New LiFePO4 Battery Model Identification for Online SOC Estimation Application

Abstract

The estimation of batteries State of charge is a crucial step in the developing of advanced plug-in and hybrid electric vehicles. In fact, the the accuracy of on line SOC estimation techniques is closely related to the reliability of the battery model which could efficiently describe the complex behavior of the battery during vehicle operation and rest periods. In this context, a new battery model is proposed and an online identification technique is developed to truck the model parameters variations and to ensure a high level of accuracy for onboard SOC estimation tasks. The accuracy of the developed model is verified by simulations using Matlab software and by experiments tests using a National Instruments platform.