|本期目录/Table of Contents|

[1]陈少华,俞万能,朱永怀.全电游船锂电池组健康诊断平台[J].集美大学学报(自然科学版),2019,24(5):364-370.
 CHEN Shaohua,YU Wanneng,ZHU Yonghuai.Health Diagnosis Platform for Lithium Battery Pack of All Electric Power Cruise Ship[J].Journal of Jimei University,2019,24(5):364-370.
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《集美大学学报(自然科学版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第24卷
期数:
2019年第5期
页码:
364-370
栏目:
船舶与机械工程
出版日期:
2019-09-28

文章信息/Info

Title:
Health Diagnosis Platform for Lithium Battery Pack of All Electric Power Cruise Ship
作者:
陈少华1俞万能12朱永怀1
(1.集美大学轮机工程学院,福建 厦门 361021,2.福建省船舶与海洋工程重点实验室,福建 厦门 361021)
Author(s):
CHEN Shaohua1YU Wanneng12ZHU Yonghuai1
(1.School of Marine Engineering,Jimei University,Xiamen 361021,China;2.Fujian Province Key Laboratory of Naval Architecture and Marine Engineering,Xiamen 361021,China)
关键词:
全电游船锂电池组健康诊断云技术
Keywords:
all electric power cruise shiplithium battery packhealth diagnosiscloud technology
分类号:
-
DOI:
-
文献标志码:
A
摘要:
为了实时监测全电游船锂电池组的运行状态,基于阿里云服务器,采用Web浏览器、4G通信以及数据库管理等应用技术,建立基于模糊神经网络的锂电池组状态诊断模型。同时开发出集监视、通讯以及控制管理为一体的全电游船锂电池组的健康诊断平台,实现对锂电池组健康状态的自动化诊断。实船测试结果表明:平台运行稳定,对电池组的运行状况监测和健康状态诊断迅速准确,达到预期目标。
Abstract:
In order to diagnose the health status of the lithium battery pack of all-electric cruise ships,based on adopting alibaba cloud server,using the technology of web browser,4G communication and database management,establishing the state diagnosis model of lithium battery pack based on fuzzy neural network,a health diagnosis platform with detection,communication and control management functions was developed to achieve automatic diagnosis of the health status of the lithium battery pack.The test results show that the platform runs stably,and the monitoring of the battery running condition and the status diagnosis of the health condition are rapid and accurate,and the expected target is achieved.

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更新日期/Last Update: 2019-11-04