A Construction Method of Truck Driving Cycles Considering Driving Style

Abstract

Typical driving cycles have an important impact on vehicle fuel consumption, emissions, and safety, and is severely affected by driving styles. In this paper, a driving cycles construction method for heavy-duty trucks is proposed, considering driving style effects. First, based on the driving operation data and vehicle status information, a k-means based clustering method is used to identify the driving styles for the same route. Then a database for different vehicle speed segments consisting with highway and suburban, is established for different drive styles, based on experimental data. Then for each segment, a Markov chain algorithm is deployed to construct the typical drive cycle for different driving styles. Simulation results show that using the constructed driving cycle the simulation time is reduced by 88.95% compared with the complete driving cycle, and the relative error of the characteristic parameters is less than 5% and the fuel consumption estimation error is less than 4%.