Published January 2012 | Version v1
Journal article

On-line supercapacitor dynamic models for energy conversion and management

  • 1. Dept. of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan (China)
  • 2. Dept. of Industrial Education, National Taiwan Normal University, Taipei, Taiwan (China)

Description

Highlights: ► On-line supercapacitor dynamic models are derived from time and frequency domains. ► Equivalent circuits with an ANN identifier are derived for nonlinear effects. ► Nonlinear effects include environmental temperature and operating voltage. ► Supercapacitor models can achieve both system fidelity and computation efficiency. - Abstract: This paper develops on-line nonlinear dynamic models of electrochemical supercapacitors which are for energy conversion and management. Based on the theory of electrochemical impedance spectroscopy, extensive alternative current impedance tests have been conducted to investigate the frequency-domain dynamics of these supercapacitors. A Nyquist diagram is plotted to help establish an equivalent electric circuit, which is regarded as the first-phase linear model. Two performance-influencing factors, environmental temperature and operating voltage, are considered as nonlinear effects. The nonlinear relationships among parameters of the capacitances and resistances in the first-phase model are established by a multi-layer artificial neural network. The neural parameters are trained using a back-propagation algorithm by feeding the experimental data bank. Combining the first-phase model and the on-line neural "parameter identifier", the algorithm produces an on-line nonlinear dynamic model. Simulation results have proved that this proposed model is able to achieve both system fidelity and computational efficiency.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2011.01.018

Additional details

Identifiers

DOI
10.1016/j.enconman.2011.01.018;
PII
S0196-8904(11)00063-X;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
53
Journal Issue
1
Journal Page Range
p. 337-345
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2011 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.