Study On Parameter Estimation Of Power Lithium Battery For Electric Vehicle

With the increasing use of energy,and the depletion of oil resources can be expected.New energy vehicle,and the development of electric vehicles has attracted more and more attention.The use of new energy vehicles can not only relieve the energy crisis,but also can protect our living environment because of its almost zero pollution characteristics.As the heart of electric vehicles,power battery pack and its battery management system(BMS)has become research hotspots in recent years.Especially the SOC and SOH estimation of battery pack is the key point of the research.In this dissertation,firstly,we introduce the basic situation of new energy vehicles,analyze the function of BMS in electric vehicles,the development of BMS at home and abroad and the development trend in the future.The key role of BMS in electric vehicle has been illustrated.Then we focus on the SOC estimation of battery management system.In this dissertation,the advantages and disadvantages of several SOC estimation methods of power battery have been analyzed.What's more,the dissertation analyze the application of Kalman filtering algorithm in SOC,which makes the research achieved leapfrog development.It makes the estimate of electric vehicles dynamic parameters in the course of driving become possible.But with the in-depth research,some shortcomings of the Kalman filter algorithm have be exposed.So the improvement of Calman filtering algorithm and the application of double extended filter(dual EKF)are introduced,which solved that Calman filtering algorithm can`t predict the state of the system and its internal parameters at the same time,and improved the accuracy and flexibility of SOC estimationThen the influence of various factors on the performance of the battery pack have been analyzed.For example,the dynamic change of the battery internal resistance,the differences of each cell in the battery pack,the ambient temperature of battery pack,the aging of battery pack and other factors will affect the performance parameters of the battery pack,which will affect the accuracy of the battery management system for the battery SOCLastly,on the basis of algorithm analysis and influence factor analysis,this dissertation propose a new SOC estimation method which based on dual Kalman filtering algorithm and considered temperature factor.The simulation results show that the proposed method is better than the traditional method.