Abstract

Dielectric elastomer generators are soft structures capable of converting mechanical energy into electrical energy. Here, we develop a theoretical model of the triangular harvesting cycle that enables the harvesting of most of the available electrical energy while not requiring active monitoring of the charge-voltage state on the DEG. This cycle is therefore interesting for small-scale generators for which a monitoring circuit would be energetically too costly. Our model enables the identification of the optimal value of the circuit’s parameters such as storage capacitor and priming voltage values and show that for capacitance swings up to 6, 94% of the available electrical energy can be harvested. The model is experimentally validated with a conical generator, and the effect of non-constant deformation amplitudes is examined. Energy densities up to 46 mJcm−3 were obtained for an electric field of 50 V µm−1.

Highlights

  • Dielectric elastomer transducers (DETs) consist of an elastomeric dielectric film sandwiched between a pair of compliant electrodes, forming a rubbery deformable capacitor

  • Shian et al have obtained an energy density of 0.76 J g−1 (Shian et al, 2014), which is Optimisation of Dielectric elastomer generators (DEGs) contribution, we investigate the ideal electronic circuit topology to harvest energy from a miniaturised DEG and optimise its parameters to maximise the energy harvested from a source of mechanical energy with varying amplitude and frequency

  • Harvesting cycles were measured for a range of capacitance swings 1.5 ≤ β^ ≤ 4.5, and for four different storage capacitor values (Figure 9)

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Summary

Introduction

Dielectric elastomer transducers (DETs) consist of an elastomeric dielectric film sandwiched between a pair of compliant electrodes, forming a rubbery deformable capacitor. They can be used as actuators for soft machines, as sensors, or as generators (Pelrine et al, 2000; Anderson et al, 2012; Rosset and Shea, 2016; Moretti et al, 2020b). In generator mode, they transform mechanical energy into electrical energy. Harvesting energy from tree branch motion could enable the deployment of wireless sensor networks for forest health or fire monitoring

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