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Model Order Reduction of Electrical Machines with Multiple Inputs

Tutkimustuotosvertaisarvioitu

Standard

Model Order Reduction of Electrical Machines with Multiple Inputs. / Farzam Far, Mehrnaz; Belahcen, Anouar; Rasilo, Paavo; Clénet, Stephane; Pierquin, Antoine.

julkaisussa: IEEE Transactions on Industry Applications, Vuosikerta 53, Nro 4, 2017, s. 3355-3360.

Tutkimustuotosvertaisarvioitu

Harvard

Farzam Far, M, Belahcen, A, Rasilo, P, Clénet, S & Pierquin, A 2017, 'Model Order Reduction of Electrical Machines with Multiple Inputs', IEEE Transactions on Industry Applications, Vuosikerta. 53, Nro 4, Sivut 3355-3360. https://doi.org/10.1109/TIA.2017.2681967

APA

Farzam Far, M., Belahcen, A., Rasilo, P., Clénet, S., & Pierquin, A. (2017). Model Order Reduction of Electrical Machines with Multiple Inputs. IEEE Transactions on Industry Applications, 53(4), 3355-3360. https://doi.org/10.1109/TIA.2017.2681967

Vancouver

Farzam Far M, Belahcen A, Rasilo P, Clénet S, Pierquin A. Model Order Reduction of Electrical Machines with Multiple Inputs. IEEE Transactions on Industry Applications. 2017;53(4):3355-3360. https://doi.org/10.1109/TIA.2017.2681967

Author

Farzam Far, Mehrnaz ; Belahcen, Anouar ; Rasilo, Paavo ; Clénet, Stephane ; Pierquin, Antoine. / Model Order Reduction of Electrical Machines with Multiple Inputs. Julkaisussa: IEEE Transactions on Industry Applications. 2017 ; Vuosikerta 53, Nro 4. Sivut 3355-3360.

Bibtex - Lataa

@article{77d7c8f5d0d24dfcabb31b221605928d,
title = "Model Order Reduction of Electrical Machines with Multiple Inputs",
abstract = "In this paper, proper orthogonal decomposition (POD) 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 POD method in the multivariable input problems. The developed methodology can be used for fast simulations of the machine.",
author = "{Farzam Far}, Mehrnaz and Anouar Belahcen and Paavo Rasilo and Stephane Cl{\'e}net and Antoine Pierquin",
year = "2017",
doi = "10.1109/TIA.2017.2681967",
language = "English",
volume = "53",
pages = "3355--3360",
journal = "IEEE Transactions on Industry Applications",
issn = "0093-9994",
publisher = "Institute of Electrical and Electronics Engineers",
number = "4",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Model Order Reduction of Electrical Machines with Multiple Inputs

AU - Farzam Far, Mehrnaz

AU - Belahcen, Anouar

AU - Rasilo, Paavo

AU - Clénet, Stephane

AU - Pierquin, Antoine

PY - 2017

Y1 - 2017

N2 - In this paper, proper orthogonal decomposition (POD) 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 POD method in the multivariable input problems. The developed methodology can be used for fast simulations of the machine.

AB - In this paper, proper orthogonal decomposition (POD) 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 POD method in the multivariable input problems. The developed methodology can be used for fast simulations of the machine.

U2 - 10.1109/TIA.2017.2681967

DO - 10.1109/TIA.2017.2681967

M3 - Article

VL - 53

SP - 3355

EP - 3360

JO - IEEE Transactions on Industry Applications

JF - IEEE Transactions on Industry Applications

SN - 0093-9994

IS - 4

ER -