Vibration energy harvesting


fundamental limits to nonlinear energy harvesting and techniques to approach them

Every little bit counts toward energy efficiency, including catching what would be lost to stray mechanical vibrations. Current research into harvesting of vibrational energy aims to exploit nonlinearity for effective energy harvesting, but one of the key challenges in designing such harvesters is the immense range of possible nonlinearities.

Rather than focusing on specific nonlinearities, we have studied the fundamental limits, and have shown that for a simple vibratory system, this limit forms into a simple non-resonant harvesting strategy called buy-low-sell-high (BLSH), for any generic excitation statistics. A harvester following this strategy outperforms the linear and conventional nonlinear harvesters. This strategy also theoretically explains high effectiveness of the extensively-studied bistable harvester as well as other multi-stable harvesters at low frequencies . To realize the BLSH strategy we have proposed two inherently non-resonant harvesting mechanisms, namely latch-assisted mechanism and adaptive bistability.

robust energy harvesting under uncertainty

Parametric and excitation uncertainties are inevitable with any physical device operating in real-world environment mainly due to manufacturing tolerances, defects, environmental effects, and non-stationarity or randomness in nature; hence, taking into account uncertainty is consequential for effective and robust harvesting. 

For passive harvesters, we have proposed and formulated a new optimization philosophy; optimization for the worst-case scenario (minimum power) rather than for the expected power. This is particularly useful when there is a minimum power requirement for the self-powered device. We have shown that harvesters optimized with our proposed perspective are much more robust to uncertainties.For active hasvesters, we have developed a novel robust and adaptive sliding mode controller that can successfully move the harvester to any desired (high-energy) attractor in the presence of uncertainties and unmodeled dynamics. 

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