Enhancing the performance of Piezoelectric Energy Harvester under electrostatic actuation using a robust metaheuristic algorithm

Abstract

This study proposes a novel shape optimization methodology based on evolutionary algorithms to maximize the harvesting energy from piezoelectric energy harvester stimulated by the β-emitted radioisotope. The parametric width function is used to model the piezoelectric layer non-prismatically. All the geometrical dimensions as well as parameters related to the parametric width function are optimized using the metaheuristic algorithms The piezoelectric layer partially covers the beam to obtain the optimal location of the piezoelectric layer. The pull-in instability causes the discharge in the system, and the piezoelectric layer converts the vibration of the released microcantilever into electricity. The nonlinear effects of electrostatic force and geometry are taken into account, and the differential equations governing the system are discretized utilizing the exact mode shapes of the system considering the geometrical effects of non-uniform microcantilever and the piezoelectric layer. The robust chaotic Harris Hawk optimization (RCHHO) algorithm is proposed for finding the optimal shape of the system. The performance of the proposed algorithm is compared with various metaheuristic algorithms in the literature. After optimizing the shape of the piezoelectric layer, the maximum voltage produced with the optimal model using the presented method was 8.105 times that of the classic model with rectangular piezoelectric layer used in previous works. Moreover, the maximum energy and average energy harvested in the optimal model were 61 and 7.22 times, respectively, of the non-optimal model.