Investigation of model order reduction techniques: A supercapacitor case study

Abstract

This paper presents several different model order reduction techniques to refine an equivalent circuit high order model of a supercapacitor. The presented model order reduction techniques are: truncation based, projection based and system identification based (data based). Upon application of these techniques to the high order model, it has been found that a reduced model with sufficient accuracy can be obtained to act as a surrogate of the real system. This is evident by the ability to reduce a 60th order supercapacitor model to 4th order whilst preserving accuracy.