An Innovative Method For Route Mapping of Battery Electric Vehicles

Route mapping is a useful method to save time for drivers, but for electric vehicles (EVs), electrical energy saving should also be considered. In this paper, a novel approach to the route mapping of battery electric vehicles (BEVs) is proposed. The objective of this approach is to simultaneously optimize the total electrical energy consumption and travel time of the BEVs driving on a path. Four factors (vehicle speed, road grade, ambient temperature, and wind speed) are considered for the electrical energy management of BEVs. An artificial neural network (ANN) is used to correct the real-time speed data. Evaluation of the proposed approach is performed on a large part of Kowloon city and is implemented by MATLAB. It was found that using this approach, reduces the total electrical energy consumption and travel time of BEVs, as well as improving their lifespan.