Optimisation-driven design of sliding mode triboelectric energy harvesters

Machado, L. Q., Zhao, H., Amjadi, M. , Ouyang, H., Basset, P. and Yurchenko, D. (2023) Optimisation-driven design of sliding mode triboelectric energy harvesters. Nano Energy, 115, 108735. (doi: 10.1016/j.nanoen.2023.108735)

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.

• Item Type: Articles
• Additional Information: The authors would like to acknowledge and are thankful for the support received from the Brazilian National Council for Scientific and Technological Development—CNPq , grant 202615/2019-7.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Amjadi Kolour, Dr Morteza

Creator Roles

Amjadi Kolour, M.: Resources, Writing – review and editing, Supervision

• Authors: Machado, L. Q., Zhao, H., Amjadi, M., Ouyang, H., Basset, P., and Yurchenko, D.
• College/School: College of Science and Engineering > School of Engineering > Biomedical Engineering
• Journal Name: Nano Energy
• Publisher: Elsevier
• ISSN: 2211-2855
• ISSN (Online): 2211-3282
• Published Online: 22 July 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Nano Energy 115:108735
• Publisher Policy: Reproduced under a Creative Commons license