Parametric amplification of broadband vibrational energy harvesters for energy-autonomous sensors enabled by field-induced striction

We investigate the influence of parametric excitations on MEMS vibration energy harvesters for energy autonomous sensor systems. In Industry 4.0 (or Industrial IoT) applications, interconnected sensors provide a means of data acquisition for automated control of the manufacturing process. Ensuring a continuous energy supply to the sensors is essential for their reliable operation. Manufacturing machines usually display a wide spectrum of vibration frequencies which needs to be covered by an array of harvester substructures in order to maintain the desired output level. We show that mechanical structures designed to implement a Helmholtz-Duffing oscillator have an increased bandwidth by exploiting several orders of parametric resonances. In contrast to concepts implementing parametric amplification in a multi-mode scenario, our concept is based on a single mechanical mode. Therefore, it is more robust against fabrication tolerances as the relevant multi-mode resonance conditions do not need to be matched on the level of single chips. Using exact transient simulations and semi-analytic models to showcase the relation of the Helmholtz-Duffing oscillator to the damped and driven Mathieu equation, we show that parametric resonances highly increase the bandwidth of the output power whenever high Helmholtz nonlinearities are present. To achieve the required nonlinearities, we suggest nonlinear stress-strain curves and we propose to achieve such nonlinearities through field-induced striction by magneto- or electrostriction. In contrast to existing approaches, where external fields are harvested using strictive effects, we employ external fields that manipulate the effective Young's modulus to achieve parametric excitations in a mechanical oscillator. Thus, we are able to propose a novel energy harvester concept incorporating strictive materials that exploits the effects of parametric excitations to achieve broadband vibrational energy harvesting. (C) 2020 Elsevier Ltd. All rights reserved.