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

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-l...

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Detalles Bibliográficos
Autores principales: Daniol, Mateusz, Boehler, Lukas, Sroka, Ryszard, Keller, Anton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664206/
https://www.ncbi.nlm.nih.gov/pubmed/33172045
http://dx.doi.org/10.3390/s20216338
Descripción
Sumario: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.