Power Inductor Optimization Using Non-linear Magnetization Characteristics

被引：1

作者：

Gareau, Jacob ^{[1
]}

Emadi, Ali ^{[1
]}

Bilgin, Berker ^{[1
]}

机构：

[1] McMaster Univ, Elect & Comp Engn Dept, Hamilton, ON, Canada

来源：

2020 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE & EXPO (ITEC) | 2020年

基金：

加拿大自然科学与工程研究理事会;

关键词：

Genetic algorithm; ferrite core; iron powder core; non-linear magnetization curve; optimization; power inductors;

D O I：

10.1109/itec48692.2020.9161550

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The inductor design plays a significant role within the power converter design as it is a major contributor to the overall size, weight, and power loss of the system. Optimal design of an inductor through iterative approaches can prove to be challenging because of the parameter inter-dependence. This paper discusses the design of power inductors through the use of the Genetic Algorithm (GA) including the non-linear magnetization characteristics of the core material. The inductor design is suitable for high power electric vehicle and hybrid electric vehicle applications. The optimization evaluates iron powder cores and ferrite cores for operation in a bi-directional boost converter rated at 60 kW. The evaluation show the potential benefit of non-linear designs by considering various frequencies and number of interleaved phases.

引用

页码：992 / 999

页数：8

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