Analysis of Fleet Data Using Machine Learning Methods

被引：0
|
作者：
Ebel, André [1 ]
Riemer, Thomas [1 ]
Reuss, Hans-Christian [2 ]
机构：
[1] Research Institute of Automotive Engineering and Vehicle Engines Stuttgart（FKFS）, Stuttgart,70569, Germany
[2] Institute of Automotive Engineering（IFS）, University of Stuttgart, Stuttgart,70569, Germany
来源：
Tongji Daxue Xuebao/Journal of Tongji University | 2021年 / 49卷
关键词：
D O I：
10.11908/j.issn.0253-374x.22735
中图分类号：
学科分类号：
摘要：
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. © 2021 Science Press. All rights reserved.
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页码：186 / 193
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