СТОХАСТИЧЕСКАЯ ИДЕНТИФИКАЦИОННАЯ МОДЕЛЬ ПРОГНОЗИРОВАНИЯ ПАРАМЕТРОВ УСТРОЙСТВ СИСТЕМ ЭЛЕКТРИЧЕСКОГО ТРАНСПОРТА
The necessity to create mathematical models of complex powerful devices of electric traction systems which provide speed and high-speed train movements using identification methods has been justified. A pulse transition function is recommended to be used as an identification model. Using correlation...
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| Datum: | 2019 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Ukrainian |
| Veröffentlicht: |
Інститут електродинаміки НАН України, Київ
2019
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| Online Zugang: | https://techned.org.ua/index.php/techned/article/view/474 |
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| Назва журналу: | Technical Electrodynamics |
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Technical Electrodynamics| Zusammenfassung: | The necessity to create mathematical models of complex powerful devices of electric traction systems which provide speed and high-speed train movements using identification methods has been justified. A pulse transition function is recommended to be used as an identification model. Using correlation theory for stochastic processes which arevoltage and currents in electric traction systems, analytic expression of correlation Wiener-Hopf integral equation has been obtained. Solution of the equation makes it possible to obtain a pulse transition function. Operational, numericaland factorization methods for the equation solving have been considered. Auto- and intercorrelation functions of stochastic current and voltage processes in the system, which are necessary for the solution of integral equation, were defined using experimental method on functioning sections of railroad. Using numerical and factorization methods a pulse transition function as a forecast model was defined for electric locomotive of a direct current DE1 used on electrified sections of Prydneprovska railway. For this purpose monitoring of stochastic voltage and traction current processes was conducted in real operating conditions. Pulse transition functions were defined as exponential functions.References 24, figures 4, table 1 |
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