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

Andrii Sokolov,Dimitri Galayko,Michael Peter Kennedy,Elena Blokhina

doi:10.1109/access.2020.3042388

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.

Highlights

I N many aspects, electronic engineering is driven by the concept of the Internet of Things (IoT) and the vision of the interconnected world
We start with conventional techniques of time series analysis that include auto-correlation functions, Fourier transforms, correlation dimensions and Autoregressive Integrated Moving Average (ARIMA) predictive modelling to investigate the correlation properties of such motion
DESCRIPTION OF THE PROPOSED DECISION ALGORITHM we propose a maximum/minimum selection algorithm to maximise the the energy extracted by a NLKEH, based on a prediction of the future of the sequence

Summary

INTRODUCTION

I N many aspects, electronic engineering is driven by the concept of the Internet of Things (IoT) and the vision of the interconnected world. The common approach to mitigate this problem is to utilise mechanical or electrically-induced nonlinearities to widen the frequency response of a resonator. In this case one can experience the problem of bimodality ( known as bi-stability) when small changes in the actuation force can lead to a spontaneous “jump” from a high-power to low-power branch. The aim of this paper is to analyse environment vibration patterns for applications that are compatible with Near Limit Energy Harvesting and to investigate its feasibility. This is an important aspect of the NLKEH since the required predictive control can be effectively implemented for signals that display a clear pattern.

NEAR LIMIT KINETIC ENERGY HARVESTERS

ANALYSIS OF ACCELERATION WAVEFORMS

ANALYSIS OF PATTERNS TROUGH CROSS-SIMILARITY

DESCRIPTION OF THE PROPOSED DECISION ALGORITHM

A POSTERIORI SELECTION OF THE OPTIMAL EXTREMA SUBSET

CONCLUSION