OMSimulator - Integrated FMI and TLM-based Co-simulation with Composite Model Editing and SSP

Ochel, Lennart; Braun, Robert; Thiele, Bernhard; Asghar, Adeel; Eek, Magnus; Fritzson, Peter; Fritzson, Dag; Horkeby, Sune; Hällquist, Robert; Kinnander, Åke; Palanisamy, Arunkumar; Pop, Adrian; Sjölund, Martin

doi:10.3384/ecp1915769

Cited by 20 publications

(12 citation statements)

References 15 publications

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“…tain TLM connections which can be interpreted as physically-motivated delayed connections. So introducing a delay between the FMUs, trajectories instead of scalars can be exchanged between the plant FMUs to improve stability and performance (Fritzson, Ståhl, and Nakhimovski 2007;Ochel et al 2019). For more advanced co-simulations algorithms, we refer the reader to Cláudio Gomes et al (2018, Section 4 Finally, the Supervisor FMU may reconfigure the Controller FMU when a certain condition is met.…”

Section: Transmission Line Modelling (Tlm) Systems Con-mentioning

confidence: 99%

The Functional Mock-up Interface 3.0 - New Features Enabling New Applications

Junghanns¹,

Gomes²,

Schulze³

et al. 2021

Linköping Electronic Conference Proceedings

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The Functional Mock-up Interface (FMI) (Modelica Association 2021b) is a tool independent standard for the exchange of dynamic models and for co-simulation. FMI 2.0, released in 2014, is recognized as the de-facto standard in industry for exchanging models and tool coupling, and is currently supported by more than 160 simulation tools. Version 3.0 of the standard brings many new features that allow for advanced co-simulation algorithms and new use cases such as packaging and simulation of highly accurate virtual Electronic Control Units (vECUs). Besides Model-Exchange and Co-Simulation, a third interface type, Scheduled Execution, is defined for purely discrete, RTOS-like, simulation and supports preemption. Clocks allow the synchronization of events between Functional Mock-up Units (FMUs) and the importer. There is better support for data types including binary data and arrays. Advanced co-simulation approaches are enabled by intermediate variable access between communication points and allowing event handling. The composition of systems from FMUs is simplified by terminals that can bundle multiple signals. The concept of layered standards allows the extension of the FMI standard.

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Section: Transmission Line Modelling (Tlm) Systems Con-mentioning

confidence: 99%

The Functional Mock-up Interface 3.0 - New Features Enabling New Applications

Junghanns¹,

Gomes²,

Schulze³

et al. 2021

Linköping Electronic Conference Proceedings

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“…Here, such cases were avoided by compiling strongly physically coupled components, such as the district heating grid, into a single FMU. Otherwise, methods such as transmission line modeling [27] (TLM) might need to be used.…”

Section: Co-simulationmentioning

confidence: 99%

Experiences from City-Scale Simulation of Thermal Grids

et al. 2021

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Dynamic simulation of district heating and cooling networks has an increased importance in the transition towards renewable energy sources and lower temperature district heating grids, as both temporal and spatial behavior need to be considered. Even though much research and development has been performed in the field, there are several pitfalls and challenges towards dynamic district heating and cooling simulation for everyday use. This article presents the experiences from developing and working with a city-scale simulator of a district heating grid located in Luleå, Sweden. The grid model in the case study is a physics based white-box model, while consumer models are either data-driven black-box or gray-box models. The control system and operator models replicate the manual and automatic operation of the combined heat and power plant. Using the functional mock-up interface standard, a co-simulation environment integrates all the models. Further, the validation of the simulator is discussed. Lessons learned from the project are presented along with future research directions, corresponding to identified gaps and challenges.

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“…Recent research projects on simulation and modelling frameworks do focus on the above mentioned topics flexibility, adaptability and model re-usability such as the AGILE [2] or the OM-simulator [3] projects. Also, commercial tool vendors support various inter-disciplinary integration environments (such as modeFRONTIER, LMS Amesim, RCE, TechnoSoft AML, ANSYS) that allow a effort-less tool integration by supporting communication protocols, workflow process control and optimization algorithms.…”

Section: Co-simulation Strategies and The Problem Of Complexitymentioning

confidence: 99%

Towards a Complete Co-Simulation Model Integration Including HMI Aspects

Staack

Schminder

Shahid

et al. 2019

Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden

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Modern aircraft can be seen as heterogeneous systems, containing multiple embedded subsystems which are in today's simulations split into different domain-specific models based on different modelling methods and tools. This paper addresses typical workflow-driven model integration problems with respect to model fidelity, accuracy in combination with the selected abstraction methods and the target system characteristics. A short overview of integration strategies with the help of cosimulation frameworks including an analysis of the inherent problems that emerge because of different domain-specific modelling methods is being given. It is shown that huge benefits can be reached with the help of a smart system break-up. In detail, the discrepancy between the cyber-physical system simulations and human-machine interaction (HMI) models are being analysed. Therefore, a close look on typical shortcomings of behavioural models are being discussed, too. To enable an effortless human-in-the-loop integration into a cyber-physical system simulation, the usage of flight simulation software, offering real-time capability and a graphical user interface is suggested. This approach is applied to overcome today's complexity and shortcomings in human psychological models. An example implementation based on a commercial flight simulator software (X-Plane) together with a high-performance system simulation tool (Hopsan) via UDP communication is presented and analysed.

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OMSimulator - Integrated FMI and TLM-based Co-simulation with Composite Model Editing and SSP

Cited by 20 publications

References 15 publications

The Functional Mock-up Interface 3.0 - New Features Enabling New Applications

The Functional Mock-up Interface 3.0 - New Features Enabling New Applications

Experiences from City-Scale Simulation of Thermal Grids

Towards a Complete Co-Simulation Model Integration Including HMI Aspects

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