Estimation of lithium-ion battery state of charge for electric vehicles based on dual extended Kalman filter

State of Charge (SOC) estimation accuracy and robustness is significant to battery energy management, safety in use and residual cycle life. However, model parameters strongly depend on the battery status such as current rate, temperature and cycle times. In the research, Dual Extended Kalman Filter (DEKF) is used to reduce the influence of measurement and system noise and provide an accurate and robust solution by estimating both the battery states and the model parameters. In addition, a novel Open Circuit Voltage (OCV) curve acquisition method is presented to eliminate the affection of temperature and keep cycle times in consider. The validation is carried out by bench testing. Results show that the algorithm can be fast convergent in 60 seconds and stable keeping error below 3% in different current rate, temperature and cycle times.