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

2019/02/01 by Peng Li, Li, Peng
Engineering · #Adaptation and Self-Organizing Systems (nlin.AO) #Advanced Algorithms and Applications #Advanced Battery Technologies Research #Embedded Systems and FPGA Design #FOS: Electrical engineering #FOS: Physical sciences #Signal Processing (eess.SP) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1902.00226

openalex publication_date 2019/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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