Indítómotorok modellezésére alkalmas módszerek összehasonlító elemzése

Abstract

This paper introduces different methods used to modeling a starter motor. There are several methods known to model an actuator. One method is to apply differential equations to describe the behaviour of the motor and afterwards validate the model based on real system. Another solution is to use black box principle. The behaviour of the motor can be described with the relations among the measured quantities. 3-layered neural networks were applied for nonlinear modeling. The training and validating dataset of the network were collected from real system measurements. The third method investigated was a grid-based lookup table method, which is widely popular in industry. Databases were built up to simulate the actuator. Using the reference points of the database, the points in the simulation can be extrapolated with a simple formula. The different methods were briefly evaluated in this paper.