Investigating Real-World Energy Consumption of Electric Vehicles: A Case Study of Shanghai

Abstract

The deployment of Battery Electric Vehicle (BEVs) has been viewed as a way to significantly reduce oil dependence, and bring about environmental and economic benefits. This study makes use of a rich database collected from 50 BEVs (i.e. Roewe E50) from Shanghai, China. We first examine BEV owners’ travel patterns with the vehicle usage data. Four factors, i.e., trip distance, speed, initial SOC, and ambient temperature, are analyzed to detect their impacts on energy consumption. Since energy consumption along a route are in part related to driving behavior, traffic conditions and infrastructure design, three routes embedded in sufficient vehicle in-use data are selected as the test objects. Each of them has a record that one particular driver traveling more than 20 times along the route. A multivariate linear regression (MLR) model is built up to estimate the trip energy consumption. The proposed method for analyzing the vehicle usage data to estimate energy consumption along routes can be used for research with larger fleets of BEVs in the future.