A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric solutions for electromagnetic fields in synchronous machines. Specifically, the intrusive version of the Proper Generalized Decomposition (PGD) is employed to simulate a Permanent-Magnet Synchronous Motor (PMSM). The result is a virtual chart allowing real-time evaluation of the magnetic vector potential as a function of the operation point of the motor, or even as a function of constructive parameters, such as the remanent flux in permanent magnets. Currently, these solutions are highly demanded by the industry, especially with the recent developments in the Electric Vehicle (EV). In this framework, standard discretization techniques require h...
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. Th...
The number of electrical machines used in modern road-vehicles is continuously increasing to meet re...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
International audienceA novel Model Order Reduction (MOR) technique is developed to compute high-dim...
The Proper Generalized Decomposition (PGD) is a model order reduction method which allows to reduce ...
A novel model order reduction (MOR) technique is presented to achieve fast and real-time predictions...
Among the model order reduction techniques, the Proper Generalized Decomposition (PGD) has shown its...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
In the domain of numerical computation, Proper Generalized Decomposition (PGD), which consists of ap...
Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to ...
Model Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in o...
Due to fine discretization in space and time, the simulation of transient electromagnetic phenomena ...
Model order reduction is an approach for reducing size, complexity, and computation cost of mathemat...
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. Th...
The number of electrical machines used in modern road-vehicles is continuously increasing to meet re...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
International audienceA novel Model Order Reduction (MOR) technique is developed to compute high-dim...
The Proper Generalized Decomposition (PGD) is a model order reduction method which allows to reduce ...
A novel model order reduction (MOR) technique is presented to achieve fast and real-time predictions...
Among the model order reduction techniques, the Proper Generalized Decomposition (PGD) has shown its...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
In the domain of numerical computation, Proper Generalized Decomposition (PGD), which consists of ap...
Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to ...
Model Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in o...
Due to fine discretization in space and time, the simulation of transient electromagnetic phenomena ...
Model order reduction is an approach for reducing size, complexity, and computation cost of mathemat...
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. Th...
The number of electrical machines used in modern road-vehicles is continuously increasing to meet re...
In order to reduce the computation time and the memory resources required to solve an electromagneti...