摘要
为了有效地对电池剩余容量进行预测,在分析了与电池剩余电量相关因数的基础上,提出了基于模糊神经网络的电池剩余电量预测模型,充分利用了模型可逼近任何多输入输出参数函数的性能.系统通过样本训练达到了较好的仿真结果.从现场实验的数据分析,该模型能较准确地预测电池剩余电量,为电池管理系统提供了一种新的预测方法.
In order t factors influencing th neural network. The Simulated results and o predict the state of e SOC of batteries, model can approach experimental results charge （ the auth the nonproved t SOC） of batteries during discharge, by analyzing the or lin he proposed a predictive SOC model based on fuzzy ear function with many input/output parameters. advantages of the new method and the significance for battery manage system.
出处
《测试技术学报》
2007年第5期405-409,共5页
Journal of Test and Measurement Technology
基金
国家973重点基础研究计划资助项目(2002CB211803)
关键词
模糊神经网络
电池
SOC估计
fuzzy neural network
battery
the estimation of state of charge
