农机使用与维修Issue(6)：95-99,5.DOI:10.14031/j.cnki.njwx.2026.06.022
新能源汽车故障诊断系统设计与优化
Design and optimization of fault diagnosis system for new energy vehicles
周盛祥1
作者信息
- 1. 江苏省东海中等专业学校,江苏 东海 222300
- 折叠
摘要
Abstract
In response to the problem of fault diagnosis in the operation of new energy vehicles,this paper collects real-time vehicle operation data based on the on-board CAN bus.After completing signal preprocessing and feature extrac-tion,a multi-source data fusion model is constructed,and combined with convolutional neural networks(CNN)and long short-term memory networks(LSTM),effective recognition of complex temporal features is achieved.The simula-tion analysis and real vehicle verification results show that the designed diagnostic system exhibits high recognition ability in various typical fault scenarios such as overheating of power batteries,insulation faults,and abnormal vibration of drive motors,with an overall accuracy rate of 96.8%.The research results indicate that the system can provide reliable tech-nical support for the intelligent operation and security of new energy vehicles,and also lay the foundation for future re-search on remote fault warning and health management based on cloud platforms.关键词
新能源汽车/故障诊断/深度学习/数据融合/系统优化Key words
new energy vehicles/fault diagnosis/deep learning/data fusion/system optimization分类
交通工程引用本文复制引用
周盛祥..新能源汽车故障诊断系统设计与优化[J].农机使用与维修,2026,(6):95-99,5.
