Identification of NOE models for a continuously variable semi-active damper

This paper discusses the identification of nonlinear black-box simulation models for a continuously variable, semi-active damper for a passenger car. Two model classes are considered and compared. While both classes have an output error model structure, the first class applies a polynomial approximation function and the second uses a neural network. The identification procedure automatically selects the regression variables by means of a state of the art model structure selection technique. Experimental validation of the proposed method shows that the obtained models are able to accurately simulate the dynamic damper behaviour.