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OPTIMIZATION BY EVOLUTIONARY ALGORITHM AND FEM TOOLS: EXAMPLE ON SWITCHED RELUCTANCE MOTOR


Barukčić, Marinko; Hederić, Željko; Benšić, Tin; Ćorluka, Venco
OPTIMIZATION BY EVOLUTIONARY ALGORITHM AND FEM TOOLS: EXAMPLE ON SWITCHED RELUCTANCE MOTOR // Digest book of the 7th SYMPOSIUM ON APPLIED ELECTROMAGNETICS SAEM’18 / Seme, Sebastijan ; Hadžiselimović, Miralem ; Štumberger, Bojan (ur.).
Maribor: University of Maribor Press, 2018. str. 17-18 doi:10.18690/978-961-286-171-1 (predavanje, međunarodna recenzija, prosireni, znanstveni)


Naslov
OPTIMIZATION BY EVOLUTIONARY ALGORITHM AND FEM TOOLS: EXAMPLE ON SWITCHED RELUCTANCE MOTOR

Autori
Barukčić, Marinko ; Hederić, Željko ; Benšić, Tin ; Ćorluka, Venco

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prosireni, znanstveni

Izvornik
Digest book of the 7th SYMPOSIUM ON APPLIED ELECTROMAGNETICS SAEM’18 / Seme, Sebastijan ; Hadžiselimović, Miralem ; Štumberger, Bojan - Maribor : University of Maribor Press, 2018, 17-18

ISBN
978-961-286-171-1

Skup
7th SYMPOSIUM ON APPLIED ELECTROMAGNETICS SAEM’18

Mjesto i datum
Podčetrtek, Slovenija, 17-20.06.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Evolutionary optimization, cosimulation, FEM, SRM

Sažetak
The application of the numerical mathematic calculation makes possible to solve very complex mathematical device models. This make able to use less neglecting and approximations in the device model which leads more realistic modelling of the devices. In case of the electrical machines the calculation of the electromagnetic fields based on Finite Element Method (FEM) is usually used for this purpose. Using FEM numerical method for simulation of the switched reluctance motor (SRM) calculations with higher accuracy can be obtained. The examples of the optimization of the SRM design can be found in [1], [2]. Thera are simulation tools for FEM simulation of the electromagnetic fields can be used for simulation of SRM. Using such simulation tools in optimization process of the SRM design required black–box optimization approach. Because of this, the optimization method can handle with black–box optimization need to be used in this case. The Evolutionary Algorithms (EA) are used here because they belong to class of global optimizer. Global optimizer no need additional information about the objective function but only the numerical function values. There are the evolutionary optimization tools as standalone tool also.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

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