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Feature selection for state-of-charge estimation of LiFePO4-Li4Ti5O12 batteries via electrochemical impedance

A safe and stable lithium-ion battery is created by pairing a lithium-iron-phosphate (LFP) cathode with a lithiumtitanate (LTO) anode. The open-circuit voltage of a LFP-LTO battery is flat over significant ranges of state of charge. The weak voltage state-of-charge relationship complicates state-ofcharge estimation algorithms that require open-circuit voltage measurements to calibrate or initialize coulomb counting. An alternative to open-circuit voltage state-of-charge calibration is analyzing the small-signal frequency response, which is stateof-charge dependent. The present paper estimates the electrochemical impedance spectra (EIS) using system-identification methods. The battery EIS is extracted from on/off current perturbations via balancing resistors. A LASSO regularization method is applied to the extracted EIS data for the purpose of obtaining frequencies of interest that are state-of-charge dependent. Extracted frequencies of interest are then utilized to create a state-of-charge predictor. The resulting method is validated using experimental results.