Optimizing the configuration and control of a novel human-powered energy harvesting system

As sensor equipped wearable systems enter the mainstream, system longevity and power-efficiency issues hamper large scale and long-term deployment, despite substantial foreseeable benefits. As power and energy efficient design, sampling, processing and communication techniques emerge to counter these issues, researchers are beginning to look on wearable energy harvesting systems as an effective counterpart solution. In this paper, we propose a novel harvesting technology to inconspicuously transduce mechanical energy from human foot-strikes and power low-power wearable systems in a self-sustaining manner. Dielectric Elastomers (DEs) are high-energy density electrostatic transducers that can transduce significant levels of energy from a user while appearing near-transparent to her, if configured and controlled properly. Towards this end, we propose DE-based harvester configuration that capitalizes on properties of human gait to enhance transduction efficiency, and further leverage these properties in an adaptive control algorithm to optimize the net energy produced by the system. We evaluate system performance from detailed analytical and empirical models of DE transduction behavior, and apply our control algorithm to the modeled DEs under experimentally collected foot pressure datasets from multiple subjects. Our evaluations show that the proposed system can achieve up to 120mJ per foot-strike, enough to power a variety of low-power wearable devices and systems.