Modeling, Simulation & Development Tools

Diagram Fahrzeug-Umwelt-Mensch Interaktion (interaction of car, environment and human) FUMI (english)
© Fraunhofer ITWM
Modeling and analysis of vehicle-environment-human interaction

In system and vehicle development, it is crucial to obtain information about the behavior of mechanical, electrical and mechatronic systems at an early stage, efficiently and cost-effectively in the development process. For this purpose, the physical system properties in different phases of the development process are simulated mathematically in order to evaluate, improve and confirm design statuses.

For example, engine dynamics, driving dynamics, vibration comfort, durability and the behavior of assistance and safety systems are calculated. Different model complexities and computation rates are required for different tasks and in different development phases. The possibility of hybrid and interactive simulation is becoming increasingly important in order to realistically include electronic control units and the driver in the computation.

The Fraunhofer Gesellschaft covers a wide spectrum of solutions, starting with the development of the actual models, through consideration of the problem-specific model complexity, to the coupling of the various simulation techniques:

  • Further development and application of methods in multi-body simulation (MBS)
  • Optimal control of technical systems
  • Simulation of coupled physical systems (Co-Simulation)
  • Inclusion of environment and usage variability in modeling and simulation
  • Digital environmental models (globally geo-referenced, locally detailed (HD Maps))
  • Virtual product development and digital lifecycle files

Another critical success factor in the automotive industry are fast, effective and efficient development processes. In development, costs, quality and times are determined for the entire product life cycle. The organization of the processes is just as important as the methodological tools and the IT infrastructure. The Fraunhofer Institutes have built up extensive expertise in this area and support the automotive and supplier industries in the design of processes as well as in the selection and provision of suitable tools for vehicle engineering.

1. Digital Engineering

© sdecoret -

Digital Engineering is engineering with digital models in product development and production planning. Virtual functional prototypes are created early in the development process and tested by means of digital simulation or in interaction with the user or developer. Virtual reality technologies are used to make the prototypes tangible and communicable in heterogeneous development and planning teams as well as in customer relationships and to decision-makers.


  • Creation of introductory concepts for virtual engineering
  • Design and organization of agile development processes
  • Modeling and simulation of physical and functional product properties
  • Real-time capable auralization of acoustic product properties in their respective acoustic application environments
  • Planning and development of systems for virtual prototyping and testing
  • Provision of simulation and VR systems and execution of engineering services


Project examples

2. Adaptive Systems, System Identification

© zapp2photo -

Reliable models are required for the dynamic processes under consideration, both in multi-body simulation in the development cycle of a new vehicle and in the design of efficient control strategies for adaptive vehicle components or for predicting the crash behavior of new materials. If sufficient information-containing measurement data of the considered dynamic process is available, a data-based model description can be derived by means of System Identification methods.


  • Prognosis of stress-strain curves or Wöhler curves of e.g. magnesium die-cast components
  • Prognosis of the crash behavior of composite materials
  • Prognosis of casting defects
  • Identification of hysteresis models for rubber bearing modeling
  • Derivation of load collectives using simulations
  • Methods for automated model comparison with real measurement data


Project example

Efficient drive signal generation through inverse modeling [Fraunhofer LBF (German)]

3. Parametric Systems & Structure Optimization

© /

The requirements for the design of systems are usually multi-criteria or multi-disciplinary, which means that the design of the optimal structure must be considered from different points of view. In addition to the »traditional« approaches, the Fraunhofer Gesellschaft offers very efficient optimization strategies by clever coupling of simulation and optimization in connection with extremely fast adaptive simulation algorithms.


  • Non-parametric optimization (topology optimization and shape optimization)
  • DOE and parametric optimization at system level
  • Multi-objective optimization by coupling simulation and goal programming
  • Function optimization with regard to physical properties (dynamics, vibration behavior, operational durability)


Project example

4. Tools for Vehicle Engineering

© Mlke -

To support the development of vehicles and components, the Fraunhofer Gesellschaft does research and develops new approaches that enable complex products to be developed in interdisciplinary teams. We understand development as an integrated business process. An integrated view of the development processes allows the holistic optimization and shortening of product development.

Wire Frame SUV / 3D render image representing an luxury SUV in wire frame on laptop
© Mlke /
Wire Frame SUV / 3D render image representing an luxury SUV in wire frame on laptop


  • Strategic supplier selection and methodical integration in distributed product development
  • Development and installation of adequate cooperation models and organizational forms
  • Process analysis and optimization
  • Introduction of key figure-based R&D
  • Complexity management in development
  • Knowledge and competence management in R&D
  • Technology scouting
  • Definition and introduction of a holistic IT infrastructure
  • Development of company-specific future scenarios for engineering
  • Optimization of the interface to production
  • Methods for Distributed Testing

Project examples

5. Simulation of Mechanical & Mechatronic Systems

© wellphoto -

The increasing complexity of the developed systems and the number of variants require simulation-based evaluation and optimization at system level more than ever before.

The Fraunhofer Gesellschaft covers the entire spectrum of simulation methods and, in addition, develops methods and procedures to constantly expand their application possibilities. An essential focus is the combination of different simulation techniques in connection with the simulation of complex complete systems.


  • Simulation of the dynamic behavior of complex systems (e.g. vehicles, test systems)
  • Multi-body simulation (MBS) with flexible bodies and control systems
  • Computation of section forces and fatigue
  • Simulation of misuse (dynamic transient FEM)
  • Development of methods and modeling in the MBS environment (rubber bearings, virtual test rigs / road)
  • Function optimization with regard to physical properties (dynamics, vibration behavior, durability)
  • Investigations into the robustness and reliability of systems


Project examples

6. Radar Simulation for Time-Dynamic Traffic Scenarios

Eine Straßenverkehrsszene von oben; Symbolbild für das autonome Fahren
© Steven Bostock /

Automotive radar sensors are an essential component of existing driver assistance systems and play an important role for the future of autonomous driving. The reliable function of such radar sensors can be investigated with the help of hardware-in-the-loop or software-in-the-loop tests based on simulated data.

In order to determine the characteristics of radar signatures generated by road users, traffic scenarios must be modeled and analyzed electromagnetically. For this purpose, researchers at Fraunhofer FHR are developing the EM simulation software GOPOSim. This software makes it possible to simulate time-dynamic traffic scenarios electro-dynamically. In order to achieve efficient modeling and short simulation times, CAD models of the road users positioned in the corresponding traffic scene are loaded and transferred to a suitable scattering center model during runtime. In this way, GOPOSim computes the radar signatures of the traffic scenarios in a time-discrete manner, taking into account the physical properties.

Visualisierung einer Verkehrsszene als Range/Doppler-Map
© Fraunhofer FHR
Visualization of a traffic scene as Range/Doppler map


  • Time-dynamic radar target simulations
  • Monostatic RCS Simulations
  • Bistatic RCS Simulations
  • Multipath propagation
  • Real-time simulation
  • Import of CAD models
  • Import of antenna diagrams
  • Modular design / expandable
EM-Simulation dynamischer Verkehrsszenarien
© Fraunhofer FHR
EM-Simulation dynamischer Verkehrsszenarien.

Project examples

7. Digital Environmental Data for Vehicle Engineering

© Fraunhofer ITWM
Photo of the real scene (Trippstadter Straße, Kaiserslautern).

Due to the constantly increasing complexity of assistance and automation functions in vehicles, however, classic testing and design procedures are increasingly reaching their limits.

Current approaches, such as the description of the logic of a road network, often fail to capture complex peripheral cases, which are present in reality. These include, for example, incomplete road markings or defective asphalt. Real assistance systems must, however, be able to achieve a safe driving condition even in the absence of road markings. This must be taken into account early in the development process.

The »VMC® Road and Scene Generator« software package which is currently developed as part of the »Virtual Measurement Campaign« (VMC®) software suite enables the virtual development and testing of automation systems based on real environmental data.

Automatische semantische Segmentierung und Klassifikation der Laserscanndaten.
© Fraunhofer ITWM
Automatic semantic segmentation and classification of laser scan data.


  • Virtual development and testing of automation systems based on real environmental data
  • Derivation of a representative city or region with regard to selected criteria (certain slope or curviness characteristics etc.)
  • Geo-referenced 3D laser scan of the environment
  • Automated identification and classification of traffic-relevant objects (vehicles, lanes, road markings, buildings etc.) from 3D point clouds
  • Generation and export of traffic-relevant environmental data in OpenDrive® format
Geo-referenzierter 3D-Laserscan der Umgebung. Digitale Umgebungsdaten: Bild 3/3
© Fraunhofer ITWM
Geo-referenced 3D laser scan of the environment.