Case Study
Tuesday, March 25
04:30 PM - 05:00 PM
Live in Berlin
Less Details
The strategic use of oriented steel in a segmented stator AC electric machine can potentially improve performance by reducing core losses compared to machines using non-oriented steel. However, the introduction of cut-edges and the stress on individual segments due to segmented stator construction may lead to unintended consequences. Despite various efforts to evaluate the impact of cut-edges or oriented steel on core losses in segmented stators, the literature lacks an analysis of the loss separation between tooth and back-iron components using manufactured stators. This gap hinders a comprehensive understanding of the true impact of using oriented steel in segmented stator construction for core loss improvement. In this study, we calculate the loss of each tooth and back-iron segment by conducting experiments with three different electromagnetic devices, specifically H-shaped steel laminations. By comparing the results from three manufactured stators, we clarify the influence of oriented steel in relation to segmented stator construction.
In this session, you will learn more about:
Dr. Anmol Aggarwal is a highly accomplished professional who holds a Ph.D. in Electrical and Computer Engineering from Michigan State University. With a profound academic background, they have demonstrated a deep understanding of the complexities within the field. Currently based in Pontiac, Michigan, USA, Anmol serves as an Electric Motor Controls Engineer at General Motors. In this capacity, he contributes his expertise to the design, development, and optimization of electric motor controls, playing a pivotal role in shaping the future of automotive technology.
Bhuvan Khoshoo is a Ph.D. candidate at Michigan State University, specializing in electric machine design, control, and optimization. As a Graduate Research Assistant at the Electric Machines and Power Electronics Research (EMPowER) Lab, he focuses on finite element analysis (FEA), multi-objective optimization, and Python-based simulation frameworks for electric motors. With industry experience spanning Nexteer Automotive, General Motors, and Schneider Electric, Bhuvan has worked on electromagnetic modeling, core loss analysis, and computational fluid dynamics (CFD) simulations. His expertise extends to automated optimization workflows for electric machines, enhancing efficiency and reducing design errors. His research contributes to advancing high-performance and energy-efficient electric powertrains, with a strong emphasis on digitalization, multi-physics modeling, and simulation-driven development.