Increasing demand for sustainable energy sources has attracted considerable attention to the issue of harvesting electrical energy from structural vibration signals through the use of piezoelectric materials. In this context, structural optimization techniques play an important role in the design of a given energy harvesting device. The goal of the present article is to compare deterministic and stochastic optimization methods applied to the design of energy harvesters. Firstly, a comprehensive discussion on the effects of aleatory uncertainties on the dynamics of a beam type piezoelectric energy harvesters carrying a tip mass is performed using the well known Monte Carlo Simulation (MCS) method. Following, a multi-parameter Sequential Quadratic Programming (SQP) optimization technique is employed in either the deterministic and stochastic problems in order to obtain a set of optimum geometric parameters for the harvester. Results from the numerical simulations simulations revealed that the superior performance of the stochastic programming approach in terms of the harvested electrical power. Additionally the improved results obtained from the stochastic programing approach also reinforces the importance of accounting for uncertainties in the design of energy harvesting systems.
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