Look-ahead gear-shifting strategy on ramps for heavy trucks with automated mechanical transmission

Abstract

Look-ahead information has been applied to vehicle shift systems and has led to the development of innovative changes in shifting strategies. A shifting strategy significantly influences the dynamic and economic performance of a truck. If a shift control system can predict the information of the road ahead, then the dynamic programming method can be used to obtain an optimal shift schedule, thereby achieving the best balance between the dynamic and the economic performance of a truck. Determining the weights of the economic and dynamic performance of a truck is critical in dynamic programming. Weight is related to road slope value; hence, this study uses different weights on 3%, 5%, and 10% ramp simulation experiments to investigate the relationship between fuel consumption and running time and to determine the optimum weight for different slopes. On the basis of the optimal shift schedule obtained via dynamic programming, the ramp information of the road ahead can be utilized to adjust the shift point to avoid unnecessary shifting before entering the slope and reduce shift times on a ramp. An actual truck test shows that the anthropomorphic shifting strategy proposed in this study meets driver expectations and is conducive to the ramp driving of trucks with automated manual transmission.