Robust design optimization of fixed-fixed beam piezoelectric energy harvester considering manufacturing uncertainties

Abstract

The piezoelectric energy harvester, which accumulates electrical energy from ambient vibration energy has emerged as an alternative energy source because of its eco-friendly characteristics. Numerous studies have been conducted on the basis of experimental methods to increase the power generating capabilities of the piezoelectric energy harvester. Recently, research using optimization techniques to improve the performance has been carried out. However, since the previous studies did not consider various uncertainties that exist in the energy harvester, it is difficult to overcome the variance of performance caused by the uncertainties. In order to obtain the highest performance from the piezoelectric energy harvester and simultaneously retain robustness while installed under the road pavement, this paper presents robust design optimization of piezoelectric energy harvester which is insensitive to the uncertainties. Prior to performing the robust optimization, statistical information of the uncertainties that exist in the piezoelectric energy harvester was measured from 30 piezoelectric experiments. Then uncertainty quantification was performed using Akaike information criterion. A statistical model calibration method, used to improve the accuracy of the simulation model for robust optimization, was proposed and implemented, based on the uncertainty data. By using the calibrated simulation model, the piezoelectric energy harvester was evaluated and optimized to achieve maximum performance and robustness simultaneously. Finally, the robust optimum design solution for the piezoelectric energy harvester was verified, showing improved performance and reduced variance.