Precise modeling of lithium-ion battery in industrial applications using Walrus optimization algorithm

Abstract

This research article demonstrates how to get a precise lithium-ion battery (LIB) model using one of the artificial intelligence algorithms called the Walrus optimization algorithm (WaOA). The model's accuracy affects several transient and dynamic analysis simulations, which are carried out for power systems, electric vehicles, and many transportation applications. The LIB model may have one, two, or three resistance-capacitance (RC) models, signifying the complexity of the optimization challenge. Therefore, the WaOA is used to minimize the cost function that relies on an integral square error criterion. This criterion calculates the error between the estimated and experimental voltages. The proposed method is validated under several conditions, taking into account load variation, battery degradation, temperature fluctuation, and different RC models. The numerical results of the WaOA method are compared with their experimental results for a 2.6 Ah LIB. In addition, the proposed WaOA model has undergone validation alongside numerous optimization algorithms-based models. It is worth noting that utilization WaOA with battery modeling stands as a reliable tool for attaining precise model.