Hybrid co-simulation: it’s about time

Abstract

Model-based design methodologies are commonly used in industry for the development of complex cyber-physical systems (CPSs). There are many different languages, tools, and formalisms for model-based design, each with its strengths and weaknesses. Instead of accepting some weaknesses of a particular tool, an alternative Communicated by Prof. J. Sztipanovits, M. Broy, and H. Daembkes. This work is partially based on previous work published by the authors [7,8,15] is to embrace heterogeneity, and to develop tool integration platforms and protocols to leverage the strengths from different environments. A fairly recent attempt in this direction is the functional mock-up interface (FMI) standard that includes support for co-simulation. Although this standard has reached acceptance in industry, it provides only limited support for simulating systems that mix continuous and discrete behavior, which are typical of CPS. This paper identifies the representation of time as a key problem, because the FMI representation does not support well the discrete events that typically occur at the cyber-physical boundary. We analyze alternatives for representing time in hybrid co-simulation and conclude that a superdense model of time using integers only solves many of these problems. We show how an execution engine can pick an adequate time resolution, and how disparities between time representations internal to co-simulated components and the resulting effects of time quantization can be managed. We propose a concrete extension to the FMI standard for supporting hybrid co-simulation that includes integer time, automatic choice of time resolution, and the use of absent signals. We explain how these extensions can be implemented modularly within the frameworks of existing simulation environments.

Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers

“…• Sound representation of different semantics (as done in (Ptolemaeus, 2014;Cremona et al, 2016) and semantic adaptations ; • Accurate event location (e.g., as done in (Zhang et al, 2008;Broman et al, 2013)); • Discontinuity identification and signal distinction (e.g., using the super-dense integer time formalization (Broman et al, 2015;Cremona et al, 2017a), or explicitly representing internal clocks (Franke et al, 2017); and • Adequate discontinuity handling (e.g., set the internal continuous numerical solvers' state (Andersson et al, 2016)). It is also important to mention that some tutorials have been published on individual standards or in the context of co-simulation projects.…”

Generating FMUs for the Feature-Based Language Bloqqi

“…The problems, as discussed in 5.3, with representing discrete time systems, or any system including events, using the Co-Simulation FMI technology with regards to matching the master algorithm's sampling with the internal events of the FMUs is discussed in Cremona et al (2017). In Cremona et al (2017), a suggestion to add new step function called "doStepHybrid" which allows for an early return of the step function. This in combination with a possibility for the master to interrogate the system using functions like getMaxStepSizeHybrid would allow for the Bloqqi FMU to assure that each sample and execution event is properly matched.…”

“…Additionally the concept of clocks and hybrid Co-Simulation is included in the alpha feature list of FMI 2.1 that was announced 2017-12-18 (fmi standard, 2017), this to support synchronization of variable changes across FMUs, and allow for co-simulation with events. Cremona et al (2017) also proposes an integer representation of time in order to increase the accuracy of the time representation in simulation of FMUs.…”

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

“…Additional difficulties arise if discrete-time models (e.g., control software) are included within a co-simulation setup (hybrid co-simulation). With regards to hybrid cosimulation, the latest FMI 2.0 standard was shown to have deficiencies and different proposals to amend these deficiencies were discussed, e.g., (Broman et al, 2013;Cremona et al, 2016;Tavella et al, 2016;Cremona et al, 2017).…”