EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 458 (2023) E3S Web of Conf., 458 (2023) 03025 References
Open Access
Issue
E3S Web of Conf.
Volume 458, 2023
International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2023)
Article Number 03025
Number of page(s) 11
Section Low Carbon Mobility and Logistics
DOI https://doi.org/10.1051/e3sconf/202345803025
Published online 07 December 2023
  1. Ablyalimov O. S. Assessment of the efficiency of transportation work of electric locomotives 3VL80S on the Kattakurgan - Navoi section of the Uzbek railway. Crede Experto: transport, society, education, language. International information and analytical journal. Irkutsk, 2018. No. 4 (19). - pp. 35 – 50. [Google Scholar]
  2. M. Miyatake and H. Ko, “Optimization of train speed profile for minimum energy consumption,” IEEE Transactions on Electrical and Electronic Engineering, vol. 5, no. 3, pp. 263–269, May 2010. [CrossRef] [Google Scholar]
  3. Nilam R. Dongre. “Optimization of Energy Consumption In Electric Traction System By Using Interior Point Method.” IOSR Journal of Electrical and Electronics Engineering (IOSRJEEE) 13.2 (2018): pp. 9–15. [Google Scholar]
  4. S. Su, T. Tang, C. Roberts, and L. Huang, “Cooperative train control for energy-saving,” in Proc. IEEE Int. Conf. Intell. Rail Transp., Beijing, China, Aug. 2013, pp. 7–12. [Google Scholar]
  5. Y. V. Bocharnikov, A. M. Tobias, and C. Roberts, “Reduction of train and net energy consumption using genetic algorithms for trajectory optimization,” in Proc. IET Conf. Railway Traction Syst., Birmingham, U.K., Apr. 2010, pp. 32–36. [Google Scholar]
  6. R. Chen, L. Liu and J. Guo, “Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm”, Journal of Traffic and Transportation Engineering. 1, 12 (2012). [Google Scholar]
  7. S. Acikbas and M. Soylemez, “Coasting point optimization for mass rail transit lines using artifical neural networks and genetic algorithms,” Proceedings of the IEE Proceedings - Electric Power Applications, vol. 2, no. 3, pp. 172–182, May 2008. [Google Scholar]
  8. Y. Ding, H. Liu, Y. Bai, and F. Zhou, “A two-level optimization model and algorithm for energy-efficient urban train operation,” J. Transp. Syst. Eng. Inf. Technol., vol. 11, no. 1, pp. 96–101, Feb. 2011. [Google Scholar]
  9. S. Sun, Y. Li and H. Xu, “Energy Consumption Optimization for High-speed Railway based on Particle Swarm Algorithm”, Proceedings of 4th International Conference on Computational Intelligence and Communication Networks, (2012) November 3–5; Mathura, India. [Google Scholar]
  10. S. Su, X. Li, T. Tang, and Z. Gao, “A subway train timetable optimization approach based on energy-efficient operation strategy,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 883–893, Jun. 2013. [CrossRef] [Google Scholar]
  11. X. Li and H. K. Lo, “An energy-efficient scheduling and speed control approach for metro rail operations,” Transp. Res. Part B.: Methodol., vol. 64, pp. 73–89, Jun. 2014. [Google Scholar]
  12. R. Liu and I. M. Golovicher, “Energy-efficient operation of rail vehicles,” Transportation Research Part A: Policy and Practice, vol. 37, no. 10, pp. 917–931, [Google Scholar]
  13. Oct. 2003. [Google Scholar]
  14. K. K. Wong and T. K. Ho, “Dwell-time and run-time control for DC mass rapid transit railways,” Proc. Inst. Elect. Eng.—Elect. Power Appl., vol. 6, no. 1, pp. 956–966, Nov. 2007. [Google Scholar]
  15. X. Yang, X. Li, B. Ning, and T. Tang, “An optimization method for train scheduling with minimum energy consumption and travel Time in metro rail systems,” Transportmetrica B: Transp. Dyn., vol. 3, no. 2, pp. 79–98, 2015. [CrossRef] [Google Scholar]
  16. X. Yang, X. Li, Z. Gao, H. Wang, and T. Tang, “A cooperative scheduling model for timetable optimization in subway systems,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, pp. 438–447, Mar. 2013. [CrossRef] [Google Scholar]
  17. Lesov A. T. Analysis of methods for solving problems of optimal control of train movement. // Electronics and electrical equipment of transport. – Tomilinsky Electronic Plant, 2022, issue. 3. – pp. 23–29. [Google Scholar]
  18. A. Grünig, Efficient Generation of Train Speed Profiles, Bachelor’s Thesis, Institute for Operations Research, ETH Zurich, 2009. [Google Scholar]
  19. H. Ko, T. Koseki, and M. Miyatake, “Application of dynamic programming to optimization of running profile of a train,” in Computers in Railways IX, WIT Press, vol. 15, Southampton, Boston, Sept. 2004, pp. 103–112. [Google Scholar]
  20. Klimovich A. V. Optimization of train movement control to minimize the cost of energy resources for traction, Moscow, Sputnik+ company, 2008, 263 p. (In Russian). [Google Scholar]
  21. Yurenko K. I. Calculation of energy-optimal modes of movement of promising rolling stock by dynamic programming method. Bulletin of universities. electromechanics, 2013, no.3, pp.78-82 (In Russian). [Google Scholar]
  22. Ablyalimov O. S. Analysis of the efficiency of using electric traction locomotives on a flat section of the railway. Electrical equipment: operation and repair. Magazine. Moscow: Publishing house. House “Panorama”, 2021. No. 10. - pp. 22–30. [Google Scholar]
  23. Ablyalimov O. S. Analysis of the efficiency of transportation work of 3VL80S electric locomotives at the Kattakurgan – Navoi section of the Uzbek railway. / О. S. Ablyalimov // Modern Technologies. System Analysis. Modeling, 2018 Vol. 60, No. 4, pp. 70–79. DOI: 10.26731/1813-9108. 2018.4(60).70-79. [Google Scholar]
  24. Oleg Ablyalimov and Nikolay Julenev. (2023, July). Logistic indicators of locomotives of diesel traction on high-speed section of the railway. In E3S Web of Conferences 401, 05023 (2023). V International Scientific Conference “Construction Mechanics, Hydraulics and Water Resources Engineering” (CONMECHYDRO – 2023). DOI: https://doi.org/10.1051/e3sconf/202340105023. [Google Scholar]
  25. 24 Ablyalimov, O. S. Optimization of locomotive transportation work: theoretical issues, methods, calculations, results. / O. S. Ablyalimov. – Text: direct // Monograph / Tashkent Institute of Railway Transport Engineers. – Tashkent: “Complex Print” nashriyoti, 2020. – 488 p. [Google Scholar]
  26. Lesov A. T. Energy optimization of train movement modes in the C# program language / A. T. Lesov, V. O. Ivashchenko // News of the St. Petersburg University of Railway Transport. – St. Petersburg: PGUPS, 2021. – T. 18, issue. 4. – pp. 480–490. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.