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Distributed Co-simulation of Embedded Control Software Using INTO-CPS

  • Nicolai PedersenEmail author
  • Kenneth Lausdahl
  • Enrique Vidal Sanchez
  • Casper Thule
  • Peter Gorm Larsen
  • Jan Madsen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 873)

Abstract

The systematic engineering of Cyber-Physical Systems is a challenging endeavour. In order to manage the complexity of such multi-disciplinary development collaborative modelling and co-simulation has been proposed. In this setting models are made of different constituent models with different mathematical formalisms using different tools. This paper demonstrates how this can be achieved for a commercial system developed by MAN Diesel & Turbo using such a co-simulation approach. The tool chain is centered around a de-facto standard called Functional Mock-up Interface, and it is open for any tools that can support version 2.0 of this standard for co-simulation. The application support emission reduction control systems for large two-stroke engines which is strategically important. It is demonstrated how this approach can reduce the need for expensive tests on the real system in order to reduce the overall costs of validation.

Keywords

INTO-CPS Cyber-Physical Systems Co-simulation Parallel simulation Distributed simulation Functional Mock-up Interface Embedded control system Exhaust Gas Recirculation 

Notes

Acknowledgements

The work presented here is partially supported by the INTO-CPS project funded by the European Commission’s Horizon 2020 programme under grant agreement number 664047.

References

  1. 1.
    Gomes, C., Thule, C., Broman, D., Larsen, P.G., Vangheluwe, H.: State of the art. Technical report, Co-simulation (2017)Google Scholar
  2. 2.
    Gomes, C., Thule, C., Broman, D., Larsen, P.G., Vangheluwe, H.: Co-simulation: a survey. ACM Comput. Surv. 51(3) (2018).  https://doi.org/10.1145/3179993. Article No. 49CrossRefGoogle Scholar
  3. 3.
    MathWorks: Matlab official website, October 2011. http://www.mathworks.com
  4. 4.
    Dassault Systèmes: 3DS official website, March 2017. https://www.3ds.com/products-services/catia/products/dymola
  5. 5.
    Kleijn, C.: Modelling and simulation of fluid power systems with 20-sim. Int. J. Fluid Power 7(3) (2006)Google Scholar
  6. 6.
    Fitzgerald, J., Larsen, P.G., Verhoef, M. (eds.): Collaborative Design for Embedded Systems - Co-modelling and Co-simulation. Springer, Heidelberg (2014).  https://doi.org/10.1007/978-3-642-54118-6CrossRefGoogle Scholar
  7. 7.
    ITEA Office Association: ITEA 3 project 07006 MODELISAR, December 2015. https://itea3.org/project/mode lisar.html. Accessed 12 June 2015
  8. 8.
    MAN Diesel & Turbo: Emission project guide, MAN BW two-stroke marine engines. Technical report, MAN Diesel & Turbo (2016)Google Scholar
  9. 9.
    Pedersen, N., Lausdahl, K., Sanchez, E.V., Larsen, P.G., Madsen, J.: Distributed co-simulation of embedded control software with Exhaust Gas Recirculation water handling system using INTO-CPS. In: Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2017), Madrid, Spain, pp. 73–82, July 2017. ISBN: 978-989-758-265-3Google Scholar
  10. 10.
    International Maritime Organization IMO: MARPOL ANNEX VI and NTC 2008 with guidelines for implementation - supplement. Technical report, September 2015Google Scholar
  11. 11.
    Pedersen, N., Bojsen, T., Madsen, J., Vejlgaard-Laursen, M.: FMI for co-simulation of embedded control software. In: Linköping Electronic Conference Proceedings, no. 124, pp. 70–77 (2016)Google Scholar
  12. 12.
    Fitzgerald, J., Gamble, C., Larsen, P.G., Pierce, K., Woodcock, J.: Cyber-Physical Systems design: formal foundations, methods and integrated tool chains. In: FormaliSE: FME Workshop on Formal Methods in Software Engineering, Florence, Italy, May 2015. ICSE 2015Google Scholar
  13. 13.
    Fitzgerald, J., Gamble, C., Payne, R., Larsen, P.G., Basagiannis, S., Mady, A.E.-D.: Collaborative model-based systems engineering for Cyber-Physical Systems – a case study in building automation. In: INCOSE 2016, Edinburgh, Scotland, July 2016Google Scholar
  14. 14.
    Larsen, P.G. Fitzgerald, J., Woodcock, J., Fritzson, P. Brauer, J., Kleijn, C., Lecomte, T., Pfeil, M., Green, O., Basagiannis, S., Sadovykh, A.: The INTO-CPS project. In: Integrated Tool Chain for Model-Integrated Tool Chain for ModelBased Design of Cyber-Physical Systems, CPS Data Workshop, Vienna, Austria (2016)Google Scholar
  15. 15.
    Bandur, V., Larsen, P.G., Lausdahl, K., Thule, C., Terkelsen, A.F., Gamble, C., Pop, A., Brosse, E., Brauer, J., Lapschies, F., Groothuis, M., Kleijn, C., Couto, L.D.: INTO-CPS tool chain user manual. Technical report, INTO-CPS Deliverable, D4.3a, December 2017Google Scholar
  16. 16.
    Thule, C., Lausdahl, K., Larsen, P.G., Meisl, G.: Maestro: the INTO-CPS co-simulation orchestration engine (2018). To be submitted to Simulation Modelling Practice and TheoryGoogle Scholar
  17. 17.
    Broman, D., Brooks, C., Greenberg, L., Lee, E.A., Masin, M., Tripakis, S., Wetter, M.: Determinate composition of FMUs for co-simulation. In: 2013 Proceedings of the International Conference on Embedded Software (EMSOFT), pp. 1–12 (2013)Google Scholar
  18. 18.
    Thule, C., Larsen, P.G.: Investigating concurrency in the co-simulation orchestration engine for INTO-CPS. In: Petrenko, A.K., Kamkin, A.S., Terekhov, A.N. (eds.) Preliminary Proceedings of the 10th Anniversary Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2016), Krasnovidovo, Russia, 30 May–1 June 2016, pp. 223–228. ISP RAS, May 2016CrossRefGoogle Scholar
  19. 19.
    Bastian, J.. Clauss, C., Wolf, S., Schneider, P.: Master for co-simulation using FMI. In: 8th International Modelica Conference (2011)Google Scholar
  20. 20.
    Pedersen, N., Madsen, J., Vejlgaard-Laursen, M.: Co-simulation of distributed engine control system and network model using FMI and SCNSL. In: 10th IFAC Conference on Manoeuvring and Control of Marine Craft MCMC 2015, vol. 48, no. 16, pp. 261–266 (2015)CrossRefGoogle Scholar
  21. 21.
    Java remotemethodinvocation specification 1.5.0 (2004). http://java.sun.com/j2se/1.5/pdf/rmi-spec-1.5.0.pdf
  22. 22.
    Gamble, C., Payne, R., Fitzgerald, J., Soudjani, S., Foldager, F.F., Larsen, P.G.: Automated exploration of parameter spaces as a method for tuning a predictive digital twin (2018). Submitted for publicationGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nicolai Pedersen
    • 1
    • 4
    Email author
  • Kenneth Lausdahl
    • 2
  • Enrique Vidal Sanchez
    • 1
  • Casper Thule
    • 3
  • Peter Gorm Larsen
    • 3
  • Jan Madsen
    • 4
  1. 1.MAN Diesel & TurboCopenhagen SVDenmark
  2. 2.Mjølner InformaticsAarhus NDenmark
  3. 3.Department of EngineeringAarhus UniversityAarhus NDenmark
  4. 4.Embedded Systems EngineeringTechnical University of DenmarkLyngbyDenmark

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