Online parameter identification for equivalent circuit model of lithium-ion battery

Abstract

Parameter identification is the most fundamental task for the model-based battery management system. However, there are some difficulties in completing this task since most of the existing methods require at least one known parameter or a time-consuming offline procedure to extract parameters from measured data. Based on the well-known thevenin equivalent circuit for battery, this paper determines the unique purpose is introducing the bounded varying forgetting factor recursive least square approach which identifies online all the parameters of the battery model at the same time. The precision of the proposed method is verified by simulation with the error converged to zero and the maximum error less than 1% of the nominal value.