Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm

Aiming at the state estimation error caused by inaccurate battery model parameter estimation, a model-based state of charge (SOC) estimation method of lithium-ion battery is proposed. This method is derived from parameter identification using an adaptive genetic algorithm (AGA) and state estimation...

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Autores principales:	Chao Fang, Zhiyang Jin, Jingjin Wu, Chenguang Liu
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	lithium-ion battery fractional-order model fractional order unscented kalman filter state of charge adaptive genetic algorithm General Works A
Acceso en línea:	https://doaj.org/article/3ef3f5ae04124b3a9f55ad61abbb0bb2
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id	oai:doaj.org-article:3ef3f5ae04124b3a9f55ad61abbb0bb2
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spelling	oai:doaj.org-article:3ef3f5ae04124b3a9f55ad61abbb0bb22021-11-05T13:06:35ZEstimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm2296-598X10.3389/fenrg.2021.769818https://doaj.org/article/3ef3f5ae04124b3a9f55ad61abbb0bb22021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fenrg.2021.769818/fullhttps://doaj.org/toc/2296-598XAiming at the state estimation error caused by inaccurate battery model parameter estimation, a model-based state of charge (SOC) estimation method of lithium-ion battery is proposed. This method is derived from parameter identification using an adaptive genetic algorithm (AGA) and state estimation using fractional-order unscented Kalman filter (FOUKF). First, the fractional-order model is proposed to simulate the characteristics of lithium-ion batteries. Second, to tackle the problem of fixed values of probabilities of crossover and mutation in the genetic algorithm (GA) in model parameter identification, an AGA has been proposed. Then, the FOUKF method is used to assess battery SOC. For the data redundancy problem caused by the fractional-order algorithm, a time window is set to enhance the computational efficiency of the fractional-order operator. Finally, the experimental results show that the developed AGA-FOUKF algorithm can increase the correctness of SOC estimation.Chao FangZhiyang JinJingjin WuChenguang LiuFrontiers Media S.A.articlelithium-ion batteryfractional-order modelfractional order unscented kalman filterstate of chargeadaptive genetic algorithmGeneral WorksAENFrontiers in Energy Research, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lithium-ion battery fractional-order model fractional order unscented kalman filter state of charge adaptive genetic algorithm General Works A
spellingShingle	lithium-ion battery fractional-order model fractional order unscented kalman filter state of charge adaptive genetic algorithm General Works A Chao Fang Zhiyang Jin Jingjin Wu Chenguang Liu Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
description	Aiming at the state estimation error caused by inaccurate battery model parameter estimation, a model-based state of charge (SOC) estimation method of lithium-ion battery is proposed. This method is derived from parameter identification using an adaptive genetic algorithm (AGA) and state estimation using fractional-order unscented Kalman filter (FOUKF). First, the fractional-order model is proposed to simulate the characteristics of lithium-ion batteries. Second, to tackle the problem of fixed values of probabilities of crossover and mutation in the genetic algorithm (GA) in model parameter identification, an AGA has been proposed. Then, the FOUKF method is used to assess battery SOC. For the data redundancy problem caused by the fractional-order algorithm, a time window is set to enhance the computational efficiency of the fractional-order operator. Finally, the experimental results show that the developed AGA-FOUKF algorithm can increase the correctness of SOC estimation.
format	article
author	Chao Fang Zhiyang Jin Jingjin Wu Chenguang Liu
author_facet	Chao Fang Zhiyang Jin Jingjin Wu Chenguang Liu
author_sort	Chao Fang
title	Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
title_short	Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
title_full	Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
title_fullStr	Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
title_full_unstemmed	Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm
title_sort	estimation of lithium-ion battery soc model based on aga-foukf algorithm
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/3ef3f5ae04124b3a9f55ad61abbb0bb2
work_keys_str_mv	AT chaofang estimationoflithiumionbatterysocmodelbasedonagafoukfalgorithm AT zhiyangjin estimationoflithiumionbatterysocmodelbasedonagafoukfalgorithm AT jingjinwu estimationoflithiumionbatterysocmodelbasedonagafoukfalgorithm AT chenguangliu estimationoflithiumionbatterysocmodelbasedonagafoukfalgorithm
_version_	1718444220876849152

Estimation of Lithium-Ion Battery SOC Model Based on AGA-FOUKF Algorithm

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