Real-Time State-of-Charge Estimation in Lithium-Ion Batteries Using Extended Kalman Filter

The autonomy of a battery applied in a system depends on the accurate estimation of its State of Charge (SoC). This paper presents real-time SoC tracking using an ESP32 module, which reads current and voltage sensors and processes an algorithm based on the Extended Kalman Filter (EKF) to estimate th...

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Bibliographic Details
Published in2023 IEEE 8th Southern Power Electronics Conference and 17th Brazilian Power Electronics Conference (SPEC/COBEP) pp. 1 - 8
Main Authors Bampi, Suelen, Waltrich, Gierri, Vaccari, Anderson
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.11.2023
Subjects
Discharges (electric)
EKF
electronic load
equivalent circuit model
Estimation
Mathematical models
real-time
Real-time systems
Resistors
Sensors
SoC
State of charge
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Summary:The autonomy of a battery applied in a system depends on the accurate estimation of its State of Charge (SoC). This paper presents real-time SoC tracking using an ESP32 module, which reads current and voltage sensors and processes an algorithm based on the Extended Kalman Filter (EKF) to estimate the SoC. The data applied to the EKF is based on an equivalent circuit model and obtained from tests conducted on a designed electronic load. The SoC estimation results obtained with LTO-66160H-2.3V40Ah batteries are consistent with expectations using EKF tracking.
ISSN:2832-2983
DOI:10.1109/SPEC56436.2023.10408586