Energy-efficient Train Control for Maglev Train Using Mixed-integer Linear Programming

Abstract

With high line adaptability, low noise and vibration, and potential in super-high operation speed compared to the wheel-rail (WR) train, the magnetic levitation (Maglev) train has attracted extensive attention from academia and industry. Although the Maglev train eliminates the energy consumption of wheel-rail friction, the huge aerodynamic energy consumption caused by its high-speed operation cannot be ignored. Due to the difference of operation mechanism and dynamic model between Maglev and WR train, the energy-efficient train operation for Maglev train considering peculiar characteristics needs to be further studied. This paper proposed a speed trajectory optimization model formulated by mixed-integer linear programming (MILP) to minimize the energy consumption of the Maglev system. Besides, piecewise linear (PWL) was utilized to deal with the nonlinear terms involved in the Maglev model. Finally, commercial software was applied to solve the model with consideration of various practical constraints of the Maglev system. The comparative result indicates that the flexible MILP model can obtain an optimal strategy efficiently with low linearization errors which are less than 0.1 %.