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Local Model Network based Dynamic Battery Cell Model Identification

机译:基于局部模型网络的动态电池模型识别

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In this paper the local model network (LMN) based dynamic battery cell model identification is presented. Such a model describes the nonlinear dynamic behaviour of the cell terminal voltage in dependance of the charge/discharge current and can be used for the state of charge (SoC) estimation in hybrid electrical vehicles. For that purpose, the model must be accurate at high C-rates in combination with a highly dynamic excitation. The LMN construction, related SoC observer structures and the appropriate experiment design are discussed in the present paper. The proposed concepts and the performance of the LMN is validated by means of real measurement data from a Lithium Ion power cell.
机译:本文提出了一种基于局部模型网络(LMN)的动态电池模型识别方法。这样的模型描述了依赖于充电/放电电流的电池单元端电压的非线性动态行为,并且可以用于混合电动车辆中的充电状态(SoC)估计。为此,结合高动态激励,模型必须在高C速率下准确。本文讨论了LMN的构造,相关的SoC观察器结构和适当的实验设计。所提出的概念和LMN的性能通过来自锂离子电池的实际测量数据进行验证。

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