Abstract
The paper is aimed at studying the energy processes in the electric traction drive and in the contact network in order to reduce energy losses and increase the performance of electric traction of trains. The calculation method is based on a refined law of energy saving in an electromagnetic field using computer simulation and the FFT spectral analysis of a nonsinusoidal voltage, current. The objects of research are the contact networks of alternating and direct current, the well-known pulse power controllers, and the controllers of the input electrical resistance of the traction electric drive, proposed in the paper. Research has proven the cause of unsatisfactory energy efficiency and a reduction in the speed of transport work - a reduction in the duration of the use of the electrical potential of a contact network for electric traction of a train. The inductance of the AC contact network and the inductance of the traction transformer cause the input converter of the AC electric locomotive to work in the short circuit mode. Therefore, considerable loss of electrical energy occurs in this equipment. A further increase in the carrying and traffic capacity of the railway with energy-saving electric traction can be realized by applying increased voltage in DC contact networks and electric semiconductor variators to control collector and three-phase asynchronous motors on the traction rolling stock. Engineering tasks to improve the electric traction of trains can be successfully solved by specialists who are free from the idea of isolating the main harmonic components of voltage and current from the entire spectrum of harmonics and from the task of developing compensators for shear power and distortion power.
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Ryabchenok, N., Alekseeva, T., Astrakhancev, L., Astashkov, N., Tikhomirov, V. (2020). Energy-Saving Driving of Heavy Trains. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 982. Springer, Cham. https://doi.org/10.1007/978-3-030-19756-8_47
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DOI: https://doi.org/10.1007/978-3-030-19756-8_47
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