Open Cyber-Physical System Model-Driven Certified Development (OPENCPS)
| Reference number | |
| Coordinator | RISE Research Institutes of Sweden AB - RISE SICS East |
| Funding from Vinnova | SEK 3 402 000 |
| Project duration | December 2015 - April 2019 |
| Status | Completed |
| Venture | Eureka cluster co-funding |
| Call | EUREKA medfinansiering kluster 2014-2015 |
Important results from the project
Cyber-Physical Systems (CPS) put increasing demands on reliability, usability and flexibility; at the same time, lead time and cost efficiency are essential for industry competitiveness. With tool interoperability, vendor lock-ins and tool life-cycle support as major challenges, this research project has focused on interoperability between the Modelica/Unified Modeling Language (UML)/Functional Mock-up Interface (FMI) standards, on improved support for state-machine modeling and debugging and on efficient simulation of large scale systems.
Expected long term effects
This project has resulted in improved support for synchronous language constructs and efficient parallel simulation in OpenModelica. State-machine modelling was developed in Papyrus and OpenModelica, providing industrial partners with tool support for modelling and debugging systems using state-machines. Another result from this work is the integration of the FMI and TLM standards, previously not available in any tools and now supported in OMSimulator. An extension to the FMI standard has been proposed as a result of this project.
Approach and implementation
OMSimulator, the main tool developed in this project is available as an open source stand alone tool as well as part of the OpenModelica tools. It will continue to be developed and used after the end of the project by RISE and the members of the Open Source Modelica Consortium. The data reconciliation method implemented in OpenModelica will allow users (mainly EDF) to optimize nuclear power plants by reducing the uncertainty of certain variables measured on the plant. OpenModelica currently has over 6k single downloads/month.