Big Data Analytics: How Big Data is Shaping Our Understanding of Electrified Vehicle Customers

Paper #:
  • 2017-01-0247

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-0247
Citation:
Ahmed, N. and Kapadia, J., "Big Data Analytics: How Big Data is Shaping Our Understanding of Electrified Vehicle Customers," SAE Int. J. Mater. Manf. 10(3):351-359, 2017, https://doi.org/10.4271/2017-01-0247.
Pages:
9
Abstract:
Electrified vehicles including Battery Electric Vehicles (BEVs) and Plug-In Hybrid Vehicles (PHEVs) made by Ford Motor Company are fitted with a telematics modem to provide customers with the means to communicate with their vehicles and, at the same time, receive insight on their vehicle usage. These services are provided through the “MyFordMobile” website and phone applications, simultaneously collecting information from the vehicle for different event triggers. In this work, we study this data by using Big Data Methodologies including a Hadoop Database for storing data and HiveQL, Pig Latin and Python scripts to perform analytics. We present electrified vehicle customer behaviors including geographical distribution, trip distances, and daily distances and compare these to the Atlanta Regional Survey data. We discuss customer behaviors pertinent to electrified vehicles including charger types used, charging occurrence, charger plug-in times etc. Throughout this discussion, we highlight the process of extracting information from this data that can be used to further refine future design. Customer data privacy concerns are also addressed, with no analysis using any personally identifiable information.
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