Lithium-Ion Battery SOC Estimation Based on Adaptive Forgetting Factor Least Squares Online Identification and Unscented Kalman Filter

In order to improve the estimation accuracy of battery state charge (SOC) based on equivalent circuit model, a lithium-ion SOC method adaptive forgetting factor least squares and unscented Kalman filtering is proposed. The Thevenin model established. Through simulated annealing optimization algorithm, adaptively changed in real-time according demand, realized by combining least-squares online identification filter. results show that terminal voltage error identified extremely small; is, parameter high, joint algorithm with filter can also achieve high-precision SOC.