PHYSICS-BASED MODELS AND DESIGN FOR STATE-OF-CHARGE ESTIMATION OF LITHIUM-ION CELL

Abstract

In recent years, environmental pollution and the energy issue have gained more attention. A lot of emphasis has been focused on lithium batteries because of their low emissions, great energy density, and safety. It is vital to create an accurate model in order to investigate the battery’s operation in more detail. In keeping with the specifications of the battery. Precise state of charge (SoC) estimate is the fundamental function of a battery management system (BMS), and it significantly extends battery life and enhances battery performance. For the purpose of cell modeling and SoC estimate, a Turnigy Graphene 5000mAh 65C cell dataset is chosen for this research. The First order and second-order Thevenin equivalent circuit model is selected as the cell model due to a tradeoff between model complexity and accuracy. The parameters to identify include OCV, internal ohmic resistance, polarized internal resistance and capacitance. They were obtained with the MATLAB toolbox at various SoC state points under different temperatures. The ‘terminal voltage comparison’ method is utilized to verify the identification’s accuracy. The simulation results turn out to be satisfactory.