Wide Input Range Research Articles

비반전 동기 벅-부스트 컨버터의 CRM 제어

Buck-Boost Converter is a non-insulated Converter with a wide input range and could receive various voltage as an input However, as research for high efficiency of power conversion system progresses, the need to reduce semiconductor losses is increased. Buck-Boost Converter has a disadvantage in that a high conduction losses and a switching losses due to a forward voltage drop of diode. In this paper, the reduction of conduction losses was verified by comparing conduction losses of Synchronous Buck-Boost Converter and conduction losses of conventional Buck-Boost Converter, and the application of CRM(Critical Conduction Mode) control was demonstrated through experiments.

A wide input range, external capacitor-less LDO with fast transient response

A high voltage, external capacitor-less low-dropout regulator (HVLDO) with transient enhancement loop is presented in this work. The proposed HVLDO is designed with high withstand voltage laterally-diffused MOS (LDMOS) transistors and a transient enhancement loop is proposed to properly inject/sink current to/from the gate and output nodes of the power transistors to achieve fast transient response and high stability. Fabricated in 0.5µm SOI BCD process, the HVLDO occupies an active area of 0.29mm2. Operating with an input voltage ranging from 5.2 to 20V, it supplies an output voltage of 5V and a maximum load of 100mA. For all load conditions, this design has the power supply rejection of -49dB@100kHz, the phase margin over 68.4deg and achieves a temperature coefficient of 13.15ppm/°C. Measurement results show that this design has a line regulation of 0.88mV/V and a load regulation of 0.22mV/mA. The proposed HVLDO features fast line transient response of 60/20mV@9.8V/µs, fast load transient response of 30/70mV@100mA/µs, and recovery time of 2µs without external capacitors. Compared with the prior art, this work achieves the best transient FOM of 12.19fs.

Efficient Power Factor Correction using Chaotic Artificial Bee Colony Algorithm-Based FOPID Controller in DC-DC Zeta Converters

Design and implementation of a Chaotic Artificial Bee Colony (ChABC) algorithm based Fractional Order Proportional Integral Derivative (FOPID) controller for Power Factor Correction (PFC) in Switched Mode Power Supply (SMPS) using DC-DC Zeta converter is proposed in this article. The dc-dc zeta converter has the advantages of high efficiency over a wide range of input and output voltages, an enormous power factor, low line current harmonics, and can convert voltages both up and down. Operating the converter in discontinuous conduction mode (DCM) achieves power factor correction and simplifies the control circuit. This article describes the design characteristics, operating principles, and controller design of the proposed converter. The design, analysis, modeling and advancement of the ChABC algorithm based FOPID controller in SMPS offers the better power quality and faster convergence of regulated output voltage. Simulation and experimental results are presented to verify power factor, % Total Harmonic Distortion (THD), output voltage regulation, stability, and robustness for various load, line, and reference voltages.

Abstract 6162: High resolution detection of HER2 copy number variation in admixed breast cancer cell lines and HER2+ FFPE donor tissue using a digital PCR multigene reference panel

Abstract The measurement of HER2 (ERBB2) gene amplification guides both the prognosis and treatment of breast cancer, as amplification correlates with worse outcomes and the recommendation for anti-HER2 treatment. Digital PCR (dPCR) can serve as a useful tool for the direct quantification of copy number variants (CNV) in this gene, without the need for calibration standards as required for qPCR, or labor-intensive histological techniques such as FISH. Furthermore, increasing the number of available partitions in a digital PCR reaction can yield substantial gains in precision, thus offering the potential for ultra-high resolution discrimination of copy number changes. In this study, we evaluated the utility of a multiplex dPCR assay for the high-resolution detection of HER2 copy number variation in clinically relevant samples. The precision achievable by digital PCR correlates with the number of partitions, and the resolution of small CNV differences greatly relies on high precision. We utilized a dPCR setup with ~100,000 physical partitions per reaction, which allowed for a theoretical precision (relative confidence) of 1%, assuming optimal input and template. Five single-plex primer and probe sets, published by the National Institute of Standards and Technology, were assembled and optimized into a multiplex configuration. The final 5-plex consisted of four reference genes and HER2 as the target of interest. The accuracy and precision of the optimized five-plex assay was tested in nine breast cancer cell lines with established HER2 amplification ratios, ranging from 1.3 to 70 fold. The assay demonstrated the precise and accurate measurement of the HER2 amplification ratio across all nine cell lines over a wide dynamic range of sample input. Along with increasing the reaction partition number, the use of multiple reference genes also improved the precision of the HER2 amplification ratio measurement and avoided inaccurate copy number calls due to outlier references. The resolution of the assay was evaluated using admixed samples simulating low tumor fraction. A minimum of a 1.03 fold difference (3% difference from wild type) was detected with statistical significance. Assay concordance was evaluated against IHC-characterized HER2+ FFPE donor tissue with concordant FISH/CISH results. The assay demonstrated robust performance in clinically relevant sample types, supporting further investigation of dPCR as a complementary or even alternative diagnostic approach to current methods. Citation Format: Tyler Landrith, Samantha Smith, Jennifer Chan, Mari Christensen, Yu Chuan Tai, Megan Gonzales, William Yee, Nicolas Newton, Wouter Pattje, Patrick Bogard, Wei Yang. High resolution detection of HER2 copy number variation in admixed breast cancer cell lines and HER2+ FFPE donor tissue using a digital PCR multigene reference panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6162.

Abstract 764: Automated walk away NGS sample preparation for constructing in-line molecular barcoded RNA libraries from Fresh Frozen and FFPE samples

Abstract RNA-Seq is a revolutionary technology for transcriptome analysis, which has been used to quantify transcript levels, confirm gene annotation, identify novel transcripts, splice variants, and fusion detection. Traditionally, the usefulness of RNA-Seq has been limited by pre-analytical (sample availability, low integrity, tumor heterogeneity, complex protocols) and analytical factors (small mRNA fraction, high read duplicate rate), which can lead to higher costs, longer turnaround times, and false negative results. We have developed and automated a streamlined workflow for construction of highly complex RNA Libraries from fresh frozen and FFPE samples that addresses these concerns. We use target enrichment by bait selection with FFPE-derived samples, where rRNA depletion is found to be inconsistent and poly(A) enrichment cannot be used due to degradation of the source material. A fully automated protocol using pre-aliquoted reagents, has been optimized on the Magnis NGS Prep System for a wide range of RNA inputs (10-200 ng), various sample types (Intact and FFPE total RNA) and equipped with 192 Unique Dual sample Indices (UDI) to minimize the effects of possible index hopping and contamination. Addition of in-line molecular barcodes incorporated at the ligation step helps differentiate fragmentation from PCR duplicates, which increases the total number of reads available for further analysis (gene expression and fusion detection). With minimal risk of contamination, this automated protocol delivers up to eight target-enriched NGS Illumina sequencing-ready cDNA libraries from total RNA input per run in about 12 hours without the need of any user intervention. Both catalog and custom probes can be utilized, and PCR cycles can easily be adjusted from the touchscreen to optimize the library yields. For Research Use Only. Not for use in Diagnostic procedures. Citation Format: Saharnaz Bigdeli, Bahram Arezi, Jan Godoski, Denise Rhodes, Ryan Aguilar, Karen William, Bernd Buehler, Ji Zhu, Ronda Allen. Automated walk away NGS sample preparation for constructing in-line molecular barcoded RNA libraries from Fresh Frozen and FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 764.

Projection onto the exponential cone: a univariate root-finding problem

The exponential function and its logarithmic counterpart are essential corner stones of nonlinear mathematical modelling. In this paper, we treat their conic extensions, the exponential cone and the relative entropy cone, in primal, dual and polar form, and show that finding the nearest mapping of a point onto these convex sets all reduce to a single univariate root-finding problem. This leads to a fast projection algorithm shown numerically robust over a wide range of inputs.

A Comparison of UAV-Derived Dense Point Clouds Using LiDAR and NIR Photogrammetry in an Australian Eucalypt Forest

Light detection and ranging (LiDAR) has been a tool of choice for 3D dense point cloud reconstructions of forest canopy over the past two decades, but advances in computer vision techniques, such as structure from motion (SfM) photogrammetry, have transformed 2D digital aerial imagery into a powerful, inexpensive and highly available alternative. Canopy modelling is complex and affected by a wide range of inputs. While studies have found dense point cloud reconstructions to be accurate, there is no standard approach to comparing outputs or assessing accuracy. Modelling is particularly challenging in native eucalypt forests, where the canopy displays abrupt vertical changes and highly varied relief. This study first investigated whether a remotely sensed LiDAR dense point cloud reconstruction of a native eucalypt forest completely reproduced canopy cover and accurately predicted tree heights. A further comparison was made with a photogrammetric reconstruction based solely on near-infrared (NIR) imagery to gain some insight into the contribution of the NIR spectral band to the 3D SfM reconstruction of native dry eucalypt open forest. The reconstructions did not produce comparable canopy height models and neither reconstruction completely reproduced canopy cover nor accurately predicted tree heights. Nonetheless, the LiDAR product was more representative of the eucalypt canopy than SfM-NIR. The SfM-NIR results were strongly affected by an absence of data in many locations, which was related to low canopy penetration by the passive optical sensor and sub-optimal feature matching in the photogrammetric pre-processing pipeline. To further investigate the contribution of NIR, future studies could combine NIR imagery captured at multiple solar elevations. A variety of photogrammetric pre-processing settings should continue to be explored in an effort to optimise image feature matching.

How railway stations can transform urban mobility and the public realm: The stakeholders’ perspective

Railway stations are massive infrastructures through which people, products, materials, and energy flow every day. They usually gather a multitude of functions and provide a wide range of services to users based on their respective specific features. Thus, railway stations have the potential to play a critical role in reshaping our cities in a sustainable manner by facilitating intermodality, green and active modes of transport and logistics, and by gathering proximity services. In this reshaping process, implementing effective and seamless mobility, as well as the proximity of services, are key challenges. However, no urban transformation process can take place without the involvement and commitment of the respective stakeholders. This paper aims to form an understanding of the views these stakeholders have towards the potential of railway stations transformation, for the broad European context, to carve out first paths towards actually achieving that transformation. This study analyses a wide range of inputs and considerations made during a series of workshops held in 2021 by the EIT Urban Mobility where experts from a wide range of fields exchanged their experiences and ideas around the topics of urban mobility and public realm. In this process, railway stations emerged as a key player to meet the challenges of cities’ sustainable development. After analysing their potential and exploring policy obstacles that are currently hampering such a transformation, this paper suggests a series of recommendations to better exploit railway stations, gained from the stakeholders’ perspective.

A novel self‐adaptive rectifier with wide input range

A 2.45-GHz self-adaptive rectifier based on a two-way Gysel power divider (PD) with switch networks (SN), an impedance transform network (ITN), a feedback network (FN) and two rectifiers is developed in this paper. The SNs and ITN are controlled by FN according to output voltages. The rectifier is in single-path mode at a low power level and switches to two-path mode at a high power level. It has been simulated, fabricated and tested. The original input power range when efficiency is above 50% is from −3 to 11 dBm. After being connected to the PD, the input power range is expanded to −6 to 15 dBm, with a maximum efficiency of 71.1% at 1400 Ω. The proposed design only leverages one type of rectifier. The outputs are symmetric.

Common Grounded Wide Voltage-Gain Range DC–DC Converter With Zero Input Current Ripple and Reduced Voltage Stresses for Fuel Cell Vehicles

A dc–dc converter used for fuel cell vehicles should be characterized by a wide voltage-gain range and low input current ripple. In order to meet the above requirements, a new nonisolated dc–dc converter consisting of an active switched-inductor cell, a zero current ripple cell, and a switched-capacitor (SC) cell was proposed in this article. The proposed converter integrates with the advantages of a wide voltage-gain range, zero input current ripple, low voltage stresses across power semiconductors, and common ground structure. Thanks to the use of a zero current ripple cell, not only the input current ripple is reduced but also the energy transfer path of the SC cell is changed, thereby reducing the instantaneous peak current of the SC structure. The operating principles, the characteristics analysis, and the parameter design of the proposed converter are given. In addition, to show the merits of the proposed converter, a comparison study is demonstrated. Finally, a prototype of 400 V, 1000 W/50 kHz is developed to validate the effectiveness of the proposed converter.

Switched-capacitor voltage buck converter with variable step-down and switching frequency controllers for low-power and high-efficiency IoT devices

This paper proposes a switched-capacitor voltage buck converter (SC-VBC) with variable step-down controller (VSC) and switching frequency controller (SFC). The VSC and SFC change the step-down ratio and switching frequency of the SC-VBC in accordance with the input voltage and load current, respectively, enabling the converter to operate efficiently with a wide-ranging input voltage and load current. Measurements of a prototype chip demonstrated that our SC-VBC achieved a wide input voltage range and high efficiency of 1.3–2.6 V and 69%, respectively.

Analysis and Experiment of Self‐Powered, Pulse‐Based Energy Harvester Using 400 V FEP‐Based Segmented Triboelectric Nanogenerators and 98.2% Tracking Efficient Power Management IC for Multi‐Functional IoT Applications

AbstractA self‐powered system for the Internet of Things (IoT) is demonstrated for efficient energy harvesting of naturally available mechanical energy. In this system, new contact‐separation mode triboelectric nanogenerators (TENGs), based on fluorinated ethylene propylene, are investigated using the segmented multi‐TENG configuration to reduce the effect of parasitic capacitance. The TENG extraction is optimized using a unit step excitation involved with the Dawson function to achieve a high voltage (400 V) and a high current (26.6 µA). To fully extract the power of the TENGs, the power management integrated circuit (PMIC) specially designed for adaptively controlled, high‐voltage (HV) maximum power point tracking (MPPT) is proposed. The PMIC implemented in a bipolar CMOS‐DMOS 180 nm process can handle a wide input range (5–70 V) by consuming 420 nW. The MPPT control allows a wide range of impedance matching from 10 to 300 MΩ, achieving a tracking efficiency of up to 98.2%. The end‐to‐end efficiency of 88% demonstrates state‐of‐the‐art performance. To supply a higher instantaneous power than that available from the TENGs, a duty‐cycling technique is successfully demonstrated. The proposed energy harvesting system provides a promising approach to realizing sustainable and autonomous energy sources for various IoT applications.

An energy-based quantitative coal burst proneness rating system for development roadways

Coal burst is one of the principal hazards in development panels of underground coal mines. This study develops a practical approach to quantitatively estimate coal burst proneness in development roadways. A rigorous numerical and statistical study is conducted to establish a novel burst proneness rating (BPR) system based on energy release characteristics. The rating system includes eight geological and geotechnical factors and covers a wide range of inputs. A dataset including 18 field cases (9 burst and 9 no-burst cases) was used to validate the proposed rating system and to determine a critical BPR value (i.e. the threshold value of burst cases). The probability hat{p}_{burst} of coal bursts was then obtained based on BPR logistic regression. The computed rating values using the BPR system can distinguish burst and no-burst cases that are in line with the scope of the eight input parameters in this study. The model results also showed that the mining depth was the most significant contributor of the energy release, along with roof elastic modulus and coal mass conditions. These results suggested that an environment that consists of relatively weak and brittle coal under high vertical stresses and surrounded by a relatively soft strata could promote unstable failures such as coal bursts.

Resonant hybrid flyback: A novel topology with wide voltage range for DC microgrid applications

DC microgrids are becoming very popular due to the increasing deployment of distributed power generation systems. This presents new challenges for power converters, including how to achieve a wide range of input and output voltages in a small volume. State-of-the-art solutions include flyback-based and LLC-based converters. The first ones are bulky due to the large size of magnetic required to store the energy and their efficiency is limited by their capability to recycle the energy from parasitic elements. The second ones offer good efficiency but a limited range for input and output voltage, and may involve a large number of semiconductors. This paper studies the application of a novel topology, the asymmetrical half-bridge flyback, whose hybrid operation principle combines the advantages of forward and flyback converters while keeping a small number of switches. A design process to accomplish the outstanding requirements with the topology is presented. The theoretical analyses are supporter by a 240 W DC–DC prototype with an input range of 320 V–400 V and an output range of 5 V–24 V. A peak efficiency of 97.6 % is measured. The achieved power density of the converter is 65 W/inch3 uncased. Finally, a comprehensive numerical comparison with the LLC and flyback converters in the state of the art is carried out to show the potential of the proposal.

High Efficiency and High Power Density Partial Power Regulation Topology With Wide Input Range

Data centers require high efficiency and high power-density dc–dc converter with wide input range and galvanic isolation. To overcome the drawbacks of traditional single-stage <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> and two-stage solutions, a novel partial power regulation topology with wide input range is proposed in this article. The proposed topology delivers the load power through a three-ports <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> -based dc transformer regulated DCX (DCX). A pulsewidth modulation (PWM) converter is cascaded with one of the input ports of the DCX and then in series with the other input port to regulate the output voltage. Since a single transformer and a partial power PWM converter are employed, high power density can be achieved. Furthermore, only a portion of the load power is transferred by the PWM converter, the efficiency sacrifice is reduced. By introducing an appropriate negative current, the zero voltage switching of the PWM is also achieved. Furthermore, when the input voltage approaches the lower or the upper limit, the switching frequency of the PWM regulator can be ultralow. As a result, switching losses and core losses are further reduced. Finally, a prototype with 190—475 V input and 12 V/500 W output is demonstrated, which achieves a peak efficiency of up to 97.2% and a power density of 153 W/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> .

A 40.68-MHz Active Rectifier With Cycle-Based On-/Off-Delay Compensation for High-Current Biomedical Implants

This article presents a 40.68-MHz active rectifier for high-current biomedical implants. Cycle-based timing control (CBTC) is proposed to significantly extend the duration for compensating both turn-on and turn-off delays of active diodes at 40.68 MHz, thereby improving both the power conversion efficiency (PCE) and the voltage conversion ratio (VCR) of the rectifier. The supply independent ramp, the delay-mimicking sample-and-hold (DMSH) circuit, and the low-voltage (LV)-stress startup scheme are also developed to maintain high PCE and VCR, and ensure rectifier reliability over a wide input range. Implemented in standard 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS, the proposed fully integrated rectifier delivers a maximum output power of 207 mW and operates at 40.68 MHz to enable the use of a small-diameter receiver coil of 4 mm. This rectifier is the first to achieve full turn-on and turn-off delay compensation at 40.68 MHz, so its maximum PCE and VCR obtain 86% and 96.3%, respectively. Compared with the prior art, this work not only provides more stable high PCE and VCR over a wider input range from 1.9 to 3.8 V at 40.68 MHz but also uses the smallest receiver coil for wireless power delivery.

A Curve-fit Traction Coefficient Relation of Mixed EHL Line Contact with Hydraulic Fluid and Steel Surfaces

Accurate modeling of hydraulic gear machine meshing torque loss, considering possible asperity contact, is required for better prediction of its hydromechanical efficiency. A model for predicting the mixed thermal EHL line contact traction coefficient is implemented in this study, considering experimental density and viscosity properties. Simulation results of traction coefficient are validated with experiments at two operating conditions. The defining components of the traction coefficient, the asperity load ratio and the hydrodynamic component are obtained at wide range of inputs. Finally, explicit curve-fit formulations of the asperity load ratio and the hydrodynamic component of traction coefficient are created in terms of input non-dimensional variables, which can be used for modeling the torque loss in a simple yet accurate way.

A 4.7-ps Resolution Recirculating Cyclic Vernier TDC Using DWA-Based Mismatch Correction and a Register-Based Time Amplifier

Herein, we present a recirculating (RC) cyclic Vernier time-to-digital converter (TDC) using dynamic element matching and a register-based time amplifier (TA). The RC TDC reuses a single conversion stage for multiple conversions that are suitable for low power and compact realization. Good matching is achieved between multiple conversions because the same stage is reused. Processing the amplified residue further enhances the TDC resolution. We propose a new TA based on a time register that achieves a well-controlled time magnification over a wide input range. Unlike conventional approaches based on regeneration or meta-stability, the register-based TA does not suffer from a narrow input range. The proposed TA achieves a relatively high gain accuracy (< 1.5%) over a wide input range from 40 to 400 ps. Compact TDC implementation is further facilitated using the multiphase operation of a gated ring oscillator (GRO) in a cyclic Vernier structure. Using the phase-preserving characteristic of the GRO, the mismatch is first order shaped by data weight averaging. The RC TDC fabricated using a 28-nm CMOS process is realized in a small area of 0.0096 mm2. Measurements show that the TDC can be successfully configured into four gain modes with a resolution of 11.5, 7.7, 5.8, and 4.7 ps in a 12-bit dynamic range. The full range linearity measurement shows an integral nonlinearity of less than 1.48 LSB. The power consumption is 0.188 mW at a conversion rate of 3.51 MHz, leading to a favorable figure of merit of 0.032 pJ/conv.-step. The results show the effectiveness of the RC structure in realizing a high-performance, compact TDC.

A 95% Efficiency Reusable Adaptive Time Control Bidirectional Buck Charge Converter for Wide Input Range Operation

A 95% efficiency reusable adaptive time control bidirectional buck charge converter for wide input range operation is presented in this brief. For keeping the switching frequency stable, a reusable adaptive time generator is proposed to improve the transient response and stability of the system. In the buck charging and reverse boost discharging mode, the circuit adopts adaptive off-time control and on-time control, respectively. In order to ensure that the converter can work over a wide input range in the above two working modes, a maximum voltage selection circuit is used to generate a stable high-voltage output signal as the power supply voltage of the system. The proposed bidirectional converter has been fabricated using 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {\mathrm {\mu }}\text{m}$ </tex-math></inline-formula> BCD process. Measurement results show that the converter has good output accuracy. The switching frequency is centered at 750kHz with less than 1.5% variation when the input voltage is 4.5-14V in the buck mode and 2.6-4.5V in the boost mode. The maximum conversion efficiency is up to 95%. Its minimum input starting voltage can be as low as 2.6V.

Targeted deep learning: Framework, methods, and applications

Deep learning systems are typically designed to perform for a wide range of test inputs. For example, deep learning systems in autonomous cars are supposed to deal with traffic situations for which they were not specifically trained. In general, the ability to cope with a broad spectrum of unseen test inputs is called generalization. Generalization is definitely important in applications where the possible test inputs are known but plentiful or simply unknown, but there are also cases where the possible inputs are few and unlabeled but known beforehand. For example, medicine is currently interested in targeting treatments to individual patients; the number of patients at any given time is usually small (typically one), their diagnoses/responses are still unknown, but their general characteristics (such as genome information, protein levels in the blood, and so forth) are known before the treatment. We propose to call deep learning in such applications In this paper, we introduce a framework for targeted deep learning, and we devise and test an approach for adapting standard pipelines to the requirements of targeted deep learning. The approach is very general yet easy to use: It can be implemented as a simple data‐preprocessing step. We demonstrate on a variety of real‐world data that our approach can indeed render standard deep learning faster and more accurate when the test inputs are known beforehand.