摘要
针对车辆能耗评价用城市行驶循环缺少弯道工况的问题,制定出了基于短行程分析的城市弯道行驶工况构建方法。采取优化后的数据处理方法获得准确的弯道工况数据并进行弯道片段分割;使用主成分分析法对实验数据进行压缩降维;使用K-均值聚类算法将所有的弯道片段分类以获得代表性弯道工况,依据相似度将代表性弯道片段添加进传统典型城市综合工况,从而获得带有弯道信息的城市复合行驶工况。结果表明,具有弯道工况信息的复合行驶工况比传统车辆循环工况更能体现车辆在城市中的实际行驶特征。
In view of the lack of the condition of driving on curve in urban driving cycle for the evaluation of vehicle energy consumption,a construction method of driving on curve condition in cities is formulated based on short trip analysis.The processing method of optimized data is used to obtain accurate curved road condition data with curved road divided into segments.Principal component analysis is used to compress the experimental data with its dimension lowered.Kmeans clustering algorithm is utilized to classify all the curved road segments for obtaining the representative driving on curve conditions and the representative curved road segments are added into the traditional typical urban comprehensive driving cycle based on the degree of similarity,so as to obtain an urban compound driving cycle covering curved road information.The results indicate that the urban compound driving cycle with the information of driving on curve condition can better embody the real driving characteristics of vehicles in cities than traditional vehicle driving cycle.
作者
孙文
荣浚材
王军年
徐佳
吕斯文
刘俐丽
Sun Wen;Rong Juncai;Wang Junnian;Xu Jia;Lü Siwen;Liu Lili(College of Automotive Engineering,Changzhou Institute of Technology,Changzhou 213001;Jilin University,State Key Laboratory of Automotive Simulation and Control,Changchun 130022)
出处
《汽车工程》
EI
CSCD
北大核心
2021年第10期1519-1527,共9页
Automotive Engineering
基金
国家自然科学基金面上项目(51875235)
江苏省高等学校自然科学研究面上项目(19KJB480006)资助。
关键词
车辆行驶工况
弯道工况
数据优化
主成分分析
K均值聚类
vehicle driving cycle
condition of driving on curve
data optimization
principal component analysis
Kmeans clustering
