A novel intelligent SOC prediction method of lithium-ion battery packs based on the improved unscented transformation

被引：2
作者：
Xie, Fei [1 ]
Wang, Shunli [1 ]
James, Coffie-ken [1 ]
Xie, Yanxin [1 ]
Liang, Xueqing [1 ]
机构：
[1] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang, Sichuan, Peoples R China
来源：
THIRD INTERNATIONAL CONFERENCE ON ENERGY ENGINEERING AND ENVIRONMENTAL PROTECTION | 2019年 / 227卷
关键词：
CHARGE ESTIMATION; STATE;
D O I：
10.1088/1755-1315/227/3/032034
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
The development of power lithium-ion battery packs is limited by the research and development level of Battery Management System (BMS). In this paper, an improved unscented transformation method is proposed, which is based on the six-section aero-lithium battery pack as the object of detection. The effective iterative calculation of State of Charge (SOC) value is realized by simplifying the process of three-particle and double Sigma processing. The accuracy of the method is verified by comparing the simulation results with the actual measurement results. Experimental results show that the error of this method is less than 3.00%, which effectively improves the SOC estimation accuracy and is of great significance to energy management and safety assurance of power lithium-ion battery packs.
引用
收藏
页数：7
相关论文
共 50 条
[41]   Dual Estimation of Lithium-ion Battery Internal Resistance and SOC Based on the UKF [J].
Liu, Yuanyuan ;
He, Zhiwei ;
Gao, Mingyu ;
Li, Yun ;
Liu, Guohua .
2012 5TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2012, :1639-1643
[42]   An improved coulomb counting method based on non-destructive charge and discharge differentiation for the SOC estimation of NCM lithium-ion battery [J].
Zhu, Yucheng ;
Xiong, Yonglian ;
Xiao, Jie ;
Yi, Ting ;
Li, Chunsheng ;
Sun, Yan .
JOURNAL OF ENERGY STORAGE, 2023, 73
[43]   Remaining capacity prediction of lithium-ion battery based on the feature transformation process neural network [J].
Cui, Zhiquan ;
Gao, Xuhong ;
Mao, Jiawei ;
Wang, Chunhui .
EXPERT SYSTEMS WITH APPLICATIONS, 2022, 190
[44]   Multi-Fault Diagnosis for Series-Connected Lithium-Ion Battery Packs Based on Improved Sensor Topology and Correlation Coefficient Method [J].
Cao, Yue ;
Tian, Engang ;
Chen, Hui ;
Chen, Huwei .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 :7833-7844
[45]   Optimization of the Heat Dissipation Structure for Lithium-Ion Battery Packs Based on Thermodynamic Analyses [J].
Li, Yan ;
Liu, Honghai ;
Ye, Min .
IEEE ACCESS, 2022, 10 :47250-47265
[46]   An improved Transformer incorporating fuzzy information entropy and average input strategy for SOC estimation of lithium-ion battery [J].
Fan, Xichen ;
Li, Bangxing ;
Xie, Zhenjun ;
Hao, Yuxin ;
Tang, Qian ;
Hu, Xiaolin .
ENERGY, 2025, 330
[47]   An online dual filters RUL prediction method of lithium-ion battery based on unscented particle filter and least squares support vector machine [J].
Li, Xin ;
Ma, Yan ;
Zhu, Jiajun .
MEASUREMENT, 2021, 184
[48]   Lithium-Ion Battery Capacity Estimation: A Method Based on Visual Cognition [J].
Cheng, Yujie ;
Tao, Laifa ;
Yang, Chao .
COMPLEXITY, 2017,
[49]   Life prediction of lithium-ion battery based on a hybrid model [J].
Chen, Xu-Dong ;
Yang, Hai-Yue ;
Wun, Jhang-Shang ;
Wang, Ching-Hsin ;
Li, Ling-Ling .
ENERGY EXPLORATION & EXPLOITATION, 2020, 38 (05) :1854-1878
[50]   Lithium-Ion Battery Remaining Useful Life Prediction Based on Hybrid Model [J].
Tang, Xuliang ;
Wan, Heng ;
Wang, Weiwen ;
Gu, Mengxu ;
Wang, Linfeng ;
Gan, Linfeng .
SUSTAINABILITY, 2023, 15 (07)
12345