DEVELOPMENT OF THE ALGORITHMS FORMATION OF ENERGY- OPTIMIZED TRAINS TRAFFIC MODES
DOI:
https://doi.org/10.15802/stp2018/154641Keywords:
traction–energy calculations, optimal mode, mathematical support, mathematical model of train, identification of model parameters, direct and inverse problemsAbstract
Purpose. The paper involves the development of algorithmic support for simulation and optimization of train traffic modes. Methodology. To describe the process of the train movement in spatial coordinates with the distributed mass along the trajectory of motion, a system model is proposed. The model takes into account traction and support parameters and their changes depending on external and internal factors. For a numerical integration of a system model, a finite-difference method is used. In addition, iterative procedures are developed to meet the boundary conditions, the formation of a sequence of traction, braking and idling modes with appropriate parameters to satisfy the criterion of optimality of traffic and technical limitations with sufficient accuracy. The criterion of optimality includes fuel and energy resources, the frequency of changes in the modes of work of traction means (significantly affect the wear of drives), cost rates, etc. Findings. The developed algorithmic, software and information support provided: calculation of driving modes of arbitrary, including standard ones for formation of traffic schedules, calculation of inter-station and station intervals, and research of influence of extreme parameters of trains on their modes of operation. The system provides for the adaptation of the parameters of the train model based on the results of experimental trips. Originality. The paper proposes the task of calculating train driving modes as a problem of optimal control and proposes a quick method for its solution. This ensured the automation of the process of solving a large set of direct and inverse modes with different optimality criteria. Practical value. The proposed approach to the formulation and solution of tasks of modeling and optimization of train driving modes was tested in the process of calculating the main components for the formation of traffic schedules, the selection of optimal parameters for the reconstruction of the roadbed for high-speed and new types of trains.
References
Afanasev, V. N., Kolmanovskiy, V. B., & Nosov, V. R. (2003). Matematicheskaya teoriya konstruirovaniya sistem upravleniya: uchebnik dlya vuzov. Moscow: Vysshaya shkola. (in Russian)
Bodnar, B. Y., Kapitsa, M. I., Afanasov, A. M., & Kyslyi, D. N. (2015). Definition of Energy Saving Acceleration Modes of Trains. Science and Transport Progress, 5(59), 40-52. doi: 10.15802/stp2015/55359 (in Ukrainian)
Kulbashna, N. I., Tarnovetska, A. H., & Balas, O. І. (2014). Novi pidkhody shchodo skladannia ratsionalnykh rezhymiv vodinnia rukhomoho skladu po marshrutakh. Proceedings of the International Conference Problemy ta perspektyvy rozvytku tekhnichnykh zasobiv transportu ta system avtomatyzatsii, October, 01-03, 2014, Kharkiv. 84-85. Kharkiv: O. M. Beketov National University of Urban Economy in Kharkiv. (in Ukrainian)
Pravila tyagovykh raschetov dlya poezdnoy raboty. (1985). Moscow: Transport. (in Russian)
Prytula, M. H., & Shpakovych, R. R. (2007). Modeliuvannia ta rozrakhunok optymalnykh parametriv rukhu poizdiv. Fizyko-matematychne modeliuvannia ta informatsiini tekhnolohii, 5, 139-145. (in Ukrainian)
Soroka, K. O., & Lychov, D. A. (2015). The Content Model and the Equations of Motion of Electric Vehicle. Science and Transport Progress. 3(57), 97-106. doi: 10.15802/stp2015/46056 (in Ukrainian)
Soroka, K. O., Pavlenko, T. P., & Lychov, D. A. (2017). System for Automatic Selection of the Speed Rate of Electric Vehicles for Reducing the Power Consumption. Science and Transport Progress, 3(69), 77-91. doi: 10.15802/stp2017/104360 (in Ukrainian)
Capasso, A., Lamedica, R., Gatta, F. M., Geri, A., Maccioni, M., Ruvio, A., … Carones, N. (2016). Individual driving style impact on traction energy consumption in railway lines: A simulation model. 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). doi: 10.1109/speedam.2016.7525929 (in English)
Wang, P. (2017). Train Trajectory Optimization Methods for Energy-Efficient Railway Operations: doctoral thesis. Retrived from http://clc.am/2oMizA (in English)
Haahr, J. T., Pisinger, D., & Sabbaghian, M. (2017). A dynamic programming approach for optimizing train speed profiles with speed restrictions and passage points. Transportation Research Part B: Methodological, 99, 167-182. doi: 10.1016/j.trb.2016.12.016 (in English)
Scheepmaker, G. M., Goverde, R. M. P., & Kroon, L. G. (2017). Review of energy-efficient train control and timetabling. European Journal of Operational Research, 257(2), 355-376. doi: 10.1016/j.ejor.2016.09.044 (in English)
Albrecht, A., Howlett, P., Pudney, P., Vu, X., & Zhou, P. (2016). The key principles of optimal train control – Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points. Transportation Research Part B: Methodological, 94, 482-508. doi: 10.1016/j.trb.2015.07.023 (in English)
Albrecht, A., Howlett, P., Pudney, P., Vu, X., & Zhou, P. (2016). The key principles of optimal train control –Part 2: Existence of an optimal strategy, the local energy minimization principle, uniqueness, computational techniques. Transportation Research Part B: Methodological, 94, 509-538. doi: 10.1016/j.trb.2015.07.024 (in English)
Ye, H., & Liu, R. (2017). Nonlinear programming methods based on closed-form expressions for optimal train control. Transportation Research Part C: Emerging Technologies, 82, 102-123. doi: 10.1016/j.trc.2017.06.011 (in English)
Downloads
Published
How to Cite
Issue
Section
License
Copyright and Licensing
This journal provides open access to all of its content.
As such, copyright for articles published in this journal is retained by the authors, under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0). The CC BY license permits commercial and non-commercial reuse. Such access is associated with increased readership and increased citation of an author's work. For more information on this approach, see the Public Knowledge Project, the Directory of Open Access Journals, or the Budapest Open Access Initiative.
The CC BY 4.0 license allows users to copy, distribute and adapt the work in any way, provided that they properly point to the author. Therefore, the editorial board of the journal does not prevent from placing published materials in third-party repositories. In order to protect manuscripts from misappropriation by unscrupulous authors, reference should be made to the original version of the work.