SOC Estimation Methods for Lithium-Ion Batteries without Current Monitoring
Source abstract
Abstract
State of charge (SOC) estimation is an important part of a battery management system (BMS). As for small portable devices powered by lithium-ion batteries, no current sensor will be configured in BMS, which presents a challenge to traditional current-based SOC estimation algorithms. In this work, an electrochemical model is developed for lithium batteries, and three methods, including the incremental seeking method, dichotomous method, and extended Kalman filter algorithm (EKF), are separately developed to establish the framework of current and SOC estimation simultaneously. The results show that the EKF algorithm performs better than the other two methods in terms of estimation accuracy and convergence speed. In addition, the estimation error of the EKF algorithm is within ±2%, which demonstrates its feasibility.
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Research context
OpenAlex topics: Advanced Battery Technologies Research · Neuroscience and Neural Engineering · Analog and Mixed-Signal Circuit Design
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, China
School of Chemical Engineering and Chemistry, Harbin Institute of Technology, Harbin 150001, China
References (33)
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