Abstract
A technique based on a double-extended Kalman filter (DEKF) is created to estimate the SOC of a lithium-ion battery pack in real time. The Kalman filter technique and the Thevenin battery model are used to develop a state-space expression for the battery model. Improved accuracy and a more faithful representation of the battery’s internal state are achieved using the least squares approach and the DEKF algorithm to determine the model’s parameters. Experiments are developed for testing batteries that adhere to the presented idea of the online estimate of charge status using the DEKF algorithm. The results of the experiments demonstrate the algorithm’s excellent accuracy and environmental flexibility in calculating SOC online in various settings. The greatest error is less than 4.5 percent. The DEKF method is shown to successfully address the issues of erroneous initial estimates and cumulative errors and to have strong convergence and resilience.
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