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Research of System Identification for Ni/MH Battery State of Charge Based on a Short Sequence and Multi-sample Process

机译:基于短序列和多样品过程的NI / MH电池电量的系统识别研究

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In the battery state of charge of a systematic analysis, the observed data has a property that is the direction of time t (referred to as vertical) for a limited length, and number of samples obtained by N (called horizontal) for the infinite data set{y_1~T}_N~∞, it is called as a short sequence and multi-sample time series. By studying the characteristic of this time series, a new system identification method has been proposed, and the system identifiability for this process has been demonstrated. Through practice simulations, a satisfactory application results have been obtained. This feature of the time series identification problem is the same in other areas have a certain reference value.
机译:在系统分析的电池充电状态下,观察到的数据具有用于有限长度的时间T(称为垂直)的性质,并且由N(称为水平)为无限数据获得的样本数设置{y_1〜t} _n〜∞,称为短序列和多采样时间序列。通过研究该时间序列的特征,已经提出了一种新的系统识别方法,并证明了该过程的系统可识别性。通过实践模拟,已经获得了令人满意的应用结果。该特征的时间序列识别问题在其他区域中是相同的,具有一定的参考值。

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