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Using a Multiobjective Approach to Compare Multiple Design Alternatives—An Application to Battery Dynamic Model Tuning

机译:使用多目标方法比较多个设计方案—在电池动态模型调整中的应用

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A design problem is usually solvable in different ways or by design alternatives. In this work, the term “concept” is used to refer to the design alternatives. Additionally, it is quite common that a design problem has to satisfy conflicting objectives. In these cases, the design problem can be formulated as a multiobjective optimization problem (MOP). One of the aims of this work was to show how to combine multiobjective requirements with concepts’ comparisons, in order to attain a satisfactory design. The second aim of this work was to take advantage of this methodology to obtain a battery model that described the dynamic behavior of the main electrical variables. Two objectives related to the model accuracy during the charge and discharge processes were used. In the final model selection, three different concepts were compared. These concepts differed in the complexity of their model structure. More complex models usually provide a good approximation of the process when identification data are used, but the approximation could be worse when validation data are applied. In this article, it is shown that a model with an intermediate complexity supplies a good approximation for both identification and validation data sets.
机译:设计问题通常可以通过不同的方式或通过设计替代方案来解决。在本文中,术语“概念”用于指代设计方案。另外,设计问题必须满足相互矛盾的目标是很常见的。在这些情况下,设计问题可以表述为多目标优化问题(MOP)。这项工作的目的之一是展示如何将多目标需求与概念的比较结合起来,以获得令人满意的设计。这项工作的第二个目的是利用这种方法获得描述主要电气变量动态行为的电池模型。在充电和放电过程中使用了两个与模型精度有关的目标。在最终的模型选择中,比较了三个不同的概念。这些概念在其模型结构的复杂性方面有所不同。使用识别数据时,更复杂的模型通常可以很好地近似过程,但是当应用验证数据时,近似情况可能更糟。在本文中,表明具有中等复杂度的模型为识别和验证数据集提供了良好的近似值。

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