No abstract

Real time traffic information systems like SYTAD1N[1l] help in route to destination planning and traffic state prediction. Energy-optimal routing for electric vehicles creates novel algorithmic challenges where the computation complexity is the main issue. This complexity is induced by the possible negative values of edge energy as well as the variability of route and vehicle variables which render the standard algorithms unsuitable (inapplicable). In this paper we present an Energy Optimal Real Time Navigation System (EORTNS), implemented on Samsung Galaxy Tab, capable of calculating the route to destination based on a information flow obtained from SYTADIN. As an application example we propose a real time energy management for a Hybrid Electrical Vehicle (HE V) composed of batteries and Super-Capacitors (SC). The EORTNS is not only capable of energy optimal route to destination calculation with respect to traffic state but also operates the On-Board power splitting between batteries and Super-Capacitors. Based on calculated 3D energy optimal route to destination and average speeds for each road segment as well as the vehicle model the state of charge (SOC) of batteries and Super-Capacitors for each receding horizon are predicted and modified in real time.