Methods of piezoelectric energy harvesting from human body motions

A lot of research has been done to enable self-powered wireless electronic devices. One of the most studied methods is the conversion of ambient vibrational energy into low-power electricity. The drastic decrease in power requirements of wearable electronics and sensors over the past decade makes the wearable devices industry a great test bed for this research. The growing interest in health and fitness monitoring, or even performance trackers in different sports provides many applications for this research. Smart flooring systems with Internet of Things integration have also received increased interest for tracking, security, and healthcare application. This work explores the potential of human-scale motion energy to enable self-powered sensor networks for on-body devices and potentially for indoor and outdoor smart flooring concepts. Electromechanical models are developed and analyzed for energy harvesting from base-excited and plucked bimorph piezoelectric cantilevers, as well as direct force excitation of curved unimorph harvesters. This thesis discusses the development and experimental validation of these models. Using measured human body acceleration and forces, the potential for energy harvesting from human motion using piezoelectric harvesters is quantified through experiments and model simulations.M.S