Leveraging nonlinear saturation-based phenomena in an L-shaped vibration energy harvesting system

• DOI: 10.1016/j.jsv.2015.11.017
• Publication Date: 2015-11-22T04:41:04Z
• Authors: R.L. Harne; A. Sun; K.W. Wang
• Keywords: Stochastic Resonance; Nonlinear resonance; Mechanical Resonance

Abstract Trees exploit intriguing mechanisms such as multimodal frequency distributions and nonlinearities to distribute and dampen the aerodynamically-induced vibration energies to which they are subjected. In dynamical systems, these mechanisms are comparable to internal resonance phenomena. In recent years, researchers have harnessed strong nonlinearities, including internal resonance, to induce energetic dynamics that enhance performance of vibration energy harvesting systems. For trees, the internal resonance-like dynamics are evidently useful to dampen swaying motions in spite of the high variation associated with excitation and structural parameters. Yet for dynamic systems, studies show narrow operating regimes which exhibit internal resonance-based behaviors; this additionally suggests that the energetic dynamics may be susceptible to deactivation if stochastic inputs corrupt ideal excitation properties. To address these issues and to investigate whether the underlying motivation of exploiting internal resonance-induced saturation dynamics is truly justified, this research evaluates the opportunities enabled by exploiting nonlinear, multimodal motions in an L-shaped energy harvester platform. The system dynamics are probed analytically, numerically, and experimentally for comprehensive insights on the versatility of internal resonance-based behaviors for energy harvesting. It is found that although activating the high amplitude nonlinear dynamics to enhance power generation is robust to significant additive noise in the harmonic excitations, parameter sensitivities may pose practical challenges in application. Discussion is provided on means to address such concerns and on future strategies that may favorably exploit nonlinearity and multimodal dynamics for robust energy harvesting performance.