Abstract
System modeling and simulation technique is aimed at the support of model-based product development. Although the technique supports analysis of systems with numerical simulation, it does not support design processes at the early stage of product development. In order to utilize the functions of system modeling and simulation techniques at the early stage of model-based product development, the paper proposes methods to analyze and visualize the parameter network of a product model, which is derived from physical phenomena that jointly construct an equation system for numerical simulation representing the model behavior. The paper also presents a method to classify simulation variables in the parameter network based on its network structure and the results of numerical simulation processed with a machine learning technique. The presented methods are demonstrated using a simple electric vehicle model described with the Modelica language.
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