Emerging industrial applications have brought electromechanical energy harvesting based on periodic but non-harmonic signal excitations – appearing as impulses – into focus. The impulses procure periodic, non-harmonic voltage signals with exponential decay at the electrical terminal of the harvester, which are at present typically characterized by the peak power and average power. However, the last-mentioned quantities describe the signal raw data insufficiently as the available energy can be deduced but not the transferable energy due to lossy interface circuits. Especially, miniaturized electromagnetic energy harvesters provide an output voltage, which is in proximity of or only a few times larger than the voltage drop of a diode and of an energy storage, leading to a reduced amount of transferrable energy.This study presents a novel, innovative signal description based on stochastic signal analysis, applicable to electromagnetic, piezo-magnetic or other transducers without intrinsic memory element as a capacitor. The main objectives are first, to represent the data meaningfully, second, to incorporate the effect of lossy rectifiers on the raw data and third, to evaluate the performance of chosen energy harvesting circuit efficiently.&nbsp;The foundation relies in considering the measured time signal as a realization of an ergodic process. The probability density function (PDF) and the cumulated density function (CDF) build the fundament and are used to link the signal magnitudes to their probability of occurrence. New distribution functions are introduced to determine both, the charges and the energy above a specific signal amplitude, which can be imposed by a voltage drop of one or several components. The presented method is further extended to calculate the efficiency of interface circuits and applied on the well-known standard interface circuit.For an easy understanding, the newly established method is demonstrated on a harmonic signal and is compared with state-of-the-art properties. Then, a signal characterization of a tire based energy harvester signal follows. In combination with an interface circuit and energy storage, the powerfulness of the tool will be practically demonstrated. At the end, the energy efficiency of an interface circuit with energy storage are calculated and compared with numerical network simulations.As a result, the paper presents a new stochastic signal representation that extends the state-of-the-art time and frequency signal analysis. Different interface circuits with energy storage can be quickly calculated for different initial conditions, much faster than powerful network simulators would do.&nbsp;

Stochastic Signal Analysis and Processing of Non-Harmonic, Periodic Vibrational Energy Harvesters

Paper Proceedings: https://asmedigitalcollection.asme.org/SMASIS/SMASIS2021/volume/85499

ASME 2021 Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS2021)

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