Opt4E: Multicriteria Synthesis and Optimization of Powertrains for Electric Vehicles
Period: 2023 – 2026
Cooperation:
TU München – Lehrstuhl für Maschinenelemente/Forschungsstelle für Zahnräder und Getriebesysteme,
Leibniz Universität Hannover – Institut für Maschinenkonstruktion und Tribologie IMKT & Institut für Antriebssysteme IAL,
AVL Deutschland GmbH,
BMW AG,
LSP Innovative Automotive Systems GmbH,
Magna Powertrain B.V. & Co. KG,
Schaeffler Technologies AG & C0. KG,
Strama-MPS Maschinenbau GmbH & Co. KG,
Vitesco Technologies GmbH
Support: Bundesministerium für Wirtschaft und Klimaschutz
Sponsor: DLR Deutsches Zentrum für Luft- und Raumfahrt
The Opt4E research project has set itself the ambitious goal of developing a holistic method for the synthesis and optimization of powertrains for battery electric vehicles. Optimization criteria derived from requirements are to be taken into account as key performance indicators. To this end, six fields of work have been defined in which in-depth investigations will be carried out. In the resulting sub-projects, methods for the development of simulation models for subsystems (such as power electronics, e-machines and transmissions) of the drivetrain are developed, which take into account the requirements for production tolerances, NVH behavior, thermal management, efficiency and drivability/driving comfort. Knowledge- and physics-based models are developed in the individual fields of work and validated with the measurement results. The aim is to develop reliable methods and tools for powertrain synthesis and optimization. An application-friendly method carrier will be programmed in the form of a development platform, which can also be used to record boundary conditions and requirements for the drivetrain. An intelligent linking and parameterization of the simulation models of the subsystems enables an automated multi-criteria powertrain design and optimization in which machine learning algorithms can be used. In the project, the IMS is responsible for managing the field of work regarding driving comfort and also for managing the development and programming of the method carrier for the multi-criteria optimization, in which the research results of the project partners are integrated.