Conference article

Integration of complex Modelica-based physics models and discrete-time control systems: Approaches and observations of numerical performance

Kai Wang
Ford Motor Company, USA

Christopher Greiner
Ford Motor Company, USA

John Batteh
Modelon, Inc., USA

Lixiang Li
Modelon, Inc., USA

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Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:59, p. 527-532

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Published: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (print), 1650-3740 (online)


As CAE simulations become more complex, the need for computational efficiency increases in order to provide timely solutions and analyses. One facet of this complexity is the integration of multiple software modeling tools and environments in order to utilize the most capable computational technologies for the different features of these complex system models. Physical plant models may be developed in Modelica and require variable step solvers to capture both fast and slow continuum dynamics while discrete time-based control systems may be developed in C-code or Simulink and require fixed time step solvers. Integrating these plant and control models into a single environment can result in computational inefficiencies due to conflicting solver time step requirements. This paper will discuss the integrated modeling of an automotive vapor compression air conditioning system and associated control systems over a dynamic drive cycle, and the associated numerical performance issues discovered, as well as some approaches taken to increase said performance.


Modelica, discrete, variable, integration


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