1 Model identification and parameter estimation for LiFePO4

lithium-ion battery We propose a method for dynamic model identification and parameter estimation of LiFePO4 cells based on current pulse measurements and electrochemical impedance spectroscopy (EIS). Modelling efforts were focused on diffusion as the predominant dynamic process relevant to battery management systems. An equivalent circuit model approach was adopted with parameters dependant on temperature and state of charge (SOC). The model was parameterised at 50 °C, 20 °C, 0 °C and-30 °C and between 10 % and 100 % SOC. Initial parameter estimations for the model identification procedure were informed by EIS. The model was validated (at constant SOC), for the entire temperature range and at C-rates between C/2 and 9C, by voltage simulation based on a dynamic drive cycle profile. Maximal residuals did not exceed 68 mV or 2 % of the nominal cell voltage (Vnom) and root-mean-square deviations remained within 28 mV or 0.8 % of Vnom at all temperatures and C-rates.