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A MATLAB Simulink Based Co-Simulation Approach for a Vehicle Systems Model Integration Architecture
- Brian C. Raczkowski - PC Krause & Associates ,
- Nicholas Jones - PC Krause & Associates ,
- Tim Deppen - PC Krause & Associates ,
- Charles Lucas - PC Krause & Associates ,
- Rodney Yeu - PC Krause & Associates ,
- Eric Walters - PC Krause & Associates ,
- Adam Donovan - US Air Force Research Laboratory ,
- Soumya Patnaik - US Air Force Research Laboratory ,
- Mark Bodie - Army Corps Of Engineers
ISSN: 2641-9637, e-ISSN: 2641-9645
Published March 10, 2020 by SAE International in United States
Citation: Raczkowski, B., Jones, N., Deppen, T., Lucas, C. et al., "A MATLAB Simulink Based Co-Simulation Approach for a Vehicle Systems Model Integration Architecture," SAE Int. J. Adv. & Curr. Prac. in Mobility 2(3):1150-1159, 2020, https://doi.org/10.4271/2020-01-0005.
In this paper, a MATLAB-Simulink based general co-simulation approach is presented which supports multi-resolution simulation of distributed models in an integrated architecture. This approach was applied to simulating aircraft thermal performance in our Vehicle Systems Model Integration (VSMI) framework. A representative advanced aircraft thermal management system consisting of an engine, engine fuel thermal management system, aircraft fuel thermal management system and a power and thermal management system was used to evaluate the advantages and tradeoffs in using a co-simulation approach to system integration modeling. For a system constituting of multiple interacting sub-systems, an integrated model architecture can rapidly, and cost effectively address technology insertions and system evaluations. Utilizing standalone sub-system models with table-based boundary conditions often fails to effectively capture dynamic subsystem interactions that occurs in an integrated system. Additionally, any control adjustments, model changes or technology insertions that are applied to any one of the connecting subsystems requires iterative updates to the boundary conditions. When evaluating a large set of trade studies, the number of boundary condition models and time to generate these models becomes intractable and affects capturing the results accurately. A single interconnected model of all the subsystems may be impractical and using additional external packages may be prohibitive in terms of cost or compatibility. This general approach requires no additional MATLAB toolboxes. Two different data interchange mechanisms are presented. A dynamic vehicle system integrated model was developed to enable customizability and flexibility. The developed co-simulation approach was combined with this flexible architecture to enable system evaluation. Example applications using the vehicle system model integrated architecture with the co-simulation approach are discussed.