State Of Charge Estimation Of The Lithium-ion Battery Based On Quadrature Kalman Filter

With the development of new energy vehicles,lithium-ion batteries have been widely used in the automotive industry.In order to ensure the safe and stable operation of vehicles,real-time monitoring of battery management systems is required.As the key part of the battery management system,the estimation accuracy requirement for the state of charge(SOC)of lithium-ion batteries are constantly improving,and the research of SOC estimation algorithms has gradually became a research hotspot in recent years.This paper takes lithium iron phosphate batteries commonly used in new energy vehicles as the research object.The influencing factors of battery SOC estimation are analyzed.Compared with the commonly used SOC estimation methods,the quadrature Kalman filter algorithm is applied to estimate battery SOC under the requirements of accuracy,stability,and real-time.The state space equation of the system is established based on the second-order RC equivalent circuit model,and the state space equation in the continuous time is discretized.The stability of the SOC estimated by the quadrature Kalman filter algorithm is analyzed,and the stability of the SOC estimated by the algorithm is proved.Under the three different conditions of constant current discharging,pulse discharging,and UDDS,the extended Kalman filter algorithm,the unscented filter algorithm,and the quadrature Kalman filter algorithm is compared to verify the accuracy of the quadrature Kalman filter algorithm.The simulation results show that the quadrature Kalman filter algorithm applied in this paper can estimate the battery SOC well.Compared with the extended Kalman filter and unscented filter algorithm,it not only improves the accuracy of the estimation,but also has the stability of the estimation,which has a reference significance for SOC estimation of automotive lithium-ion batteries in practical applications.