Title :
Traffic light assistant system for optimized energy consumption in an electric vehicle
Author :
Emre Kural;Stephen Jones;Alejandro Ferreira Parrilla;Anders Grauers
Author_Institution :
AVL Powertrain Engineering, AVL GmbH, Graz, Austria
Abstract :
Increasingly intelligent vehicle driving systems are rapidly being developed, and will in the future become a necessity for sustainable, convenient and safe mobility in our ever more urbanized world. This paper presents an innovative approach for the control of a fully electric vehicle approaching a road segment with Multiple Traffic Lights (TL). By utilizing Vehicle to Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, the energy consumption for the maneuver completion can be reduced. The problem is approached from a Model Predictive Control (MPC) framework. The performance of the system is evaluated using a complex simulation toolchain representing the vehicle, powertrain, driver, and road including the traffic conditions. The results have shown an overall energy consumption reduction of 29 % for an idealized case and 17 % for a real road simulated scenario as compared to `normal´ human driver behavior.
Keywords :
"Acceleration","Mechanical power transmission","Electric vehicles","Mathematical model","Optimization","Predictive models"
Conference_Titel :
Connected Vehicles and Expo (ICCVE), 2014 International Conference on
DOI :
10.1109/ICCVE.2014.7297619