摘要
为构建成都市燃料电池公交车示范运行行驶工况,基于示范区内燃料电池公交车实际行驶数据,对预处理后的有效运行数据进行运动学片段划分,采用主成分分析法进行数据降维处理;利用肘部法则确定最佳聚类数目,使用K-means++算法对主成分进行聚类;以不同聚类所占比例和距中心点距离确定最优运动学片段。结果表明:构建出的行驶工况能够反映成都市燃料电池公交车示范区内交通行驶特征,且时长为1577 s;成都市燃料电池公交车示范运行行驶工况与中国城市客车行驶工况在某些特征参数上存在一些差异。此工况的建立为研制燃料电池公交车智能能量管理系统奠定了基础。
In order to construct the driving cycle of the demonstration operation of fuel cell buses in Chengdu,based on the actual driving data of the fuel cell buses in the demonstration area,the pre-processed effective operation data was divided into kinematics segments,and the principal component analysis method was used for data dimensionality reduction processing.The elbow rule was applied to determine the optimal number of clusters,and the K-means++algorithm was used to cluster the principal components.The optimal kinematics segments were determined based on the proportions of different clusters and the distance from the center point.The results showes that the constructed driving cycle reflects the driving characteristics of the traffic situation in the fuel cell bus demonstration zone in Chengdu and the driving cycle time is 1577 s;there are some differences in certain characteristic parameters between the driving cycle of fuel cell buses in Chengdu demonstration area and that of Chinese city buses.The above working lays the foundation for the development of an intelligent energy management system for fuel cell buses.
作者
金思含
彭忆强
武小花
韩震
JIN Sihan;PENG Yiqiang;WU Xiaohua;HAN Zhen(School of Automobile and Transportation,Xihua University,Chengdu 610039,China;Vehicle Measurement,Control and Safety Key Laboratory of Sichuan Province,Chengdu 610039,China;Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan,Chengdu 610039,China)
出处
《汽车安全与节能学报》
CAS
CSCD
北大核心
2022年第1期202-208,共7页
Journal of Automotive Safety and Energy
基金
四川省科技厅重大科技项目(2019ZDZX0002)
四川省区域创新合作项目(2020YFQ0037)
四川省重点研发计划项目(2021YFG0071)
成都科技项目(2019-RK00-00025-ZF,2019-YF08-00003-GX)。
