Research, Innovation and Commercialization
At VibraPower, we are revolutionizing the traditional vibration energy harvesters, with the aid of nonlinear oscillator and dynamic Hebbian learning, a resonance tracking vibration energy harvester is built, which can harness the maximum natural and wasted vibration energy to generate electricity.
Resonance Tracking Vibration Energy Harvester
Vibratory energy harvesters can mostly be divided into two groups: (1) Excellent at capturing the energy from a narrowband vibratory source, (2) Good at capturing the broadband vibratory energy. While the above-mentioned two vibration energy harvesters are not particularly efficient for common vibratory energy sources, which are non-stationary.
Our technology creates a high Q-factor oscillator that can harvest non-stationary vibratory energy sources, which we call a resonance-tracking vibration energy harvester.
Shown on the left is an experimental demonstration of resonance-tracking technology when the external vibration input frequency varies, where the rod length can be adapted accordingly based on the feedback information from the system dynamics.
The resonance tracking technology utilizes the dynamic Hebbian learning based adaptive oscillators, which are a subset of nonlinear oscillators that can intrinsically learn and store information into its states.
Our vibration energy harvester technology could be efficiently and widely applied to many applications, as the actual vibration source is generally non-stationary.
Academic Publications
XiaoFu Li, Md Raf E Ul Shougat, Tushar Mollik, Robert Dean, Aubrey Beal, Edmon Perkins, “Field-programmable analog array (FPAA) based four-state adaptive oscillator for analog frequency analysis”, Review of Scientific Instruments (2023).
XiaoFu Li, Aubrey Beal, Robert Dean, Edmon Perkins, “Chaos in a Pendulum Adaptive Frequency Oscillator Circuit Experiment”, Chaos Theory & Applications (2023).
XiaoFu Li, Pawan Kallepalli, Tushar Mollik, Md Raf E Ul Shougat, Scott Kennedy, Sean Frabitore*, Edmon Perkins, “The Pendulum Adaptive Frequency Oscillator”, Mechanical Systems and Signal Processing (2022).
XiaoFu Li, Md Raf E Ul Shougat, Tushar Mollik, Aubrey N. Beal, Robert Dean, Edmon Perkins, “Stochastic Effects on a Hopf Adaptive Frequency Oscillator”, Journal of Applied Physics (2021).
XiaoFu Li, Md Raf E Ul Shougat, Scott Kennedy, Casey Fendley, Aubrey N. Beal, Robert N. Dean, Edmon Perkins, “A four-state adaptive Hopf oscillator”, PLoS One (2021).