Probabilistic response analysis of nonlinear vibration energy harvesting system driven by Gaussian colored noise
Di Liu,
Yong Xu and
Junlin Li
Chaos, Solitons & Fractals, 2017, vol. 104, issue C, 806-812
Abstract:
A new quasi-conservative stochastic averaging method is proposed to analyze the Probabilistic response of nonlinear vibration energy harvesting (VEH) system driven by exponentially correlated Gaussian colored noise. By introducing a method combining a transformation and the residual phase, the nonlinear vibration electromechanical coupling system is equivalent to a single degree of freedom system, which contains the energy-dependent frequency functions. Then the corresponding drift and diffusion coefficients of the averaged Ito^ stochastic differential equation for the equivalent nonlinear system are derived, which are dependent on the correlation time of Gaussian colored noise. The probability density function (PDF) of stationary responses is derived through solving the associated Fokker–Plank–Kolmogorov (FPK) equation. Finally, the mean-square electric voltage and mean output power are analytically obtained through the relation between the electric voltage and the vibration displacement, and the output power has a linear square relationship with the electric voltage, respectively. The main results on probabilistic response of VEH system are obtained to illustrate the proposed stochastic averaging method, and Monte Carlo (MC) simulation method is also conducted to show that the proposed method is quite effective.
Keywords: Nonlinear vibration energy harvesting; Quasi-conservative averaging method; Mean-square electric voltage; Gaussian colored noise; Correlation time (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077917303958
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:104:y:2017:i:c:p:806-812
DOI: 10.1016/j.chaos.2017.09.027
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().