Decision-making Support in Analyzing the Rolling Stock Energy Efficiency

In analyzing the energy efficiency of such energy-intensive segment of Russia’s economy as railway transport, it is advisable to look for significant reserves for reducing specific energy expenditures at the lowest level of data detail – the level of trips performed by locomotive crews. The article presents an approach to studying the energy efficiency of rolling stock in an operational locomotive depot based on a statistical study of data arrays from automated systems on the performance of transportation work and the consumption of fuel and energy resources to draw conclusions about the currently existing situation. In doing so, it is important to screen out unreliable data that entered the databases due to a malfunction of technical accounting means, on-board systems, or as a result of an operator error at the information entry stage. Data are subjected to filtration out after the information array has been decomposed by rolling stock series, types of traffic, and types of work. If necessary, detailing can be carried out down to each specific locomotive or locomotive crew. Based on the findings obtained, a program for increasing energy efficiency is worked out or, if necessary, adjusted in relation to the train traction, which is the most expensive part of the railway enterprise budget. It should be noted that the analysis has been performed mainly to identify rolling stock units that have increased energy consumption due to their technical condition or locomotive crews that have not mastered effective train driving techniques. This algorithm can be implemented in a decision support system connected with analyzing the train traction energy expenditures.