Objectives and results

Volatile economic developments and the dynamically advancing technical progress in the field of electric traction drives lead to a high degree of uncertainty with regard to the expected quantities and technologies used. This results in the need for an agile development and production process. 
In this project, the existing digital design process at the ETI is to be expanded and its efficiency increased. In particular, the design process should take into account the interactions with the production system. The process will then be applied to develop a product kit from requirements and technologies previously defined at IPEK. The corresponding agile production system will be developed by the wbk and various industrial partners under the consortium leadership of Schaeffler AG.

Contents and Approach

The design process is implemented at ETI in the form of a tool chain. For this purpose, various simulation environments are bundled. This tool chain is to be extended to include mechanical and thermal simulation. This will enable a quick multi-physical assessment of the machine. In addition, an optimiser will be connected to the tool chain, with the help of which the most suitable machine designs for a specific application can be identified.  The optimiser also takes into account the individual tolerances of the machine so that robust optima can be found. 
The optimisation is based on surrogate models that use machine learning algorithms to map various machine parameters. The consistent use of these models should further increase the efficiency of the design.

Furthermore, the potential of surrogate models in non-parametric optimisation (topology optimisation) is to be investigated. In a subsequent step, the design space of the product construction kit is to be stored with surrogate models and a scaling tool with the help of the tool chain. This enables a later optimisation within the modular system without further costly FEM simulations.