Driver and Traffic Impact on Battery Electric Vehicle Driving Range

Abstract

The energy consumption and driving range of a Battery Electric Vehicle (BEV) is determined from tests on a chassis dynamometer under standardized conditions. However, when a customer is driving his/her car on the road, the energy consumption and range may be significantly different due to many factors, such as driving style, ambient conditions, road, traffic, etc. The aim of the thesis work is to develop a method for analyzing the impact of various traffic situations, and driver behavior on electric vehicle’s driving range. In order to capture real world traffic situation and driver behaviour, a virtual road network of rural, urban and motorway road segment picked from CEVT defined real world driving route was created in SUMO. Driving cycle obtained from traffic simulation in SUMO were fed manually to CEVT built vehicle model in CarMaker. Post process script was written in Python to extract the result for the simulation. A new method to capture the effect of traffic and driver behaviour was implemented and it was found that mainly traffic situations and driver behavior had impact on energy consumption and range of BEV.