DocumentCode
3671619
Title
Intelligent energy consumption estimation for electric vehicles: Business processes and services
Author
Vasileios Asthenopoulos;Pavlos Kosmides;Evgenia Adamopoulou;Konstantinos Demestichas
Author_Institution
Institute of Communication and Computer Systems - ICCS, National Technical University of Athens, Zografou-Athens, Greece
fYear
2014
Firstpage
293
Lastpage
298
Abstract
Nowadays, Fully Electric Vehicles are in the spotlight of energy-efficient and sustainable mobility. Their overall efficiency however, as well as their commercial viability, depend strongly on the degree of confidence they offer to the driver in terms of energy savings and range characteristics. To this end, advanced consumption prediction mechanisms must be implemented in order to enable the provision of energy-based routing functionalities. In this context, this paper presents an innovative energy consumption estimation service that relies on the vehicles´ travelling history and experience and deploys machine learning mechanisms in order to obtain accurate, robust and cost-efficient estimations.
Keywords
"Training","Databases","Maximum likelihood estimation","Engines","Roads","Energy consumption"
Publisher
ieee
Conference_Titel
Connected Vehicles and Expo (ICCVE), 2014 International Conference on
Type
conf
DOI
10.1109/ICCVE.2014.7297559
Filename
7297559
Link To Document