Response Analysis of Asymmetric Monostable Harvesters Driven by Color Noise and Band-Limited Noise

Abstract

In this paper, we investigate the response of asymmetric potential monostable energy harvesters (MEHs) excited by color noise and band-limited noise. The motivation for this study is that environmental vibrations always have the characteristic of randomness, and it is difficult to modulate a perfectly symmetric MEH. For the excitation of exponentially correlated color noise, the moment differential equation was applied to evaluate the output performance of the asymmetric potential MEHs. Numerical and theoretical analyses were carried out to investigate the influence of noise intensity and internal system parameters on the output power of the system. Our results demonstrate that the output performance of the asymmetric MEH decreases with the increase in the correlation time, which determines the character of the color noise. On the contrary, the increase in the asymmetric degree enhances the output power of the asymmetric MEH subjected to color noise. For the band-limited noise excitation, numerical simulation is undertaken to consider the response of the asymmetric MEHs, and outcomes indicate that the frequency bandwidth and center frequency have a significant influence on the output performance. Regarding the asymmetric potential, its appearance leads the MEHs to generate higher output power at lower frequencies and this phenomenon is more obvious with the increase in the degree of asymmetry. Finally, we observed that the characteristics of the response bandwidth of asymmetric MEHs subjected to band-limited noise excitation are similar to the response under harmonic excitation.

A Bio-Inspired Bistable Piezoelectric Structure for Low-Frequency Energy Harvesting Applied to Reduce Stress Concentration

“…Vibration energy, being widely present, is a potential source of energy that could be harvested to power sensors [ 2 , 3 , 4 ]. The production of low-frequency energy harvesters is essential, as the vibration sources in ambient conditions, such as human walking, water flow, heartbeats, wind, or vehicle tires, tend to be in the range of 0–20 Hz [ 5 , 6 ]. This is of particular importance considering the development of wireless self-powered sensors for the IoT.…”