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结合混沌的长相关锂电池寿命预测方法 被引量:1

Prediction method for lithium-ion battery life using long-range dependence and chaos
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摘要 提出了一种结合混沌理论的分数自回归滑动平均(FARIMA)模型的锂电池剩余寿命预测方法。首先在利用模型预测之前,先通过计算锂电池的Lyapunov指数给出其剩余寿命的最大可预测时间尺度;并介绍FARIMA模型的基本原理并给出判断模型长相关性重要参数-Hurst指数(H)的计算。然后给出RUL预测的定义,具体过程与形式。最后本文选择锂电池电池容量退化数据模型作为预测对象,代入FARIMA模型给出RUL预测结果。 A prediction method for remaining life of lithium battery based on fractional auto-regressive moving average(FARIMA)model combined with chaos theory is proposed.Firstly,before using model to predict,the maximum predictable time scale of the remaining life of lithium battery is given by calculating the Lyapunov exponent.Secondly,basic principle of FARIMA model is introduced and calculate the Hurst exponent H,the parameter for judging long-range dependence(LRD)of FARIMA.Then the definition,process and form of RUL prediction are given.Finally,model for capacity degradation data of lithium battery is selected as the prediction target,and the RUL prediction results are given by the FARIMA model.
作者 王海洋 宋万清 WANG Haiyang;SONG Wanqing(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201600,China)
出处 《传感器与微系统》 CSCD 北大核心 2021年第7期32-34,共3页 Transducer and Microsystem Technologies
关键词 LYAPUNOV指数 剩余寿命预测 分数自回归滑动平均 HURST指数 Lyapunov exponent remaining useful life prediction fractional auto-regressive moving average(FARIMA) Hurst exponent
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