Article

Received 28.07.2025

Revised 03.11.2025

Accepted 29.12.2025

Retrieved from Vol. 28, No. 2, 2025

Pages 7 -20

Liashenko, V., & Yatsko, S. (2025). Study of influence of imprecision of primary information on energy consumption of rolling stock. The National Transport University Bulletin: A Scientific and Technical Journal, 28(2), 7-20. https://doi.org/10.32703/2617-9040-2025-46-1

Study of influence of imprecision of primary information on energy consumption of rolling stock

Vadym Liashenko Serhii Yatsko

The energy efficiency of urban rail transportation systems is a crucial indicator, as traction energy consumption  typically  accounts  for  40-60%  of  the  total  energy  consumption  of  the  transportation system. This study examines the sensitivity of energy consumption to deviations from nominal conditions under the implementation of pre-calculated optimized trajectories for electric rolling stock, considering rolling stock  with  operation  modes  typical  for  suburban  and  urban  transport.  To  determine  globally optimal  control  strategies  that  minimize  energy  consumption  while  complying  with  operational constraints,  the  study  uses  dynamic  programming  based  on  Bellman's  optimality  principle.  The optimization model divides the  track section into discrete segments  and uses the backward  induction method to establish optimal control laws, producing speed trajectories as functions of the train's current coordinates  on  a  given  gradient  profile.  The  trade-off  between  energy  and  time  is  represented  by  an indefinite Lagrange multiplier to ensure adherence to the timetable. Sensitivity analysis is performed by simulating inaccuracies in the estimates of the train's current coordinates and variations in its passenger load. Modelling of a targeted braking system has been implemented so as to ensure stopping accuracy in  the  event  of  measurement  inaccuracies.Modelling  was  performed  using  three  typical  gradient profiles,  characteristic  primarily  of  underground  railways;  for  comparison,  modelling  was  also performed on a conditional section with a negligible gradient. The research methodology allows for a quantitative assessment of the degree of energy overconsumption that may be caused by deviations in train passenger load factors and errors in the estimation of the position of rolling stock (±25 meters), which  provides  information for assessing the  effectiveness of pre-calculated optimized trajectories in real operating conditions

speed trajectory optimization; urban rail transport; energy efficiency; dynamic programming
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https://doi.org/10.32703/2617-9040-2025-46-1