Energy-Efficient Train Tracking Operation Based on Multiple Optimization Models

Abstract

This paper studies the energy-efficient operation problem of two trains operating along the same line consecutively in urban trail transit (URT). In URT, a moving block signaling (MBS) system is utilized in which the following train's tracking target point is moving forward continuously with the leading train's running. In this case, the following train may be influenced by the leading train's exceptional situations, leading to energy wasting and arrival time delay. In order to reduce energy consumption and arrival delay for the following train, a multiple-optimization-model-based energy-efficient operation method is proposed and verified in this paper. The novelty of this paper lies on the establishment of a novel multiple-model-based switching optimization framework to reduce energy consumption while guaranteeing the punctuality during train tracking operation. More specifically, the operation status of the leading train is combined into the operation optimization for the following train, based on which eight energy-efficient tracking scenarios are discovered and classified into four optimization problems. Then, a general form of running phase sequence is designed to describe the energy-efficient train tracking operation strategy, and a new energy consumption function is proposed. Based on these, the four optimization problems are built into small-scale nonlinear programming models, which are computationally inexpensive and easy for online implementation. During the tracking process, the following train can obtain the energy-efficient strategies through switching among these four optimization models. In this framework, the following train is able to arrive at the next station by the fastest arrival time with lower energy consumption even when the arrival time is delayed by the leading train. Simulation results show the feasibility and effectiveness of the new method.