Assist. Prof. Dr. Frédéric DUBAS| Semi-analytical mode | Best Researcher Award
Associate Professor. Femto-ST / uFC, France
Frédéric Dubas (b. June 16, 1978, Vesoul, France) is a prominent Associate Professor (MCF) at Université de Franche-Comté, with an extensive background in electrical engineering. Based in Belfort, France, he is affiliated with the FEMTO-ST Institute’s Energy Department. His contributions are recognized through leadership roles, numerous publications, and industrial collaborations that bridge academic research with applied energy solutions, especially in electro-mechanical systems. His research excellence is highlighted by awards from IEEE and industry leaders, positioning him as a key innovator in electrical machinery.
Profile
Publications Top Notes📚
Slotting Effects in Permanent-Magnet Motors: Dubas and Espanet (2009) tackled the no-load vector potential and flux density calculations, essential for accurate modeling of magnetic behavior in motors with slotting effects.
Eddy-Current Losses in Slotless PMSM: His 2013 study with Rahideh presented a two-dimensional approach for eddy-current loss estimation in slotless PMSMs with surface-inset magnets.
Switched Reluctance Machines: In 2017, Dubas and colleagues introduced a nonlinear analytical prediction method for magnetic fields in switched reluctance machines, enhancing performance predictions under various operating conditions.
Subdomain Techniques: Dubas has been pivotal in developing subdomain techniques for magnetic field calculations, notably in radial-flux electrical machines, with applications extending to both Cartesian and polar coordinates.
Axial-Flux Motor Design for Automotive Applications: His research includes motor design tailored to electric and hybrid vehicles, comparing performance across different rotor topologies.
Conclusion
The researcher is a strong candidate for the Best Researcher Award due to their pioneering contributions, technical depth, and commitment to advancing semi-analytical methods in electromagnetic analysis. Their work supports critical advancements in machine efficiency and performance, especially within high-demand industries like automotive and power generation. Addressing minor improvements, such as broader application diversity and increased collaboration, could further amplify their research impact. Given these strengths, the researcher has a robust foundation that aligns well with the standards and goals of the award.