Parameters Identification For Lithium-ion Battery Model And Simulation Analysis For SOC

Nowadays, low-carbon life, energy-conservation and environment protection are been advocated, under the background, electric vehicle which possess advantages of low emission and low noise has been rapid development. Consequently, as a key component of electric vehicle, power battery also become a research focus. For the research field of power battery, focal point and difficulty lies in the selection of equivalent model and accuracy of SOC(state of charge) estimation. In this thesis, lithium-ion battery is taken as a research object, we get the parameter identification of battery equivalent circuit model, and research the algorithm of battery SOC numerical estimation.For the equivalent model of lithium-ion battery and estimation of SOC, this thesis made the following aspects of workFirst of all, the research background is introduced, then, make a comparison of several common power batteries, and summarize their advantages and disadvantages in performance. the results point out that lithium-ion battery as a power battery has superiority in performance, thereby, lithium-ion battery is taken as the research object. The thesis analyzes the existing battery equivalent model, sums up the research status of SOC estimation algorithm, notes the problems exists at the present stage.Second, the development history, composition and reaction principle of lithium-ion battery is introduced. Analyze the law of lithium-ion battery when it’s been charged and discharged, the composition of battery’s internal resistance, the trends of internal resistance in working condition and the factor of battery capacity reducing. Finally, several common used SOC estimation methods are illustrated.Building a lithium-ion battery equivalent model accurately is crucial for battery SOC estimation, because of that, several types of lithium-ion battery equivalent models have been expounded as typical examples, through above summary, select second-order RC circuit as a lithium-ion battery equivalent model, and deduce mathematical modal base on it. Get the lithium-ion battery OCV-SOC curve through measuring, and calculate the parameters of second-order equivalent circuit model by using curve fitting method and analyze the results. Compare the simulation model and the actual data to prove the accuracy of the second order RC equivalent circuit model. In order to meet the requirements of the application, under custom condition, use forgetting factor recursive least squares method to identify the parameters of model, with referring the recognition results of battery characteristics,Correctness and rationality of the recognition method are proved.At last, based on the online identification results, estimate SOC value of battery by Extended Kalman filter algorithm. Put SOC of battery into state-space equation, estimate SOC value of battery by joint algorithm, which is using FFRLS to identify and correct the model parameters, then estimate SOC value of battery by Extended Kalman filter algorithm, compare the results with actual battery SOC value, finally, the accuracy of joint algorithm which is used to estimate battery SOC under custom condition.