Yizhao Gao, Simona Onori
State-of-charge (SOC) estimation for LiFePO 4 (LFP) batteries presents challenges due to their flat open-circuit voltage. Recent studies suggest that electrochemical impedance spectroscopy (EIS) offers a promising approach for SOC estimation in LFP cells. This work investigates a practical SOC estimation method based on EIS data obtained from short-duration sinusoidal current pulses. First, the EIS of LFP cells is characterized across a broad frequency range [0.01 Hz, 1000 Hz] and SOC range [0, 1]. The EIS magnitude and phase at 0.01 Hz exhibit the highest signal-to-noise ratio and are thus selected as features for SOC estimation. An EIS identification algorithm is then developed and validated to reconstruct EIS at 0.01 Hz. This method utilizes Fourier series expansion to approximate the voltage response to small sine-wave current perturbations. SOC estimation is subsequently performed by mapping the reconstructed EIS to experimental EIS data. Finally, the proposed SOC estimation approach is validated using sine-wave currents of varying amplitudes (0.05A and 0.1A) and different cell operation modes (discharge and charge). The results demonstrate rapid and accurate initialization of LFP cell SOC using this estimation algorithm. • Rapid EIS-based SOC estimation method for LiFePO4 batteries using sine-wave currents. • EIS at 0.01 Hz shows highest signal-to-noise ratio for accurate SOC estimation. • SOC estimation algorithm addresses challenges posed by flat OCV-SOC curve in LFP cells. • Sine-wave pulses effectively reconstruct EIS, achieving reliable SOC prediction. • Practical SOC estimation without costly equipment using current/voltage signal data.