Next Article in Journal
Evaluation of PHEVs Fuel Efficiency and Cost Using Monte Carlo Analysis
Previous Article in Journal
EP Tender: Enabling to Drive 98% Electric, at the Same TCO and Convenience as 100% ICE
World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

Data Management for Geographically and Temporally Rich Plug-in Hybrid Vehicle “Big Data”

1
Department of Mechanical Engineering, Colorado State University, Fort Collins, CO, USA
2
Electric Power Research Institute, Palo Alto, CA, USA
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2016, 8(1), 293-304; https://doi.org/10.3390/wevj8010293
Published: 25 March 2016
PDF [755 KB, uploaded 14 May 2018]

Abstract

The Electric Power Research Institute (EPRI) and its project partners have developed some of the highest resolution and most complete Light- and Medium-Duty Plug-in Hybrid Electric Vehicle Truck operational data for Odyne and Via trucks. This data was collected through a CDMA / GMS transmitter plugged into the CAN communication bus of the fleet. This paper discusses the process of transforming these raw datasets into a scientific database of driving and charging events using data quality management, filtering, processing and decision support tool development. The result is a dataset with demonstrable utility for vehicle design, policy analysis, and operator feedback.
Keywords: PHEV (Plug in Hybrid Electric Vehicle); medium-duty; bucket truck; data acquisition; policy PHEV (Plug in Hybrid Electric Vehicle); medium-duty; bucket truck; data acquisition; policy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Vore, S.; Kosowski, M.; Wilkins, Z.; Bradley, T.H. Data Management for Geographically and Temporally Rich Plug-in Hybrid Vehicle “Big Data”. World Electr. Veh. J. 2016, 8, 293-304.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
World Electr. Veh. J. EISSN 2032-6653 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top