Author:
Feng Juqiang,Si Yuwen,Huang Kaifeng,Lu Jun,Zhang Xing
Abstract
Abstract
The online identification model parameters can reflect the real terminal voltage state of the battery in real time and provide accurate observation data for battery SOC estimation. BMS is an important part of new energy vehicles, which supervises and controls the working process of the battery. The core of BMS is SOC estimation, and the accuracy of its estimation is related to whether the battery works efficiently and safely. Based on Thevenin model, FFRLS-EKF and KF-EKF were used to estimate the SOC of ternary lithium battery under DST condition. The estimation results show that FFRLS-EKF has a maximum error of 0.0079, which can estimate the SOC of the battery well.
Subject
General Physics and Astronomy
Reference10 articles.
1. Adaptive State of Charge Estimation of Lithium-Ion Batteries With Parameter and Thermal Uncertainties[J];Chaoui,2016
2. Temperature, Ageing and Thermal Management of Lithium-Ion Batteries[J];Spitthoff;Energies,2021
3. Review on state of charge estimation methods for Li-ion batteries[J];Zhang;Transactions on Electrical and Electronic Materials,2017
4. A Dynamic State-of-Charge Estimation Method for Electric Vehicle Lithium-Ion Batteries[J];Liu;Energies,2019
5. Online Estimation and Error Analysis of both SOC and SOH of Lithium-ion Battery based on DEKF Method[J];Lf;Energy Procedia,2019
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献