Research On Battery Management Data Analysis System Of Pure Electric Vehicle

Lithium ion battery has advantages of high voltage, long cycle life, wide workingtemperature range, etc. It has broad market prospects among the batteries of electricvehicle.There are a lot of equivalent model applied in the batteries of EV. On the basisof summarizing the common battery model, this paper chooses the thevenin equivalentcircuit model which is simple and effective. A linear regression method in Excel is usedto identify open circuit voltage, ohmic resistance, polarization resistance and timeconstant offline. Using extended kalman filtering method to identify the modelparameter online on the MATLAB platform. And the offline and online parameteridentification results under different working conditions are compared. Theeffectiveness of online parameter identification method is verified.Then on the basis of comprehensive analysis of the current SOC estimation methodof battery. SOC estimation method based on battery model parameter identificationonline is presented. And determine to use OCV curve relationship with SOC identifiedonline under DST condition to estimate the SOC of the battery under FUDS conditionsthrough comparison and analysis.In order to analyze the changing characteristics of the battery under actual workenvironment of EV and according to the functional requirements of the data analysis,characteristics data analysis system for EV power battery is developed. And the SOCestimation method put forward in this paper is integrated into the system. The reading,analysis, fault diagnosis and display of different EVs data are realized intelligently.Finally, the model parameters of battery pack in bench test and electric vehicle areidentified. Which is to verify per se inconsistencies and inconsistencies due to differentSOC of the batteries under simulation and actual working conditions. In the dataanalysis system, comparing and analyzing SOC curves of the electric vehicle batteryusing three algorithms including ampere-hour integration, AH-OCV method and themethod based on battery model parameter identification. Which verifies theeffectiveness of the SOC estimation algorithm in this paper.