Resumen: A novel model order reduction (MOR) technique is presented to achieve fast and real-time predictions as well as high-dimensional parametric solutions for the electromagnetic force which will help the design, analysis of performance and implementation of electric machines concerning industrial applications such as the noise, vibration, and harshness in electric motors. The approach allows to avoid the long-time simulations needed to analyze the electric machine at different operation points. In addition, it facilitates the computation and coupling of the motor model in other physical subsystems. Specifically, we propose a novel formulation of the sparse proper generalized decomposition procedure, combining it with a reduced basis approach, which is used to fit correctly the reduced order model with the numerical simulations as well as to obtain a further data compression. This technique can be applied to construct a regression model from high-dimensional data. These data can come, for example, from finite element simulations. As will be shown, an excellent agreement between the results of the proposed approach and the finite element method models are observed. Idioma: Inglés DOI: 10.1007/s42452-021-04310-3 Año: 2021 Publicado en: SN Applied Sciences 3, 3 (2021), 355 [19 pp] ISSN: 2523-3963 Factor impacto CITESCORE: 2.7 - Earth and Planetary Sciences (Q2) - Environmental Science (Q2) - Engineering (Q2) - Chemical Engineering (Q3) - Materials Science (Q3) - Physics and Astronomy (Q3)