LAUSR

As an essential part of the transportation industry, it is necessary to reduce the fuel consumption of commercial vehicles from the perspective of the environment and economy. Previous studies have shown that optimizing the gear sequence can reduce vehicle fuel consumption. This paper presents a gear decision method based on predictive road information. Under the model predictive control framework, the dynamic programming algorithm is used to solve the multi-objective optimization problem of gear decision. To solve the problem of the long calculation time of the dynamic programming algorithm, the nonlinear optimization algorithm is used to optimize the dynamic programming sub-problem, and the optimal gear sequence of fuel consumption is obtained. The final optimized gear sequence is obtained through the dynamic programming algorithm. The simulation analysis of the proposed gear shift decision method shows that the gear shift decision method can effectively reduce fuel consumption under fixed working conditions. Compared with the economic shift schedule, the fuel consumption is reduced by 5%, and the computing speed is improved compared with the dynamic programming algorithm.