The use of correlation and regression analysis for assessment of the energy effectiveness of the dc electric locomotives auxiliary equipment

• Main Author: Istomin Stanislav
• Format: Article
• Language: English
• Published: EDP Sciences 2018-01-01
• Series: MATEC Web of Conferences
• Online Access: https://doi.org/10.1051/matecconf/201823901038

Through additional processing of the modern movement parameter recorders data of the DC electric locomotive 2ES6 the article first presents the results of the actual consumption of electricity for own needs and the proportion of these costs from the consumption of trains traction is determined, which in terms of operational depot is difficult to implement. The estimation of influencing factors on the energy consumption for own needs of 2ES6 series electric locomotives is made. As a result it was found that the internal energy consumption is influenced by such factors as rolling stock mass, axle load and environment temperature. Statistic models were made to normalize internal electricity consumption and their quality estimation was fulfilled. It is found that the remainders of the multiple regression equation, which take the above factors into account, obey the normal distribution law, indicating the adequacy of their further use to assess the energy efficiency of the 2ES6 series DC electric locomotives auxiliary equipment. The use of regression models will allow to identify electric locomotives with auxiliary equipment with low energy efficiency and to send them to unscheduled repairs in time to restore the required technical condition.