Application of extended Kalman filter algorithm in optimizing SOC estimation

Nowadays, in the automotive industry, pure electric vehicles are gradually becoming the focus of attention. As the core energy storage component of electric vehicles, the battery plays an increasingly important role. Among them, The parameter of SOC plays an important role in the practical application of the battery. It can directly reflect the remaining power of the car, so that users can have a clearer understanding of the remaining mileage of their car, thereby improving the user's driving experience. At present, the parameter of SOC can not be obtained directly by experimental equipment, which requires us to find the most suitable method to solve the SOC parameters of the battery. Our research will start with the 18650 lithium battery, which is widely used at present, and study the application of the extended Kalman filter algorithm model to optimize SOC estimation.