The research group E-Mobility and Alternative Drivetrains (EMD) focuses on advancing sustainable road transport through digital innovation in e-mobility and alternative drivetrains. We address the urgent need for decarbonization by developing solutions that improve energy efficiency and reduce emissions in transportation systems.

We bring research to practical applications, achieving both environmental sustainability and economic feasibility. Our work supports the transition to a carbon-neutral future while delivering measurable value to industry and society.

Research Focus

• Multi-objective design optimization of electric drives (OPED, more below)
• Reduction of indirect greenhouse gas emissions of electric powertrains
• Circular economy for powertrains
• Simulation of electric and electrified powertrains
• Decarbonization of road traffic
• Digitalization of development processes
• Functional Safety of powertrains

OPED - Optimization of Electric Drives

Our software OPED enables a multi-objective design optimization of electric drives, consisting of inverter, electric machine and gearbox. To do so, an evolutionary optimization algorithm from AI methods varies a multitude of design parameters of the electric powertrain to find best possible design solutions. Starting from requirements on system level, the optimization thus automatically generates optimal solutions regarding, e.g., performance, package, cost, energy efficiency and carbon footprint. The result is represented by a Pareto front of optimal solutions from which decision makers can select the most promising one.

OPED is a TU Graz development and the result of over a decade of research. It is also successfully established in industry application of a top worldwide Tier-1 automotive supplier to both accelerate and improve product development. Beyond purely electric powertrains, the method has also been applied to hybrid powertrains. 

The underlying technology can be applied to optimize any model-based engineering design task - Reach out to us to discuss your engineering optimization challenge!