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A Markov Model Accounting for Charge Recovery in Energy Harvesting Devices

机译:能量收集装置中电荷回收的马尔可夫模型

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Energy harvesting is an important feature that can be implemented in mobile devices to provide them with extended autonomy, yet it poses several challenges in terms of optimal battery usage. In this paper, we highlight that some non-ideal effects, especially the so-called "charge recovery," can have a dramatic impact on the operation policy of autonomous devices. To do so, we construct a Markov model, where we introduce a bidimensional battery value, including the apparent energy level, which is what available at the electrodes to power the device, and the actual energy level stored in the battery. When power is not drained by the device, these levels tend to equalize due to charge recovery, but, in the case of intense battery usage, they can be significantly different. We show that this non- ideality leads to considerably different estimates of undesirable events such as battery outages, and may cause a general underutilization of the devices if not properly accounted for.
机译:能量收集是一项重要功能,可以在移动设备中实现,以为它们提供扩展的自主权,但在最佳电池使用方面却带来了一些挑战。在本文中,我们强调了一些非理想的影响,尤其是所谓的“电荷恢复”,会对自主设备的运行策略产生巨大影响。为此,我们构建了一个马尔可夫模型,在其中引入了二维电池值,包括视在能量水平(在电极上为设备供电的能量水平)以及存储在电池中的实际能量水平。当设备不消耗电力时,由于电荷恢复,这些水平趋于均衡,但是在电池使用量很高的情况下,它们可能会大不相同。我们表明,这种不理想导致对不良事件(如电池故障)的估计大不相同,并且如果没有适当考虑的话,可能会导致设备的普遍利用不足。

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