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

页数：7

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