Electrostatic Near-Limits Kinetic Energy Harvesting from Arbitrary Input Vibrations

TL;DR

This paper presents a novel electrostatic kinetic energy harvester architecture that approaches the physical limits of energy conversion from arbitrary environmental vibrations, utilizing optimized mass dynamics and control strategies.

Contribution

It introduces a near-limits KEH architecture that maximizes energy harvesting from arbitrary vibrations through synthesized mass dynamics and an integrated control system.

Findings

Achieved 68% of the absolute energy input limit in simulations.

Demonstrated proof of concept with a new control and interface circuit design.

Potential for further optimization to reach closer to physical energy limits.

Abstract

The full architecture of an electrostatic kinetic energy harvester (KEH) based on the concept of near-limits KEH is reported. This concept refers to the conversion of kinetic energy to electric energy, from environmental vibrations of arbitrary forms, and at rates that target the physical limits set by the device's size and the input excitation characteristics. This is achieved thanks to the synthesis of particular KEH's mass dynamics, that maximize the harvested energy. Synthesizing these dynamics requires little hypotheses on the exact form of the input vibrations. In the proposed architecture, these dynamics are implemented by an adequate mechanical control which is synthesized by the electrostatic transducer. An interface circuit is proposed to carry out the necessary energy transfers between the transducer and the system's energy tank. A computation and finite-state automaton unit controls the interface circuit, based on the external input and on the system's mechanical state. The operation of the reported near-limits KEH is illustrated in simulations that demonstrate proof of concept of the proposed architecture. A figure of $68\%$ of the absolute limit of the KEH's input energy for the considered excitation is attained. This can be further improved by complete system optimization that takes into account the application constraints, the control law, the mechanical design of the transducer, the electrical interface design, and the sensing and computation blocks.