Modeling a lithium-ion power battery based on a Hammerstein-ARMAX model

Zhi Zhang; Shuhua Bai; Baiqing He; Lei Wu; Jinliang Huang; Wenzhan Zhang

doi:10.1117/12.3024636

13 May 2024 Modeling a lithium-ion power battery based on a Hammerstein-ARMAX model

Zhi Zhang, Shuhua Bai, Baiqing He, Lei Wu, Jinliang Huang, Wenzhan Zhang

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 131594H (2024) https://doi.org/10.1117/12.3024636
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

Accompanied by the soaring development of the new energy industry, Lithium-ion power battery, as an efficient energy storage method, has become an essential part of electric vehicles. An advanced battery management system is an imperative means to ensure the efficient and safe operation of Lithium-ion power batteries. Amid the functions of a battery management system, the high precision modeling of a battery holds paramount concern. In practical applications, the battery is not a linear system, wherein the input and output demonstrate nonlinear characteristics due to external disturbances and so on. The battery model exhibits nonlinear characteristics since its output is subject to the interference of manifold external factors, thus directly affecting the parameter identification effect and then the model precision. Thus, nonlinear modeling for Lithium-ion power batteries has progressively turned into the focus of research. In light of this, this paper embarks on a study on the Hammerstein-ARMAX (Autoregressive Moving Average with Extra Input) model construction and parameters estimation method of Lithium-ion power battery, aiming at improving the accuracy of the model. The experimental results show the effectiveness of the proposed method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhi Zhang, Shuhua Bai, Baiqing He, Lei Wu, Jinliang Huang, and Wenzhan Zhang "Modeling a lithium-ion power battery based on a Hammerstein-ARMAX model", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 131594H (13 May 2024); https://doi.org/10.1117/12.3024636

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KEYWORDS

Batteries

Modeling

Data modeling

Systems modeling

Complex systems

Autoregressive models

Error analysis

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