An adaptive version of the Kalman Filter (KF) algorithm is investigated as a potential for State of Charge (SOC) estimation in Li-Ion cells. SoC estimation results of the adaptive KF via Battery Management System (BMS) model simulations in MATLAB & Simulink are discussed. The minimal SoC estimation error obtained in the results indicate strong KF adaptability to the complex non-linear cell behavior that typically occurs in active operation, especially in comparison with the Coulomb Counting (CC) current integration, and non-adaptive KF estimation methods.
Adaptive Method for Li-Ion Cell State-of-Charge Estimation in Smart Aircraft Applications
28.08.2023
1167201 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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