The process of collecting low-level kinetic energy, which is present in all moving systems, by using energy harvesting principles, is of particular interest in wearable technology, especially in ultra-low power devices for medical applications. In fact, the replacement of batteries with innovative piezoelectric energy harvesting devices can result in mass and size reduction, favoring the miniaturization of wearable devices, as well as drastically increasing their autonomy. The aim of this work is to assess the power requirements of wearable sensors for medical applications, and address the intrinsic problem of piezoelectric kinetic energy harvesting devices that can be used to power them; namely, the narrow area of optimal operation around the eigenfrequencies of a specific device. This is achieved by using complex numerical models comprising modal, harmonic and transient analyses. In order to overcome the random nature of excitations generated by human motion, novel excitation modalities are investigated with the goal of increasing the specific power outputs. A solution embracing an optimized harvester geometry and relying on an excitation mechanism suitable for wearable medical sensors is hence proposed. The electrical circuitry required for efficient energy management is considered as well.

This paper presents a novel modeling method for a magnetostrictive energy harvester connected to a resonant circuit. The method is based on analytical calculations coupled with experimental parameter identifications. The magnetic flux leakages from the pickup coil and the magnetostrictive material are considered. Under the assumptions of linearity and fundamental oscillation, the governing equations of the magnetostrictive energy harvester were derived from the Euler-Lagrange equations for an electromagnetic-mechanically coupled system. The energy harvesting efficiency of the harvester was obtained by solving the derived governing equations, and it can be described with five non-dimensional parameters. Among the non-dimensional parameters, the natural frequency ratio and damping ratio of the load resistance have optimal values to maximize the energy harvesting efficiency. This study derived these optimal design parameters depending on the circuit configuration and types of energy given to the harvester. In the magnetostrictive energy harvester with a series-resonant circuit subject to kinetic energy impact, these optimal design parameters can be obtained in simple algebraic forms. Experimental validations were conducted for the magnetostrictive energy harvester with a pure resistive circuit, with series- and parallel-resonant circuits, respectively to compare their energy harvesting efficiencies. While the pure resistive configuration can harvest 21 % of given mechanical energy, both series- and parallel-resonant configurations can harvest 23 %.

In the recent years triboelectric energy harvesting has gained a lot of research attention, and numerous triboelectric harvester designs have been proposed. We introduce a novel triboelectric energy harvesting architecture, where animal hair is used as the active material with a high positive charge affinity. To induce the triboelectric effect, animal hair is then brought into contact with polytetrafluoroethylene which in turn has a high negative charge affinity. In our approach, the electrodes are built as an array of individual charge collecting pins, which protrude into and interweave with the animal hair and skin and act as the net charge collector. The generators are built with two different approaches: a) by using 3D-printed structures with miniature electrode arrays and b) by using conductive fabrics arranged in a specific laminated structure. These are then tested in the laboratory in interaction with different animal hair materials with a novel methodology based on using a robotic manipulator test bed.