State of Charge Estimation of Lithium Battery Based on FFRLS-SRUKF Algorithm

摘要

Aiming at the problem of parameter change of battery model and difficulty in accurately estimating the state of charge (SOC), this paper takes lithium iron phosphate battery as the research object, and based on the first-order RC equivalent circuit model of battery, dynamically identifies the parameters of the model through the recursive least square algorithm with forgotten factor, and establishes the timevarying parameter model of battery. Then, the state equation and observation equation of the battery are established by time-varying parameter model, and the SOC estimation of the battery is realized by using the square-root unscented kalman filter algorithm. This SOC estimation method can adapt to the parameter changes of the model, and has the ability to correct the error of the initial value. Experiments show that the time-varying parameter model can accurately simulate the changes of battery terminal voltage, and the SOC estimation strategy adopted can still accurately estimate the SOC of the battery under the condition that the initial value has a large error.