Extended Kalman Filter Based Estimation of the State of Charge of Lithium Iron Phosphate Battery Using an Equivalent Circuit Model

State of charge (SoC) estimation is vital for battery management systems in electric vehicles (EVs). Lithium-iron phosphate (LFP) batteries, known for their power density, cycle life, and thermal stability, present unique challenges due to flat voltage and hysteresis effects. This study employs a pu...

Full description

Saved in:
Bibliographic Details
Published in2024 6th International Conference on Energy, Power and Environment (ICEPE) pp. 1 - 6
Main Authors Antony, A Johnson, Kamakshy, Selvajyothi
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.06.2024
Subjects
Batteries
Equivalent Circuit Model
Estimation
Extended Kalman filter
Hysteresis effect
Integrated circuit modeling
Kalman filters
State of charge
Vehicle dynamics
Voltage
Online AccessGet full text

Cover

More Information
Summary:State of charge (SoC) estimation is vital for battery management systems in electric vehicles (EVs). Lithium-iron phosphate (LFP) batteries, known for their power density, cycle life, and thermal stability, present unique challenges due to flat voltage and hysteresis effects. This study employs a pulse current test to identify parameters for two RC Equivalent Circuit Models (ECMs) and uses the Extended Kalman Filter (EKF) for SoC estimation. Three ECMs are developed and compared, with the model incorporating a hysteresis correction factor (HCF) showing superior performance. Validated with Dynamic Stress Test (DST) and Federal Urban Driving Schedule (FUDS) cycles, the HCF model reduces average error and RMSE significantly, demonstrating robust and accurate SoC estimation for LFP batteries
ISSN:2832-8973
DOI:10.1109/ICEPE63236.2024.10668934