A Parameter Identification Method for Lithium-Ion Batteries Using Simplified Impedance Model and Fractional Order Kalman Filter

Reliable battery model and identified model parameter are the preconditions for Power battery state estimation with high precision. Aiming at the disadvantage of existing integer order impedance modeling in characterizing the dynamic characteristics of Lithium-ion ferrous phosphate (LFP) batteries, a simplified fractional order (FO) impedance model including constant phase element and Warburg element is proposed based on the analysis of simplified electrochemical impedance spectroscopy curve. With the Grunwald-Letnikov definition based factional order numerical calculation, the FO Kalman filter (FO-KF) method based on the derived model is designed to identify the FO impedance model parameter and terminal voltage. The proposed FO impedance model can better represent the nonlinear dynamic performances of LFP batteries, and the Grunwald-Letnikov definition based FO-KF algorithm can maintain good accuracy in the numerical calculation of FO parameter identification. The experimental validation results show that the combination of simplified FO impedance model and FO-KF method can improve the modeling precision and parameter identification performance compared with the common integer order impedance model under two different test conditions.

Automated summary

The study introduces a FO-KF method based on a fractional impedance model to improve the accuracy of modeling dynamic characteristics of LFP batteries and the performance of parameter identification.