METHOD AND SYSTEM OF LITHIUM BATTERY STATE OF CHARGE ESTIMATION BASED ON SECOND-ORDER DIFFERENCE PARTICLE FILTERING

摘要

A method and a system of lithium battery state of charge (SOC) estimation based on second-order difference particle filtering belonging to the technical field of battery management are provided. The method includes the following steps: building a second-order RC battery model of a lithium battery; performing model parameterization by using a least squares algorithm with a forgetting factor; and generating an importance density function through a second-order central difference Kalman filtering (SCDKF) algorithm, improving a particle filtering algorithm to obtain a second-order difference particle filtering (SCDPF) algorithm, and performing SOC estimation on a lithium battery by using the SCDPF. The estimation method provided by the disclosure is accurate and has greater estimation accuracy than an unscented particle filtering algorithm (UPF), an unscented Kalman filtering algorithm (UKF), and an extended Kalman filtering algorithm (EKF). An SOC value of the lithium battery may thus be accurately estimated.