利用新能源汽车监测大数据分析里程焦虑

Lina Xia, Chuan Chen, Huanhuan Ren, Zejun Kang
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引用次数: 0

摘要

续驶里程不足引起的里程焦虑是影响消费者购买纯电动汽车意愿的重要因素之一。目前,对里程焦虑的研究多依赖于问卷调查,分析结果具有主观性。为了提高里程焦虑分析的准确性,提高新能源汽车的普及率,我们提出了一种基于新能源汽车监测大数据的分析方法。该方法利用充电行为和驾驶行为两个维度的数据,从充电紧迫性和里程信任两个方面分析里程焦虑。结果客观可靠。分析结果表明,受环境温度和空调耗电量的影响,里程焦虑呈季节性波动趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of range anxiety using NEV monitoring big data
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.
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