Energy-efficient trajectory planning for high-speed trains via an mixed integer linear programming approach

This paper proposes an energy-efficient trajectory planning approach for high speed trains to reduce the traction energy consumption. Firstly, an optimization model is developed by defining the objective function as a weighted sum of the traction energy consumption and passengers' riding comfort. Besides the constraints in the classic optimal train control problem (such as the trip time, running resistance, speed limit, and the train characteristics), the discrete throttles, split phase zone, and the sectionalized tunnel resistance are introduced in this paper. Then, all the nonlinear constraints are approximated through the piecewise affine function and the energy-efficient trajectory planning problem is turned into an mixed integer linear programming (MILP) problem. The MILP problem can be solved by existing solvers CPLEX and YALMIP. Finally, some cases are conducted to illustrate the effectiveness of the proposed approach. The result shows that the traction energy consumption is increased by 4.5% when the ridding comfort is taken into consideration.