Research on Electrochemical Characteristics and Parameter Identification of Lithium-ion Batteries at Different Temperatures

With the widespread application of electric vehicles, lithium-ion batteries (LIBs) are widely used, but how to ensure the stability and reliability of LIBs during the operation is still concern toady. The study systematically investigates the complex relationship between temperature variation and the electrochemical characteristics of the LIBs, and reveals the nonlinear parameter evolution mechanism in different temperature ranges by quantitatively analyzing the effect of temperature on the electrochemical impedance spectra (EIS) and open-circuit voltage (OCV) characteristics. Then, based on investigate results, a hybrid particle swarm optimization-Kalman filter (PSO-KF) optimization method is proposed, which can adapt to the robust battery parameter identification in complex environments, and by designing an objective function, the influence of noise interference on the filtering accuracy is effectively reduced. Finally, the results demonstrate that the EIS and OCV curves of the battery will undergo substantial alterations under varying operating conditions, and the proposed method can significantly improve the accuracy of parameter identification, achieving voltage identification errors of less than 20 mV across three temperature scenarios.