McLeod, Iain and Clemente, Daniel and Santos, Paulo Rosa and Pinto, Francisco Taveira and Rosati, Marco and Ringwood, John (2023) Mathematical Modelling of a TENG-Powered Data Buoy. OCEANS 2023. pp. 1-10.

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Abstract

Triboelectric nanogenerators, or TENGs, are prominent among power take off (PTO) systems being researched for use in specifically small scale wave energy converters (WECs). The low power requirements, and modest size of data buoys, suggests TENGs as an ideal PTO for this small-scale wave energy application. However, a physics-based model of the relationship between the movement of the buoy and the performance of the onboard TENG is difficult, particularly for rolling-ball-type TENGs. This paper develops three multiple input single output system identification (SI), black-box models for a rolling-ball-type TENG. The SI models are identified, and validated, using input-output data gathered from real wave tank tests on a 1:8 Froude-scaled model of a navigation buoy. The models described in this paper, relate the TENG’s current output to the displacement, in 6 degrees of freedom (DoFs), of the buoy to which it is mounted, across a range of wave conditions. The SI models used include linear autoregressive with exogenous input (ARX), and nonlinear Kolmogorov-Gabor polynomial (KGP).

Item Type:	Article
Keywords:	navigation buoy; wave energy converter; triboelectric nanogenerator; TENG parameterization; data-based modelling; linear ARX model; nonlinear KGP model; system identification;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	18959
Identification Number:	https://doi.org/10.1109/OCEANSLimerick52467.2023.10244462
Depositing User:	Professor John Ringwood
Date Deposited:	01 Oct 2024 16:04
Journal or Publication Title:	OCEANS 2023
Publisher:	IEEE
Refereed:	Yes
URI:	Organisation
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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