Research On The Parameters Of LiFePO₄ Power Battery Second-order RC Model

With the intensification of environmental pollution and energy shortage, as the most ideal new energy lithium ion battery energy storage is more and more aroused people’s concern.Especially the LiFePO4 battery with its superior performance is considered the most potential power battery. In the applications of LiFePO4 battery, the state of charged (SOC) of battery system is directly related to correctly battery system’s performance, life and safety.This article in view of the current LiFePO4 battery not system aspects of second-order RC model and algorithm to consider the state of the environment temperature, working condition and their own defects, and on the analysis of the basis of LiFePO4 battery electrode composition, structure, and the electrochemical process, through the method of pulse experiment to research the variation regularity of open circuit voltage, ohmic internal resistance, polarization resistance and polarization loop time constant of RC model parameters with the environment temperature, charge and discharge current and LiFePO4 battery charged state itself, establish a complete function of model parameters with the environment temperature, charge and discharge current, and LiFePO4 battery charged state itself.In addition, this paper also studied the coefficient of LiFePO4 battery coulomb’s law along with the change of environmental temperature and charging and discharging rate, coefficient of LiFePO4 battery coulomb and environment temperature and the function relationship between the charge and discharge rate.And the charging and discharging rate section, by the method of least squares matrix, kalman filtering the noise coefficient of correction of the algorithm.Finally, through the programming will be a revised model parameter function relation into extended kalman filtering algorithm, in the MATLAB environment of current, temperature and noise coefficient of three series of SOC simulation calculation.It is concluded that the simulation results compared with the commercial battery test system its maximum error is less than 2%, than without the extended kalman filtering algorithm of parameter correction calculation results have improved significantly.To verify the feasibility of this article research results in practice, can adapt to various working condition, environment temperature and LiFeP04 battery status of SOC estimation precision, and can further improve the filtering effect of extended kalman filtering algorithm.