HintCO – Hint-based Configuration of Co-simulations

Abstract

Simulation-based analyses of Cyber-Physical Systems are fundamental in industrial design and testing approaches. The utility of analyses relies on the correct configuration of the simulation tools, which can be highly complicated. System engineers can normally judge the results, and either evaluate multiple simulation algorithms, or change the models. However, this is not possible in a co-simulation approach. Co-simulation is a technique to perform full-system simulation, by combining multiple black-box simulators, each responsible for a part of the system. In this paper, we demonstrate the difficulty of correctly configuring a co-simulation scenario using an industrial case study. We propose an approach to tackle this challenge by allowing multiple engineers, specialized in different domains, to encode some of their experience in the form of hints. These hints, together with state-of-the-art best practices, are then used to semi-automatically guide the configuration process of the co-simulation. We report the application of this approach to a use case proposed by our industrial partners, and discuss some of the lessons learned.

Seismic Hybrid Testing using FMI-based Co-Simulation

“…Coupling -Denotes the strategy that the orchestrator uses, in order to ensure that physical laws are respected. While it is common to mix the Orchestrator and Coupling together as one concept, as we will show later, the distinction is useful because the Orchestrator is generic and can be applied to many different simulation scenarios (e.g., consider the Jacobi and Gauss-Seidel schemes (Kübler and Schiehlen 2000; Bastian et al 2011)), but the Coupling is often specifically designed for a particular simulation scenario (e.g., the coupling can be implemented as a semantic adaptation (Gomes, Meyers et al 2018), or automatically generated from hints (Gomes, Oakes et al 2019;Oakes et al 2021)).…”

“…The consequence is that the cosimulation framework must accept some kind of description of the ordering in which the FMUs shall be stepped. The FMI standard 2.1 offers no mechanism to provide this information, even though it plays an important role in reducing co-simulation errors (Gomes, Thule, Lúcio et al 2020;Oakes et al 2021;Gomes, Oakes et al 2019;Gomes, Lucio and Vangheluwe 2019).…”

The Effect and Selection of Solution Sequence in Co-Simulation

“…In the category of non-adaptive master algorithms, notable works are presented in (Benedikt and Holzinger 2016, Holzinger and Benedikt 2019b, Holzinger and Benedikt 2019a, Oakes et al 2021, Gomes et al 2019, Hansen et al 2021). Here, the main theme is to formulate a constrained optimization problem of which the cost function is an approximation of the error made by a specific choice of co-simulation algorithm.…”