Energy-Efficient Operation of Single Train Based on the Control Strategy of ATO

Abstract

Energy efficiency is paid more and more attention in urban rail transit systems. Optimization on Automatic Train Operation (ATO) is important to energy-efficient operation of trains. ATO generates the recommended speed curve based on the railway line parameters, the scheduled time table, and the vehicle conditions. The control strategy of ATO makes the train running along the recommended speed curve to meet the requirements on precision of train stopping, punctuality, energy-saving and riding comfort. The optimization of recommended speed curve in traditional research does not consider the influence of the control strategy of ATO. The energy consumption calculated by such a recommended speed curve and the practical curve of the train operation have a significant deviation. In this paper, a more accurate model of the train energy consumption is presented by considering the control strategy of ATO. Two modifications of Tabu Search (TS) algorithm, which are named as Acceleration Rate Decided Modification (ARDM) and Distance Decided Modification (DDM), are proposed to optimize train recommended speed curve based on the presented model. Case studies have been conducted based on Beijing Subway to illustrate that the proposed algorithm results in good performance with regards to energy saving. In addition, the computation time is within 1 s, which is short enough to be applied in the online control of trains.