Abstract

In this work, the relationship between the accumulated mileage of a hybrid electric vehicle (HEV) and the data provided from vehicle parts has been analyzed. Data were collected while traveling over 70,000 km in various paths. The collected data were aggregated for 10 min and characterized in terms of centrality and variability. It has been examined whether the statistical properties of vehicle parts are different for each cumulative mileage interval. When the cumulative mileage interval is categorized into 30,000–50,000, 50,000–60,000, and 60,000–70,000, the statistical properties contributed in classifying the mileage interval with accuracy of 92.68%, 82.58%, and 80.65%, respectively. This indicates that if the data of the vehicle parts are collected by operating the HEV for 10 min, the cumulative mileage interval of the vehicle can be estimated. This makes it possible to detect abnormality or characteristics change in the vehicle parts relative to the accumulated mileage. It also can be used to detect abnormal aging of vehicle parts and to inform maintenance necessity. Furthermore, a part or module that has a significant change in characteristics according to the mileage interval has been identified.

Highlights

  • There has been continuous development and distribution of high-performance electric vehicles, including smart cars featured with artificial intelligence and partial self-driving functions

  • We visualized the characteristics of the statistical values for voltage (VB), current (IB), temperature (Temp. of Batt.), and state of charge (SOC) of the battery, which are the main parts of a hybrid car

  • The results indicate that the characteristics of vehicle parts that significantly change depend on the mileage interval

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Summary

Introduction

There has been continuous development and distribution of high-performance electric vehicles, including smart cars featured with artificial intelligence and partial self-driving functions These are based on innovative technologies in various fields, such as semiconductor and information communication technology. A sharing economy represents these changes, and new business models must be developed in new vehicle-sharing systems in large cities These changes will continue to be incorporated in innovations in the automotive industry, related upstream or downstream industry, and automobile culture in the future. The scope of innovation in the automotive industry will be expanded to cars owned by corporates as well as those owned by individuals It will include an effective and safe maintenance and management system so that periodic maintenance and post-repair management will be transformed into preventative maintenance and predictive management. Techniques such as condition-based maintenance (CBM) and prognostic health monitoring (PHM) are being gradually applied to the automotive industry

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