This paper presents the fabrication, characterization and modeling of a wideband MEMS electrostatic energy harvester utilizing nonlinear springs. The experimental results show that the vibration energy harvester displays a strong softening spring effect. For narrow band vibration, the energy harvester exhibits a widening bandwidth during frequency down-sweeps. For increasing levels of broadband random noise vibration, the energy harvester displays a broadening bandwidth response. Furthermore, the vibration energy harvester with softening springs not only increases the bandwidth, but also harvests more output power than a linear energy harvester at a sufficient level of broadband random vibration. At a broadband random vibration of 7.0 × 10 −4 g 2 Hz −1 , we found that the bandwidth increases by more than 13 times and the average harvesting output power increases by 68% compared to that of a linear vibration energy harvester. Numerical analysis confirmed that the softening springs are responsible for the band broadening.
Micro-scale energy harvesting from motion has received increasing research interest. The energy harvesters can be used as replacements for batteries in low-power wireless electronic devices. Conventional vibration energy harvesters are designed as linear resonance structures.These have a very narrow bandwidth and operate efficiently only when the excitation frequency is very close to the resonant frequency of the harvester. The narrow bandwidth limits their applications in realworld environments that have a wide spectrum of frequencies or varying vibration spectra.This thesis investigates a method to extend the bandwidth of the energy harvesters. We exploit nonlinearities of suspensions, in particular softening and bistable characteristics, to widen the harvesting bandwidth. The nonlinear-spring characteristics are obtained purely through their geometrical design without relying on extra features such as permanent magnets that can interfere with the surroundings.Two electrostatic energy harvesters are designed, fabricated and characterized based on microelectromechanical systems (MEMS). The first harvester with a quad-angled spring, which displays a softening characteristic, is made by through-wafer-thickness deep-reactive ion etching onto a silicon wafer. The experimental results show that a 13-fold increase in the bandwidth of the harvester with the angled springs and an average output power increase of 68% compared with that of linear-vibrating energy harvesters at a broadband random vibration of 7×10 −4 g 2 /Hz.We also find that the harvester is tolerant to variations both in the center frequency and bandwidth of vibration, and can perform close to its theoretical maximum with wideband vibrations.The second MEMS electrostatic energy harvester with curved springs is fabricated on a silicon-on-insulator wafer using bulk micro-fabrication technology. The curved springs display an asymmetrical bistable behavior obtained purely through geometrical design. The experimental results with a white noise vibration at 4×10 −3 g 2 /Hz show that the harvester bandwidth reaches 715 Hz, representing the largest bandwidth reported in the literature so far.Such wideband harvesters are well-suited to extract power from a wide spectrum of vibrations or from sources with a wide range of variability in the spectrum.
PrefaceThis thesis is submitted in partial fulfillment of the requirements for the degree of Philosophiae Doctor (Ph.D) at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo. The thesis consists of a set of eight papers, including five journal articles and three conference papers, and an extensive Introduction.
We demonstrate the feasibility of using novel, small energy harvesters to power atmospheric sensors and radios simply attached to a single conductor of existing overhead power distribution lines. We demonstrate the ability to harvest the required power for operating multiple atmospheric and power-system sensors, together with short-range radios that could broadcast atmospheric sensor data to the cellphones of people nearby. Occasional long-range broadcasts of the data could also be made of both atmospheric and power-line conditions.
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