A joint model and SOC estimation method for lithium battery based on the sigma point KF

Abstract

Lithium-ion batteries have been widely used in electric vehicles (EV). The working state of the battery is very important to the safety of an EV. Online estimation of the state of charge (SOC) is essential in obtaining the battery working conditions. In order to achieve an accurate estimation of the SOC, the battery model should be adjustable when the battery is aged. A joint battery model and SOC estimation method based on the sigma point kalman filter (SPKF) is presented. A combined battery model is used to depict the relationship between the open circuit voltage (OCV) and the SOC of the battery. The main battery model parameter for estimation is the internal resistance and it is jointly estimated with the SOC online. Experimental results show that the SPKF based joint estimation method is effective.