Near-Limit Kinetic Energy Harvesting From Arbitrary Acceleration Waveforms: Feasibility Study by the Example of Human Motion

Abstract

Kinetic energy harvesters have become a common power source for autonomous sensors operating at micro- and meso-scales. The conventional approach to kinetic energy harvesting is to assume that the proof mass of the mechanical component in an energy harvester is actuated by external motion produced by the sensor's environment. This approach, dominant since the beginning of micro-scale energy harvesting, has now resulted in the design of advanced, nonlinear harvesters suitable for non-harmonic vibrations produced by many systems of interest. In this paper, we present a feasibility study of an alternative approach to kinetic energy harvesting, where the motion of the proof mass is actively synthesized.

Keywords

• Energy harvesting
• microelectromechanical systems
• transducers
• algorithm design and analysis
• statistical learning
• time series analysis