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In this work a multicriteria optimization approach to minimize weight and maximize power output in piezoelectric energy harvesting systems for aerospace applications is studied. The design variables are the geometric and electric circuit parameters of the vibration-based piezoelectric energy harvester (PEH). A finite element model is developed to model the dynamic behavior of the composite plate-type harvester with embedded piezoelectric layers. The cantilever PEH structure is subjected to constraints in the bending stresses which must be lower than or equal to the tensile yield strength of the piezoelectric material. For solving the multi-objective optimization problem, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the Non-dominated Sorting Genetic Algorithm III (NSGA-III) and the Generalized Differential Evolution 3 (GDE3) algorithm are employed. It is shown that the proposed algorithms are effective in developing optimal Pareto front curves for maximum electrical power output and minimum mass of the PEH system. A comparative assessment of the solutions generated on the Pareto Front show that GDE3 achieved solutions that generate higher maximum power output and performs better compared to the two other algorithms.

Multicriteria Approach for Design Optimization of Lightweight Piezoelectric Energy Harvesters Subjected to Stress Constraints