Functional Mock-up Interface
The vision of FMI is to support this approach: if the real product is to be assembled from a wide range of parts interacting in complex ways, each controlled by a complex set of physical laws, then it should be possible to create a virtual product that can be assembled from a set of models that each represent a combination of parts, each a model of the physical laws as well as a model of the control systems (using electronics, hydraulics, digital software, ..) assembled digitally. The FMI standard thus provides the means for model based development of systems and is used for example for designing functions that are driven by electronic devices inside vehicles (e.g. ESP controllers, active safety systems, combustion controllers). Activities from systems modelling, simulation, validation and test can be covered with the FMI based approach.
To create the FMI standard, a large number of software companies and research centers have worked in a cooperation project established through a European consortium that has been conducted by Dassault Systèmes under the name of MODELISAR. The MODELISAR project started in 2008 to define the FMI specifications, deliver technology studies, prove the FMI concepts through Use Cases elaborated by the consortium partners and enable tool vendors to build advanced prototypes or in some cases even products.
The development of the FMI specifications was coordinated by Daimler AG.
The four required FMI aspects of creating models capable of being assembled have been covered in Modelisar project:
- FMI for model exchange,
- FMI for co-simulation,
- FMI for applications,
- FMI for PLM (integration of models and related data in product life-cycle management).
In practice, the FMI implementation by a software modelling tool enables the creation of a simulation model that can be interconnected or the creation of a software library called FMU (Functional Mock-up Unit).
The FMI approach
The typical FMI approach is described in the following stages:
- a modelling environment describes a product sub-system by differential, algebraic and discrete equations with time, state and step-events. These models can be large for usage in off-line or on-line simulation or can be used in embedded control systems;
- as an alternative, an engineering tool defines the controller code for controlling a vehicle system;
- such tools generate and export the component in an FMU (Functional Mock-up Unit);
- an FMU can then be imported in another environment to be executed;
- several FMUs can – by this way – cooperate at runtime through a co-simulation environment, thanks to the FMI definitions of their interfaces.
The FMI specifications are distributed under open source licenses:
- the specifications are licensed under CC-BY-SA (Creative Commons Attribution-Sharealike 3.0 Unported) CC_BY_SA 3.0
- the C-header and XML-schema files that accompany this document are available under the BSD license with the extension that modifications must also be provided under the BSD license.
- an XML file containing among other things the definition of the variables used by the FMU;
- all the equations used by the model (defined as a set of C functions);
- optional other data, such as parameter tables, user interface, documentation which may be needed by the model.
Below is an example of an FMI model description issued from Modelica.
<?xml version="1.0" encoding="UTF8"?> <fmiModelDescription fmiVersion="1.0" modelName="ModelicaExample" modelIdentifier="ModelicaExample_Friction" ... <UnitDefinitions> <BaseUnit unit="rad"> <DisplayUnitDefinition displayUnit="deg" gain="23.26"/> </BaseUnit> </UnitDefinitions> <TypeDefinitions> <Type name="Modelica.SIunits.AngularVelocity"> <RealType quantity="AngularVelocity" unit="rad/s"/> </Type> </TypeDefinitions> <ModelVariables> <ScalarVariable name="inertia1.J" valueReference="16777217" description="Moment of inertia" variability="parameter"> <Real declaredType="Modelica.SIunits.Torque" start="1"/> </ScalarVariable> ... </ModelVariables> </fmiModelDescription>
FMI is often compared to Simulink S-Functions since both technologies can be used to integrate third-party tools together. S-Functions are used to specify a computer language description of a dynamic system. They are compiled as MEX-files that are dynamically linked into MATLAB when needed. S-Functions use a calling syntax that interacts with Simulink’s equation solvers. This interaction is similar to the interaction that takes place between built-in Simulink blocks and the solvers.
FMI proponents explain that FMI models have several advantages over Simulink S-Functions:
- S-Functions format is proprietary, whereas the FMI schema is licensed under a BSD license.
- The building blocks of S-Functions are much more complex than FMI, making it very difficult to integrate in simulators other than Simulink itself.
- Furthermore, the S-Functions format is specific to Simulink.
- S-Functions are not suited for embedded systems, due to the memory overhead of S-Functions.
There are also several limitations cited when using FMI/FMU:
- Memory - Parameters, states, inputs, and outputs are not exposed directly to the outside, which is in contrast to how ECU software is normally organized with respect to memory to allow transparency, simplicity, and efficiency.
- Event handling - Events could increase the runtime for real-time systems in an unpredictable manner.
- Potentially dangerous features can be included on ECU - Some features that make sense for offline simulations should not be present on the ECU. Examples of features that are either supported or not explicitly forbidden in the FMI include logging and I/O operations such as print().
- Data type support - More supported data types are necessary for optimized code. For example, there is not a way to distinguish between a uint8 and uint32 variable.
- AMESim – Simulation software for the modeling and analysis of multi-domain mechatronics systems from Siemens PLM Software
- ANSYS SCADE Display - Embedded software design for Human Machine Interface
- ANSYS SCADE Suite - Model-based embedded software development for critical systems
- ANSYS Simplorer - Physical modeling & simulation for electrified systems
- ASIM – AUTOSAR Builder from Dassault Systèmes
- Adams - High end multibody dynamics simulation software from MSC Software
- Atego Ace – Co-simulation environment with AUTOSAR and HIL support
- CANoe - Comprehensive software tool for development, test and analysis of entire ECU networks and individual ECUs
- CATIA V6R2012 – Environment for Product Design and Innovation, including systems engineering tools based on Modelica, by Dassault Systèmes
- ControlBuild – Environment for IEC 61131-3 control applications from Dassault Systèmes
- coreDS™ for FMI: Turns a FMU (Functional Mock-up Unit) into a full featured HLA federate and/or DIS simulation
- CosiMate– Co-simulation Environment from ChiasTek
- Cybernetica CENIT - Industrial product for nonlinear Model Predictive Control (NMPC) from Cybernetica
- Cybernetica ModelFit - Software for model verification, state and parameter estimation, using logged process data. By Cybernetica
- DSHplus – Fluid power simulation software from FLUIDON* Dymola 7.4 – Modelica environment from Dassault Systèmes
- ePHASORsim from OPAL-RT Technologies Inc., via
- Flowmaster - Simulation software for modeling thermo-fluid systems
- FMI Add-In for Excel – Batch simulation of FMUs in Microsoft Excel
- FMI Library – C library for importing FMUs in custom applications
- FMU compliance checker – Software for verifying FMI standard compliance of FMUs
- FMU SDK – FMU Software Development Kit from QTronic
- FMU Trust Centre - cryptographic protection and signature of models including their safe PLM storage; secure authentication and authorization for protected (co-)simulation
- GT-SUITE - Multi-Physics Simulation Platform for Powertrain and Vehicle Systems
- Hopsan - Distributed system simulation tool using the TLM method
- ICOS Independent Co-Simulation – independent co-simulation environment from Virtual Vehicle Research Center
- IPG CarMaker – via Modeling and Co-Simulation environment by Modelon
- ISOLAR-EVE – Software tool from ETAS for creation and test of virtual ECUs
- JModelica.org – Open source Modelica environment from Modelon
- MapleSim - via the MapleSim Connector for FMI from Maplesoft
- MATLAB – via FMI Toolbox from Modelon or via the FMU Export from Simulink from Dassault Systèmes
- MWorks 2.5 – Modelica environment from Suzhou Tongyuan
- NI LabVIEW – Graphical programming environment for measurement, test, and control systems from National Instruments
- NI VeriStand – Real-Time Testing and Simulation Software from National Instruments
- Model.CONNECT - neutral model integration and co-simulation platform from AVL
- OpenModelica – Open source Modelica environment from OSMC OpenModelica for transient stability simulations of power systems
- OPTIMICA Studio – Modelica environment from Modelon
- Python – via PyFMI from Modelon, also available as part of JModelica.org
- Silver 2.0 – Virtual integration platform for Software in the Loop from QTronic
- SIMPACK 9 – High end multi-body simulation software from SIMPACK AG
- SimulationX 3.4 – Modelica environment from ITI
- Simulink – via Dymola 7.4 using Real-Time Workshop
- Simulink – via @Source
- Simulink – via FMI Toolbox from Modelon
- TISC – Co-simulation environment from TLK-Thermo
- TWT Co-Simulation Framework - Communication layer tool to flexibly plug together models for performing a co-simulation; front-end for set-up, monitoring and post-processing included
- TWT Matlab/Simulink FMU Interface - FMI-compatible plug-and-play interface to Matlab/Simulink, available as an integrated block
- Virtual.Lab Motion - Virtual.Lab Motion is a high end multi body software from Siemens PLM Software
- Wolfram SystemModeler - Modelica environment from Wolfram Research
- xMOD - Heterogeneous model integration environment & virtual instrumentation and experimentation laboratory from IFPEN distributed by D2T.
Accompanying Standards and Recommendations
In May 2014, the Project Group Smart Systems Engineering (SmartSE) of the ProSTEP iViP Association published its Recommendation PSI 11 for the cross-company behavior model exchange. FMI thereby is the technological basis. The PSI 11 specifies interaction scenarios, use cases, a reference process and templates, which thereby could ease the industrial application. End of 2016 the group published a movie, which should highlight the industrial benefits.
- "Functional Mockup Interface (FMI)". modelica.org. January 2010. Retrieved 2011-012-22.
On Jan. 26, version 1.0 of the open Functional Mockup Interface was released (FMI for model exchange 1.0). This interface was developed in the ITEA2 MODELISAR project to support the model exchange between modelling and simulation tools. The Modelisar project is coordinated by Dassault Systèmes. The FMI development has been organized by Daimler.Check date values in:
- Stepan Ozana; Martin Pies. "Using Simulink S-Functions with Finite Difference Method Applied for Heat Exchangers" (PDF). Proceedings of the 13th WSEAS International Conference on SYSTEMS). Retrieved 2015-08-05.
- Martin Otter; Hilding Elmqvist; Torsten Blochwitz; Jakob Mauss; Andreas Junghanns; Hans Olsson. "Functional Mockup Interface – Overview" (PDF). http://synchronics.inria.fr (INRIA). Archived from the original (PDF) on July 20, 2011. Retrieved 2011-01-23. External link in
- Christian Bertsch; Jonathan Neudorfer; Elmar Ahle; Siva Sankar Arumugham; Karthikeyan Ramachandran; Andreas Thuy. "FMI for physical models on automotive embedded targets" (PDF). Proceedings of the 11th International Modelica Conference). Retrieved 2015-09-21.
- ProSTEP iViP Recommendation PSI 11, Smart Systems Engineering, Behavior Model Exchange, V 1.0, May 2014.
- Benefits of utilizing FMI for realizing cross-company Systems Engineering, Status February 2017