Research on modeling method of life prediction for satellite lithium battery based on SVR

被引：1

作者：

Pang, Bo ^{[1
,2
]}

Feng, Wenquan ^{[1
]}

Zhao, Hongbo ^{[1
]}

Li, Wenjuan ^{[2
]}

Chen, Shijie ^{[2
]}

机构：

[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China

[2] Beijing Inst Spacecraft Syst Engn, Dept Elect & Informat, Beijing 100094, Peoples R China

来源：

2018 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHONGQING 2018) | 2018年

关键词：

life prediction; SVR; lithium battery;

D O I：

10.1109/PHM-Chongqing.2018.00179

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

With the increasing application of high reliability lithium battery in the satellite, the research on its life prediction has been paid more attention. However, because of the small sample amount of the satellite lithium battery products, it is difficult to obtain accurate prediction results only using a small amount of battery capacity data. In this paper, based on the application environment of satellite lithium battery, the on-line residual life prediction method of lithium battery based on data driven is studied. An on-line life prediction method of lithium battery based on Support Vector Regression (SVR) is proposed, and the degradation relation between the health factor of the on-line test and the battery capacity is constructed. The model is used to predict the remaining life. Based on this, an effective technical means to predict the life of the satellite battery on orbit is provided.

引用

页码：1004 / 1009

页数：6

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