State of Charge Estimation Based on Adaptive Neuro-Fuzzy Inference System

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 toitby modifying the membershipfunction 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.

关键词： State of charge (SOC) Adaptive Neuro-Fuzzy Inference System (ANFIS) battery

作者: GUAN Jiansheng XU Wenjin ZHANG Abu

作者单位: Department of Automation Xiamen University Xiamen 361005, China

会议类型: 国际会议

会议名称: 第一届国际计算机新科技与教育学术会议(Proceedings of the First International Conference on Computer Science & Education ICCSE2006)

会议地点: 厦门

会议语种:英文

页码: 840-843

在线出版日期: 2006-07-27（万方平台首次上网日期，不代表论文的发表时间）