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http://hdl.handle.net/2080/3415Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ram, Saswat Kumar | - |
| dc.contributor.author | Swain, Ayas Kanta | - |
| dc.date.accessioned | 2019-12-27T05:51:20Z | - |
| dc.date.available | 2019-12-27T05:51:20Z | - |
| dc.date.issued | 2019-12 | - |
| dc.identifier.citation | 5th IEEE International Symposium on Smart Electronic Systems ( IEEE-iSES 2019 ) Rourkela, India, 16- 18 December 2019. | en_US |
| dc.identifier.uri | http://hdl.handle.net/2080/3415 | - |
| dc.description | Copyright of this document belongs to proceedings publisher. | en_US |
| dc.description.abstract | An Ultra-low power solar energy harvesting system(EHS) for IoT end node devices is presented in this paper.To provide an uninterrupted power supply to IoT nodes is a challenge. The solar cell is used as an input source and this low input voltage is boosted by using the DC-DC converter. The charge pump is used as a voltage booster and the impedance matching between the solar cell and the converter is achieved through frequency tuning and capacitor value modulation. A hill-climbing technique is used for maximum power point (MPP) achievement. The EHS designed is self-sustainable and the output is in the range of 3-3.55 V with an input of 1-1.5 V. The EHSis designed in CMOS 90 nm technology library. The simulation results validate the proposed concept and the EHS is consuming a power of 22μW, which is within the Ultra-low power range of IoT smart nodes. | en_US |
| dc.subject | Charge Pumps | en_US |
| dc.subject | Internet of Things (IoT) | en_US |
| dc.subject | Wire-less Sensor Networks (WSNs) | en_US |
| dc.subject | Capacitor Value Modulation(CVM) | en_US |
| dc.subject | Resistor Bank | en_US |
| dc.title | Ultra-Low Power Solar Energy Harvester for IoTEdge Node Devices | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Conference Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2019_ISES_SKRam_UltraLow.pdf | Conference paper | 309.04 kB | Adobe PDF | View/Open |
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