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arxiv: 1508.02126 · v1 · pith:TONAPHHPnew · submitted 2015-08-10 · ❄️ cond-mat.other

Energy harvesting via an adaptive bistable potential

classification ❄️ cond-mat.other
keywords bistableexcitationsadaptiveenergynon-stationarybuy-low-sell-highefficiencyharvester
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Narrow bandwidth and easy detuning, inefficiency in broadband and non-stationary excitations, and difficulties in matching linear harvester's resonance frequency to low-frequency excitations at small scales, have convinced the researchers to investigate the nonlinear, in particular the bistable energy harvesters in the recent years. However, the bistable harvesters suffer from co-existing low and high energy orbits, and sensitivity to initial conditions, and have been recently proven inefficient when subjected to many real-world random and non-stationary excitations. Here, we propose a novel buy-low-sell-high strategy that can significantly improve the harvester's efficiency at low-frequencies in a much more robust fashion. This strategy could be realized by a passive adaptive bistable system. Simulation results confirm high efficiency of the adaptive bistable system following a buy-low-sell-high logic when subjected to harmonic and random non-stationary walking excitations compared to its conventional bistable and linear counterparts.

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