Electret based energy scavenging devices utilize electro-static induction to convert mechanical energy into electrical energy. Uses for these devices include harvesting ambient energy in the environment and acting as sensors for a range of applications. These types of devices have been used in MEMS applications for over a decade. However, recently there is an interest in triboelectric generators/harvesters, i.e., electret based harvesters that utilize triboelectrification as well as electrostatic induction. The literature is filled with a variety of designs for the latter devices, constructed from materials ranging from paper and thin films; rendering the generators lightweight, flexible and inexpensive. However, most of the design of these devices is ad-hoc and not based on exploiting the underlying physics that govern their behavior; the few models that exist neglect the coupled electromechanical behavior of the devices. Motivated by the lack of a comprehensive dynamic model of these devices this manuscript presents a generalized framework based on a Lagrangian formulation to derive electromechanical equation for a lumped parameter dynamic model of an electret-based harvester. The framework is robust, capturing the effects of traditional MEMS devices as well as triboelectric generators. Exploiting numerical simulations the predictions are used to examine the behavior of electret based devices for a variety of loading conditions simulating real-world applications such as power scavengers under simple harmonic forcing and in pedestrian walking.
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Dynamic Modeling of Triboelectric Generators Using Lagrange’s Equation
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Gauntt, S, Batt, G, & Gibert, J. "Dynamic Modeling of Triboelectric Generators Using Lagrange’s Equation." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies. Snowbird, Utah, USA. September 18–20, 2017. V001T07A009. ASME. https://doi.org/10.1115/SMASIS2017-3844
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