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郑智勇参加ICPE 2019-ECCE Asia会议汇报

发布时间:2019年06月05日 作者: 浏览次数:

会议名称:ICPE 2019-ECCE Asia

全称:第 10 届国际电力电子大会 - ECCE亚洲(10th International Conference on Power Electronics - Asia)

报告时间:2019年6月11日(星期二)下午 14:00

报告地点:铁道校区第二综合实验楼513

报告人:郑智勇

报告题目:Online learning ANN model for SoC estimationof the Lithium-Ion battery in case of smallamount of data for practical applications

报告摘要:A battery's state of charge (SoC) estimation with accuracy is presented in this paper. Its calculation time is accelerated using online model approach (during operation) with optimal generalization. This novel idea minimizes the initial error of the SoC with the help of artificial neural network (ANN). It is realized by an online learning with offline update parameter estimating model for a battery equivalent circuit. Although degradation of Lithium-Ion battery cell is inevitable, accurate estimation of the actual state is needed to extend its life of usage. It is, however,difficult to calculate the parameters by conventional methods, because the parameters are non-linearly involved in the mathematical notation of the battery impedance and all other variables related with SoC estimation.

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