Model-based SOC Estimation Of Lithium Ion Battery

Coal,oil and natural gas are fossil fuels.The large-scale use of fossil fuels has greatly promoted economic development and gradually became a dependence on many industries such as transportation and aviation,but it has also brought about increasingly serious environmental problems.In order to alleviate environmental pollution and improve energy structure,China is actively promoting the development of new energy automobile industry,especially the development of pure electric vehicle industry.The power source for pure electric vehicles is the power battery.The accurate estimation of the state of charge(SOC)of the power battery is one of the indispensable functions of the battery management system(BMS).It is difficult to measure directly by instrument or sensor.Inaccurate SOC estimation may cause overcharging and over discharging of the battery or even overheating of the battery,which may cause the battery to explode and cause a safety accident.Therefore,an accurate SOC estimation algorithm is very important.This paper takes a 40 Ah ternary lithium-ion battery produced by a domestic battery manufacturer as the research object,and combines the extended Kalman filter algorithm(EKF)to study the battery SOC estimation algorithm.The main research contents are as follows:(1)Researched the power battery and its characteristics which commonly used in new energy vehicles,focusing on the comparison of lithium iron phosphate battery and ternary lithium ion battery,based on the current proportion of the two in the pure electric vehicle market and the future development trend of the power battery industry.The ternary lithium ion power battery was selected as the research object.(2)In order to fully understand the characteristics of the ternary lithium-ion battery in this paper,the capacity test experiment at different temperatures,the capacity test experiment under different discharge rates,the battery open circuit voltage calibration test and the DST discharge experiment were designed.(3)According to the data measured by the battery experiment,the second-order RC equivalent circuit model of the battery is identified by MATLAB,and a complete second-order RC equivalent circuit model is established.The model is validated by experimental data,and the simulation results show the model accuracy meets the modeling requirements.(4)Based on Kalman filter algorithm,combined with the second-order RC equivalent circuit model of battery,the measurement equation of EKF algorithm and its state equation are established.Finally,the battery SOC estimation algorithm is realized.The SOC algorithm is simulated and verified by the 14 A constant current discharge condition and the experimental data measured by the urban dynamometer driving schedule condition.The verification results show that the established SOC algorithm is accurate and meets the accuracy requirements of the SOC algorithm.