同济大学学报（自然科学版）2021，Vol.49Issue(z1)：186-193,8.DOI:10.11908/j.issn.0253-374x.22735
基于机器学习的车队数据分析
Analysis of Fleet Data Using Machine Learning Methods
EBEL André 1RIEMER Thomas 1REUSS Hans-Christian2
作者信息
- 1. Research Institute of Automotive Engineering and Vehicle Engines Stuttgart(FKFS),斯图加特70569,德国
- 2. Institute of Automotive Engineering(IFS),University of Stuttgart,斯图加特70569,德国
- 折叠
摘要
Abstract
To enhance the functions and improve the safety of the new generation of vehicles, this paper collected abundant history data of vehicles and then created a rule-based model by using machine learning methods,so as to detect the faulty vehicle in a fleet. Several steps were designed for detailed illustration,and the validation of the method was conducted through electrical fault of the LV (lithium-cobalt) battery. The results can be used as input for the test bench tests of the following vehicle generations.关键词
车队数据/机器学习/规则学习/测试条件Key words
fleet data/machine learning/rule learning/test conditions分类
交通工程引用本文复制引用
EBEL André,RIEMER Thomas,REUSS Hans-Christian..基于机器学习的车队数据分析[J].同济大学学报（自然科学版）,2021,49(z1):186-193,8.
