EE-Navi: Energy-Efficient Navigation Service for Electric Vehicle

With the increasing tension of global energy and the situation of worsening ecological environment, the development of electric vehicle, especially efficiency, has become the focus of automobile industries in various countries. However, there is still no energy-efficient navigation service available due to lack of data support. In this paper, we develop a navigation service, called EE-Navi, that finds the most energy-efficient route of electric vehicle. A service framework is designed to map energy consumption of electric vehicles on city streets using driving dataset of electric vehicles and map data so that users find the most energy-efficient route between any two endpoints. The most energy-efficient route does not always coincide with the shortest and fastest routes, which is closely related to road conditions. We collected electric vehicles driving dataset in a Chinese city, Xi'an. The dataset includes more than 30,000 electric vehicles with a data volume of 1TB. We adopted a novel method of power consumption prediction to derive the energy consumption regression model directly from the physical model, which is more professional. If the most energy-saving route recommended by the EE-Navi service is used, an average 7% savings in energy is achieved from the experiment.