Research On SOC Estimation And Active Equalization Method For Lithium Ion Battery Management System

Battery management technology is still a bottleneck in the development of the electric vehicle industry.Lithium-ion batteries have attracted much attention because of their high energy density,long life,high nominal voltage,high power density,and low cost.Intelligent battery management system is one of the indispensable components of electric vehicles.It can not only accurately measure the battery status parameters,but also ensure the safe use of the battery and extend its life.The main function of the system is to estimate the state of charge(SOC)and battery equalization.This paper focuses on the SOC estimation and active equalization methods of automotive energy storage lithium batteries.First,the characteristics analysis and battery modeling of the lithium battery are carried out.This article analyzes the properties of lithium batteries and the principle of internal ion transfer,compares the characteristics of six different material batteries that have been put into use in some power systems,and chooses lithium iron phosphate as the model for analysis.At the same time,after analyzing various battery models,the Thevenin model is selected as the battery model in this paper and the SOC estimation is performed on the basis of it.Then complete the charge and discharge experiment of the required working conditions through the battery test equipment,import the experimental data into the engineering software MATLAB to fit the parameters of the battery model,and obtain the functional relationship between the model parameters and the SOC to complete the parameter identification.Secondly,the estimation method of SOC is studied.This article analyzes the current common SOC estimation methods,and then analyzes the influencing factors of these methods and the complex reasons that lead to inaccurate SOC estimation.Then use the established battery model to estimate the SOC using the improved extended Kalman filter method and build the MATLAB / Simulink test environment and model program,import the parameter data of the battery,and run the calculation model before and after the improvement respectively and compare the results.It is verified that the improved extended Kalman filtering method has higher estimation accuracy and better convergence than before the improvement.Finally,by comparing various active equalization methods,a combined equalization scheme based on the principle of bidirectional flyback conversion and the principle of multi-inductance equalization is designed to achieve active balancing of the battery pack.Compare the average value of the SOC value of the cell with the SOC value in the group,set the upper threshold of the difference between the two,and use it as a condition for performing equalization control.At the same time,set the upper and lower limits of the cell voltage,and use this as a condition to screen for overcharge / Discharged battery,overcharge / discharge protection for it in time.Set up a test environment in MATLAB / Simulink,compare the combined method and the traditional multi-inductance method,and balance different numbers of batteries.The results show that the designed combined circuit equalization method can achieve a bidirectional transfer of energy between the battery pack and the single cell,It has good balancing efficiency when the number of batteries is small,and it also has better balancing performance when the number of cells increases.