Optimization of ATO Control for Urban Rail Trains Considering Variation of Motor Parameters

This paper investigates the optimization of automatic train operation (ATO) system for urban rail trains considering the variation of motor parameters. With the rapid development of urban rail transit, improving the efficiency and reliability of train operation has become an important research direction. However, the variation of motor parameters may lead to fluctuations in train traction and energy consumption, which in turn affects the performance of the ATO system. A mathematical model considering the variation of motor parameters is established to describe the relationship between the train traction force and the variation of motor parameters. Based on this model, a state observer-based compensation method for the ATO system is proposed with the aim of optimizing the dynamic performance of the train. In order to verify the effectiveness of the proposed optimization method, simulation experiments are conducted. By comparing with the conventional ATO system, the simulation results show that the optimized ATO system, which takes into account the variation of motor parameters, can significantly improve the train operation performance.