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A 33nW Fully Autonomous SoC With Distributed Cooperative Energy Harvesting and Multi-Chip Power Management for
IEEE Transactions on Biomedical Circuits and Systems
|August 29, 2023
Summary
This study introduces an autonomous system-on-chip for ultra-low-power sensing. It efficiently harvests and shares energy, enabling operation in resource-constrained fiber environments.
Area of Science:
- Integrated Circuits
- Energy Harvesting
- Low-Power Electronics
Background:
- Traditional sensing systems require significant power, limiting their deployment in remote or resource-constrained environments.
- Existing solutions often lack autonomy and efficient energy management for continuous operation.
- Developing ultra-low-power (ULP) integrated systems is crucial for enabling pervasive sensing.
Purpose of the Study:
- To present a fully autonomous system-on-chip (SoC) for ULP sensing applications in fiber environments.
- To demonstrate simultaneous energy harvesting, cooperative performance scaling, power sharing, and booting among in-fiber SoCs.
- To achieve nanowatt power levels for sensing and computation.
Main Methods:
- Development of a custom switched capacitor energy harvesting and power management unit (EHPMU).
- Integration of a ULP RISC-V digital core and temperature sensor.
- Implementation of ripple boot-up and cooperative dynamic voltage and frequency scaling (DVFS).
- Fabrication using 65 nm technology and integration into a mm-scale polymer fiber.
Main Results:
- Achieved 33 nW total chip power consumption under 92 Lux lighting.
- Reduced EHPMU control power to 2.7 nW.
- Decreased required illuminance for operation by over 7x (down to 12 Lux) using power sharing and cooperative DVFS.
- Demonstrated feasibility of autonomous ULP on-body sensing in fiber.
Conclusions:
- The proposed SoC enables fully autonomous and ULP sensing in challenging fiber environments.
- The integrated energy harvesting, power management, and cooperative scaling techniques significantly reduce power requirements.
- This work paves the way for self-sustaining, distributed sensing systems in resource-limited applications.
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