An Estimation Algorithm of Extended Kalman Filter based on improved Thevenin Model for the management of Lithium Battery System

TL;DR

This paper introduces an improved Thevenin model-based extended Kalman filter algorithm for lithium battery SOC estimation, demonstrating accurate online estimation with experimental validation on lithium cobalt acid batteries.

Contribution

The paper presents a novel EKF estimation algorithm based on an improved Thevenin model for better lithium battery SOC estimation.

Findings

Estimation error remains within acceptable bounds.

Algorithm satisfies online SOC estimation requirements.

Validated with experiments on lithium cobalt acid batteries.

Abstract

We proposed a new estimation algorithm of extended Kalman filter (EKF) based on improved Thevenin model; Experiments were carried out to verify the validity with seven 4Ah lithium cobalt acid batteries in series. The experimental results showed that when using the algorithm, the estimation error of SOC is in the scope of error allowed, and the requirement of online SOC estimation can be satisfied.