arrow
返回

Multi-Objective Optimization of Multi-Level DC-DC Converters Using Geometric Programming

delete2019-12-01
delete45
PRE
AI
A
Andrija Stupar *
T
Timothy McRae
N
Nenad Vukadinovic
A
Aleksandar Prodić
J
Josh A. Taylor
DOI:10.1109/TPEL.2019.2908826delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Multi-objective optimization of power converters is a time-consuming task, especially when multiple operating points and multiple converter topologies must be considered. As a result, various steps are often taken to simplify the design problem and restrict the size of the design space prior to going through an optimization procedure. While this saves time, it produces potentially sub-optimal designs, and existing approaches must tradeoff between running time and design optimality. This paper presents an optimization-oriented method for modeling power converters and their components as posynomial functions, allowing multi-objective optimization of converters to be formulated as a geometric program, a type of convex optimization problem. This allows the use of fast, powerful solvers that guarantee global optimality of solutions. The method is demonstrated using the example of low-power multi-level flying capacitor step-down converters. Results show that, using geometric programming, sets of globally Pareto-optimal designs of two-, three-, and four-level converters with respect to efficiency and power density, for one design space and one operating point, can be generated in as little as 25 s, on a mid-to upper range laptop computer. Thus, optimal designs for three different converter topologies for hundreds of different operating points and/or design spaces can he generated in several hours-less than the time required to globally optimize one converter topology at one operating point for one design space using currently prevalent methods. This paper also demonstrates how geometric programming can be used to quickly perform sensitivity and tradeoff analysis of optimal converter designs.
Keyword:
DC-DC power converters
pareto optimization
switching converters
power supplies
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Power Electronics 封面图
IEEE Transactions on Power Electronics
IF:
6.5
论文数:
1.7W
被引数:
8.3W

机构

U
university of toronto
学者数:
14.8W
论文数: 12.0W
被引数: 165
引用论文

引用论文

Disparities among Older Persons in China
err2017-01-30
err0
PREAI
errPeng Du; Asghar Zaidi; He Chen; Yan Gu
err分享
err收藏
Guideline for a Simplified Differential-Mode EMI Filter Design
err2010-03-01
err156
PREAI
errRaggl, Klaus; Nussbaumer, Thomas; Kolar, Johann W.
err分享
err收藏
Correlation of SF-36 and SF-12 Component Scores in Patients With Diabetic Foot Disease
err2016-07-01
err0
errOAAI
errDane K. Wukich; Tresa L. Sambenedetto; Natalie M. Mota; Natalie C. Suder; Bedda L. Rosario
err分享
err收藏
An Analytical Method to Evaluate and Design Hybrid Switched-Capacitor and Multilevel Converters
err2018-03-01
err134
PREAI
errLei, Yutian; Liu, Wen-Chuen; Pilawa-Podgurski, Robert Carl Nikolai
err分享
err收藏
Automated Design of a High-Power High-Frequency LCC Resonant Converter for Electrostatic Precipitators
err2013-11-01
err114
PREAI
errSoeiro, Thiago B.; Muehlethaler, Jonas; Linner, Jorgen; Ranstad, Per; Kolar, Johann W.
err分享
err收藏
Nano-sized ceria particles prepared by spray pyrolysis using polymeric precursor solution
err2006-02-01
err0
PREAI
errHee Sang Kang; Yun Chan Kang; Hye Young Koo; Seo Hee Ju; Do Youp Kim; Seung Kwon Hong; Jong Rak Sohn; Kyeong Youl Jung; Seung Bin Park
err分享
err收藏
err分享
err收藏
学者 查看更多内容