Identifying the Unknown Parameters of Equivalent Circuit Model for Li-Ion Battery Using Rao-1 Algorithm
Badis Lekouaghet, Walid Merrouche, Elouahab Bouguenna, Yassine Himeur
Abstract
Accurately estimating the parameters for the equivalent circuit model (ECM) of lithium-ion batteries (LiBs), especially those that are not provided in the manufacturer’s datasheets, is crucial to improving their behavior modeling and our understanding. Therefore, this study focuses on investigating a precise method—the Rao-1 algorithm—for extracting the optimal values of the ECM’s parameters. The primary objective is to minimize the difference between the estimated voltage derived from the ECM and the measured voltage of the battery. To evaluate the effectiveness of this approach, a real-world driving data-based test profile is employed. Moreover, a comparative analysis is conducted against recent state-of-the-art optimization algorithms. The simulation results demonstrate that the employed method is proficient in accurately and relatively quickly estimating the parameters of the ECM and that it surpasses other methods in terms of accuracy.