Tracking Of Maximum Electrical Power for a Piezoelectric Energy Harvesting System

Recent global environmental challenges have urged researchers to work on renewable energy resources. One major category of these resources is piezoelectric materials. This paper presents dynamic modeling of a piezoelectric energy harvesting system and then presents two level methodology using artificial neural networks to reach its maximum power output. Simulation results show desirable performance of the system, which leads to output increasing and tracking of maximum power in a limited time.