A group of engineers at the University of Texas at Arlington (UT Arlington) will develop hybrid software and hardware approaches to testing electric machines during the design stage.
The team will create highly accurate models that incorporate high-frequency effects and mimic the hardware prototype as closely as possible, at nearly real-time speed, on a desktop platform.
Led by UT Arlington professor Ali Davoudi, the team will start with the fundamental physics, and then apply the findings to create order-reduction techniques that will accelerate model simulations by as much as 1 million times. The researchers will then install the models on hardware-centric simulation platforms to run parallel simulations and further improve the simulation speed.
"If this research is successful, we will be able to design, optimize, and run tests quickly and push out improvements in a much shorter timeframe," Davoudi says.
The team has received a $285,000 grant from the U.S. National Science Foundation to pursue this project.
"Annual energy consumption by electric motors is expected to exceed 10 quadrillion watt-hours soon," Davoudi notes. "Any improvement we can make in the process will have a huge impact in the way we generate, convert, and store energy."
From UT Arlington News Center
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