A Nonlinear Observer SOC Estimation Method Based on Electrochemical Model for Lithium-Ion Battery

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TitreA Nonlinear Observer SOC Estimation Method Based on Electrochemical Model for Lithium-Ion Battery
Type de publicationJournal Article
Year of Publication2021
AuteursLiu Y, Ma R, Pang S, Xu L, Zhao D, Wei J, Huangfu Y, Gao F
JournalIEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
Volume57
Pagination1094-1104
Date PublishedJAN
Type of ArticleArticle
ISSN0093-9994
Mots-clésComputational modeling, Electrodes, Estimation, Integrated circuit modeling, Lithium-ion batteries (LIB), Mathematical model, measurement noise error, nonlinear observer, Observers, single particle (SP) model, state of charge, state of charge (SOC) estimation
Résumé

As the global environmental pollution and energy crisis become more serious, lithium-ion batteries (LIB) received an increasing research interest due to their low self-discharge rates, long cycle life, and high power density for the transportation applications. Battery management system (BMS) plays an essential part for the LIB system as it can guarantee an efficient and stable operation through LIB state of charge (SOC) estimation. In this article, a nonlinear observer with terminal voltage feedback injection (VFNO) is designed based on the electrochemical single particle (SP) model to monitor the SOC of LIB. The convergence of the SP-VFNO system in consideration of measurement error is proved in terms of Lyapunov stability theory. The current, the terminal voltage, and the SOC reference value are measured in the battery testing system. Besides, the extended Kalman filter (EKF) based on both the SP model and the second-order resistor-capacitor (SORC) model to estimate SOC is adopted for comparison. The experimental results indicate that the proposed SP-VFNO method has superiority with a faster convergence rate and a higher estimation precision, which can help the accurate SOC estimation for BMS in practical application.

DOI10.1109/TIA.2020.3040140