Research On Battery Management System Based On Active Balance

Non-renewable fossil energy sources such as oil,natural gas and coal are increasingly exhausted,which will definitely affect the development of the traditional fuel automobile industry.Electric vehicles have the characteristics of "zero" emissions,so all countries in the world are actively advocating and supporting the development of electric vehicle industry and have made a prohibition schedule for traditional fuel vehicles.As the power source of electric vehicle,lithium ion battery is favored by peop le all over the world.Because of its high energy density,long cycle life,no pollution and other advantages,it becomes the best power source for electric vehicles.Battery management system is the brain of lithium ion power battery,which can improve the energy utilization rate of power battery and extends the service life of battery,and indirectly alleviates the expanding trend of energy crisis.This research focuses on the State of Charge(SOC)estimation and balance of battery management system.The main work is are as follows:Firstly,the advantages and disadvantages of SOC technology for lithium ion batteries are studied.The open-circuit voltage and SOC values of the battery model were obtained by using the second order davenin model and extended kalman filter.Based on the simulation data,the corresponding curve relationship between open circuit voltage(OCV)and SOC is established,and then the SOC estimation is obtained.STM32F103RCT6 is used as the main control chip of the battery management s ystem and the system parameters are collected by it.Using extended kalman filter alone can not eliminate the acquisition error.Aiming at the problem of acquisition error,a joint estimation method of classical complementary filtering and extended kalman f iltering is proposed,and the SOC estimation experiment is carried out by using the joint algorithm.The results show that the joint algorithm is more accurate than the extended kalman filter method and can eliminate the acquisition error.Secondly,the problem of low energy utilization of passive equalization system and inconsistency of battery are analyzed.A multi-criteria defined inductance active balancing topology is designed.Use the function of inductance to store energy,transfer the unbalanced quantity of battery and eliminate the inconsistency of battery.The circuit structure with left and right similarity is adopted.And SOC is selected as the evaluation standard for battery inconsistency,and multiple equilibrium thresholds are set to make the active equalization system simple in structure,with multiple equalization paths and high equalization accuracy.The Matlab/Simulink simulation model is established,and the simulation results verify the availability of the active equalization system schem e designed in this paper.Finally,the overall hardware structure and experimental scheme of the active equalization system are designed,the software and hardware experimental platform of the system are established,the multi-criteria limited inductive active equalization system is studied,and the equalization experiment of the lithium-ion battery pack is completed and the experimental results are analyzed.The results show that the SOC estimation method combined with the classical complementary filtering method and the extended kalman filtering method proposed in this paper can eliminate the acquisition error of the main control chip STM32F103RCT6,improve the estimation accuracy,and can be used as the basis for the judgment of the active equalization system.The multi-criterion finite inductance active equalization system designed in this paper has the advantages of simple structure,high equalization efficiency and good practicability.