Study On Soh Estimation Method Of Lithium-ion Battery Pack For Electric Vehicle

As the ideal power source of the new generation electric vehicles,the state of health about lithium-ion battery pack plays a vital role in the actual operation of electric vehicles.In order to ensure the safety and stability of the electric vehicle during operation,it is necessary to carry on the research and management to its vehicle power battery.In this paper,SOH estimation method of lithium ion battery pack for electric vehicle is studied by using lithium ion battery pack as the research object.The following contents are studied by a large number of experiments and simulations:(1)Firstly,the characteristics of lithium ion batteries are analyzed,including the characteristics,structure and working principle of lithium ion batteries,and the evaluation indexes of lithium ion battery SOH are given.Then,the paper introduces the factors that affect the SOH of the lithium-ion battery pack.Based on the angle of inconsistency and the connection mode of the single cell,this paper analyses the influence of them on the SOH of the battery pack,and emphatically analyses the influence of the different connection modes of the single cell on the SOH performance of the battery.Because of the internal resistance of the battery can not only connect with the battery voltage,current and other relevant parameters,but also can reflect the change of battery’s characteristics very well,so this paper chooses the change of resistance as the characterization parameter for the SOH of the battery.(2)After analyzing several kinds of single cell model,it is found that the battery equivalent physical model can not only reflect the physical characteristics of the battery,but also establish a certain relationship with its chemical properties.Therefore,on the basis of this model,two lithium-ion batteries in parallel are considered as a simplified sub-system.And such N sub-systems in series can be used to form the equivalent model of the power battery,then we can carry on the mathematical modeling and experimental analysis of the lithium-ion battery pack.The next step is to select the type of 50AH/3.6V lithium ion battery to measure the performanceparameters of the battery,and based on the experimental data,the least square parameter identification method is used to identify the model parameters.Finally,the feasibility of the model parameter identification is verified by the least squares fitting tool in Matlab.(3)Based on the theory of particle filter algorithm and the established battery pack model,the internal resistance of the battery is tracked and predicted,but the algorithm has serious particle degradation.In order to overcome this phenomenon,this paper attempts to introduce SVM into the particle filter algorithm to increase the particle diversity to improve the prediction accuracy of the SOH of the battery.Finally,the experimental results of the two algorithms are compared and analyzed,and they show that the tracking curve under SVM-PF algorithm has a smaller overall fluctuation range,and its smoothness and prediction accuracy are better than particle filter algorithm.It is explained that the SVM-PF algorithm is effective and superior to the tracking prediction of the internal resistance of the battery to a certain extent.