基于云端大数据的电动汽车低温续驶里程工况构建

Construction of Low Temperature Driving Range of Electric Vehicles Based on Cloud Big Data

为了构建电动汽车的低温续驶里程工况,利用用户自然场景中电动汽车的T-BOX云端大数据平台,应用主成分分析选取了速度相关参数,通过聚类分析方法获取了低速、中速和高速的运动学片段,对比了电动汽车在常温和低温下的行驶速度差异,根据概率密度计算结果建立了适用于低温试验的速度曲线,同时提取环境温度、空调等级与空调温度等维度的信息,分析了环境温度与空调设置的关系,得到适用于低温试验的环境温度和空调设置信息。结果表明,低温与常温相比,电动汽车低速行驶时间延长了3%,中速和高速的行驶时间分别降低了2%和1%,并且环境温度截止至-22℃,空调等级设置为3级,空调温度设置为26℃可以代表大多数用户的使用场景,最终构建了更加贴近用户实际的电动汽车低温续驶里程工况。

In order to build low-temperature driving range conditions for electric vehicles,this paper utilizes the TBOX cloud based big data platform for electric vehicles in natural user scenarios,selects speed-related parameters by application principal component analysis,obtaining kinematic fragments of low-speed,medium-speed and high-speed through cluster analysis methods,compares the difference in travel speed of trams at normal temperature and low temperature,establishes a speed curve suitable for low temperature test according to the probability density calculation results,and simultaneously extracts the information of ambient temperature,air conditioning grade and air conditioning temperature.The relationship between ambient temperature and air conditioning setting is analyzed,the ambient temperature and air conditioning setting information suitable for low temperature test are obtained.The results show that compared with normal temperature,the low-speed driving time is extended by 3%,the medium-speed and high-speed driving time are reduced by 2%and 1%respectively,and the ambient temperature setting to-22℃,the air conditioning level setting to 3,and the air conditioning temperature setting to 26℃can represent the using scenarios of most users,finally building a low temperature driving rangeworking condition of electric vehicles which is closer to the user’s actual situation.