Train driving strategy optimization using control parameterization enhancing technique

Abstract

Train energy consumption accounts for the largest proportion of total energy consumption in railway systems. Applying the optimal driving strategy is an important way to reduce train energy consumption. In this paper, an efficient numerical approach - control parameterization enhancing technique (CPET) is employed to determine the optimal train driving strategy, which is essentially a problem of optimal control. Using CPET, the train control forces are indicated by piecewise constant function with variable switching nodes. Then, CPET transforms the original problem of optimal train control into a nonlinear optimization problem by considering both the piecewise constant control values on each subinterval and the lengths of the subintervals as decision parameters. Finally, the transformed optimization problem is solved efficiently by using an exact penalty method to handle the train speed constraint and applying a sensitivity approach to obtain the gradient of the cost function. A case study is carried out to demonstrate that the optimal driving strategy obtained by the CPET is more energy-efficient than that obtained by the traditional control parameterization method under same conditions.