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An automated framework for generating variable-accuracy battery models from datasheet information

机译:从数据表信息生成可变精度电池模型的自动化框架

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Models based on an electrical circuit equivalent have become the most popular choice for modeling the behavior of batteries, thanks to their ease of co-simulation with other parts of a digital system. Such circuit models are actually model templates: the specific values of their electrical elements must be derived by the analysis of the specific battery devices to be modeled. This process requires either to measure the battery characteristics or to derive them from the datasheet. In the latter case, however, very often not all information are available and the model fitting becomes then unfeasible. In this paper we present a methodology for deriving, in a semi-automatic way, circuit equivalent battery models solely from data available in a battery datasheet. In order to account for the different amount of information available, we introduce the concept of “level” of a model, so that models with different accuracy can be derived depending on the available data. The methodology requires only minimal intervention by the designer and it automatically generates MATLAB models once the required data for the corresponding model level are transcribed from the datasheet. Simulation results show that our methodology allows to accurately reconstruct the information reported in the datasheet as well as to derive missing ones.
机译:由于它们易于与数字系统的其他部分进行协同仿真,因此基于等效电路的模型已成为建模电池行为的最受欢迎的选择。这样的电路模型实际上是模型模板:其电气元件的特定值必须通过对要建模的特定电池设备的分析得出。此过程需要测量电池特性或从数据表中得出。但是,在后一种情况下,通常并非所有信息都可用,因此模型拟合变得不可行。在本文中,我们提出了一种仅通过电池数据表中可用数据以半自动方式得出等效电路电池模型的方法。为了解决可用信息量的差异,我们引入了模型的“级别”概念,以便可以根据可用数据得出具有不同精度的模型。该方法仅需设计人员最少的干预,并且一旦从数据表中抄录了相应模型级别所需的数据,它就会自动生成MATLAB模型。仿真结果表明,我们的方法可以准确地重建数据表中报告的信息,并得出缺失的信息。

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