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计算机系统应用英文版:2017,26(2):235-239
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工业锂电池退化过程研究与剩余使用寿命预测
(1.中国科学院大学, 北京 100049;2.中国科学院沈阳计算技术研究所, 沈阳 110168)
Degradation Process Research and Remaining Useful Life Prediction for Industrial Lithium-ion Battery
(1.University of Chinese Academy of Sciences, Beijing 100049, China;2.Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China)
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Received:May 13, 2016    Revised:June 16, 2016
中文摘要: 随着锂离子电池在航空航天、军工建设、工业制造、电动汽车以及储能设备等领域的广泛研究与应用,其剩余使用寿命预测具有重要意义.本文通过对锂离子电池退化原理与退化过程数据分析,剔除锂离子电池松弛效应,建立含随机效应的Wiener退化过程模型.在获知其退化阈值的情况下,推导出锂离子电池的寿命分布,并在此基础上,对单个锂离子电池剩余使用寿命进行预测.最后在NASA的PCoE数据库提供的电池数据集进行实例验证,结果表明相对于参考文献所述传统的设备贮存-工作联合退化模型,Wiener过程退化模型具有更高的预测精度.
Abstract:With the lithium-ion batteries widely research and application in the aerospace, military construction, industrial manufacturing, electric vehicles and energy storage equipment areas, its remaining useful life prediction is of great significant. Through analyzing the principle of the lithium ion degradation process data and eliminating lithium-ion battery relaxation effect, this paper establishes Wiener process degradation model with random effects. Knowing its degradation threshold, lithium ion battery life distribution is deduced, and on this basis, we can predict a single lithium-ion battery remaining useful life. Finally using the battery data of NASA PCoE database to verify, the results show that compared with the traditional equipment storage-work joint degradation model, which is mentioned in the references, Wiener process degradation model has higher precision of prediction.
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基金项目:沈阳市2014年科技计划项目(F14-056-7-00);“高档数控机床与基础制造装备”科技重大专项(2013ZX04007031)
引用文本:
陶耀东,李宁.工业锂电池退化过程研究与剩余使用寿命预测.计算机系统应用,2017,26(2):235-239
TAO Yao-Dong,LI Ning.Degradation Process Research and Remaining Useful Life Prediction for Industrial Lithium-ion Battery.COMPUTER SYSTEMS APPLICATIONS,2017,26(2):235-239