A5
Automotive 1

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08:35
conference time (CEST, Berlin)
Future Virtualized Engineering – A Journey From Applied Research Perspective
26/10/2021 08:35 conference time (CEST, Berlin)
Room: A
B. Fachbach (Virtual Vehicle Research GmbH, AUT)
B. Fachbach (Virtual Vehicle Research GmbH, AUT)
Automotive industry is undergoing more or less radical change at different levels. Environmental requirements gain higher interest, mobility concepts influence the traditional business cases, the product is getting smarter, and new partners on the market or from other domains force industry to re-think collaboration. Challenges and fields of action cover a huge range from availability and reliability of data, gaining effectiveness in the early development phase, a more consequent integration of systems engineering into lifecycle processes, the lacking interoperability of data and models, demand for simulation governance and traceability, to the adequate role of data analytics and machine learning within continuous system integration and deployment. The risk is to take decisions and measures without having a big picture or vision what has to be expected within the next 5-10 years. The lecture will analyze major differences of current and future development, give an overview on the future oriented fields of action in the context of advanced virtualized development, and takes a look on some promising methodical and technological approaches.
08:55
conference time (CEST, Berlin)
Virtual Automotive Powertrain Development
26/10/2021 08:55 conference time (CEST, Berlin)
Room: A
P. Fietkau (Dr. Ing. h.c. F. Porsche AG, DEU)
P. Fietkau (Dr. Ing. h.c. F. Porsche AG, DEU)
09:15
conference time (CEST, Berlin)
Simulation Governance – Building Simulation Capability
26/10/2021 09:15 conference time (CEST, Berlin)
Room: A
I. Krajinović (Rimac Automobili d.o.o., HRV)
I. Krajinović (Rimac Automobili d.o.o., HRV)
With ever increasing need to bring products to the market faster, at lower costs or with increased efficiency, need for virtual prototyping is rising in many companies and industries. Simulations Department in Rimac Automobili is also a product of a such need. Rimac Automobili is focused on design, engineering, and production of high-performance electric vehicle components for the global automotive industry. To be able to deliver such components, numerical simulations are extensively used. Simulations Department has been formed by combining experts for several other departments. From its early stages it has been crucial to deliver fast and accurate insights of different designs of electric vehicle powertrain and battery systems using different types of calculations. With growth of the Rimac Automobili as a company, Simulations department is expanding its capabilities, toolset, and the team to be ready for future challenges in the development of electric vehicles. Now, several years in existence, many valuable lessons, and general rules of how to build highly functional simulations team and how to develop new simulations capabilities have been learned. These lessons and rules will be presented and discussed in this presentation. There are several aspects of building simulations capability presented. One of the aspects covered in this presentation is people management and communication of both inside of the team and outside of the team. Several lessons learned from interviewing process to the communication of the results will be presented. In parallel with the building of the team, it is necessary to expand simulations software and hardware capabilities. Discussions between selections of open source versus commercial software and local hardware versus cloud computing will also be presented. Other aspect that is discussed is experimental validation of simulations’ results. Experimental validation is crucial and inseparable part of simulations process needed to increase accuracy of the results and selections of the right modeling strategies. General guidelines how to perform experimental validation will be shown. Final aspect of building simulations capabilities is simulations data management. Process from initiating simulations request to data storing will be shown and discussed. Presented lessons and rules will be shown together with real life examples from projects that Simulations Department has been working on with special focus on Rimac Automobili’s all electric hypercar Nevera.
09:35
conference time (CEST, Berlin)
CFD Simulation of a Vehicle Driving in Snow
26/10/2021 09:35 conference time (CEST, Berlin)
Room: A
D. Bäder (Audi AG, DEU); A. Oliva, P. Kolar (AVL, DEU)
D. Bäder (Audi AG, DEU); A. Oliva, P. Kolar (AVL, DEU)
Motor vehicles are designed for different purposes. For the development of motor vehicles it is essential that the vehicles function without problems in winter. For this purpose, winter test drives are carried out in elaborate trials in order to determine, for example, how much snow is deposited on which structural components in the wheel arch. For the tests, ready-to-run vehicles must be available, which are often only available at a late stage of the development process and are usually very expensive to purchase. In this publication, a 3D CFD calculation method is presented. The calculation method is based on a SPH method, with which the snow entry into the wheelhouse is simulated. First, the simulated snow in the form of wet snow is validated on simple experiments. Then, the validated snow parameters are used to calculate the snow entry into the wheelhouse of a real, complex vehicle. In a first step the aerodynamics is neglected and the simulation is focused on purely the snow phase, i.e. a very slow driving speed. In a second step, the influence of airflow on snow input is investigated. Herefore a higher speed of the car is assumed. The results of the snow entry with and without the influence of the airflow field are compared and a discussion is given. Finally the simulation results are validated with real experiments. Herefore an Audi Q7 was tested on an ice field covered with new snow. Different cameras attached to the car have filmed the snow entry into the wheel arch. Important components of the vehicle, like for example the tires, have been 3D scanned in order to set up a simulation where the geometry is almost identical to the tested real car. A comparison of the experimental and numerical results is presented. Overall a CFD setup is presented that is able to simulate wet snow on a complex real car wheel arch geometry.
Snow, Simulation, CFD, SPH, Automotive, Vehicle
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