SOC Estimation of Ship Lithium Battery Based on UKF-VFFRLS

Battery management system (BMS), as the core monitoring system of lithium battery system for pure electric ships, is a core technology in the development of pure electric ships, and the estimation of battery state of charge (SOC) in BMS is even more crucial. At present, the most commonly used method for lithium battery model parameter identification is the recursive least squares (RLS) method, but the forgetting factor in this algorithm is fixed, which may not be able to meet the various working conditions of lithium batteries. Therefore, this paper proposes a SOC estimation algorithm that combines the Unscented Kalman Filter (UKF) filtering algorithm and Variable Forgetting Factor Recursive Least Squares (VFFRLS). Experiments show that this algorithm has higher accuracy than the single filtering algorithm.