Computing Battery Lifetime Distributions

L. Cloth, M. Jongerden, B. Haverkort
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引用次数: 54

Abstract

The usage of mobile devices like cell phones, navigation systems, or laptop computers, is limited by the lifetime of the included batteries. This lifetime depends naturally on the rate at which energy is consumed, however, it also depends on the usage pattern of the battery. Continuous drawing of a high current results in an excessive drop of residual capacity. However, during intervals with no or very small currents, batteries do recover to a certain extend. We model this complex behaviour with an inhomogeneous Markov reward model, following the approach of the so-called kinetic battery model (KiBaM). The state-dependent reward rates thereby correspond to the power consumption of the attached device and to the available charge, respectively. We develop a tailored numerical algorithm for the computation of the distribution of the consumed energy and show how different workload patterns influence the overall lifetime of a battery.
计算电池寿命分布
手机、导航系统或笔记本电脑等移动设备的使用受到随附电池寿命的限制。这个寿命自然取决于能量消耗的速率,然而,它也取决于电池的使用模式。连续的大电流引出会导致剩余容量的过度下降。然而,在没有电流或电流非常小的间隔时间内,电池确实可以在一定程度上恢复。我们按照所谓的动力电池模型(KiBaM)的方法,用非齐次马尔可夫奖励模型来模拟这种复杂的行为。因此,状态相关的奖励率分别对应于所附设备的功耗和可用电荷。我们开发了一个定制的数值算法来计算消耗能量的分布,并展示了不同的工作负载模式如何影响电池的整体寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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