Study on the Estimate of the State of Charge for Battery Applied on Electric Vehicle

被引:0
|
作者
Zeng, Qi [1 ]
机构
[1] Luzhou Vocat & Tech Coll, Luzhou, Sichuan, Peoples R China
关键词
D O I
暂无
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
Estimating the state of charge (SoC) of power battery is of great importance and playing important role in the battery management system technology. Meanwhile, it is also the accordance of the battery balanced management. This paper introduces the definition of battery state of charge, analyzing SoC estimation significance, and then the common estimation methods of the state of charge are summarized. On the basis of pointing out the principles and advantages and disadvantages of the common estimation methodologies of SoC, the extended Kalman filter algorithm for battery state of charge estimation was brought forward. The results indicate that the extended Kalman filter algorithm for battery state of charge estimating can meet the requirements of working conditions of electric vehicles, having a good feasibility and superiority, and higher estimation accuracy can be achieved.
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页码:42 / 46
页数:5
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