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A New Operation-Oriented Mixed Integer Linear Programming Model for Energy-Efficient Train Operations

The study on the train speed profile optimization has attracted many attentions from the industry and academia since it leads to energy reduction for greener railway transportation. One of the gaps existing between the academic research and industry application is that the speed profile cannot be accurately tracked due to high inertia and large time-delay of the railway traction systems. In both manual and automatic operations, it is considered more practical to provide train operation strategies such as traction or coasting rather than offering an accurate train speed to follow. In this paper, we introduce a new modelling process using a series of binary variables to represent the corresponding operation strategies as the decision variables, so that it is easy to be adopted in real operations. The train operation process is discretized based on distance and the model is solved by mixed integer linear programming. Instead of providing train speeds, this modelling outputs offer selective operations for various distance sections. Based on the results, computational efficiency of the model relaxing the restriction on the applied force are almost the same compared to the previous work using the speed as the decision variable and the calculation time increases from 50 ms to 650 ms when the range of applied force is limited to 85 kN under the maximum tractive efforts. The operation-oriented decisions lead to more flexible adoptions in rail industry applications as the train only needs to switch between different operation modes at the corresponding locations rather than tracking the train speeds.