Study On The Method Of Estimation Of The Lithium-ion Battery Management System SOC

The concept of environmental protection and energy-saving attracts more and more attention because of the aggravated environmental pollution and the lack of energy sources, which also makes the new energy electric vehicles enter people’s vision. The Battery Management System, working as the most critical part of the electric vehicles, decides the direction of electric vehicles’ development in future. Estimation of the State of Charge(SOC) has always been the core component in Battery Management System. Its accuracy will not only influence the battery life but also decide the performance of the Battery Management System.Study on the estimation method of Li-ion battery SOC of this paper.The main contents of the topic include:1. It overviewed briefly the electric vehicles, Li-ion battery and Battery Management System, introduced the battery’s working theory and characteristics, analysed the advantages and disadvantags of the main estimation methods of SOC.2. First of all, the category of battery model and modeling was presented in detail. Every construct and parameter of battery model was analysed and put forward on the basis of model selection, finally Thevenin was chosen as test model. Secondly, it introduces the test platform structure of battery management system and collectes experimental data by the platform. The model parameters are recognized by method of battery pulse discharge. At last, the paper applies MATLAB combined with extended Kalman filtering algorithm to estimate SOC. The simulation curves could detect the change of SOC rapidly, suffer little interference and have high precision.3. To reflect the dynamic and static characters of battery better, the paper raised an electrical model suited for Li-ion battery specially, considering the effect of cell polarization on SOC estimation. At the same time, it combines with adaptive control based on extended Kalman filtering. Through simulation analyses, it proved the model adaptative extended Kalman filtering algorithm had better stability and robustness to estimate SOC under the polarization effect.