Energy-efficient Operation Of Single Train Based On The Control Strategy Of ATO

With the development of urban rail transit system and the increase of traffic demand, the total energy consumption of train in urban rail transit system has been growing rapidly. The traction energy consumption of train occupies large proportion of the total energy consumption. The main goal of energy-saving control for train operation is to reduce the traction energy consumption of train as far as possible. Because ATO has been widely used in urban rail transit now, the optimization on Automatic Train Operation (ATO) is significant for energy-efficient operation of trains.Atypical ATO system generally consists of two levels. The high-level control generates the recommended speed curve based on the railway line parameters, the scheduled time table, and the vehicle conditions to meet the requirements on precision of train stopping, punctuality, energy-saving and riding comfort. The low-level control makes the train running along the recommended speed curve based on the tracking control strategy of ATO and generates the practical curve of the train operation. The traditional research has only focused on the high-level control to optimize the recommended speed curve, but did not practically consider the low-level control of the ATO system. The energy consumption calculated by such a recommended speed curve and the practical curve of the train operation have a significant deviation.Different from the previous researches, this paper presented a more accurate model of the train energy consumption by considering the control strategy of ATO. After which we proposed two modifications of Tabu Search (TS) algorithm, which were named as Up-Down Modification (UDM) and Left-Right Modification (LRM), to optimize train recommended speed curve based on the presented model. In addition, we optimized the tracking control strategy of ATO based on TS algorithm. Finally, we carried on the integrated optimization of the recommended speed curve combined with the tracking control strategy of ATO. The simulation results based on the Beijing Yizhuang Subway Line illustrate that the proposed approach can achieve a good performance energy reduction. Sensitivities of the parameters are analyzed to illustrate that the proposed approach is practical and meaningful. In addition, the computation time is within 2 s, which is short enough to be applied in the real-time control of trains.