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하이브리드자동차 장기간 주행데이터 분석Long-term Driving Data Analysis of Hybrid Electric Vehicle

Other Titles
Long-term Driving Data Analysis of Hybrid Electric Vehicle
Authors
우지영양인범
Issue Date
2018
Publisher
한국컴퓨터정보학회
Keywords
Hybrid electric vehicle; OBD-II; Driving data; Mileage; Machine learning
Citation
한국컴퓨터정보학회논문지, v.23, no.3, pp.63 - 70
Journal Title
한국컴퓨터정보학회논문지
Volume
23
Number
3
Start Page
63
End Page
70
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/6715
DOI
10.9708/jksci.2018.23.03.063
ISSN
1598-849X
Abstract
In this work, we analyze the relationship between the accumulated mileage of hybrid electric vehicle(HEV) and the data provided from vehicle parts. Data were collected while traveling over 70,000 Km in various paths. The data collected in seconds are aggregated for 10 minutes and characterized in terms of centrality, variability, normality, and so on. We examined whether the statistical properties of vehicle parts are different for each cumulative mileage interval of a hybrid car. When the cumulative mileage interval is categorized into =< 30,000, <= 50,000, and >50,000, the statistical properties are classified by the mileage interval as 82.3% accuracy. This indicates that if the data of the vehicle parts is collected by operating the hybrid vehicle for 10 minutes, the cumulative mileage interval of the vehicle can be estimated. This makes it possible to detect the abnormality of the vehicle part relative to the accumulated mileage. It can be used to detect abnormal aging of vehicle parts and to inform maintenance necessity.
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SCH Media Labs > Department of Smart Automobile > 1. Journal Articles
SCH Media Labs > Department of Big Data Engineering > 1. Journal Articles

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