Title :
Output Voltage Estimation for Vibration Energy Harvesters Using Relevance Vector Mechines
Author :
Li, Chuan ; Hong, Daewoong ; Kwon, Kwang-Ho ; Jeong, Jaehwa
Abstract :
By converting natural vibration into electricity, vibration energy harvesters (VEHs) provide promising self-power resources to drive wireless electronic systems. The output voltage is a vital parameter to evaluate the performance of a VEH. Considering the fact that relation between the operation conditions and the output voltage is nonlinear, a relevance vector machine (RVM) -based approach is proposed to estimate the output voltage. The vibration frequency, acceleration amplitude, and load resistance are employed as the input vectors so as to model the harvested electricity voltage which is the output vector of the RVM. An experimental set-up is used to collect real data for RVM modeling and precision evaluation. The results show that the proposed method is capable of estimating the output voltage for the VEH with good precision.
Keywords :
acceleration; electric potential; energy harvesting; mechanical engineering computing; power engineering computing; support vector machines; vibrations; RVM-based approach; acceleration amplitude; electricity; load resistance; natural vibration; operation condition; output voltage estimation; relevance vector machines; vibration energy harvester; vibration frequency; wireless electronic system; Acceleration; Data models; Estimation; Mathematical model; Support vector machines; Vectors; Vibrations; estimation; nonlinearity; relevance vector machine; vibration energy harvester; voltage;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.201
