Lithium Ion Battery Parameter Estimation Using Machine Learning

Resistance and capacitance are two important electrical factors that affect the longevity and performance of Li-ion batteries. To improve energy efficiency, forecast battery life, and optimize battery management systems (BMS), these factors must be estimated accurately. Based on input data like temperature, current, terminal voltage, output voltage, and state of charge (SOC), this study uses machine learning approaches to predict a Li-ion battery’s resistance and capacitance. To simulate the behavior of the battery, a two-parameter RC circuit model is employed, and curve fitting and machine learning are used to estimate the parameters. More dependable battery performance modeling is made possible by the results, which demonstrate encouraging accuracy in forecasting the important battery parameters.