Strategies and Techniques for Powering Wireless Sensor Nodes through Energy Harvesting and Wireless Power Transfer

Area of Science:

• Electrical Engineering
• Computer Engineering
• Materials Science

Background:

• The proliferation of Internet of Things (IoT) devices necessitates sustainable power solutions, particularly for Wireless Sensor Nodes (WSNs) in hard-to-reach locations.
• Traditional batteries pose maintenance challenges and limit the widespread deployment of WSNs.
• Radio Frequency (RF) energy harvesting (EH) and wireless power transfer (WPT) offer promising avenues for battery-free, maintenance-free IoT architectures.

Purpose of the Study:

• To present a state-of-the-art, ultra-low power System on Chip (SoC) for multi-source energy harvesting and wireless power transfer.
• To enable battery-free operation for Wireless Sensor Nodes (WSNs) by leveraging pervasive RF energy.
• To introduce a versatile solution with minimal external components for diverse energy sources and use cases.

Main Methods:

• Design and implementation of a highly integrated mixed-signal SoC with an ultra-low power intelligent power management unit.
• Development of a sensitive RF-to-DC converter with high power conversion efficiency (PCE).
• Integration of Amplitude-Shift-Keying/Frequency-Shift-Keying (ASK/FSK) receiver and digital circuitry for versatile energy source management.

Main Results:

• Achieved an ultra-low power consumption of 2.5 μW.
• Demonstrated a highly integrated SoC capable of multi-source energy harvesting and wireless power transfer.
• Validated the system's ability to efficiently convert RF energy with low power sensitivity and high PCE.

Conclusions:

• The developed SoC provides a viable solution for powering Wireless Sensor Nodes (WSNs) through energy harvesting and wireless power transfer.
• This technology facilitates the creation of maintenance-free, low-cost, and widely deployable IoT devices.
• The integrated design offers versatility in managing various energy sources, paving the way for advanced smart sensing architectures.