Optimal control strategies for efficient energy harvesting from ambient vibration

Abstract

Ease of miniaturization and minimal maintenance are among the advantages for replacing conventional batteries with vibratory energy harvesters in a wide of range of disciplines and applications, from wireless communication sensors to medical implants. However, the current harvesters do not extract energy from the ambient vibrations in a very efficient and robust fashion, and hence, there need to be more optimal harvesting approaches. In this paper, we introduce a generic architecture for vibration energy harvesting and delineate the key challenges in the field. Then, we formulate an optimal control problem to maximize the harvested energy. Though possessing similar structure to that of the standard LQG problem, this optimal control problem is inherently different from the LQG problem and poses theoretical challenges to control community. As the first step, we simplify it to a tractable problem of optimizing control gains for a linear system subjected to Gaussian white noise excitation, and show that this optimal problem has non-trivial optimal solutions in both time and frequency domains.

Architectures for wrist-worn energy harvesting

“…Firstly, a linear viscous damper can indeed represent an optimal transducer force capable of maximizing harvester power output in response to certain excitations [19,20]. However, it would be unwise to assume the optimality of linear viscous damper transducer dynamics for all-or even most-architectures and all excitations [21][22][23][24].…”

Design of vibratory energy harvesters under stochastic parametric uncertainty: a new optimization philosophy

“…Since most of the energy is carried by the lowest excited harmonic of the vibratory structure, the cantilever beam PEH is usually modeled as a single-degree-of-freedom (SDOF) oscillator coupled with an electrical circuit as shown in figure 1. Assuming that the piezoelectric patches are directly connected to a load resistance, and that the harvester is base-excited the governing dynamic equations of the system could be written as [23,24] ˙˙˙()…”

Optimization of vibratory energy harvesters with stochastic parametric uncertainty: a new perspective

“…In its simplest form when the piezoelectric patches are connected to an electrical resistance, and when the vibratory system is base excited, the governing dynamic equations of the system could be written as 23,24 …”