The development of vehicle components is a lengthy and therefore very costly process. Researchers at Graz University of Technology (TU Graz) have developed a method that can shorten the development phase of the powertrain of battery electric vehicles by several months.
A team led by Martin Hofstetter from the Institute of Automotive Engineering is combining simulation models of components with evolutionary optimization algorithms. Their work was presented at the CTI Symposium.
This AI system automatically optimizes the entire powertrain—from the power electronics to the electric machine through to the transmission—in line with the manufacturer’s technical requirements, taking into account targets such as production costs, efficiency and package space requirements in the vehicle.
The OPED (Optimization of Electric Drives) software solution was developed at TU Graz and is the result of almost ten years of research. It is already being used successfully by a renowned Austrian automotive supplier.
The starting point for automatic optimization is the input of the technical requirements that the powertrain must fulfill: these include the power output, the minimum service life, the maximum speed to be achieved and the maximum space available in the vehicle.
“Electric drives consist of a large number of components that can be designed very differently in order to fulfill the desired requirements,” explains Martin Hofstetter.
“If I make a small change to the electric machine, it has an effect on the transmission and the power electronics. So it’s extremely complex to make optimal decisions.”
An additional difficulty is that there is no one perfect solution for a powertrain, as the priorities of the manufacturers also play a role. These could be production costs, the weight and volume of the powertrain or energy efficiency.
One day instead of several months
The OPED software solution makes it possible to significantly reduce this complexity. Based on the technical requirements, the software varies and combines around 50 design parameters simultaneously and compares the simulated powertrains with the manufacturers’ priorities.
Bad variants are dropped, better ones are further optimized. After several hundred thousand calculation and simulation cycles, OPED finds solutions that come closest to the manufacturers’ priorities. They can then select from a manageable number of variants those that they would like to develop and implement in detail.
“What engineers would need months to do without AI support takes about a day with OPED,” says Martin Hofstetter. “This allows the development teams to focus on top-level decisions instead of investing their limited time in manual calculation and simulation work.”
Optimization for an entire vehicle platform
The OPED system can also be flexibly expanded. As an optimization criterion, the researchers have added the CO2 emissions generated during the use of the powertrain as well as its production across the entire supply chain. This means that sustainability is already taken into account in the early development phase.
As a recent innovation, Dominik Lechleitner has succeeded in extending OPED for the optimization of electric powertrains for an entire vehicle platform as part of his doctoral thesis. The method helps to find optimal components that can be used as carry-over parts in the powertrains of different models of a platform in order to save development and production costs.
“The OPED approach can be used for a wide variety of product developments,” explains Martin Hofstetter, “and we are happy to work with new industrial partners to adapt it to their challenges and goals.”
Martin Hofstetter and Dominik Lechleitner were awarded the VDI Prize 2024 by the Association of German Engineers for their development. Martin Hofstetter also received the Kamm-Jante Medal of the Scientific Society for Automotive and Engine Technology (WKM) and the 1st Prize of the Vehicle Association Anniversary Foundation, awarded by the Austrian Economic Chamber’s Automotive Industry Association.
More information:
Lechleitner, D., et al. Minimising Scope 3 Emissions by Electric Powertrain Design Optimization. Proceedings of the CTI Symposium (2024) graz.elsevierpure.com/en/publi … rtrain-design-optimi
Graz University of Technology
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E-mobility: AI system accelerates the development of powertrains (2025, January 30)
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