Lithium-ion battery has been paid more attention because of its cycle life.In order to predict the remaining cycle useful life of lithium-ion battery,a particle filter algorithm is adopted.Firstly,the particle filter algorithm is briefly analyzed.Then the algorithm is used to predict the remaining cycle life of the battery.The experimental results of three groups of battery data are briefly described and compared with extended kalman filter.The experimental results show that the absolute error of the particle filter algorithm in three groups data of the average value is approximate 4％ and the root mean square error of average value is approximate 5％.But the absolute error of the extended kalmanfilter algorithm in three groups data of the average value is approximate 6％ and the root mean square error of average value is approximate 7％,respectively.The experimental results show the higher precision of particle filter in the life prediction of lithium-ion batteries than extended kalman filtering.%锂离子电池因其循环寿命产生的问题更加被重视.为了对锂离子电池的剩余循环使用寿命进行预测研究,采用了粒子滤波算法.首先对粒子滤波算法进行了概述.然后用它对电池的剩余使用寿命预测.简要描述了3组电池数据下的实验;并与扩展卡尔曼滤波进行了对比实验分析.实验结果表明了粒子滤波算法在3组数据下的绝对误差平均值近似4％,均方根误差平均值近似5％,扩展卡尔曼滤波的绝对误差平均值和均方根误差平均值分别近似6％和7％.说明了粒子滤波在锂离子电池剩余使用寿命预测中比扩展卡尔曼滤波精度更高.
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