40 research outputs found

    A 9.2-ns to 1-ÎĽs digitally controlled multituned deadtime optimization for efficient GaN HEMT power converters

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    ABSTRACT: This paper presents a tunable new deadtime control circuit providing an optimal delay for power converter optimization. Our method can reduce the deadtime loss while improving the efficiency and power density of a given power converter. The circuit presents a reconfigurable delay element to generate a wide range of deadtime for different power conversion applications with varying loads and input voltages. The optimal deadtime equation for buck converters is derived, and its dependency on the input voltage and load is discussed. Experimental results show that the presented circuit can provide a wide range of deadtime delays, ranging from 9.2 ns to 1000 ns. The power consumption of the presented circuit is measured for different capacitive loads (CL) and operating frequencies ( f s). The circuit consumed a power between 610 µW and 850 µW across the measured deadtime ranges while CL = 12 pF, Vdd = 3.3 V, and fs = 200 kHz. The proposed deadtime generator can operate up to 18 MHz when the minimum deadtime of 9.2 ns is selected. The presented circuit occupies an area of 150µ m × 260µm. The fabricated chip is connected to a buck converter to validate the operation of the proposed circuit. The efficiency of a typical buck converter with minimum TDLH and optimal TDHL at ILoad = 25 mA is improved by 12% compared to a converter with a fixed deadtime of TDLH = TDHL = 12 ns

    Toward an energy-efficient high-voltage compliant visual intracortical multichannel stimulator

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    ABSTRACT: We present, in this paper, a new multichip system aimed toward building an implantable visual intracortical stimulation device. The objective is to deliver energy-optimum pulse patterns to neural sites with needed compliance voltage across high electrode–tissue interface impedance of implantable microelectrodes. The first chip is an energy-efficient stimuli generator (SG), and the second one is a high-impedance microelectrode array driver (MED) output stage. The fourchannel SG produces rectangular, half-sine, plateau-sine, and other types of current pulse with stimulation current ranging from 2.32 to 220 μA per channel. The microelectrode array driver is able to deliver 20 V per anodic or cathodic phase across the microelectrode–tissue interface for ±13 V power supplies. The MED supplies different current levels with the maximum value of 400 μA per input and 100 μA per output channel simultaneously to 8–16 stimulation sites through microelectrodes, connected either in bipolar or monopolar configuration. Both chips receive power via inductive link and data through capacitive coupling. The SG and MED chips have been fabricated in 0.13-μm CMOS and 0.8-μm 5-/20-V CMOS/double-diffused metal-oxidesemiconductor technologies. The measured dc power budgets consumed by low- and mid-voltage chips are 2.56 and 2.1 mW consecutively. The system, modular in architecture, is interfaced with a newly developed platinum-coated pyramidal microelectrode array. In vitro test results with 0.9% phosphate buffer saline show the microelectrode impedance of 70 Ωk at 1 kHz

    The Effect of EMI Generated from Spread-Spectrum-Modulated SiC-Based Buck Converter on the G3-PLC Channel

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    6siPower line communication (PLC) is increasingly emerging as an important communication technology for the smart-grid environment. As PLC systems use the existing infrastructure, they are always exposed to conducted electromagnetic interference (EMI) from switching mode power converters, which need to be tightly controlled to meet EMC regulations and to ensure the proper operation of the PLC system. For this purpose, spread-spectrum modulation (SSM) techniques are widely adopted to decrease the amplitude of the generated EMI from the power converters so as to comply with EMC regulations. In this paper, the influence of a spread-spectrum-modulated SiC-based buck converter on the G3-PLC channel performance is described in terms of channel capacity reduction using the Shannon–Hartley equation. The experimental setup was implemented to emulate a specific coupling path between the power and communication circuits and the channel capacity reduction was evaluated by the Shannon–Hartley equation in several operating scenarios and compared with the measured frame error rate. Based on the obtained results, SSM provides the EMI spectral peak amplitude reduction required to pass the electromagnetic compatibility (EMC) tests, but results in increased EMI-induced channel capacity degradation and increased transmission error rate in PLC systems.openopenWaseem El Sayed; Piotr Lezynski; Robert Smolenski; Niek Moonen; Paolo Crovetti; Dave W. P. ThomasEl Sayed, Waseem; Lezynski, Piotr; Smolenski, Robert; Moonen, Niek; Crovetti, PAOLO STEFANO; Thomas, Dave W. P

    Modeling, design and implementation of a low-power FPGA based asynchronous wake-up receiver for wireless applications

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    Power consumption is a major concern for wireless sensor networks (WSNs) nodes, and it is often dominated by the power consumption of communication means. For such networks, devices are most of the time battery-powered and need to have very low power consumption. Moreover, for WSNs, limited amount of data are periodically sent and then the radio should be in idle or deep sleep mode most of the time. Thus using event-triggered radios is well suited and could lead to significant reduction of the overall power consumption of WSNs. Therefore this paper explores the design of an asynchronous module that can wake up the main receiver when another node is trying to send data. Furthermore, we implement the proposed solution in an FPGA to decrease the fabrication cost for low volume applications and make it easier to design, re-use and enhance. To decrease the static power consumption, we explore the possibility of reducing the supply voltage. The observed overall power consumption is under 5ÎĽW at 250 kbps. Moreover, using a new asynchronous design technique, we observed that power consumption can be further reduced

    A Novel Framework for Parametric Loewner Matrix Interpolation

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    The generation of black-box macromodels of passive components at the chip, package, and board levels has become an important step of the electronic design automation (EDA) workflow. The vector fitting (VF) scheme is a very popular method for the extraction of such macromodels, and several multivariate extensions are now available for embedding external parameters in the model structure, thus enabling model-based variability analysis and design optimization. The Loewner matrix interpolation framework was recently suggested as an effective and promising alternative macromodeling approach to VF. In this article, we propose a parametric version of Loewner interpolation, which embeds orthogonal polynomials as an integral part of the parameterization framework. This approach is shown to be efficient and accurate and presents various advantages with respect to competing multivariate rational interpolation methods. These advantages include better control of model smoothness in the parameter space and a particularly efficient implementation of the singular value decomposition, which is the core of the model extraction scheme. These advantages are confirmed through several examples relevant for signal and power integrity applications

    Magnetic properties of ferromagnetic particles under alternating magnetic fields: Focus on particle detection sensor applications

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    © 2018 by the authors. Licensee MDPI, Basel, Switzerland. The electromagnetic wear particles detection sensor has been widely studied due to its ability to monitor the wear status of equipment in real time. To precisely estimate the change of the magnetic energy of the sensor coil caused by the wear particles, the magnetic property models of wear particles under the alternating magnetic field was established. The models consider the hysteresis effect and the eddy current effect of the wear particles. The analysis and experimental results show that with the increase of the effective field frequency, the change of the magnetic energy caused by the wear particles gradually decrease, which makes the induced electromotive force output by the sensor reduce with the decrease of the particle speed, so a signal compensation method is presented to obtain a unified signal when the same wear particle passing through the sensor in different speeds. The magnetic coupling effect between the two adjacent wear particles is analyzed. The result illustrates that the change of the magnetic energy caused by the dual wear particles system is larger than the sum of the energy variation caused by two independent wear particles, and with the increase of the interparticle distance, the magnetic coupling effect gradually weakens and disappears

    A Comprehensive Survey on RF Energy Harvesting: Applications and Performance Determinants

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    \ua9 2022 by the authors. Licensee MDPI, Basel, Switzerland.There has been an explosion in research focused on Internet of Things (IoT) devices in recent years, with a broad range of use cases in different domains ranging from industrial automation to business analytics. Being battery-powered, these small devices are expected to last for extended periods (i.e., in some instances up to tens of years) to ensure network longevity and data streams with the required temporal and spatial granularity. It becomes even more critical when IoT devices are installed within a harsh environment where battery replacement/charging is both costly and labour intensive. Recent developments in the energy harvesting paradigm have significantly contributed towards mitigating this critical energy issue by incorporating the renewable energy potentially available within any environment in which a sensor network is deployed. Radio Frequency (RF) energy harvesting is one of the promising approaches being investigated in the research community to address this challenge, conducted by harvesting energy from the incident radio waves from both ambient and dedicated radio sources. A limited number of studies are available covering the state of the art related to specific research topics in this space, but there is a gap in the consolidation of domain knowledge associated with the factors influencing the performance of RF power harvesting systems. Moreover, a number of topics and research challenges affecting the performance of RF harvesting systems are still unreported, which deserve special attention. To this end, this article starts by providing an overview of the different application domains of RF power harvesting outlining their performance requirements and summarizing the RF power harvesting techniques with their associated power densities. It then comprehensively surveys the available literature on the horizons that affect the performance of RF energy harvesting, taking into account the evaluation metrics, power propagation models, rectenna architectures, and MAC protocols for RF energy harvesting. Finally, it summarizes the available literature associated with RF powered networks and highlights the limitations, challenges, and future research directions by synthesizing the research efforts in the field of RF energy harvesting to progress research in this area

    Sparse methods for blind source separation of frequency hopping rf sources

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    Blind source separation (BSS) is performed on frequency hopping (FH) sources. These radio frequency (RF) signals are observed by a uniform linear array (ULA) over a Spatial Channel Model (SCM) in four different propagation environments: (i) line-of-sight (LOS), (ii) single-cluster, (iii) multiple-cluster, and (iv) LOS with interference. The sources are spatially sparse, and their activity is intermittent and assumed to follow a hidden Markov model (HMM). BSS is achieved by utilizing direction of arrival (DOA) of the sources and clusters. A sparse detection framework is applied to obtain estimates of the sources\u27 FH and DOA patterns. The solutions are binned according to a frequency grid and a DOA dictionary. A method is proposed to reduce the effect of falsely detected active sources and mitigate the effects of interference, by leveraging the activity model of the intermittent sources. The proposed method is a state filtering technique, referred to as hidden state filtering (HSF), and is used to improve BSS performance. Multiple activity patterns associated with different DOAs are considered similar if they match over a prescribed fraction of the time samples. A method pairing DOA and FH estimates associates the FH patterns to specific sources via their estimated DOAs. Numerical results demonstrate that the proposed algorithm is capable of separating multiple spatially sparse FH sources with intermittent activity, by providing estimates of their FH patterns and DOA

    Prospects on Time-Domain Diffuse Optical Tomography Based on Time-Correlated Single Photon Counting for Small Animal Imaging

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    This paper discusses instrumentation based on multiview parallel high temporal resolution (<50 ps) time-domain (TD) measurements for diffuse optical tomography (DOT) and a prospective view on the steps to undertake as regards such instrumentation to make TD-DOT a viable technology for small animal molecular imaging. TD measurements provide information-richest data, and we briefly review the interaction of light with biological tissues to provide an understanding of this. This data richness is yet to be exploited to its full potential to increase the spatial resolution of DOT imaging and to allow probing, via the fluorescence lifetime, tissue biochemical parameters, and processes that are otherwise not accessible in fluorescence DOT. TD data acquisition time is, however, the main factor that currently compromises the viability of TD-DOT. Current high temporal resolution TD-DOT scanners simply do not integrate sufficient detection channels. Based on our past experience in developing TD-DOT instrumentation, we review and discuss promising technologies to overcome this difficulty. These are single photon avalanche diode (SPAD) detectors and fully parallel highly integrated electronics for time-correlated single photon counting (TCSPC). We present experimental results obtained with such technologies demonstrating the feasibility of next-generation multiview TD-DOT therewith
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