Frequency Domain Identification and Identifiability Analysis of a Nonlinear Vehicle Drivetrain Model

Abstract

Physical parameters of a vehicle drivetrain are required in many applications. In the context of fault diagnosis, for example, knowledge about the installed components or parts can provide insights in order to verify if they behave in accordance with standards or deviate from them in a way that adversely affects the operating performance. For this purpose a frequency domain identification approach is presented, which is based only on standard mounted sensors. In the presented method in particular nonlinear effects are taken into account resulting from backlash. In order to guarantee a unique parameter set a local identifiability analysis is performed. The main idea of the method is to exploit the dependency between the frequency response of the nonlinear system and the magnitude of the test-signal to improve optimization of the physical parameters. Finally, identification results using real measurement data are presented.