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Stochastic Response Determination of Hysteretic Vibratory Energy Harvesters with Fractional Derivatives via Stochastic Averaging
https://orcid.org/0000-0002-4049-678X
https://orcid.org/0009-0001-6339-6810
The realistic modeling of vibratory energy harvesters is necessary to ensure their reliable performance when subjected to random excitation. However, the hysteretic behavior of piezoelectric materials and the nonlocality of fractional electrical components make the numerical estimation of their stochastic response computationally challenging. This paper proposes an iterative method based on equivalent linearization and stochastic averaging for estimating the stationary probability density function of the output voltage amplitude of vibratory energy harvesters modeled as a hysteretic oscillator with fractional electrical components subject to a broadband stochastic process. By estimating the average of hysteretic terms, one can find an amplitude-dependent linear governing equation for the output voltage, from which one can determine a stochastic differential equation governing the evolution of the output voltage amplitude. We obtain the stationary solution of the corresponding Fokker–Planck equation in a semianalytical form, and we include comparisons with pertinent Monte Carlo simulation data to show that the estimated probability density functions are accurate and obtained at a minimal computational cost.
Stochastic Response Determination of Hysteretic Vibratory Energy Harvesters with Fractional Derivatives via Stochastic Averaging
https://orcid.org/0000-0002-4049-678X
https://orcid.org/0009-0001-6339-6810
The realistic modeling of vibratory energy harvesters is necessary to ensure their reliable performance when subjected to random excitation. However, the hysteretic behavior of piezoelectric materials and the nonlocality of fractional electrical components make the numerical estimation of their stochastic response computationally challenging. This paper proposes an iterative method based on equivalent linearization and stochastic averaging for estimating the stationary probability density function of the output voltage amplitude of vibratory energy harvesters modeled as a hysteretic oscillator with fractional electrical components subject to a broadband stochastic process. By estimating the average of hysteretic terms, one can find an amplitude-dependent linear governing equation for the output voltage, from which one can determine a stochastic differential equation governing the evolution of the output voltage amplitude. We obtain the stationary solution of the corresponding Fokker–Planck equation in a semianalytical form, and we include comparisons with pertinent Monte Carlo simulation data to show that the estimated probability density functions are accurate and obtained at a minimal computational cost.
Stochastic Response Determination of Hysteretic Vibratory Energy Harvesters with Fractional Derivatives via Stochastic Averaging
https://orcid.org/0000-0002-4049-678X
https://orcid.org/0009-0001-6339-6810
The realistic modeling of vibratory energy harvesters is necessary to ensure their reliable performance when subjected to random excitation. However, the hysteretic behavior of piezoelectric materials and the nonlocality of fractional electrical components make the numerical estimation of their stochastic response computationally challenging. This paper proposes an iterative method based on equivalent linearization and stochastic averaging for estimating the stationary probability density function of the output voltage amplitude of vibratory energy harvesters modeled as a hysteretic oscillator with fractional electrical components subject to a broadband stochastic process. By estimating the average of hysteretic terms, one can find an amplitude-dependent linear governing equation for the output voltage, from which one can determine a stochastic differential equation governing the evolution of the output voltage amplitude. We obtain the stationary solution of the corresponding Fokker–Planck equation in a semianalytical form, and we include comparisons with pertinent Monte Carlo simulation data to show that the estimated probability density functions are accurate and obtained at a minimal computational cost.
Stochastic Response Determination of Hysteretic Vibratory Energy Harvesters with Fractional Derivatives via Stochastic Averaging
J. Eng. Mech.
dos Santos, Ketson R. M. (author) / Duarte, João G. C. S. (author)
2024-07-01
Article (Journal)
Electronic Resource
English
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