Honey Badger Algorithm for Estimating the Parameters of Li-ion Battery 3rd Order ECM

Konferenz: NEIS 2023 - Conference on Sustainable Energy Supply and Energy Storage Systems
04.09.2023–05.09.2023 in Hamburg, Germany

Tagungsband: NEIS 2023

Seiten: 7Sprache: EnglischTyp: PDF

Autoren:
Merrouche, Walid; Bouguenna, Elouahab (Center for Renewable Energies Development, CDER, Bouzareah, Algiers, Algeria)
Lekouaghet, Badis (Research Center in Industrial Technologies, CRTI, Cheraga, Algiers, Algeria)

Inhalt:
The accurate estimation of parameters in Lithium-ion battery models is crucial for the development of efficient battery management systems. This article proposes a novel optimization algorithm called the Honey Badger Algorithm (HBA) for estimating the parameters of a Third order Equivalent Circuit Model (ECM) used to describe the behavior of Lithium-ion batteries. The HBA is inspired by the unique foraging behavior of honey badgers, which are known for their tenacity and adaptability in finding resources. The proposed HBA algorithm mimics the foraging behavior of honey badgers to search for the optimal parameter values. To evaluate the performance of the algorithm, experimental data from Lithium-ion battery is utilized. The results demonstrate that the HBA offers a promising approach for parameter estimation of Lithium-ion battery model in terms of accuracy and convergence speed. By effectively capturing the complex dynamics of Lithium-ion batteries, it enables accurate prediction of battery performance and enhances the design and optimization of battery management systems.