State Estimation of Lithium-Ion Battery at Different Temperatures Based on DEKF and RLS

Abstract

Lithium-ion power battery is the power source of many electronic control systems. The battery state of charge (SOC) and state of health (SOH) are very important to the safety and reliability of the electronic system. Therefore, high-precision estimation of battery SOC and SOH has become one of the current research hotspots in the battery field. In order to realize the state estimation of lithium-ion power battery, an equivalent circuit model of lithium-ion power battery is established. This article is based on the HPPC pulse experiment data and the second-order Thevenin equivalent circuit model. At different temperatures (0°C, 25°C, 45°C), the recursive least square (RLS) method is used to identify of parameters of the equivalent model circuit. The state equation and measurement equation of the double extended Kalman filter (DEKF) algorithm are used to estimate SOC and SOH. Finally, this article uses experimental data of the single cell to estimate the battery state. The accuracy and adaptability of the combination of least squares algorithm and dual extended Kalman filter are verified. This is of great significance for improving the safety, reliability and economic benefits of the battery system.