A method and system for realizing operation and control of railway locomotives from offline to online

Abstract

The invention provides a method and system for achieving railway locomotive operation control from an off-line mode to an on-line mode. A sequence pattern excavation method is used for obtaining a control gear sequence from original operation data of a locomotive in an off-line mode, an off-line optimization algorithm is used for optimizing the time distribution proportions of specific gears in the control gear sequence, a neural network model is constructed according to the time distribution proportion sequence with the optimal energy consumption, association rules of the specific locomotive, line parameters and the control gear sequence are obtained according to the neural network model, finally, the control sequence with the optimal energy consumption is used for guiding the locomotive to operate in an on-line mode. Due to the fact that off-line calculation is not affected by time factors so that an off-line part can own better optimized space, and in the operation process of the locomotive, a good energy-saving effect can be achieved by utilizing the control gear sequence of operation of the locomotive, wherein the control gear sequence is obtained in the off-line mode. In addition, an on-line control operation result of the locomotive serves as the data input of the off-line sequence pattern excavation method and the optimization algorithm, and therefore off-line learning can be adjusted and optimized continuously.

Description

technical field [0001] The invention relates to a locomotive operation optimization control technology, in particular to a method and a system for realizing the railway locomotive operation optimization control from offline to online. Background technique [0002] Railway locomotive operation control is a typical multi-objective, multi-constraint, nonlinear complex real-time changing process. Therefore, the operation and manipulation of railway locomotives is a nonlinear and constrained dynamic optimization problem. [0003] The existing methods of optimizing railway locomotive operation and manipulation mainly use various optimization techniques such as fuzzy control technology, genetic algorithm and their integrated algorithms to guide the operation of locomotive operation optimization calculation. [0004] The above-mentioned fuzzy control technology establishes fuzzy rules from the perspective of combining fuzzy reasoning and predictive control, and builds a railway loc...

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Problems solved by technology

Therefore, the operation and handling problem for railway locomotives is a nonlinear and constrained dynamic optimization problem.

[0006] The above-mentioned online optimization algorithms are currently unable to meet the requirements of online control. The optimization search takes a long time and cannot be applied to the online optimization calculation of locomotives. The reliability of the method and the optimization of the results will inevitably be restricted, and it is impossible to obtain a good energy-saving effect during the operation of the railway locomotive, and the initial strategy calculated by the above method mostly depends on manual experience. Therefore, for general-purpose locomotives and lines, Its optimization rationality is difficult to support, so there is a lot of room for optimization from the perspective of locomotive running time and energy consumption

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