Genetic optimization of a fuzzy system for charging batteries

被引：62

作者：

Surmann, H

机构：

[1] German National Research Center for Information Technology

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 1996年 / 43卷 / 05期

关键词：

genetic algorithm; fuzzy rule-based systems; high current battery charger; fuzzy rule-based entropy;

D O I：

10.1109/41.538611

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A large variety of nickel cadmium (NiCd) batteries have been developed to meet a wide range of user needs, ranging from low-current-level uses like emergency power sources for semiconductor memories to very high-power applications such as motor-operated cordless drills, This paper presents a genetic algorithm approach to optimize a fuzzy rule-based system for charging high-power NiCd batteries, For the optimization of the fuzzy system a special objective function is developed which is based on the entropy of a fuzzy system, The resulting fuzzy system is able to charge high-power NiCd batteries in about 10 min with a current of 6 A.

引用

页码：541 / 548

页数：8