基于新能源高频大数据的驾驶行为与能耗分析

近年来,在新能源汽车示范推广和财政补贴的大背景下,我国新能源汽车产业快速发展。但与传统燃油车相比,新能源汽车的技术成熟度尚且不足,在研发、运行阶段仍存在诸多问题等待解决,其中能耗和续航问题的关注度尤为突出。本文基于车载终端采集到的新能源高频大数据,提取能够反映驾驶行为精细时空变化特征的特征参数集,采用主成分分析方法将特征参数集进行优化,利用K-means算法实现驾驶行为的自动分级,并分析了不同级别驾驶行为的能耗分布情况。分析结果表明,驾驶行为影响新能源汽车能耗水平,其中平稳驾驶对应的能耗较低,对新能源汽车产品升级和用户驾驶习惯优化具有一定的参考价值。

Driving behavior and energy consumption analysis based on NEV high-frequency big data

In recent years,under the background of NEV demonstration and fi nancial subsidies,NEV industry in China has developed rapidly.Compared with traditional fuel vehicles,the technological maturity of NEV is still insuffi cient,and there are still many problems waiting to be solved,among which energy consumption and endurance issues are particularly concerned.Based on the NEV high-frequency big data collected by the vehicle terminal,this paper extracts the feature parameters that can refl ect the spatiotemporal changes of driving behavior,optimizes the feature parameter set using the principal component analysis method,and realizes automatic classifi cation of driving behavior by the K-means algorithm,and analyzes the energy consumption of diff erent of driving behaviors.The analysis result of this article shows that driving behavior aff ects the energy consumption of NEV,and stable driving behavior can reduce energy consumption.The analysis result has certain reference value for NEV product upgrades and driving behavior optimization.