A model-based eco-routing strategy for electric vehicles in large urban networks

Abstract : A novel eco-routing navigation strategy and energy consumption modeling approach for electric vehicles are presented in this work. Speed fluctuations and road network infrastructure have a large impact on vehicular energy consumption. Neglecting these effects may lead to large errors in eco-routing navigation, which could trivially select the route with the lowest average speed. We propose an energy consumption model that considers both accelerations and impact of the road infrastructure, also separating the costs of all the possible turning movements in the transportation network by means of the adjoint graph. The approach makes use of only aggregated data available from existing map services. We demonstrate that the proposed strategy is more effective and reliable than the existing approaches in predicting vehicle energy consumption and in suggesting an energy-efficient route.
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Communication dans un congrès
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Nov 2016, Rio de Janeiro, Brazil. 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp.2301 - 2306, 2016, 〈10.1109/ITSC.2016.7795927〉
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Giovanni De Nunzio, Laurent Thibault, Antonio Sciarretta. A model-based eco-routing strategy for electric vehicles in large urban networks. 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Nov 2016, Rio de Janeiro, Brazil. 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp.2301 - 2306, 2016, 〈10.1109/ITSC.2016.7795927〉. 〈hal-01515215〉

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