Flexible PV-cell Modeling for Energy Harvesting in Wearable IoT Applications

Flexible PV-cell Modeling for Energy Harvesting in Wearable IoT Applications
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用于可穿戴物联网应用中能量收集的灵活光伏电池建模

DOI:
10.1145/3126568
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发表时间:
2017
影响因子:
2
通讯作者:
Ogras, Umit Y.
Ogras, Umit Y.
中科院分区:
计算机科学3区
文献类型:
--
作者:
Park, Jaehyun;Joshi, Hitesh;Lee, Hyung Gyu;Kiaei, Sayfe;Ogras, Umit Y.

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随着物联网(IoT)和低功耗设计技术的进步,具有传感、处理和通信功能的可穿戴设备已经变得可行。由于电池的尺寸和重量限制,能量收集对于可穿戴物联网设备至关重要。光伏电池由于其结构简单、输出功率高而成为最广泛使用的能量收集源之一。特别是,柔性光伏电池为可穿戴应用提供了巨大的潜力。本文首次对弯曲光伏电池如何显着影响收集的能量进行了建模。此外,我们推导出一个分析模型来量化收集的能量作为曲率半径的函数。我们验证了所提出的模型经验使用商业PV电池在广泛的弯曲情况下,光强度和仰角。最后,我们表明,该模型可以加速最大功率点跟踪算法,并增加了高达25.0%的收获能量。
Wearable devices with sensing, processing and communication capabilities have become feasible with the advances in internet-of-things (IoT) and low power design technologies. Energy harvesting is extremely important for wearable IoT devices due to size and weight limitations of batteries. One of the most widely used energy harvesting sources is photovoltaic cell (PV-cell) owing to its simplicity and high output power. In particular, flexible PV-cells offer great potential for wearable applications. This paper models,for the first time, how bending a PV-cell significantly impacts the harvested energy. Furthermore, we derive an analytical model to quantify the harvested energy as a function of the radius of curvature. We validate the proposed model empirically using a commercial PV-cell under a wide range of bending scenarios, light intensities and elevation angles. Finally, we show that the proposed model can accelerate maximum power point tracking algorithms and increase the harvested energy by up to 25.0%.
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