Coupling Model Exchange FMUs for Aggregated Simulation by Open Source Tools

Reconciling interoperability with efficient Verification and Validation within open source simulation environments

Co-simulation is a means to combine and leverage the strengths of different modeling tools, environments and formalisms and has been applied successfully in various domains. The Functional Mock-Up Interface (FMI) is the most commonly used standard for co-simulation. In this paper we extend UniFMU, a tool that allows users to build Functional Mock-Up Units (FMUs) in virtually any programming language, to support execution within Docker. As a result the generated FMUs can be distributed in an environment containing all runtime dependencies. To describe the process of creating dockerized FMUs using UniFMU, we show how to model and co-simulate a robotic arm and a controller using two Python-based FMUs.

This paper describes the results of an evaluation of vehicle power network modeling using Functional Mock-up Interface (FMI). FMI, developed by the Modelica Association, is a tool-independent standard for a model interface. This study compared simulation results between the vehicle power network model with Functional Mock-up Units (FMUs) connected and the model without FMUs. Conversion adaptors were inserted to generate and connect each FMU because it was necessary to convert physical connections from acausal connections to causal inputs and outputs. Using FMI for Model Exchange, it was confirmed that the results for both simulations showed good matches, without any time delays although algebraic loops which would often occur in electrical circuit modeling were included. This method possesses significant potential to reduce the validation effort using models created by other departments or suppliers.

Different causes have contributed to the shift of paradigm in the automation field from centralized to modular and distributable. Software and hardware of Programmable Logic Controllers (PLCs) have evolved to be synchronized with the demands nowadays and new standards are trying to follow this trend. One of them is the IEC 61499 standard, which is intended for modelling distributed industrial solutions with a vendor-independent format. This shifting is also bringing new challenges and this paper focuses on the virtual commissioning of plants, which can become a harder task when the system is distributed and involves different interconnected modules. A major problem when doing a virtual commissioning is the coupling between the different physical systems and controlling tools since many vendors still offer closed integrated solutions. Functional Mockup Interface (FMI) is a standard for a cosimulation interface which intends to fill the gaps between different modelling tools, by packaging the models into Functional Mockup Unit (FMU) and allowing a co-simulation master algorithm to have access to the inside model through the proposed interface. This paper presents a mapping between IEC 61499 models and the FMI standard and an implementation of a tool that can export IEC 61499 models into FMUs, which would allow the co-simulation of physical plants and the PLCs software that controls it. An experiment is shown where a simple Proportional-Integral-Derivative (PID) controller of a tank system is exported as an FMU and co-simulated together with a tank system modelled using OpenModelica.

Multi-tool modeling and co-simulation of complex systems is a difficult problem. The missile power distribution system is a typical multidisciplinary combination of electrical, mechanical, dynamic, magnetic and cybernetics. Traditional professional software can only simulate a specific domain model. In order to study the coupling characteristics of the missile system and verify the rationality of the system model design, a multi-domain model simulation tool is needed. This paper proposes a multi-domain simulation method based on FMI (Functional Mock-up Interface) to simulate complex systems. It can use the advantages of different software and its professional model library, and overcome the difficulty of multi-source model co-simulation in the process of complex system development. This paper makes study in two aspects. On the one hand, the missile electrical characteristics are taken as the research object, the missile system is analyzed and decoupled according to the function. The missile subsystem models are established by using different professional software, and then the original model of the subsystem is converted into an FMU (Functional Mock-up Unit) model that conforms to the FMI standard. On the other hand, a simulation platform supporting the FMI standard was developed for co-simulation of the entire missile power distribution system. Finally, the simulation results show the correctness of the FMI based simulation scheme and the effectiveness of the simulation platform.

The aircraft power distribution system is a combination of electrical, mechanical, magnetics, and control system. Traditional professional software can only simulate one specific domain, in order to study the coupling characteristics of aircraft power distribution system, a multi-domain simulation tool is needed. A FMI (Functional Mock-up Interface) based multi-domain simulation method is proposed in this paper to utilize the advantages of different software and their professional model libraries. As a case study, this paper built the controllers of aircraft power distribution by Simulink, and then exported as the FMU (Functional Mock-up Unit) model to Dymola platform according to the FMI standard for the modeling and simulation of whole systems. Those models which exported according FMI standard can be independent from the original simulator and applied to other platforms corresponded FMI standard, which realize multi-domain modeling and simulation.

District heating grids (DHG) face the problem of seasonal variability and peak demands, e.g., there is a high demand for heat in winter and a low demand in summer. Operators of district heating networks and energy suppliers are therefore seeking solutions to store heat and access it at peak times, thus reducing the use of carbon-emitting heat sources. Aquifers are well suited for heat storage because of high storage capacity relative to the surface occupancy and reasonably high recovery efficiency, if geological suitable. In this study, the potential of Aquifer Thermal Energy Storages (ATES) contribution in decreasing seasonal peak heat loads is investigated by numerical modelling. Each part of the overall system (surface and subsurface) is modelled in their corresponding simulation environment. They are numerically coupled with a novel approach, allowing for highest accuracy in both subsystems. The District Heating Grid is modelled in the object-oriented modelling language Modelica including the Open-Source library MoSDH. Using the Functional Mock-Up Interface (FMI) the Modelica models are exported to executable Functional Mock-Up Units (FMU). The groundwater flow and heat transport processes are modelled in the finite-element software FEFLOW. By developing a C++ Plug-In for FEFLOW the FMU is imported and dynamically co-simulated. This approach allows for easier adjustments in both subsystems and more coupling options to existing models and softwares.  Through numerical analysis different hydrological and geological scenarios of the ATES and different operational cycles are investigated to determine the long-term efficiency and capacity of the storage. This modelling approach can be used to develop strategies for the operation of the ATES as well as to evaluate in advance whether geological conditions are suitable for the particular network situation.

Ecos is a cross-platform framework for running co-simulations adhering to the Functional Mockup Interface (FMI) standard (Blochwitz et al., 2012); an open standard for model exchange and co-simulation of dynamic systems.The FMI Standard provides three interface types for difference aspects of models, namely: FMI for Model Exchange (ME), FMI for Co-simulation (CS), and FMI for Scheduled execution (Since FMI 3.0).Ecos supports the co-simulation mode, which is the most widely used interface type.An FMU (Functional Mock-up Unit) is a self-contained component that implements the FMI standard.It is packaged as a zip archive containing:

The Electro-Hydrostatic Actuation (EHA) nose landing gear system is a complex multi-domain system. in order to study the coupling characteristics of EHA system, a multi-domain simulation tool is needed. In this paper, a EHA block diagram based on extraction and retraction of nose landing gear is described and established from the mathematic model, and then completed the modeling and simulation of EHA system in Dymola. A controller of EHA system is exported as the Functional Mock-up Unit (FMU) model from Simulink to Dymola according to the Functional Mock-up Interface (FMI) standard.

In this paper, we describe how we generate Functional Mock-up Units (FMUs) for the automation block language Bloqqi. This allows Bloqqi control programs to be tested with simulations of the physical processes they control. The physical process can be specified in any tool that supports the Functional Mockup-Interface (FMI) standard. For example, we have successfully run Bloqqi programs together with Modelica models exported as FMUs. Bloqqi programs execute at discrete times, and we describe how this is handled in the implementation of the DoStep function, specified in the standard.

Digital twins are virtual replicas of physical systems updated real time and are increasingly vital for complex systems like batteries. Being electrochemical black boxes that degrade with use, batteries benefit from digital twins for monitoring, predictive maintenance, and optimization. Data-driven models are popular for digital twins due to their adaptability, but are limited by dependence on large datasets, weak interpretability, and poor generalization. In contrast, physics-based approaches such as Pseudo-2D (P2D) models offer higher accuracy, interpretability, and require less operational data. These models can be packaged and deployed across platforms using the Functional Mock-up Interface (FMI) and Functional Mock-up Units (FMUs). Through FMU deployment, this paper illustrates the challenges and opportunities in balancing model depth and scale across battery chemistries, as well as the robustness and efficiency of numerical methods across spatial and temporal scales. In addition, the paper highlights how classical models already integrate data-driven elements, such as empirical fits for open-circuit voltage and electrolyte properties. The most effective digital twin strategies for batteries are therefore hybrid models that combine the rigor of physics-based methods with the flexibility of data-driven tools. Such interpretable, scalable, and fast models are essential for advancing energy storage and enabling real-time control in diverse applications.

This paper describes the implementation of the scenario-based testing, a test method for autonomous driving software, by coupling a plant model described using MATLAB/Simulink with another plant model provided as Functional Mock-up Unit on a cloud platform. During the implementation of plant models into the cloud environment using the functional mock-up interface, there are problems and countermeasure challenges were identified. In addition, the impacts of integrating multiple models on simulation time by parallelizing test cases are measured.lly and more efficiently. The introduced software is available under an open-source license.

The paper presents novel tools for model-based control system design based on FMI/FMU standard (Functional Mock-up Interface / Unit). It is focused on application of FMI standard for easy integration of control system development cycle starting with Model-in-the-Loop (MIL) simulation and finishing with Hardware-in-the-Loop (HIL) simulation. It is shown, how the Functional Mock-up Units (FMU) containing dynamic differential-algebraic equations of various parts of the device (mechanical, electrical, hydraulic, thermal, etc.) can be easily deployed to unified simulation environment where the control system is designed, consequently. The procedure allows to combine inputs from various Modelica-based tools at the process model side, utilizing power of Matlab/Simulink for design, analysis and optimization of control system and perform final test via HIL scenario where both the model and control system are simulated in real-time on separated HW units. The pros and cons of both FMI concepts, i.e. Co-Simulation and Model Exchange are discussed in detail. The whole procedure is demonstrated on a steam turbine example combining component-based and equation based modeling. Both the turbine model and the full control loop are validated in all phases of control system development. It is shown, that monolithic simulation block with proprietary solver reduces computational burden compared to automatic FMU concept.

Automated monitoring of deployed Cyber-physical Systems during operation can assist in detecting misbehavior. One way to achieve such monitoring is via co-simulation of a modelled system corresponding to the deployed system. Our work addresses the topic of brokering external data into an Functional Mock-up Interface 2.0 enabled co-simulation via a Functional Mock-up Unit (a simulation unit) called RabbitMQ FMU and an external message queue. Our contribution includes a formal specification that captures the semantics of RabbitMQ FMU and ensures a maximum delay on the messages relayed to the co-simulation even through an unreliable network. This formal specification is used to generate test cases that exercise all states and transitions. The implementation is subjected to these test cases to verify that it is a refinement of the specification. The verification is ongoing and the implementation has successfully been subjected to 1,539,246 tests.

A co-simulation modelling approach for the assessment of a ventilated double-skin complex fenestration system coupled with a compact fan-coil unit