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基于 TEG 的能量收集系统在蒸汽灭菌监测传感器节点中的建模与实现。

Modeling and Implementation of TEG-Based Energy Harvesting System for Steam Sterilization Surveillance Sensor Node.

机构信息

Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, 30-059 Kraków, Poland.

B. Braun Aesculap AG, D-78532 Tuttlingen, Germany.

出版信息

Sensors (Basel). 2020 Nov 6;20(21):6338. doi: 10.3390/s20216338.

Abstract

The aim of this work is a proof of concept, that medical Internet of Things (IoT) sterilization surveillance sensors can be powered by using the heat during a steam sterilization procedure. Hereby, the focus was on the use of thermo-electrical generators (TEG) to generate enough power for an ultra-low-power sensor application. Power generation requirement of the sensor was 1.6 mW over the single sterilization cycle. The thermal gradient across the TEG has been achieved using a highly efficient aerogel-foam-based thermal insulation, shielding a heat storage unit (HSU), connected to one side of the TEG. The evaluation of the developed system was carried out with thermal and electrical simulations based on the parameters extracted from the TEG manufacturer's datasheet. The developed model has been validated with a real prototype using the thermal step response method. It was important for the authors to focus on rapid-prototyping and using off-the-shelf devices and materials. Based on comparison with the physical prototype, the SPICE model was adjusted. With a thermal gradient of 12 °C, the simulated model generated over 2 mW of power. The results show that a significant power generation with this system is possible and usable for sensor applications in medial IoT.

摘要

本工作旨在验证一个概念,即医疗物联网(IoT)灭菌监测传感器可以利用蒸汽灭菌过程中的热量来供电。为此,重点是使用热电发生器(TEG)为超低功耗传感器应用产生足够的功率。传感器的发电要求在单个灭菌周期内为 1.6mW。通过使用基于高效气凝胶泡沫的隔热材料在 TEG 上产生热梯度,该隔热材料屏蔽了与 TEG 一侧相连的蓄热单元(HSU)。所开发系统的评估是基于从 TEG 制造商数据表中提取的参数进行的热和电气模拟。使用热阶跃响应方法,通过实际原型对开发的模型进行了验证。对于作者来说,专注于快速原型制作以及使用现成的设备和材料非常重要。通过与物理原型进行比较,对 SPICE 模型进行了调整。在 12°C 的热梯度下,模拟模型产生了超过 2mW 的功率。结果表明,该系统可以实现显著的发电,并且可用于医疗物联网中的传感器应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b194/7664206/5f6b6ac34946/sensors-20-06338-g001.jpg

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