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Magnetic Material Model Optimization and Characterization Software

Magnetic Material Model Optimization and Characterization Software
Magnetic Material Model Optimization and Characterization Software
The accurate characterization and modeling of magnetic materials are critical in simulating the performance analysis of electrical circuits incorporating magnetic components. Software has therefore been developed including genetic algorithm optimization techniques and metric based goal functions to enable appropriate accuracy in the final model. Multiple loop optimization has been developed to allow a wide range of operating conditions to be used in the goal function, with appropriate weighting for the ultimate application. Sensitivity and Monte Carlo analyses ensure the models are stable and tolerant of parameter variations. Comparisons of simulated BH curves with measured results demonstrate the capability of the software.
Wilson, Peter R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Ross, J. Neil
7099831f-3f8e-41b1-8d02-f6bd1cdf4f2f
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Wilson, Peter R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Ross, J. Neil
7099831f-3f8e-41b1-8d02-f6bd1cdf4f2f
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0

Wilson, Peter R., Ross, J. Neil and Brown, Andrew D. (2001) Magnetic Material Model Optimization and Characterization Software. Compumag, Evian.

Record type: Conference or Workshop Item (Paper)

Abstract

The accurate characterization and modeling of magnetic materials are critical in simulating the performance analysis of electrical circuits incorporating magnetic components. Software has therefore been developed including genetic algorithm optimization techniques and metric based goal functions to enable appropriate accuracy in the final model. Multiple loop optimization has been developed to allow a wide range of operating conditions to be used in the goal function, with appropriate weighting for the ultimate application. Sensitivity and Monte Carlo analyses ensure the models are stable and tolerant of parameter variations. Comparisons of simulated BH curves with measured results demonstrate the capability of the software.

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More information

Published date: July 2001
Additional Information: Event Dates: June 2001 Organisation: IEEE
Venue - Dates: Compumag, Evian, 2001-05-31
Organisations: EEE

Identifiers

Local EPrints ID: 256618
URI: http://eprints.soton.ac.uk/id/eprint/256618
PURE UUID: fada5fe1-c5eb-492d-8386-51272fdba749

Catalogue record

Date deposited: 17 Jun 2002
Last modified: 10 Dec 2021 20:45

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Contributors

Author: Peter R. Wilson
Author: J. Neil Ross
Author: Andrew D. Brown

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