Aging Performances and Cycle-life Predictions of Li-ion Battery

被引：0

作者：

Huang Hai ^{[1
]}

Cui Naxin ^{[1
]}

Shang Yunlong ^{[1
]}

Zhang Chenghui ^{[1
]}

机构：

[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China

来源：

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年

关键词：

Li-ion battery; Cycle-life prediction; Artificial Neural Network; Support Vector Machine; ELECTRIC VEHICLES; PROGNOSTICS; CELLS; MODEL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The state of health and cycle life predictions of power battery are the key points to battery monitoring and maintenance. For the purpose of solving this problem, firstly this paper set up battery experimental platform and collects battery change/discharge data. Then aging performances are analyzed according to the data and battery remaining useful life is predicted using data-driven methods. Finally, the results of BP algorithm and SVM algorithm beingused in the predictions are evaluated. The results indicate that the SVM algorithm is more efficient in the cycle life predictions of Li-ion cells.

引用

页码：8710 / 8715

页数：6

共 17 条

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