Optimisation-driven design of sliding mode triboelectric energy harvesters

Lucas Q. Machado, Huai Zhao, Morteza Amjadi, Huajiang Ouyang, Philippe Basset, Daniil Yurchenko

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
33 Downloads (Pure)

Abstract

With the increasing demand of emerging technologies for autonomous sensing, the modelling and optimisation of complete energy harvesting systems are essential to achieve efficient power output. To date, most of the optimisation efforts in enhancing the performance of triboelectric energy harvesters have been focused on the improvement of material properties and on the establishment of figures of merit to assist in the definition of parameters. However, these efforts do not consider the complex relationship between the device structure and power output, physical constraints in place, and varying excitation conditions. This paper fills that gap for the first time by applying an optimisation algorithm to establish mechanisms for optimisation-driven design of sliding-mode triboelectric energy harvesters. A global optimisation methodology is developed to improve its performance, having experimentally validated the numerical model adopted. This work highlights the need for a more robust design framework for applications of triboelectric energy harvesting and proposes a hybrid approach combining the finite element method with analytical models to consider different energy harvesting parameters including the degradation of the charge transfer efficiency due to the edge effect. A novel high-power output sliding-mode triboelectric energy harvesting concept is proposed and its performance is optimised, using the proposed methodology.
Original languageEnglish
Article number108735
JournalNano Energy
Volume115
Early online date22 Jul 2023
DOIs
Publication statusPublished - Oct 2023

Keywords

  • Energy harvesting
  • Global optimisation
  • Triboelectricity

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • General Materials Science
  • Electrical and Electronic Engineering

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