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. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ U. Nabholz, L. Lamprecht and P. Degenfeld-Schonburg are with Robert
Energy autonomous sensors for I4.0 applications powered by kinetic energy harvesters (KEHs) are widely discussed-especially in terms of vibration harvesting. Typically, industrial linear stages offer weak vibrations, so other inertia-based harvesting methods are investigated. This study investigates the usability of human motion energy harvesters in industrial linear motion technology for the first time. Two KEHs-harvesting swing or shocks, respectively-are tested while controlling the parameters velocity, acceleration, and jerk-limitation according to the real applications' parameter ranges. The swing-KEH and the shock-KEH harvested up to 106 and 124 mW, respectively. Furthermore, a parameter study is performed assuming constant driving lengths with optimised stroke rates to obtain a generalised power and energy profile for each harvester. The analytically obtained overall average power is 22 mW for the swing-KEH and 14 mW for the shock-KEH. The analytical investigation revealed that a reciprocal dependency of performance and velocity exists for both KEHs, respectively. Both experimental and analytical parts show that the wireless sensor node for I4.0 on industrial linear stages can be powered by harvesters made for human motions.
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