摘要
基于车联网T-BOX采集的用户大数据,采用短行程分析法,关联驾驶特性及电驱动系统的特性构建出工况特征参数,采用主成分分析法对特征参数降维,利用K-Means聚类出5类不同典型的工况。结合驱动系统轴系损伤及线性损伤理论,选出具有代表性的短行程,构建新的可靠性工况载荷谱。
Based on the user big data collected by the Internet of vehicles T-box,the working condition characteristic parameters are constructed by using the short travel analysis method and associating the driving characteristics and the characteristics of the electric drive system.The dimension of the characteristic parameters is reduced by using the principal component analysis method,and five different typical working conditions are clustered by K-means.Combined with the shafting damage and linear damage theory of the drive system,the representative short stroke is selected and a new reliability working condition load spectrum is constructed.
作者
钟根丁
程小强
龚春辉
ZHONG Gending;CHEN Xiaoqiang;GONG Chunhui(Product research and Development Institute Jiangling Motors.Co.,Ltd.,Jiangxi Nanchang 330000)
出处
《汽车实用技术》
2021年第22期129-131,共3页
Automobile Applied Technology
关键词
大数据
可靠性
聚类分析
Big data
Reliability
Cluster analysis
