A method for the prediction of future driving conditions and for the energy management optimisation of a hybrid electric vehicle. (19th June 2012)

• Record Type: Journal Article
• Authors: Donateo, Teresa; Pacella, Damiano; Laforgia, Domenico
• Is Part Of: International journal of vehicle design. Volume 58:Number 2/3/4(2011)
• Page Start: 111
• Page End: 133
• Publication Date: 2012-06-19
• Subjects: hybrid electric vehicles -- ecological vehicles -- plug–in HEVs -- energy management strategy -- vehicular communications -- traffic simulation -- simulation based prediction -- genetic algorithms -- clustering algorithms -- K–Means algorithm -- vehicle design; Motor vehicles -- Design and construction -- Periodicals; 629.231
• Languages: English
• ISSNs: 0143-3369

Abstract

Vehicular communications are expected to enable the development of Intelligent Cooperative Systems for solving crucial problems related to mobility: road safety, traffic management etc. Information and Communication Technologies could also play an important role in order to optimise the energy management of conventional, hybrid and electrical vehicles and, thus, to reduce their environment impact. In particular, vehicular communications could be used to predict driving conditions with the objective to determine future load power demand. An adaptive energy management strategy for series Hybrid Electric Vehicles (HEVs) based on genetic algorithm optimised maps and the Simulation of Urban Mobility (SUMO) predictor is presented here.