Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

Abstract

The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. This paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to perturbations. A case of a 2nd-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. Simulation and experiment results validate the analysis and demonstrate the superiority of the continuous-time system identification methods in battery applications.