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The article is devoted to the research of the of wind load effect on the aerodynamic component to the movement of a freight train. These findings contribute to a better understanding of the impact of aerodynamic resistance on the consumption of fuel and energy resources (FER) on train traction. The article shows the high significance of this problem for Joint Stock Company Russian Railways (RZD JSC). The conclusions were drawn from the analysis of statistical data on the routes of locomotive drivers, working on the Pallasovka-Verkhniy Baskunchak section, which is undergone to wind loads. The SOLIDWORKS application was used to design a train with a locomotive and gondola cars coupled on an embankment, and SOLIDWORKS Flow Simulation plug-in was used to simulate wind load, different in speed, varying from 0 to 90º. The values of the force of aerodynamic resistance to movement for the train as a whole and for each unit of the rolling stock separately were obtained. Using the methods of the theory of train traction, the influence of aerodynamic drag on fuel consumption for traction has been assessed. Based on the obtained values of the aerodynamic drag forces and patterns of air flow distribution, conclusions were drawn about the effect of loading a gondola car on an increase in traffic resistance. Conclusions are drawn about the effect of wind load on each unit of rolling stock in the train. It was found that when the wind is directed at an angle to the axis of the path, the force of the wind effect increases, compared with the case when the angle between the axis of the path and the velocity vector is zero. The experimental data on the increase in resistance from the wind load are confirmed by theoretical calculation, as well as practical processing of routes machinists. This article demonstrates the need for a separate regulation of fuel and energy resources in the event of wind loads, and may be useful in further detailed study of the aerodynamic drag of freight trains.

A mathematical model has been developed for an adaptive automatic brake control system for a freight train using an Extended Kalman Filter (EKF) to identify the actual parameters of the train and its braking system. To evaluate the performance of the proposed automatic control system, a simulation experiment was carried out using a probabilistic formulation of the research problem and the developed automatic brake control model. The purpose of the experiment is to determine the probabilistic characteristics of the random variable representing the deviation of the train’s stopping coordinate from the specified value. The adequacy of the number of simulation runs for obtaining reliable statistical characteristics in this study was determined using a method for estimating the confidence interval bounds for the sample mean and variance for the given number of trials. Histograms were obtained for the distribution of stopping-point deviation during targeted braking with the EKF algorithm switched off and on. To estimate the probability that the stopping-point deviation exceeds the specified limit, a theoretical distribution law for the random variable was selected and verified using the nw2 goodness-of-fit test. It is shown that without the proposed algorithm for identifying braking system and train parameters (the Extended Kalman Filter, EKF), the deviation from the target stopping point during precision braking can lead to serious violations of train-operation safety. The proposed automatic pneumatic brake control system provides high-quality control, improving the accuracy of targeted stopping of a train at a specified track coordinate. The work was carried out at the expense of budget financing within the framework of the state assignment No. 103-00001-25-02 dated 20.03.2025.

One of the ways to increase the capacity of railways is to use long-distance freight trains with a distributed traction system. In order to reduce the influence of the human factor, it is advisable to use automatic speed control systems on the locomotives of such trains, that take into account the transients occurring in the train. Determination of the longitudinal forces that occur in the train can be carried out by using either a reference mathematical model of the train, or pre-calculated dependencies of these forces on the parameters of the train movement. The second method allows you to simplify the structure and improve the performance of automatic control systems.