Search results

The subject of research is the evaluation of the effectiveness of different modes of energy-optimal control of the movement of a freight train of a unified mass by AC freight electric locomotives of the Uz-El series with asynchronous electric motors on the flat section of Kokand - Andijan of the Uzbek railway. Purpose of the study: substantiation of the main performance indicators of electric traction locomotives, taking into account the given traffic schedule, using various options for the optimal mode of controlling the movement of a freight train with a unified train mass on a real flat section of the Uzbek railway. The methods and methodology of the research are the theoretical foundations of locomotive traction, the mathematical theory of optimal object control, as well as the C # programming language (C Sharp) with the development of mock-up applications in the Microsoft Visual Studio 12.0 programming environment.As a result of the study, energy-optimal curves, kinematic parameters of the movement of a freight train and parameters of the main indicators of the energy efficiency of the investigated electric locomotive for different options for traction calculation on the real flat section of Kokand - Andijan of the Uzbek railway were obtained. The obtained kinematic parameters of the movement of freight trains with a unified mass of the train and the parameters of the efficiency indicators for the use of the studied electric locomotives can be used in the Kokand locomotive depot, which will allow developing regime maps for driving freight trains by these electric locomotives, depending on the level of complexity of the track profile and various conditions for organizing rail transportation of goods.

The problem of optimizing train driving modes continues to be relevant for a long time, despite a large number of scientific research and development in this subject area. This is due both to the general complexity of the implementation of the technological process of running the train, and to parametric uncertainty and significant variations in the parameters of the control object itself and the external environment. Well-known methods for calculating energy-optimal train driving modes (calculus of variations, the maximum principle, dynamic programming) and auto-driving systems based on them assume some simplifications of the original problem, and, as a result, implement quasi-optimal control in practice. In this regard, the development of methods for searching for the global extremum of a functional defined on the set of permissible trajectories of a train as a dynamic system is both theoretically and practically a significant task. The aim of the work is to create a computationally efficient metaheuristic algorithm for searching for energy-optimal control as a global extremum of the objective function, the values of which are calculated using a reference model of the control object. The authors have developed a problem-oriented evolutionary algorithm for calculating the optimal control of train movement based on the theory of random search. Its features are the proposed specialized operators of local random search, taking into account the specifics of the control object as a multi-mode system; combined procedures of local and global optimization based on the concept of a multi-island population algorithm with superpopulation, as well as a method of selection (selection) of promising options based on the clustering algorithm. Computational experiments have shown good convergence of the algorithm and repeatability of the calculation results. Based on the solutions obtained, a train running time controller can be implemented that implements asymptotically optimal control.