On Friday, March 18, IDEPA renewed its commitment to the Wolfast team, reaffirming its interest in contributing to the development of young talent in the Principality of Asturias. On the day of the renewal, the team visited IDEPA’s facilities, where team members presented the results of the previous year’s motorcycle in the 6th edition of MotoStudent.
Several IDEPA members had the opportunity to see the motorcycle in person. Subsequently, they attended the auditorium where Eva Pando, General Director of IDEPA, briefly introduced the project. Following this, Álvaro Noriega, the project supervisor, explained and shared the competition’s objectives and the new requirements for the upcoming MS7 edition.
This event confirmed the sponsorship renewal for MS7 in the electric category, demonstrating the institution’s strong support for the project. The sponsorship is not only linked to research and development (I+D) but also contributes to nurturing young talent from the University of Oviedo.
Various topics were addressed during the event, ranging from the impact on the grid and its management for the integration of electric vehicles to the technology involved in electric vehicles, considering applications such as buses, trains, light vehicles, commercial vehicles, and future prospects, especially in the country of Chile.
Two professors from the University of Oviedo participated in this event: Ángel Navarro Rodríguez and Fernando Briz. Ángel is an honors graduate from the University of Castilla-La Mancha, a member of the LEMUR research group, project supervisor for motostudent, and a professor at the University of Oviedo. During the event, he presented the motostudent project, covering team organization, work methodology, and design considerations for the electric traction system applied to the MS6 and MS7 prototypes. He also showcased a low-voltage series hybrid traction application in agriculture.
On the other hand, Professor Fernando Briz discussed the origins and fundamentals of electric and hybrid traction systems, as well as the estimation of variables in permanent magnet motors.