Co-Estimation of State-of-Charge and State-of-Health for Lithium-Ion Batteries Considering Temperature and Ageing

State-of-charge (SOC) estimation of lithium-ion batteries (LIBs) is the basis other state estimations. However, its accuracy can be affected by many factors, such as temperature and ageing. To handle this bottleneck issue, we here propose a joint SOC-SOH method considering influence temperature. It combines Forgetting Factor Recursive Least Squares (FFRLS) algorithm, Total (TLS) Unscented Kalman Filter (UKF) algorithm. First, FFRLS algorithm used to identify update parameters equivalent circuit model in real time under different battery ageing degrees. Then, TLS estimate SOH improve prior SOC. Next, SOC calculated UKF finally, more accurate obtained according UKF-based trajectory. The battery-in-the-loop experiments are utilized verify proposed For cases change up 35 °C capacity decay 10%, our estimator achieve ultra-low errors, bounded 2%, respectively, for paves way advancement use applications, electric vehicles microgrid applications.