基于实车道路数据的插电式混合动力能耗敏感性分析

Sensitivity Analysis on Energy Consumption of PHEV Based on Real Vehicle Road Data

为评价插电式混合动力(PHEV)在实际行驶过程中的能耗水平,分析影响PHEV能耗水平的关键因素,本文中基于180人次的实车行驶记录数据,构建车辆行驶状态和驾驶员驾驶行为与PHEV整车综合能耗之间的相关关系。首先,利用主成分分析法,对行驶工况参数矩阵进行特征解耦,提取对整体信息累计贡献度达84%的5项主成分,并根据影响系数矩阵的数值分布对主成分进行指标定义。然后,基于运动学片段,利用K均值聚类算法对各主成分进行依次约束,从而形成目标实车道路工况,并将其代入整车能量流仿真模型中计算综合能耗水平。最后,计算各主成分与综合能耗水平之间的皮尔逊相关系数和协方差值,并对其进行聚类和敏感性定义。结果表明,本文中提取出的人车路3项代表性指标与能耗呈现出较强的敏感性关系。本文中的结论对于插电式混合动力汽车整车参数和控制参数的选取有重要的指导意义。

In order to evaluate the energy consumption level of plug-in hybrid vehicles(PHEV)in actual driving process and study the essential factors affecting the energy consumption level of PHEV,this paper explores the relationship between the vehicle driving status and driving behavior and the overall energy consumption of PHEV based on the driving record data of 180 drivers.Firstly,principal component analysis(PCA)method is employed to decouple the characteristics of parameter matrix of driving conditions,and the first 5 PCs contributing accumulatively 84%to the overall information are extracted.The principle components are also defined according to the numerical distribution of the influence coefficient matrix.Then,based on kinematics fragments,the K-means algorithm is used to constrain the principal components in turn to form target real vehicle road conditions,which is put into vehicle power flow model to calculate the comprehensive energy consumption level.Finally,Pearson correlation coefficient and covariance value between each principle component and comprehensive energy consumption level are calculated and clustering and sensitivity definitions are given.The results show that the three significant factors representing human-vehicle-road extracted in this paper have a strong sensitivity relationship with energy consumption.The conclusions of this paper have important guiding significance for the selection of PHEV design and control parameters.