基于混沌神经网络的蓄电池寿命预测  

Research of Battery Life Prediction Based on Chaotic Neural Network

作　　者：王飞 符琦[1] 尚坤豪 崔力 巴冰 WANG Fei;FU Qi;SHANG Kunhao;CUI Li;BA Bing(School of Computer Science and Engineering,Hunan University of Science and Technology,Xiangtan 411201,China)

机构地区：[1]湖南科技大学计算机科学与工程学院,湖南湘潭411201

出　　处：《湖南科技大学学报（自然科学版）》2021年第2期81-84,共4页Journal of Hunan University of Science And Technology：Natural Science Edition

摘　　要：利用蓄电池对光伏系统进行供电,不可避免地会出现电压不稳等问题.而目前对蓄电池的管理主要依靠充放电实验和外观观察等技术手段,在蓄电池数量较多时,无法有效兼顾.如何科学有效地预测蓄电池寿命成为需要研究的重大课题.文章基于霍普菲尔德人工神经网络(CHNN)得到一种新的混沌神经网络模型,将它运用到光伏蓄电池的预测系统中,通过混沌神经网络图像与李雅普诺夫图像的对比实验,成功预测了蓄电池的寿命.The use of battery power supply to photovoltaic system will inevitably lead to voltage instability and other problems.At present,the management of battery mainly relies on technical means such as charge and discharge experiment and external observation.When there are a large number of batteries,it can not take into account effectively.How to predict the battery life scientifically and effectively had become a major issue to be studied.A new chaotic neural network model was gotten based on Hopfield artificial neural network(CHNN)and it was applied to the prediction system of photovoltaic battery.Through the comparative experiment of chaotic neural network image and Lyapunov image,a new chaotic neural network model was gotten.The life of the battery was predicted successfully.It is found that the chaotic neural network is of great significance for the life prediction of the battery.

关 键 词：混沌神经网络 李雅普诺夫指数 蓄电池寿命 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]