A novel energy consumption prediction model with combination of road information and driving style of BEVs

Abstract

There is evidence that battery electric vehicles (BEVs) suffer criticism with respect to the short driving range and unprecise remaining range prediction, accordingly, a novel energy consumption prediction method for BEVs based on road information and driving style optimization is proposed in this paper. The crucial role of road information, as the considerable influence on energy consumption, has to be obtained by OSM (Open Street Map) and SRTM (Shuttle Radar Topography Mission), allowing for the further combination of energy consumption model building. In an effort to overcome velocity prediction, a driving cycle prediction model relied on a linear prediction approach is built. The modeling proposed can further to give the basis for remaining range prediction and route planning which can be regarded as a tool to assist drivers in decision making. In general, it conclusively exhibits acceptable performance with error within 5%, which is sufficiently robust to be applied to energy consumption prediction.