Gray-Box Identification and Optimization of Reactor Inductance

Analytical and numerical methods are widely used in the calculation of reactor inductance. However, it cannot meet the need of optimal design in terms of calculation accuracy and efficiency. An identifiable gray-box model for inductance calculation is established based on electromagnetic principles,...

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Bibliographic Details
Published in2022 IEEE 20th Biennial Conference on Electromagnetic Field Computation (CEFC) pp. 1 - 2
Main Authors Zhu, Dengfeng, Jin, Liang
Format Conference Proceeding
LanguageEnglish
Published IEEE 24.10.2022
Subjects
Computational modeling
Data models
Electromagnetic fields
Few data
gray-box model
Inductance
Inductors
Numerical models
Numerical simulation
parameter identification
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Summary:Analytical and numerical methods are widely used in the calculation of reactor inductance. However, it cannot meet the need of optimal design in terms of calculation accuracy and efficiency. An identifiable gray-box model for inductance calculation is established based on electromagnetic principles, and a sample data set of Inductance is generated by numerical simulation. The elite-retaining genetic algorithm is used to identify the parameters of the gray-box model, and the NSGA-III algorithm is utilized to perform the multi-objective optimization design of the reactor. After optimization, the quality and loss of the conductors are greatly reduced.
DOI:10.1109/CEFC55061.2022.9940845