Translated Title

SOC estimation of lithium battery based on improved AFFRLS-AUKF

Translated Abstract

The　accurate　estimation　of　the　state　of　charge(SOC)of　lithium　batteries　is　one　of　the　im-portant　prerequisites　for　ensuring　the　safe　and　stable　operation　of　battery　management　systems.In　order　to　improve　the　accuracy　of　SOC　estimation　of　lithium　ion　batteries,an　SOC　estimation　method　of　lithium　ion　batteries　combined　improved　adaptive　forgetting　factor　least　squares(AFFRLS)with　adaptive　unscented　Kalman　filter(AUKF)algorithm　was　proposed.The　improved　AFFRLS　was　used　to　identify　the　parameters　of　the　established　second-order　RC　equivalent　circuit　model,and　the　AUKF　was　used　to　estimate　the　SOC　of　lithium-ion　batteries.The　average　absolute　error　of　the　joint　estimation　is　0.44%and　the　root　mean　square　error　is　0.61%through　the　verification　of　DST　and　UDDS　conditions,which　shows　that　the　improved　AFFRLS-AUKF　method　improves　the　accuracy　and　robustness　of　parameter　identification　and　battery　SOC　estimation.

Translated Keyword

adaptive forgetting factor
lithium-ion battery
state of charge
unscented Kalman filtering

Classification

Type

Project Name

Project No.

Access Number

WF:perioarticaldianyjs202406020

Language

Chinese

Corresponding s email

Author Info