Sensitivity Analysis of Inverse Thermal Modeling to Determine Power Losses in Electrical Machines

Research output: Contribution to journalArticleScientificpeer-review

Standard

Sensitivity Analysis of Inverse Thermal Modeling to Determine Power Losses in Electrical Machines. / Nair, Devi Geetha; Rasilo, Paavo; Arkkio, Antero.

In: IEEE Transactions on Magnetics, Vol. 54, No. 11, 8109405, 11.2018.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

APA

Vancouver

Author

Bibtex - Download

@article{fddc86dad04946ae9c0dc362009d5921,
title = "Sensitivity Analysis of Inverse Thermal Modeling to Determine Power Losses in Electrical Machines",
abstract = "Inverse analysis is a known mathematical approach, which has been used to solve physical problems of a particular nature. Nevertheless, it has seldom been applied directly for loss reconstruction of electrical machines. This paper aims to verify the accuracy of an inverse methodology used in mapping power loss distribution in an induction motor. Conjugate gradient method is used to iteratively find the unique inverse solution when simulated temperature measurement data are available. Realistic measurement situations are considered and the measurement errors corresponding to thermographic measurements and temperature sensor measurements are used to generate simulated numerical measurement data. An accurate 2-D finite-element thermal model of a 37 kW cage induction motor serves as the forward solution. The inverse model's objective is to map the power loss density in the motor accurately from noisy temperature measurements made on the motor housing's outer surface. Furthermore, the sensitivity of the adopted inverse methodology to variations in the number of available measurements is also considered. Filtering the applied noise to acceptable ranges is shown to improve the inverse mapping results.",
keywords = "Heat transfer, Heating systems, induction motor, Induction motors, inverse problems, Loss measurement, Noise measurement, Stator windings, Temperature measurement",
author = "Nair, {Devi Geetha} and Paavo Rasilo and Antero Arkkio",
note = "| openaire: EC/FP7/339380/EU//ALEM",
year = "2018",
month = "11",
doi = "10.1109/TMAG.2018.2853084",
language = "English",
volume = "54",
journal = "IEEE Transactions on Magnetics",
issn = "0018-9464",
number = "11",

}

RIS - Download

TY - JOUR

T1 - Sensitivity Analysis of Inverse Thermal Modeling to Determine Power Losses in Electrical Machines

AU - Nair, Devi Geetha

AU - Rasilo, Paavo

AU - Arkkio, Antero

N1 - | openaire: EC/FP7/339380/EU//ALEM

PY - 2018/11

Y1 - 2018/11

N2 - Inverse analysis is a known mathematical approach, which has been used to solve physical problems of a particular nature. Nevertheless, it has seldom been applied directly for loss reconstruction of electrical machines. This paper aims to verify the accuracy of an inverse methodology used in mapping power loss distribution in an induction motor. Conjugate gradient method is used to iteratively find the unique inverse solution when simulated temperature measurement data are available. Realistic measurement situations are considered and the measurement errors corresponding to thermographic measurements and temperature sensor measurements are used to generate simulated numerical measurement data. An accurate 2-D finite-element thermal model of a 37 kW cage induction motor serves as the forward solution. The inverse model's objective is to map the power loss density in the motor accurately from noisy temperature measurements made on the motor housing's outer surface. Furthermore, the sensitivity of the adopted inverse methodology to variations in the number of available measurements is also considered. Filtering the applied noise to acceptable ranges is shown to improve the inverse mapping results.

AB - Inverse analysis is a known mathematical approach, which has been used to solve physical problems of a particular nature. Nevertheless, it has seldom been applied directly for loss reconstruction of electrical machines. This paper aims to verify the accuracy of an inverse methodology used in mapping power loss distribution in an induction motor. Conjugate gradient method is used to iteratively find the unique inverse solution when simulated temperature measurement data are available. Realistic measurement situations are considered and the measurement errors corresponding to thermographic measurements and temperature sensor measurements are used to generate simulated numerical measurement data. An accurate 2-D finite-element thermal model of a 37 kW cage induction motor serves as the forward solution. The inverse model's objective is to map the power loss density in the motor accurately from noisy temperature measurements made on the motor housing's outer surface. Furthermore, the sensitivity of the adopted inverse methodology to variations in the number of available measurements is also considered. Filtering the applied noise to acceptable ranges is shown to improve the inverse mapping results.

KW - Heat transfer

KW - Heating systems

KW - induction motor

KW - Induction motors

KW - inverse problems

KW - Loss measurement

KW - Noise measurement

KW - Stator windings

KW - Temperature measurement

UR - http://www.scopus.com/inward/record.url?scp=85050587914&partnerID=8YFLogxK

U2 - 10.1109/TMAG.2018.2853084

DO - 10.1109/TMAG.2018.2853084

M3 - Article

VL - 54

JO - IEEE Transactions on Magnetics

JF - IEEE Transactions on Magnetics

SN - 0018-9464

IS - 11

M1 - 8109405

ER -

ID: 27556795