Design And Implementation Of Automatic Train Operation Algorithm Of Metro Train

Recently, the rapid development of metro train plays an increasingly important role in reducing environmental pollution and solving the traffic congestion problem in cities. The application of ATO (Automatic Train Operation) system in metro trains not only could effectively ensure train safe operation and comfortability of passengers, but also has a better performance in automatic adjustment of train speed, accurate stopping and reducing energy consumption, compared with manual operation. The train speed curve is crucial in achieving automatic train operation of metro trains, so an energy-saving optimized train speed curve could help improve the operation efficiency further and reduce the energy consumption significantly. And it is also a key point to trace the optimized speed curve accurately in ATO system of metro trains. The following work in this paper was carried out against the background mentioned above:Firstly, the traction calculation model of train was established on the basis of analysis of train's dynamic operation. And characteristics of train operation and forces carried out in different modes were analyzed. Then primary energy consumption sources were summarized and several strategies of lowering operation energy were derived.Secondly, the energy-saving optimization of train speed curve was analyzed and researched. When trains run in a certain section at maximum capacity, the shortest running time could be found. Then the rich time used for energy-saving optimization could be calculated. Two algorithms of energy-saving optimization were proposed, which were respectively based on coasting control and altering constant speed. Then combined with specific line and train data, two algorithms were implemented on the basis of C language programming in Matlab, and the simulation results demonstrated that feasibility and correctness of two optimization algorithms in this paper were verified.Thirdly, the theory of fuzzy control was briefly introduced. Then through applying predictive fuzzy control algorithm, for six main performance indexes of ATO, including safety, punctuality, accuracy of stop, traceability of target curve, comfortability and energy-saving, corresponding fuzzy membership functions were established. And then based on summaries of metro train's manual operation strategies,corresponding fuzzy control rules were concluded. Last, this algorithm was established and verified by Matlab simulation, the conclusion was that actual trains could trace the optimized target curve accurately and meet requirements of accuracy of stop and punctual operation.Finally, on the basis of the Vxworks embedded real-time operating system, design and function of hardware development kit and host computer were analyzed, then data structure and process of algorithms execution were discussed, optimization algorithm and predictive fuzzy control algorithm were successfully transferred into Vxworks embedded system. Last,simulation result in Vxworks revealed that Vxworks has a better performance in real-time ability and reliability.