基于大数据的电动汽车用户行为对电池老化影响分析

Analysis on the Effects of User Behavior on Battery Aging of Electric Vehicles Based on Big Data

为探究用户的行为习惯对电动汽车电池老化的影响,本文基于大数据的统计分析方法,依托企业监管平台大量高品质的用户和车辆数据,开展了用户车辆所在地域、用户的充电方式偏好和驾驶风格对电池老化的影响规律研究。结果表明:随着电池平均运行温度的升高,电池容量衰减呈先减后增的趋势;北京用户的电池老化程度比广东用户整体高10.59%~19.09%;随着快充频率的升高,电池的容量衰减率呈逐渐增大的趋势,但增大的速率逐渐减小;偏好快充充电的用户车辆的电池老化比偏好慢充充电的用户快33.45%~56.24%;激进的驾驶模式会加剧电池老化,整体比温和型的驾驶模式快1.73%~10.37%。研究成果对车企优化整车功能设计,指导用户健康行车具有借鉴意义。

In order to explore the influence of users′ behaviors on the battery aging of electric vehicles,a statistical analysis method based on big data is proposed to study the influence of the region user′s vehicle located,the charging mode preference and driving style of users on battery aging,relying on a large number of high-quality user and vehicle data on the enterprise supervision platform. The results show that with the increase of the average operating temperature of battery,the attenuation of battery capacity reduces first and then increases. The battery aging degree of Beijing users is 10.59%~19.09% higher than that of Guangdong users. With the rise of fast charging frequency,the attenuation rate of battery capacity gradually increases,but with the increasing rate declining. The battery aging of the user preferring fast charging is 33.45%~56.24% faster than that of users preferring slow charging. Aggressive driving mode may accelerate battery aging,with an aging rate 1.73%~10.37% faster than gentle driving mode. The research results have reference significance for vehicle enterprises to optimize vehicle function design and guide the users to drive healthily.