Fuel-wasting Behavior Analysis And Economically Longitudinal Control Of Commercial Vehicles

Economical driving is a new type of fuel-saving technology used for road traffic systems,which is of great significance to improve vehicle fuel economy and reduce pollutant emissions.Fuel-wasting behavior analysis and economically longitudinal control of commercial vehicles are important ways to realize economical driving.The existing research usually adopt simple driving conditions and overlook the inherent characteristics of vehicles.Besides,there is no clear relationship model between driving behavior and fuel consumption.To address those issues,this paper presents an automatic driving conditions segment method with adaptive rule thresholds based on a natural driving data set of 108 commercial vehicles,builds a multi-linear model of the relationship between driving behavior and fuel consumption,designs a model based predictive automatically follow-up controller considering the road slope information,and verifies its function by simulation.Firstly,the driving data set is preprocessed through consistency correcting,abnormal value detecting and noise smoothing.To automatically segment driving conditions under low quality data,a classifier with adaptive rule thresholds is designed,which can divide the whole driving data into 9 typical conditions.Based on these results,an integral vehicle quality identification method is designed to unify the fuel consumption evaluation index as well as improve the analysis accuracy,and the error of quality identification is limited to 10%.Secondly,the multi-linear model between driver behavior and fuel consumption is constructed.To quantitatively describe the driving operation under each driving condition,132 driving operation indexes are extracted based on the analysis of vehicle longitudinal dynamics.To qualify the relationship between driving operation and fuel consumption,its multi-linear model under different consumption levels is established by stepwise multiple linear regression.The differences of driving operations among different consumption levels are analyzed by variance analysis.And the feedback is provided to the drivers with high fuel consumption.Thirdly,a fuel-saving oriented automatically follow-up controller considering road slope information is designed,and its function is verified by simulation.The predictive optimal control problem of the follow-up controller is built based on road slope information,vehicle powertrains with high nonlinearity and spatiotemporal constraint from preceding vehicle.The feasibility of this controller is enhanced by softening non-safety related hard constraints.To reduce the computation burden,the optimal control problem is transformed to a nonlinear programming problem by pseudospectral discretization technique,which can achieve high accuracy with less sample points.The simulation results show that compared to a normal controller,the tracking error and fuel consumption are reduced by 81.15% and 4.63% respectively.