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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Sun, 03 Mar 2024 07:15:44 GMT2024-03-03T07:15:44ZModel Order Reduction of Electrical Machines with Multiple Inputs
http://hdl.handle.net/10985/11834
Model Order Reduction of Electrical Machines with Multiple Inputs
FARZAM FAR, Mernhaz; BELAHCEN, Anouar; RASILO, Paavo; CLENET, Stéphane; PIERQUIN, Antoine
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model from a high-order nonlinear permanent magnet synchronous machine model with multiple inputs. Three parameters are selected as the multiple inputs of the machine. These parameters are terminal current, angle of the terminal current, and rotation angle. To produce the lower-rank system, snapshots or instantaneous system states are projected onto a set of orthonormal basis functions with small dimension. The reduced model is then validated by comparing the vector potential, flux density distribution, and torque results of the original model, which indicates the capability of using the proper orthogonal decomposition method in the multi-variable input problems. The developed methodology can be used for fast simulations of the machine.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/118342017-01-01T00:00:00ZFARZAM FAR, MernhazBELAHCEN, AnouarRASILO, PaavoCLENET, StéphanePIERQUIN, AntoineIn this paper, proper orthogonal decomposition method is employed to build a reduced-order model from a high-order nonlinear permanent magnet synchronous machine model with multiple inputs. Three parameters are selected as the multiple inputs of the machine. These parameters are terminal current, angle of the terminal current, and rotation angle. To produce the lower-rank system, snapshots or instantaneous system states are projected onto a set of orthonormal basis functions with small dimension. The reduced model is then validated by comparing the vector potential, flux density distribution, and torque results of the original model, which indicates the capability of using the proper orthogonal decomposition method in the multi-variable input problems. The developed methodology can be used for fast simulations of the machine.