neuron, using the exponential integrate-and-fire model as an example. These results extend the level of biological detail included in models of synaptic transmission and will allow for the incorporation of more complex and physiologically relevant firing patterns into future studies of neuronal networks.

Analysis the Effect of Control Factors Optimization on the Threshold Voltage of 18 nm PMOS Using L27 Taguchi Method

This research paper is about the investigation of Halo Implantation, Halo Implantation Energy, Halo Tilt, Compensation Implantation and Source/Drain Implantation. They are types of control factors that used in achievement of the threshold voltage value. To support the successfully of the threshold voltage (VTH) producing, Taguchi method by using L27 orthogonal array was used to optimize the control factors variation. This analysis has involved with 2 main factors which are break down into five control factors and two noise factors. The five control factors were varied with three levels of each and the two noise factors were varied with two levels of each in 27 experiments. In Taguchi method, the statistics data of 18 nm PMOS transistor are from the signal noise ratio (SNR) with nominal-the best (NTB) and the analysis of variance (ANOVA) are executed to minimize the variance of threshold voltage. This experiment implanted by using Virtual Wafer Fabrication SILVACO software which is to design and fabricate the transistor device. Experimental results revealed that the optimization method is achieved to perform the threshold voltage value with least variance and the percent, which is only 2.16%. The threshold voltage value from the experiment shows -0.308517 volts while the target value that is -0.302 volts from value of International Technology Roadmap of semiconductor, ITRS 2012. The threshold voltage value for 18 nm PMOS transistor is well within the range of -0.302 ± 12.7% volts that is recommendation by the International Roadmap for Semiconductor prediction 2012.

On Voltage and Power Indicators for Thermal Noise in Metals

Recently a formula for the variance of the thermal voltage between the ends of a conductor has been proposed. We discuss this formula and present numerical values of theoretic voltage and power indicators for a selection of metals. The values obtained for copper are compared with some empirical data. AMS Subject Classification: 83B30, 83B31.

A Fast and Series-Stacked IGBT Switch With Balanced Voltage Sharing for Pulsed Power Applications

The series configuration of fast semiconductor switches seems to be the key component in the high-voltage and fast rising time pulse generation. In this approach, two important issues must be considered. The first is to provide a safe operating condition for the switches in transient intervals. The second is to design a gate drive system with the capability of driving a large number of discrete devices simultaneously. The aim of this paper is to obviate these two requirements. First, different factors affecting the unbalanced voltage sharing between the series switches are discussed. In this investigation, the switch-to-ground parasitic capacitance effect has been recognized as the major effect on the unbalanced voltage sharing in the transient interval. Two schemes for abating this effect are proposed. To solve the unbalanced voltage distribution, the structure with a snubber circuit in the clamp mode operation is suggested. This scheme can be used for any number of switches without destructively affecting their behavior. In addition, the output pulse with a fast rising time could be obtained by the proposed gate drive system. In order to evaluate the operation of the proposed structure, a stacked switch with the voltage capability of 36 kV is tested experimentally. The characteristics of the obtained pulse are the fast rising time (69.5 ns) with the dV/dt of 460 kv/ $\mu \text{s}$ and the wide range of the pulsewidth adjusting to 0.5–15 $\mu \text{s}$ . In addition, the voltage variance of the switches level in the series structure is about 10%.

A Precise FCC Estimation Algorithm Based on Recursive Least-Squares Identification of Li-Ion Batteries with Adaptive Forgetting Factor Tuning

Li-ion batteries are remarkable devices due to their high capability to store energy densely. The FCC (full charge capacity) estimation is essential for capturing the state of secondary battery. In this paper, precise FCC estimation is devised by estimation of internal parameter and SOC (state of charge). Comparted with the conventional identification techniques [1], the adaptive forgetting factor is more suitable for Li-ion battery. The open circuit voltage, OCV, is affected by SOC value. Therefore, the rate of change of OCV is not linear to time. In order to solve this problem, a heuristic adaptive forgetting factor is introduced based on terminal voltage and terminal current. To apply the system identification approach, the battery equivalent circuit model shown in Fig.1 is used. The subject of the system identification is OCV. OCV is physical quantity depending on SOC, and the relationship between OCV and SOC is given as Fig. 2. OCV-SOC curve has a significant role to achieve SOC estimation. The difference equation of u L is obtained by the equivalent circuit. Then, Equation (1) is obtained as observation function using the variables defined in Equation (2), and adding w (k) which is observation noise. T s is the sampling period. In equation (1), parameterθ regards as a unknown parameter, being estimated by using recursive least-squares identification. The value of R a, R b, C b, u OCV can be calculated by parameterθ with equation (3). SOC is obtained by referring the OCV-SOC curve. A heuristic forgetting factor λ(k) is defined by Equation (4). In this equation, G is gain, m uL is average variance of voltage u L preserving in buffer, and i avg is average value of current i. Estimation of OCV is performed using discharge patterns indicated in Fig.3. Table1 shows the average values of SOC estimation error. The average error is the smallest in the case of using the adaptive forgetting factor. Table2 shows the error dependent on temperature in the case of using the adaptive forgetting factor. SOC estimation is successful since the maximum value of average SOC estimation error is less than 0.05. Then, FCC is estimated with the estimated SOC. FCC is calculated by quotient of the value of current accumulation from time t0 to t1 and the change of estimated SOC value from t0 to t1. Ten percent discharges are executed from the 10 points of SOCs. The starting points of the discharge are from 0.97 to 0.92 by 0.05 intervals. The result of FCC estimation is shown Fig.4. In the case of 0.5A, the maximum value of average SOC estimation error is 0.049. Compared with the conventional techniques [2], the amount of calculation with proposed method is much less. The conventional technique [3] needs huge amount of data before estimation. In contrast, proposed method needs few data. This FCC estimation system pulls the maximum capability of secondary batteries with precise SOC estimation, and controls the batteries’ state by grasp of FCC. In addition, the amount of calculation and data needed preparing before estimation are less than conventional technique. Therefore, this proposed method can be implemented easily with inexpensive microcomputer. The experimentation has been executed in several conditions, and similar accurate results were obtained. [1] C. Fleischera, W. Waaga, H. Heyna, and D. U. Sauera, “On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models: Part 1. Requirements, critical review of methods and modeling,” J. Power Sources, vol. 260, no. 15, pp. 276-291, 2014. [2] T. Kim, Y. Wang, Z. Sahinoglu, T. Wada, S. Hara, W. Qiao, “A rayleigh quotient-based recursive total-least-squares online maximum capacity estimation for litium-ion batteries, ”IEEE trans. on energy conversion, vol. 30, no.3, pp. 842-850, 2015. [3] C. Hu, G. Jain, C. Schmidt, C. Strief, M. Sullivan, “Online estimation of lithium-ion battery capacity using sparse Bayesian learning, ” J. Power Sources, 289, pp. 105-113, 2015 Figure 1

Trigeminal neurons detect cellphone radiation: Thermal or nonthermal is not the question

ABSTRACTCellphone electromagnetic radiation produces temperature alterations in facial skin. We hypothesized that the radiation-induced heat was transduced by warmth-sensing trigeminal neurons, as evidenced by changes in cognitive processing of the afferent signals. Ten human volunteers were exposed on the right side of the face to 1 GHz radiation in the absence of acoustic, tactile, and low-frequency electromagnetic stimuli produced by cellphones. Cognitive processing manifested in the electroencephalogram (EEG) was quantitated by analysis of brain recurrence (a nonlinear technique). The theoretical temperature sensitivity of warmth-sensing neurons was estimated by comparing changes in membrane voltage expected as a result of heat transduction with membrane–voltage variance caused by thermal noise. Each participant underwent sixty 12-s trials. The recurrence variable r (“percent recurrence”) was computed second by second for the ∆ band of EEGs from two bilaterally symmetric derivations (decussated and nondecussated). Percent recurrence during radiation exposure (first 4 s of each trial) was reduced in the decussated afferent signal compared with the control (last four seconds of each trial); mean difference, r = 1.1 ± 0.5%, p < 0.005. Mean relative ∆ power did not differ between the exposed and control intervals, as expected. Trigeminal neurons were capable of detecting temperature changes far below skin temperature increases caused by cellphone radiation. Simulated cellphone radiation affected brain electrical activity associated with nonlinear cognitive processing of radiation-induced thermal afferent signals. Radiation standards for cellphones based on a thermal/nonthermal binary distinction do not prevent neurophysiological consequences of cellphone radiation.

Security implications of simultaneous dynamic and leakage power analysis attacks on nanoscale cryptographic circuits

The implications of simultaneous differential power analysis (DPA) and leakage power analysis (LPA) attacks are investigated on nanoscale cryptographic circuits which employ dynamic voltage scaling (DVS) or aggressive voltage scaling techniques. As compared with individually performing a DPA or an LPA attack on the corresponding cryptographic circuits, the number of required plaintexts to disclose the key with a 0.9 success rate reduces by 93.5% (as compared with DPA attacks) and 93.06% (as compared with LPA attacks), respectively, when the variance of supply voltage is 0.0833 V 2.

Congestion Avoidance for Recharging Electric Vehicles Using Smoothed Particle Hydrodynamics

In this paper, a novel approach for recharging electric vehicles (EVs) is proposed based on managing multiple discrete units of electric power flow, named energy demand particles (EDPs). Key similarities between EDPs and fluid particles (FPs) are established that allow the use of a smoothed particle hydrodynamics (SPH) method for scheduling the recharging times of EVs. It is shown, via simulation, that the scheduling procedure not only minimizes the variance of voltage drops in the secondary circuits, but it also can be used to implement a dynamic demand response and frequency control mechanism. The performance of the proposed scheduling procedure is also compared with alternative approaches recently published in the literature.

순환최소자승법을 이용한 직류도시철도 변전소의 가선전압변동 모델링

The DC overhead line voltage of an electric railway substation swings depending on the accelerating and regenerative-braking energy of trains, and it deteriorates the energy quality of the electric facility in the DC railway substation and restricts the powering and braking performance of subway trains. Recently, an energy storage system or a regenerative inverter has been introduced into railway traction substations to diminish both the variance of the overhead line voltage and the peak power consumption. In this study, the variance of the overhead line voltage in a DC railway substation is modelled by RC parallel circuits in each feeder, and the RC parameters are estimated using the recursive least mean square (RLMS) scheme. The forgetting factor values for the RLMS are selected using simulated annealing optimization, and the modelling scheme of the overhead line voltage variation is evaluated through raw data measured in a downtown railway substation.

Synaptic transmission of spike trains with arbitrary interspike intervals

Short-term synaptic depression, caused by depletion of releasable neurotransmitter vesicles, modulates the strength of neuronal connections in an activity-dependent manner [1,2]. Quantifying the statistics of this form of synaptic transmission requires the development of stochastic models linking probabilistic neurotransmitter release with the spike-train statistics of the presynaptic population [3,4]. A common approach has been to model the presynaptic spike train as either regular or a memory-less Poisson process [5] few analytical results are available that describe the behaviour of a depressing synapse when the afferent spike train has more complex, temporally correlated statistics. Recently, we have derived a series of results that allow for the fraction of occupied release sites and the neurotransmitter release probability to be calculated for a presynaptic spike train with arbitrary interspike interval (ISI) statistics. The results take a particularly compact form when the presynaptic spike times are generated by a renewal process, i.e. when the ISIs are independent. This encompasses a broad range of models that are currently used for circuit and network analyses, including the class of integrate-and-fire models. Our approach also allows for the postsynaptic voltage mean and variance to be calculated, which in turn allows for an approximation of the firing rate of a neuron driven by depressing synapses from non-Poissonian presynaptic neurons (Figure 1). These results will allow for the incorporation of more complex and physiologically relevant firing patterns

Electrode Erosion Characteristics of Repetitive Long-Life Gas Spark Switch Under Airtight Conditions

With the rapid developments in pulse power technology, the gas spark switch has broadened its application in both industrial fields and research fields, such as the extraction of unconventional gas resources and underwater electrical wire explosion. Thus, the repetitive switch needs high current capability, small breakdown voltage variance, and long lifetime in an airtight cavity. The performances of the switch directly influence the output characteristics of the system, but electrode erosion is inevitable, which may decrease the self-breakdown voltage and the lifetime. The purpose of this paper was to investigate the electrode erosion characteristics under adverse conditions. The cathode showed a worse erosion surface. Compared with the central zone of the electrodes, the outer zone showed a worse surface roughness for both the cathode and the anode.

Copper Ion-containing Ionic Liquids Provide Improved Endurance and Switching Voltage Distributions of Conducting-bridge Random Access Memory

Abstract Remarkable improvement of cycling endurance and working voltage variance has been achieved by the addition of a trace amount of a [bmim][Tf2N] solution containing Cu(Tf2N)2 to the HfO2 film layer of a CB-RAM with a Cu/HfO2/Pt structure.