Energy Scavenging for Body Sensor Networks

Abstract

For small, inexpensive, ubiquitous wireless sensors to be realized, all constituents of the device, including the power source, must be directly integratable. For long term application the device must be capable of scavenging power from its surrounding environment. An apparent solution lies in conversion of mechanical energy to electrical output via the growth and direct integration of piezoelectric thin films unimorphs with the wireless electronics. Current devices are limited by both their design and material selection. This paper will address optimizing the design of microscale devices by showing how the device strains under input vibration are directly proportional to its power output, and by proposing some designs which increase the strain distribution over more of the device volume. Finite element modeling (ANSYS ®) was used to determine the strain distribution in a cantilever, modified cantilever, trapezoid, and spiral shaped piezoelectric microscale energy scavenging system. The devices have been fabricated and initial results are presented.

Modeling and analysis of energy harvesting nodes in wireless sensor networks

“…By continuing this procedure for states n and N + n for n = 1, ..., N − 1, we can conclude that π n = απ N +n−1 (9) where α = 1−p p . The equilibrium equation for a boundary around state n, where 1 ≤ n ≤ N − 2 ( Figure 1, Boundary C) results in…”

Performance evaluation of low‐power wireless sensor node with hybrid energy storage

“…In this paper, we consider the SNs as vibration energy harvester as also demonstrated in the previous studies. 21,25,26 The energy is harvested independently by every sensor node. It is considered that there is randomness in the vibration-based harvested energy.…”

“…Hence, total ESU cost V C C max + V B B max must be less than or equivalent to V T .Our goal is to find optimum value of C max and B max which is denoted by C' max and B' max , respectively, that maximizes and minimizes the TEO duration. We use Equation25 to calculate C′ max and B' max . The optimization problem can be stated as C′ max ; B′ max ð Þ¼ arg max…”