Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise

• Published in: Mechanical systems and signal processing Vol. 104; pp. 134 - 144
• Main Authors: Quaranta, Giuseppe, Trentadue, Francesco, Maruccio, Claudio, Marano, Giuseppe C.
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 01.05.2018; Elsevier BV
• Subjects: Cantilever beams; Computer simulation; Electrical loads; Electricity; Energy; Energy harvesting; Euler-Bernoulli beams; Eulers equations; Gaussian distribution; Harvesters; Normal distribution; Piezoelectricity; Probabilistic analysis; Probabilistic methods; Random noise; Random vibrations; Smart structures; Standard deviation; Structural monitoring; Vibration; Vibration mode; Smart structures; Structural monitoring; Energy harvesting; Random vibrations
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2017.10.031

•This work is concerned with linear piezoelectric bimorphs under random vibrations.•The base motion is modeled as modulated and filtered white Gaussian noise.•A semi-analytical procedure is developed for the probabilistic analysis.•Mean and standard deviation of the generated electrical energy are estimated. This paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers.