Analysis of the model-based corrector approach for explicit cosimulation

Timo Haid*, Daniel Watzenig, Georg Stettinger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In many industries, the focus of testing is currently shifting away from classical hardware tests to the virtual verification and validation of products. To this end, cosimulation has become a common tool for the simulation and analysis of complex systems that span multiple engineering domains and usually involve multiple, heterogeneous and application-specific simulation environments. In particular, the so-called explicit cosimulation allows a widespread application since it has minimal requirements regarding the capabilities of the tool interfaces. However, explicit cosimulation also poses a numerical challenge, especially when the system includes stiff coupling loops. The model-based corrector approach presented in Haid et al. (The 5th Joint International Conference on Multibody System Dynamics, 2018) provides a method for the efficient cosimulation of such systems. In this article, this model-based corrector approach is extended to additional extrapolation methods. By modeling the cosimulation process through a linear recurrence equation and applying it to the two-mass oscillator test model, the influence of model-based correction on the underlying extrapolation methods in terms of stability, accuracy, and error convergence is analyzed. It is shown that adding model-based correction can significantly improve the overall cosimulation, allowing > 10 times larger macrostep sizes or reducing the cosimulation error by a factor of 10 or more in some cases.

Original languageEnglish
Pages (from-to)137-163
Number of pages27
JournalMultibody System Dynamics
Issue number1-2
Publication statusPublished - Jun 2022


  • Accuracy analysis
  • Error convergence
  • Explicit cosimulation
  • Model-based correction
  • Propagation matrix
  • Stability analysis

ASJC Scopus subject areas

  • Modelling and Simulation
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Control and Optimization


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