Performance boost of an electromagnetic energy harvester using vibrational resonance

Journal article


Diala, U., Omoteso, K. and Roy-Layinde, T. O. 2024. Performance boost of an electromagnetic energy harvester using vibrational resonance. International Journal of Non-Linear Mechanics. 170, pp. 1-13. https://doi.org/10.1016/j.ijnonlinmec.2024.104989
AuthorsDiala, U., Omoteso, K. and Roy-Layinde, T. O.
Abstract

Inherent nonlinearities, present in dynamical systems are employed to solve various engineering problems. Nonlinear dynamics involve responses that are not directly proportional to inputs, allowing for more effective system management. The beneficial characteristics of nonlinear systems and its growing associated literature have contributed to mitigating industrial and environmental energy-related challenges. Several recommendations have been provided for increasing the efficiency of a vibration energy harvesting (VEH) system. In this study, we investigated the occurrence of vibrational resonance (VR) in a Duffing-type energy harvester with electromagnetic transduction structure. We explored the impact of system nonlinearities on the occurrence of VR and system performance. We employed both analytical and numerical approaches to show the impact of the system parameters, especially the nonlinear stiffness parameter on the response amplitude at low-frequency excitations. Furthermore, the estimated average power absorbed by the VEH system is selected as the system performance metric, which can be optimised using the system’s parameters of interest. The VEH system demonstrated an improved performance as a significant amount of energy was harvested based on the nonlinear parameters of interest. Our investigation points to a new approach for the design and optimization of electromagnetic energy harvester.

KeywordsNonlinear systems; Bi-harmonics; Vibrational resonance; Vibration energy harvester; Average power
Year2024
JournalInternational Journal of Non-Linear Mechanics
Journal citation170, pp. 1-13
PublisherElsevier
ISSN1878-5638
Digital Object Identifier (DOI)https://doi.org/10.1016/j.ijnonlinmec.2024.104989
Web address (URL)https://www.sciencedirect.com/science/article/pii/S0020746224003548?via%3Dihub
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Output statusPublished
Publication dates
Online17 Dec 2024
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Deposited06 Mar 2025
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