This work presents a new energy management system (EMS) based on states for a hybrid charging station of electric vehicles (EV). The hybrid charging station is composed of a photovoltaic (PV) system, a complete hydrog...
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ISBN:
(数字)9781665435970
ISBN:
(纸本)9781665411738
This work presents a new energy management system (EMS) based on states for a hybrid charging station of electric vehicles (EV). The hybrid charging station is composed of a photovoltaic (PV) system, a complete hydrogen system based on fuel cell (FC), electrolyzer (EZ) and tank as energy storage system (ESS), a battery energy storage system (BES), a grid connection, and six fast charging units, all of them connected to a common MVDC bus through Z-sources converters (ZSC). The states-based EMS is designed to control the power flow among the energy sources of the hybrid charging station. The viability of the EMS is proved under a long-term simulation of 25 years in Simulink by using an EV load profile taken from the Strategy technology Energy Plan of the EU and real data for the sun irradiance.
This paper focuses on the stability analysis of a formation shape displayed by a team of mobile robots that uses heterogeneous sensing mechanism. Depending on the convenience and reliability of the local information, ...
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— In this letter, we investigate the formation control problem of mobile robots moving in the plane where, instead of assuming robots to be simple points, each robot is assumed to have the form of a disk with equal r...
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Convolution neural networks (CNNs) have been widely used in many applications. Field-Programmable Gate Array (FPGA) based accelerator is an ideal solution for CNNs in embedded systems. However, the single event upset ...
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ISBN:
(数字)9781728149226
ISBN:
(纸本)9781728149233
Convolution neural networks (CNNs) have been widely used in many applications. Field-Programmable Gate Array (FPGA) based accelerator is an ideal solution for CNNs in embedded systems. However, the single event upset (SEU) effect in FPGA device may have a significant influence on the performance of CNNs. In this paper, we analyze the sensibility of CNNs to SEU and present a fault-tolerant design for CNN accelerators. First, we find that SEU in processing elements (PEs) has the worst effects on CNNs since it produces proportional errors and will not get refreshed. Furthermore, it is indicated that the large positive perturbation contributes almost all of the performance loss. Based on such observations, we propose an error detecting scheme to locate incorrect PEs and give an error masking method to achieve fault-tolerance. Experiments demonstrate that the proposed method achieves similar fault-tolerant performance with the triple modular redundancy (TMR) scheme while the overhead is much lower than it.
This work investigates the interaction between Neg-ative Bias Temperature Instability (NBTI)and radiation effects in 14nm FinFET devices. Due to the complex interaction between traps generated by NBTI and induced char...
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This work investigates the interaction between Neg-ative Bias Temperature Instability (NBTI)and radiation effects in 14nm FinFET devices. Due to the complex interaction between traps generated by NBTI and induced charges by strikes of ionizing particles, we opted for a complete physical-based analysis using TCAD mixed-mode simulations. This enables an accurate estimation and then modeling of the duration a circuit requires to recover from a particle strike and, thus, return to correct operation under the effects of NBTI. This a crucial aspect, because the longer the recovery time, the higher the probabilities of a soft-error and that this error remains undetected. Further, our employed setup enables an accurate determination of the critical charge (Q crit ), i. e. the minimum collected charge that results into a faulty transition of a circuit's output node. Our investigation reveals that there is indeed a strong relation between NBTI and the time a circuit remains in faulty state. Consequently, detection schemes must be adapted during circuit's operation to take aging into account in order to avoid that errors remain undetected.
State governments in the U.S. have been facing difficult decisions involving tradeoffs between economic and health-related outcomes during the COVID-19 pandemic. Despite evidence of the effectiveness of government-man...
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By integrating both energy harvesting and backscatter communication technologies, so-called `battery-free tag' emerges as a promising solution to the energy related issues in IoT. However, such tags present new ch...
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ISBN:
(数字)9781728166070
ISBN:
(纸本)9781728166087
By integrating both energy harvesting and backscatter communication technologies, so-called `battery-free tag' emerges as a promising solution to the energy related issues in IoT. However, such tags present new challenges due to the unstable energy supply and excitation signals, which are critical to realize successful backscatter communications. In this paper, we present a novel system, denoted as ecUWB, which enables robust communication for battery-free tags where unstable WiFi signals act as the unified source for both energy supply and excitation signals. At tag side, we propose a charging-transmission division scheme to achieve better signal utilization, and introduce a re-transmission mechanism for possible excitation signal interruption. At receiver side, we implement a simply method which is based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to predict the uncontrollable signals, and propose an energy-centric tag scheduling method according to the tag energy estimation results. Extensive experiments are carried out on customized tags and NI USRP platform. The results show that ecUWB outperforms the existing ones in terms of performance and efficiency under the unstable WiFi signals.
Neural relation extraction discovers semantic relations between entities from unstructured text using deep learning methods. In this study, we present a comprehensive review of methods on neural network based relation...
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This paper proposes a mechanism to accelerate and optimize the energy consumption of a face detection software based on Haar-like cascading classifiers, taking advantage of the features of low-cost asymmetric multicor...
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The lightweight nature of tensegrity structures calls for the formulation of computational tools that are able to analyze the stability problem of such structures, both in statics and dynamics. The present work analyz...
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