Rajeevan Amirtharajah

Self-powered signal processing using vibration-based power generation

Low power design trends raise the possibility of using ambient energy to power future digital systems. A chip has been designed and tested to demonstrate the feasibility of operating a digital system from power generated by vibrations in its environment. A moving coil electromagnetic transducer was used as a power generator. Calculations show that power on the order of 400 /spl mu/W can be generated. The test chip integrates an ultra-low power controller to regulate the generator voltage using delay feedback techniques, and a low power subband filter DSP load circuit. Tests verify 500 kHz self-powered operation of the subband filter, a level of performance suitable for sensor applications. The entire system, including the DSP load, consumes 18 /spl mu/W of power. The chip is implemented in a standard 0.8 /spl mu/m CMOS process. A single generator excitation produced 23 ms of valid DSP operation at a 500 kHz clock frequency, corresponding to 11,700 cycles.

Vibration-to-electric energy conversion

A system is proposed to convert ambient mechanical vibration into electrical energy for use in powering autonomous low-power electronic systems. The energy is transduced through the use of a variable capacitor, which has been designed with MEMS (microelectromechanical systems) technology. A low-power controller IC has been fabricated in a 0.6 /spl mu/m CMOS process and has been tested and measured for losses. Based on the tests, the system is expected to produce 8 /spl mu/W of usable power.

High-efficiency multiple-output DC-DC conversion for low-voltage systems

This versatile power converter controller provides dual outputs at a fixed switching frequency and can regulate either output voltage or target system delay (using an external L-C filter). In the voltage regulation mode, the output voltage is monitored with an analog-digital (A/D) converter, and the feedback compensation network is implemented digitally. The generation of the pulsewidth modulation (PWM) signal is done with a hybrid delay line/counter approach, which saves power and area relative to previous implementations. Power devices are included on chip to create the two independently regulated output PWM signals. The key features of this design are its low-power dissipation, reconfigurability, use of either delay or voltage feedback, and multiple outputs.

Integrated Solar Energy Harvesting and Storage

To explore integrated solar energy harvesting as a power source for low power systems, an array of energy scavenging photodiodes based on a passive-pixel architecture for CMOS imagers has been fabricated together with storage capacitors implemented using on-chip interconnect in a 0.35-mum bulk process. Integrated vertical plate capacitors enable dense energy storage without limiting optical efficiency. Tests were conducted with both a white light source and a green laser. Measurements indicate that 225 muW/mm2 output power may be generated by white light with an intensity of 20 kLUX.

Integrated solar energy harvesting and storage

To explore integrated solar energy harvesting as a power source for low power systems such as wireless sensor nodes, an array of energy scavenging photodiodes based on a passive-pixel architecture for imagers and have been fabricated together with storage capacitors implemented using on-chip interconnect in a 0.35 mum CMOS logic process. Integrated vertical plate capacitors enable dense energy storage without limiting optical efficiency. Measurements show 225 muW/mm2 output power generated by a light intensity of 20k LUX

A micropower programmable DSP powered using a MEMS-based vibration-to-electric energy converter

An ultra-low-power programmable DSP for sensor applications enables systems to be powered by ambient vibration. The three-chip system consists of a MEMS transducer that converts vibration to a voltage delivered to a conversion IC. The conversion IC creates a stable power supply that provides energy to the sensor DSP load. The system exploits ambient mechanical vibration as its energy source.

A micropower programmable DSP using approximate signal processing based on distributed arithmetic

A recent trend in low-power design has been the employment of reduced precision processing methods for decreasing arithmetic activity and average power dissipation. Such designs can trade off power and arithmetic precision as system requirements change. This work explores the potential of distributed arithmetic (DA) computation structures for low-power precision-on-demand computation. We present an ultralow-power DSP which uses variable precision arithmetic, low-voltage circuits, and conditional clocks to implement a biomedical detection and classification algorithm using only 560 nW. Low energy consumption enables self-powered operation using ambient mechanical vibrations, converted to electric energy by a MEMS transducer and accompanying power electronics. The MEMS energy scavenging system is estimated to deliver 4.3 to 5.6 /spl mu/W of power to the DSP load.

DSPs for energy harvesting sensors: applications and architectures

Energy harvesting from human or environmental sources shows promise as an alternative to battery power for embedded digital electronics. Digital signal processors that harvest power from ambient mechanical vibration are particularly promising for sensor networks.

Circuits for energy harvesting sensor signal processing

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, power-on-reset circuitry, and memory for energy harvesting AC power supplies. These techniques can also be applied to energy harvesting from other sources. A chip was fabricated to test the proposed circuits

Power scalable processing using distributed arithmetic

A recent trend in low power design has been the employment of reduced precision processing methods for decreasing arithmetic activity and average power dissipation. Such designs can trade off power and arithmetic precision as system requirements change. This work explores the potential of Distributed Arithmetic (DA) computation structures for low power precision-on-demand computation. We present two proof-of-concept VLSI implementations whose power dissipation changes according to the precision of the computation performed.