Identification of physically realistic state-space models for accurate component synthesis
Journal article, 2020

For components that are difficult to model with conventional analytical or numerical tools, experimentally derived state-space models can instead be used in system synthesis. For successful state-space synthesis, a physically realistic model must be identified. For this purpose, a hybrid first- and second-order system description is used here as the basis for identification. In the identification procedure, a physically motivated rigid body rank constraint is imposed together with a reciprocity constraint. The two constraints are enforced during a re-estimation phase of the state-space matrices following after a traditional state-space subspace identification phase. In this paper, two complex and modally dense industrial components are combined into a dynamical system. An experimental model of a car body-in-white structure is identified. The identified subsystem model is coupled with a finite element model of a rear subframe in a system synthesis. The two subsystems are attached through four rubber bushings modelled by finite element procedures. It is shown that the experimental-analytical assembly successfully predicts the reference measured system, with higher accuracy than what could be achieved with a model based solely on finite elements. It is also shown that synthesis with individually calibrated rear subframe models can capture the variability in the coupled system.

System identification

Reciprocity constraint

Physical constraints

State-space synthesis

Variability

Author

Mladen Gibanica

Chalmers, Mechanics and Maritime Sciences, Dynamics

Volvo Cars

Thomas Abrahamsson

Chalmers, Mechanics and Maritime Sciences, Dynamics

Mechanical Systems and Signal Processing

0888-3270 (ISSN) 1096-1216 (eISSN)

Vol. 145 106906

Subject Categories

Applied Mechanics

Computational Mathematics

Control Engineering

Signal Processing

DOI

10.1016/j.ymssp.2020.106906

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Latest update

1/8/2021 2