A new method for lithium-ion battery's SOH estimation and RUL prediction

State of health (SOH) estimation and remaining useful lifetime (RUL) prediction are important for a battery management system (BMS). This paper presents a new method to estimate SOH by taking local voltage variation and capacity variation in charging or discharging process of the battery as SOH indexes, and realizes RUL prediction based on a particle filter. The effectiveness is validated using a NCM/LTO lithiumion battery pack.