Computing Battery Lifetime Distributions
Computing Battery Lifetime Distributions
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DOI：
10.1109/dsn.2007.26
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发表时间：
2007-06
期刊：
影响因子：
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通讯作者：
L. Cloth;M. Jongerden;B. Haverkort
中科院分区：
文献类型：
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作者：
L. Cloth;M. Jongerden;B. Haverkort
手机、导航系统或笔记本电脑等移动的设备的使用受到所含电池寿命的限制。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。连续抽取高电流会导致剩余容量过度下降。然而，在没有或非常小的电流的间隔期间，电池确实恢复到一定程度。我们用非齐次马尔可夫奖励模型来模拟这种复杂的行为，遵循所谓的动力电池模型（KiBaM）的方法。因此，依赖于状态的奖励率分别对应于附接设备的功耗和可用电荷。我们开发了一种量身定制的数值算法，用于计算所消耗的能量的分布，并显示不同的工作负载模式如何影响电池的整体寿命。
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.