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On the Use of Vehicular Communications for Efficient Energy Management of Hybrid Electric Vehicles
FISITA2010/F2010E047

Authors

Ciccarese Giovanni - Computer Networks Laboratory, Department of Innovation Engineering, University of Salento, Lecce, Italy
Donateo Teresa - CREA, Energy and Environment Research Center, Department of Innovation Engineering, University of Salento, Lecce, Italy
Marra Pierluig - Computer Networks Laboratory, Department of Innovation Engineering, University of Salento, Lecce, Italy
Pacella Damiano - CREA, Energy and Environment Research Center, Department of Innovation Engineering,University of Salento, Lecce, Italy
Palazzo Cosimo* - Computer Networks Laboratory, Department of Innovation Engineering, University of Salento, Lecce, Italy

Abstract

ABSTRACT – Vehicular communications are expected to enable the development of Intelligent Cooperative Systems to be exploited for solving crucial problems related to mobility: road safety, traffic management, energy saving. In this paper, the use of vehicular communications for the energy management of a Hybrid Electric Vehicle (HEV) is presented. The supervisory controller of a HEV should select the power split appropriately at any time in order to optimize the energy management. To this, it could base the control strategy on the future driving profile (speed and related power demand) and try to estimate the last by processing the status information broadcasted by surrounding vehicles (position, speed, acceleration, etc.) and by the infrastructure (i.e. the current status of traffic lights). A simulation tool has been developed with the objective to validate the proposed approach. It consists of a number of components, that are a traffic simulator, a network simulator, a predictor of the future speed profile, a powertrain simulator and an optimizer. A local instance of the traffic simulator (SUMO) running on board of the HEV has been conceived as a predictor. The accuracy of the predictor has been evaluated by considering a number of vehicles moving on the road network of the Ecotekne campus at the University of Salento and by comparing the actual speed profile of a test HEV with that predicted on board. Simulation results have shown that the prediction error, in terms of the root mean square, is quite low and, particularly, its maximum value is about 4 km/h for a horizon duration equal to 60 s.

KEYWORDS – Vehicular communications, energy management, Hybrid Electric Vehicles, traffic simulation, simulation-based prediction

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