.png){kind=icon}
返回
Induction Machine Parameter Range Constraints in Genetic Algorithm Based Efficiency Estimation Techniques
.png){kind=icon}
PRE
AI
DOI：10.1109/TIA.2018.2836344.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Estimation of induction machine parameters, which are commonly used in efficiency evaluation and control methods, can be effectively achieved by utilizing genetic algorithms (GAs). One of the difficulties of using GAs for efficiency estimation is the determination of variable (parameter) constraints (ranges). This paper focuses on the range determination of the parameters (variables) for GA applications. A wide range of variables can cause unstable outcomes. Hence, it is essential to determine an acceptable range for each variable prior to a GA run to produce stable and repeatable results. In this paper, relationships based on the nameplate information and a large database of tested induction motors provided by Hydro-Quebec are proposed to determine reasonable induction motor parameter ranges. The proposed method is applied to three different cases. The results of the three cases are compared to each other and also against the corresponding experimental results, which validate the effectiveness and accuracy of the proposed method.
Keyword:
Efficiency estimation
genetic algorithm (GA)
Hydro-Quebec
induction machine (IM)
parameter estimation
parameter range
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
IF:
4.5
论文数:
1.1W
被引数:
3.5W
机构
引用论文
.png){kind=icon}
An In Situ Efficiency Estimation Technique for Induction Machines Working With Unbalanced Supplies
PREAI
分享收藏
查看更多内容