A Neural Network Based Method for Instantaneous Power Estimation in Electric Vehicles' Li-ion Batteries

被引：0
|
作者：
Hussein, Ala A. [1 ]
机构：
[1] Yarmouk Univ, Dept Elect Power Engn, POB 566, Irbid, Jordan
来源：
2017 THIRTY SECOND ANNUAL IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION (APEC) | 2017年
关键词：
SYSTEMS; MODEL; PACK;
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：
In electric vehicles (EVs), a battery is used as a main or auxiliary bidirectional power source. In order to optimize the battery operation, the power sourced or sinked by the battery must be estimated in real time under any condition. The battery's power is a function of terminal current, state-of-charge (SOC), ambient temperature and state-of-health (SOH). This paper proposes a method for estimating the battery power using artificial neural networks (ANNs). Experimental data obtained by performing a standardized EVs test on a 12V/150Ah commercial lithium-ion (Li-ion) battery are presented and used for model evaluation.
引用
收藏
页码：3122 / 3126
页数：5
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