Experimental Data Driven Model Parameter Identificationfor LiFePO₄ Battery Packs

In the context of the popularization of electric vehicles, the estimation accuracy of power batteries affects battery life and safety. Because the SOC of lithium batteries cannot be measured directly and the internal structure is complex, a mathematical model needs to be established. This paper uses a second-order RC equivalent circuit model for lithium iron phosphate battery modules, and uses 0.25C - 0.75C pulse charge and discharge experiments to test the 75-string battery packs in four stages, and uses voltage response characteristics and least squares method to identify model parameters. Models are constructed in MATLAB, fit the SOC to open-circuit voltage relationship and introduce current segmentation control. Simulation results show that the model has a maximum error of 1.67% and an average error of 0.52% compared to experimental data, providing a feasible solution for estimating the SOC of lithium iron phosphate batteries in electric vehicles.