Parameters identification of electric vehicle lithium battery model
ZHANG Qun, YAN Shirong
（College of Mechanical Engineering, Fuzhou university, Fuzhou 350108, China）
 

Abstract: Aiming at the parameters identification of the equivalent model of the power Liion battery in the pure electric vehicle, a threeelement lithium battery group used for driving electric vehicles which was composed of 87 single 84 Ah nickel cobalt manganese lithiumion cells in series, was studied.A second order RC equivalent model was selected, based on the urban driving data, and the parameters of the equivalent model were identified. Based on the overall battery data, 8 segments of battery data was selected, for each segment that in the 12(and above 12) sampling periods the absolute value of the current change of the two abject sampling points was more than 0.2 C. And parameter identification of the single cell with the maximum and minimum open circuit voltage was carried out respectively. Using the least square method to identify the parameters of a battery data segment with the longest continuous change as the result of the parameter identification.And the parameters of the identified results were verified by the overall battery data.The results indicate that the mean of the absolute error of the cell with maximum initial open circuit voltage is 3.62%, and the mean of the absolute error of the cell with minimum initial open circuit voltage is 3.24%, which can meet the requirements of the engineering, can be used in engineering practice.
Key words: second order RC equivalent model; electric vehicle; three element lithium battery; driving data; least square method; parameter identification