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首页> 外文期刊>IEEE transactions on very large scale integration (VLSI) systems >Maximizing the Lifetime of Embedded Systems Powered by Fuel Cell-Battery Hybrids
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Maximizing the Lifetime of Embedded Systems Powered by Fuel Cell-Battery Hybrids

机译:最大限度地延长由燃料电池-电池混合动力驱动的嵌入式系统的使用寿命

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摘要

Fuel cell (FC) is a viable alternative power source for portable applications; it has higher energy density than traditional Li-ion battery and thus can achieve longer lifetime for the same weight or volume. However, because of its limited power density, it can hardly track fast fluctuations in the load current of digital systems. A hybrid power source, which consists of a FC and a Li-ion battery, has the advantages of long lifetime and good load following capabilities. In this paper, we consider the problem of extending the lifetime of a fuel-cell-based hybrid source that is used to provide power to an embedded system which supports dynamic voltage scaling (DVS). We propose an energy-based optimization framework that considers the characteristics of both the energy consumer (the embedded system) and the energy provider (the hybrid power source). We use this framework to develop algorithms that determine the output power level of the FC and the scaling factor of the DVS processor during task scheduling. Simulations on task traces based on a real-application (Path Finder) and a randomized version demonstrate significant superiority of our algorithms with respect to a conventional DVS algorithm which only considers energy minimization of the embedded system.
机译:燃料电池(FC)是便携式应用的可行替代电源。与传统的锂离子电池相比,它具有更高的能量密度,因此在相同的重量或体积下可以实现更长的使用寿命。但是,由于其功率密度有限,它几乎无法跟踪数字系统负载电流的快速波动。由FC和锂离子电池组成的混合电源具有使用寿命长和良好的负载跟随能力的优点。在本文中,我们考虑了延长基于燃料电池的混合动力源寿命的问题,该混合动力源用于为支持动态电压缩放(DVS)的嵌入式系统提供动力。我们提出了一个基于能源的优化框架,该框架考虑了能源消耗者(嵌入式系统)和能源提供者(混合动力源)的特征。我们使用此框架来开发确定任务调度期间FC的输出功率水平和DVS处理器的缩放因子的算法。基于真实应用程序(路径查找器)和随机版本的任务跟踪的仿真证明,相对于仅考虑嵌入式系统能耗最小的传统DVS算法,我们的算法具有显着优势。

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