A hybrid approach on estimating state of charge of lithium-ion batteries based on data driven Model

Abstract

The precise estimation State of Charge (SOC) becomes great significance for Bettery Balancing Charge and Discharge Mangement (BBCDM). In this paper, aimed at this challenge, one hybrid methodology for estimating the State of Charge(SOC) of Lithium-ion Battery(LIB) is presented adopting Extended Kalman Filter (EKF) as well as combine with Recursive Lest Square(RLS). Fist, the mathematical model is estimated including the experimental data acquisition with an Open Circuit Voltage (OCV) method is presented. Second, a hybrid strategy with EKF and RLS was adopted to describe state space equation and identify model parameters during the LIB charge/discharge test. Finally, estimation of SOC adopt proposed method revealing dynamic characteristics of LIB. The simulation results have shown the effectiveness of the new methodology and better accuracy and data maintenance ability.