首页> 外国专利> WAVELET NOISE REDUCTION AND RELEVANCE VECTOR MACHINE-BASED METHOD FOR PREDICTING REMAINING LIFE OF LITHIUM BATTERY

WAVELET NOISE REDUCTION AND RELEVANCE VECTOR MACHINE-BASED METHOD FOR PREDICTING REMAINING LIFE OF LITHIUM BATTERY

机译:基于小波降噪和相关矢量机的锂电池剩余寿命预测方法

摘要

A wavelet noise reduction and relevance vector machine-based method for predicting the remaining life of a lithium battery. The present invention relates to a method for estimating the health of a lithium battery and predicting the remaining life thereof, and comprises the following steps: measuring health data of a lithium battery with charge and discharge cycles (1); performing wavelet secondary noise reduction on measured lithium battery capacity data (2); calculating a capacity threshold for lithium battery failure (3); on the basis of a lithium battery capacity data sequence and a charge and discharge cycle data sequence, applying a differential evolution algorithm to a width factor of a relevance vector machine algorithm to perform optimisation selection (4); applying the relevance vector machine algorithm optimised by the differential evolution algorithm to predict the remaining life of the lithium battery (5). The method is simple and effective, and accurately predicts the remaining life of a lithium battery.
机译:基于小波降噪和相关矢量机的锂电池剩余寿命预测方法。本发明涉及一种估计锂电池的健康并预测其剩余寿命的方法,其包括以下步骤:以充放电循环(1)测量锂电池的健康数据;对测得的锂电池容量数据进行小波二次降噪(2);计算锂电池故障的容量阈值(3);根据锂电池容量数据序列和充放电循环数据序列,对相关向量机算法的宽度因子应用差分演化算法进行优化选择(4);应用由差分进化算法优化的关联向量机算法预测锂电池的剩余寿命(5)。该方法简单有效,可以准确预测锂电池的剩余寿命。

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