Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm

With the aim of increasing the model accuracy of lithium-ion batteries (LIBs), this paper presents a complex-order beetle swarm optimization (CBSO) method, which employs complex-order (CO) operator concepts and mutation into the traditional beetle swarm optimization (BSO). Firstly, a fractional-orde...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Xiaohua, Li, Haolin, Zhang, Wenfeng, Lopes, António M., Wu, Xiaobo, Chen, Liping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960356/
https://www.ncbi.nlm.nih.gov/pubmed/36838113
http://dx.doi.org/10.3390/mi14020413
_version_ 1784895494400507904
author Zhang, Xiaohua
Li, Haolin
Zhang, Wenfeng
Lopes, António M.
Wu, Xiaobo
Chen, Liping
author_facet Zhang, Xiaohua
Li, Haolin
Zhang, Wenfeng
Lopes, António M.
Wu, Xiaobo
Chen, Liping
author_sort Zhang, Xiaohua
collection PubMed
description With the aim of increasing the model accuracy of lithium-ion batteries (LIBs), this paper presents a complex-order beetle swarm optimization (CBSO) method, which employs complex-order (CO) operator concepts and mutation into the traditional beetle swarm optimization (BSO). Firstly, a fractional-order equivalent circuit model of LIBs is established based on electrochemical impedance spectroscopy (EIS). Secondly, the CBSO is used for model parameters’ identification, and the model accuracy is verified by simulation experiments. The root-mean-square error (RMSE) and maximum absolute error (MAE) optimization metrics show that the model accuracy with CBSO is superior when compared with the fractional-order BSO.
format Online
Article
Text
id pubmed-9960356
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-99603562023-02-26 Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm Zhang, Xiaohua Li, Haolin Zhang, Wenfeng Lopes, António M. Wu, Xiaobo Chen, Liping Micromachines (Basel) Article With the aim of increasing the model accuracy of lithium-ion batteries (LIBs), this paper presents a complex-order beetle swarm optimization (CBSO) method, which employs complex-order (CO) operator concepts and mutation into the traditional beetle swarm optimization (BSO). Firstly, a fractional-order equivalent circuit model of LIBs is established based on electrochemical impedance spectroscopy (EIS). Secondly, the CBSO is used for model parameters’ identification, and the model accuracy is verified by simulation experiments. The root-mean-square error (RMSE) and maximum absolute error (MAE) optimization metrics show that the model accuracy with CBSO is superior when compared with the fractional-order BSO. MDPI 2023-02-09 /pmc/articles/PMC9960356/ /pubmed/36838113 http://dx.doi.org/10.3390/mi14020413 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Xiaohua
Li, Haolin
Zhang, Wenfeng
Lopes, António M.
Wu, Xiaobo
Chen, Liping
Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title_full Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title_fullStr Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title_full_unstemmed Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title_short Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm
title_sort improved parameter identification for lithium-ion batteries based on complex-order beetle swarm optimization algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960356/
https://www.ncbi.nlm.nih.gov/pubmed/36838113
http://dx.doi.org/10.3390/mi14020413
work_keys_str_mv AT zhangxiaohua improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm
AT lihaolin improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm
AT zhangwenfeng improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm
AT lopesantoniom improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm
AT wuxiaobo improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm
AT chenliping improvedparameteridentificationforlithiumionbatteriesbasedoncomplexorderbeetleswarmoptimizationalgorithm

Ejemplares similares