Research On Modeling And SOC Estimation Of Lithium Battery For Electric Vehicle

Compared with traditional cars,new energy electric vehicles have significant advantages that can alleviate the shortage of fossil energy,avoid environmental and noise pollution,etc.,and have been vigorously promoted by countries around the world.In China,the development and promotion of electric vehicles have been written into the country for five years.Plan and formulate a number of special plans to promote the layout of the electric vehicle industry.As the research and development of electric vehicle-related technologies continues to progress,it is necessary to solve problems related to vehicle range,use safety and stability,and so on.Research on power source lithium batteries has received increasing attention.Among them,the battery management system(BMS,Battery Management System)is used as The core and center of the system can ensure the safety and stability of the system's work,reduce capacity loss and battery performance degradation,and improve the overall efficiency of the power system,which is the top priority of research.The key core of BMS technology is the estimation of SOC(State of Charge)of lithium battery.This article takes the lithium battery of electric vehicles as the research object,analyzes its basic characteristics,establishes an online second-order MC equivalent circuit model,studies the model's basic parameter identification algorithm and fitting method,and applies three algorithms: UKF(Unscented Kalman Filter),Sage-Husa filtering,and SR(Square Root)square root filtering.The combined ASRUKF(Adaptive Square-root Unscented Kalman Filter)algorithm estimates the SOC and conducts a lot of experimental analysis and simulation verification.First of all,based on the current development of the automobile industry,the necessity of energy transformation is analyzed,and the many advantages and development status of electric vehicle technology are explained,according to the performance requirements of automotive power batteries,the characteristics of various types of power batteries are compared to explain the reasons for selectinglithium batteries for research.Through the introduction of the battery management system,this article analyzes the significance of building an accurate and stable battery model,improving the accuracy of model parameter identification,and researching SOC estimation methods,and introduces the research status of related technologies.Secondly,the working mechanism and main technical parameters of the lithium battery are introduced,and the principle that the internal and external factors such as voltage,current,and temperature affect the performance of the lithium battery is specifically explained,and the battery model in the simulation tool is analyzed.A large number of relationship characteristics experiments were performed,and the basic characteristics of the parameters such as the capacity,dynamic impedance,and SOC of the lithium battery were analyzed in detail according to the experimental results,providing theoretical and data support for subsequent modeling and SOC estimation.Thirdly,the equivalent circuit model commonly used in lithium batteries is analyzed,and the second-order MC model is selected for comparison and modeling.The model exponential fitting offline identification algorithm and LS online identification algorithm are introduced in detail,and the upgraded recursive RLS algorithm is used for parameter identification.Next,explore the effects of ambient temperature and state of charge on the dynamic impedance of lithium batteries,and obtain a mathematical expression of each dynamic impedance by building a piecewise three-dimensional fitting model.The offline and online second-order MC equivalent circuit models are established,and the results of statistical parameter identification are used to obtain the simulation error of the equivalent circuit model.The accuracy of the model established in this paper is verified through error comparison.Finally,explain the relationship and definition of remaining power and SOC,briefly analyze seven commonly used SOC estimation methods and propose the use of ASRUKF algorithm to estimate the SOC of lithium batteries,introduce the principle of the algorithm in detail,and insert the System function into the simulation model to achieve SOC Estimate.According to the estimation results,the analysis results of the three algorithms EKF,UKF and ASRUKF are compared and analyzed.It is confirmedthat the ASRUKF algorithm has higher estimation accuracy and better performance under various operating conditions such as charging,discharging,extreme initial error,and urban road driving.