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Modeling of Back-Propagation Neural Network Based State-of-Charge Estimation for Lithium-Ion Batteries with Consideration of Capacity AttenuationZHANG, S.   , GUO, X. , ZHANG, X. |
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Author keywords
attenuation measurement, backpropagation, battery management systems, lithium batteries, neural networks
References keywords
state(38), charge(30), estimation(28), power(24), lithium(24), battery(24), energy(23), batteries(22), sources(18), jjpowsour(16)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03001
Web of Science Accession Number: 000486574100001
SCOPUS ID: 85072196257
Abstract
The state of charge of lithium-ion batteries reflects the power available in the battery. Precise SOC estimation is a challenging task for battery management system. In this paper, a novel hybrid method by fusion of back-propagation (BP) neural network and improved ampere-hour counting method is proposed for SOC estimation of lithium-ion battery, which considers the impact of battery capacity attenuation on SOC estimation during the process of charging and discharging. The predictive accuracy and effectiveness of model are validated by NASA lithium-ion battery dataset. Moreover, the adaptability and feasibility of this method are further demonstrated using dataset of accelerated life experiment. The validation results indicate that the proposed method can provide accurate SOC estimation in different capacity attenuation stage. |
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Digital Object Identifier: 10.1007/s11581-024-05749-1 [CrossRef]
[2] A novel one-way transmitted co-estimation framework for capacity and state-of-charge of lithium-ion battery based on double adaptive extended Kalman filters, Shuzhi, Zhang, Xu, Guo, Xiongwen, Zhang, Journal of Energy Storage, ISSN 2352-152X, Issue , 2021.
Digital Object Identifier: 10.1016/j.est.2020.102093 [CrossRef]
[3] An improved grey wolf optimization–double adaptive extended Kalman filtering algorithm for co-estimation of state of charge and state of health for lithium-ion batteries based on temperature-dependent second-order RC model, Chen, Lu, Wang, Shunli, Chen, Lei, Gao, Haiying, Fernandez, Carlos, Ionics, ISSN 0947-7047, Issue 8, Volume 30, 2024.
Digital Object Identifier: 10.1007/s11581-024-05610-5 [CrossRef]
[4] Electric Vehicle NiMH Battery State of Charge Estimation Using Artificial Neural Networks of Backpropagation and Radial Basis, Hernández, Jordy Alexander, Fernández, Efrén, Torres, Hugo, World Electric Vehicle Journal, ISSN 2032-6653, Issue 11, Volume 14, 2023.
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[5] A novel fuzzy‐extended Kalman filter‐ampere‐hour (F‐EKF‐Ah) algorithm based on improved second‐order PNGV model to estimate state of charge of lithium‐ion batteries, Liu, Donglei, Wang, Shunli, Fan, Yongcun, Xia, Lili, Qiu, Jingsong, International Journal of Circuit Theory and Applications, ISSN 0098-9886, Issue 11, Volume 50, 2022.
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[7] An adaptive fractional-order extended Kalman filtering approach for estimating state of charge of lithium-ion batteries, Song, Dandan, Gao, Zhe, Chai, Haoyu, Jiao, Zhiyuan, Journal of Energy Storage, ISSN 2352-152X, Issue , 2024.
Digital Object Identifier: 10.1016/j.est.2024.111089 [CrossRef]
[8] A purpose-oriented shuffled complex evolution optimization algorithm for energy management of multi-microgrid systems considering outage duration uncertainty, Bayat, Peyman, Afrakhte, Hossein, Journal of Intelligent & Fuzzy Systems, ISSN 1064-1246, Issue 2, Volume 38, 2020.
Digital Object Identifier: 10.3233/JIFS-190666 [CrossRef]
[9] Online parameters identification and state of charge estimation for lithium‐ion batteries using improved adaptive dual unscented Kalman filter, Peng, Nian, Zhang, Shuzhi, Guo, Xu, Zhang, Xiongwen, International Journal of Energy Research, ISSN 0363-907X, Issue 1, Volume 45, 2021.
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[10] A data-driven coulomb counting method for state of charge calibration and estimation of lithium-ion battery, Zhang, Shuzhi, Guo, Xu, Dou, Xiaoxin, Zhang, Xiongwen, Sustainable Energy Technologies and Assessments, ISSN 2213-1388, Issue , 2020.
Digital Object Identifier: 10.1016/j.seta.2020.100752 [CrossRef]
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Digital Object Identifier: 10.1177/0020294020923057 [CrossRef]
[13] An improved adaptive unscented kalman filtering for state of charge online estimation of lithium-ion battery, Zhang, Shuzhi, Guo, Xu, Zhang, Xiongwen, Journal of Energy Storage, ISSN 2352-152X, Issue , 2020.
Digital Object Identifier: 10.1016/j.est.2020.101980 [CrossRef]
[14] Co-estimation for capacity and state of charge for lithium-ion batteries using improved adaptive extended Kalman filter, Nian, Peng, Shuzhi, Zhang, Xiongwen, Zhang, Journal of Energy Storage, ISSN 2352-152X, Issue , 2021.
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Digital Object Identifier: 10.4028/p-iiDzS6 [CrossRef]
[16] Nonlinear Modeling of Lithium-Ion Battery Cells for Electric Vehicles using a Hammerstein–Wiener Model, Khalfi, Jaouad, Boumaaz, Najib, Soulmani, Abdallah, Laadissi, El Mehdi, Journal of Electrical Engineering & Technology, ISSN 1975-0102, Issue 2, Volume 16, 2021.
Digital Object Identifier: 10.1007/s42835-020-00607-2 [CrossRef]
[17] Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery, Qi, Nan, Yan, Kang, Yu, Yajuan, Li, Rui, Huang, Rong, Chen, Lai, Su, Yuefeng, Frontiers in Energy, ISSN 2095-1701, Issue 2, Volume 18, 2024.
Digital Object Identifier: 10.1007/s11708-023-0891-7 [CrossRef]
[18] Improved Long Short-Term Memory: Statistical Regression Model for High Precision SOC Estimation of Lithium-Ion Batteries Adaptive to Complex Current Variation Conditions, Wang, Zhi, Wang, Shunli, Yu, Chunmei, Qiao, Jialu, Journal of The Electrochemical Society, ISSN 0013-4651, Issue 5, Volume 170, 2023.
Digital Object Identifier: 10.1149/1945-7111/acce71 [CrossRef]
[19] A rapid online calculation method for state of health of lithium-ion battery based on coulomb counting method and differential voltage analysis, Zhang, Shuzhi, Guo, Xu, Dou, Xiaoxin, Zhang, Xiongwen, Journal of Power Sources, ISSN 0378-7753, Issue , 2020.
Digital Object Identifier: 10.1016/j.jpowsour.2020.228740 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
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