AEKF-based Method of SOC Estimation for Batteries under the Active Short-time External Short Circuit

Abstract

State of charge (SOC) estimation is a key function of battery management system. This study examines the possibility of estimating the battery SOC under a certain short time External short circuit (ESC) process. Active short time ESC is sometimes useful in special applications that may not cause serious outcomes. The following contents are introduced in this papery. Firstly, ESC of cell experiment is designed under different SOC and temperatures. Then, genetic algorithm (GA) is used to identify model parameter, and SOC is estimated based adaptive extended Kalman filter (AEKF). It is illustrated that the presented SOC estimation can be well used in active ESC process with error less than 0.2%.