Passive energy harvesting from mechanical vibration has wide application in wearable and embedded sensors to complement or replace batteries. Energy harvesting efficiency can be increased by eliminating AC/DC conversion. A test chip demonstrating self-timing, power-on-reset circuitry, and memory for energy harvesting AC voltages has been designed in 180 nm CMOS and tested. Circuit operation is confirmed for supply frequencies between 60 Hz and 1 kHz with power consumption below 130 µW.

Passive energy harvesting from mechanical vibration has wide application in wearable devices and wireless sensors to complement or replace batteries. Energy harvesting efficiency can be increased by eliminating AC/DC conversion. A test chip demonstrating self-timing, power-on reset circuitry, and dynamic memory for energy harvesting AC voltages has been designed in 180 nm CMOS and tested. An energy scalable DSP architecture implements FIR filters that consume as little as 170 pJ per output sample. The on-chip DRAM retains data for up to 28 ms while register data is retained down to a supply voltage of 153 mV. Circuit operation is confirmed for supply frequencies between 60 Hz and 1 kHz with power consumption below 130 μW. Reaching the limits of miniaturization will require approaching the limits of power dissipation. We extrapolate from this DSP architecture to find the minimum volume required for mechanical vibration energy harvesting sensors.

The recent explosion in capability of embedded and portable electronics has not been matched by battery technology. The slow growth of battery energy density has limited device lifetime and added weight and volume. Passive energy harvesting from solar radiation, thermal sources, or mechanical vibration has potentially wide application in wearable and embedded sensors to complement batteries. The amount of energy from harvesting is typically small and highly variable, requiring circuits and architectures which are low power and can scale their power consumption with user requirements and available energy. We describe several circuit techniques for achieving these goals in signal processing applications for wireless sensor network nodes such as using Distributed Arithmetic to implement energy scalable signal processing algorithms. In addition, we propose increasing vibration energy harvesting efficiency by eliminating AC/DC conversion electronics, and have investigated self-timed circuits, poweron-reset circuitry, and memory for energy harvesting AC power supplies. These techniques can also be applied to energy harvesting from other sources. A chip will be fabricated to test the proposed circuits.

Abstract-Wireless sensors and implantable medical devices have driven IC design to extremes of low power consumption to maximize system operating lifetimes from fixed energy stores or from energy harvested from the environment. Reaching the limits of miniaturization will require approaching the limits of power dissipation. We describe three key sensor subsystems: integrated diodes for solar energy harvesting, efficient microwatt power conversion circuits, and supply-voltage-ripple-tolerant digital circuits. We then extrapolate from these examples to find the minimum surface area and volume required for energy harvesting sensors.

Abstract