SoC Estimation Lithium Polymer Battery Based on Equivalent Circuit Model and Extended Kalman Filter

The advancement of a battery management system is notably decisive in small unmanned aircraft. One of its roles is estimating the State of Charge. Where the State of Charge is used to determine the battery capacity to preventing over-discharging and under-discharging processes. Moreover, this is very important in maintaining the security of the electrical energy distribution process to the onboard electrical system on small-scale unmanned aircraft. In this study, the 5000 mAh Lithium Polymer battery modelling based on the Electrical Equivalent Circuit methods and the EKF algorithm was used to estimate the SoC, because this method provides low complexity and low computational requirements. The estimation results show that the MAE and RSME with this method showed less than 1%. Moreover, determination of noise is added to implemented in real conditions, where the results show that the SoC estimation is adaptive to a given disturbance.

I. Introduction

Battery Management System (BMS) is important in providing secure Lithium Polymer batteries for small unmanned aircraft vehicles by monitoring several indicators such as voltage, current and State of Charge (SoC) [1], [2]. Furthermore, State of Charge general-purpose is for knowing battery capacity [3].