Analysis of range anxiety using NEV monitoring big data

Abstract

Range anxiety caused by the insufficient driving range is one of the important factors that affect the willingness of consumers to buy battery electric vehicles. Currently, the research on range anxiety mostly relies on questionnaire surveys, and the analysis results are subjective. In order to improve the accuracy of range anxiety analysis and increase the penetration rate of new energy vehicles (NEV), we proposed a new analysis method based on NEV monitoring big data. This method uses data from two dimensions of charging behavior and driving behavior to analyze range anxiety from the aspects of charging urgency and range trust. The results are objective and highly reliable. The analysis results show that due to the influence of ambient temperature and air conditioner power consumption, range anxiety presents a seasonal fluctuation trend.