Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6879429 | AEU - International Journal of Electronics and Communications | 2018 | 19 Pages |
Abstract
To support real-time power management of the supercapacitor-powered embedded systems, an online model parameter identification method is proposed for predicting the supercapacitor behavior. In the proposed method, an optimization problem is formulated based on our previously developed supercapacitor model, and a weighting bat algorithm (WBA) with the weighting solution update method is proposed for solving this problem in each model parameter updating time window. Simulation and experimental results show that the proposed online model parameter identification method can accurately capture the terminal behavior of a supercapacitor, and the proposed WBA-based optimization method has better performance for the supercapacitor model parameter identification compared with other benchmark algorithms.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Geng Sun, Yanheng Liu, Ruizhi Chai, Fang Mei, Ying Zhang,