State of charge estimation based on adaptive neuro-fuzzy inference system

被引：0

作者：

Guan Jiansheng ^{[1
]}

Xu Wenjin ^{[1
]}

Zhang Abu ^{[1
]}

机构：

[1] Xiamen Univ, Dept Automat, Xiamen 361005, Peoples R China

来源：

ICCSE'2006: Proceedings of the First International Conference on Computer Science & Education: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION | 2006年

关键词：

state of charge (SOC); Adaptive Neuro-Fuzzy Inference System (ANFIS); battery;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we describe a method to estimate state of charge using an adaptive neuro-fuzzy inference system (ANFIS). Using a given input/output battery data set we obtain a fuzzy inference system (FIS) whose membership function parameters are tuned using an optimization algorithm. This allows fuzzy system to learn from the data he is modelling. That is, we use ANFIS to train a FIS model to emulate the data presented to it by modifying the membership function parameters according to a chosen error criterion. Input variables include the AC resistance, the DC internal resistance and the load voltage in battery management system. SOC are the output.

引用

页码：840 / 843

页数：4

共 6 条

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