Energy harvesting from electrospun piezoelectric nanofibers: analysis and design under non-stationary random vibrations

The possibility of adopting vibration-powered wireless sensors for structural monitoring applications has received great attention in the last few years. Therefore, the development of effective computational approaches in this field is of paramount importance in order to evaluate the feasibility of such technology and to improve current design procedures. In this perspective, the present paper illustrates an efficient approach for the electromechanical probabilistic analysis and design of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN). Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN which is filtered through the Clough-Penzien filter, whose dominant frequency is a time-dependent deterministic parameter. The considered piezoelectric harvester is a cantilever bimorph modelled as Euler-Bernoulli beam with a concentrated mass at the free-end and its global behaviour is approximated by the fundamental vibration mode. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original semi-analytical procedure is adopted to estimate mean and standard deviation of the generated electrical energy. Finally, a probabilistic-based optimum design problem for energy harvesters under random vibrations is proposed.