METHODOLOGY OF CHOOSING PARAMETERS FOR DIAGNOSING ELEMENTS OF URBAN ELECTRIC VEHICLES

  • V. Shavkun O.M. Beketov National University of Urban Economy in Kharkiv
Keywords: diagnostic system, diagnostic parameter, frequency of control, object of diagnosis, control algorithm, failure rate, vehicle, efficient operation.

Abstract

The operation of various vehicles in the field of urban electric transport is accompanied by high costs to maintain their working condition throughout the service life. Preservation of serviceability of vehicles is provided by performance of planned and preventive works on maintenance (MOT) and repair, and also the unscheduled repairs which are carried out for elimination of failures which arise in the interprophylactic periods, and malfunctions.

As already noted, in the planned preventive maintenance and repair system, the vehicle after a certain mileage (time) is forcibly subjected to preventive actions in the prescribed amount. At the same time, despite the adjustment of maintenance and repair modes depending on a number of factors, there is no individual approach to each rolling stock.

However, there is a need for such an approach, because even when rolling stock under the same conditions, the technical condition of each of them at the same time due to a number of reasons (individual characteristics of rolling stock, driving quality, maintenance, etc.) can differ significantly. Not every rolling stock requires all the operations provided by the "hard" volume of a particular type of maintenance. Execution of these "unnecessary" operations leads, on the one hand, to incomplete realization of individual properties of a rolling stock, increase in expenses for MOT, on the other, at all does not promote improvement of its technical condition. On the contrary, more frequent interventions in the work of joints of units and mechanisms contribute to increased wear of bonded surfaces, the appearance of damage to joints, violation of the tightness of joints. Significant losses of labor and material resources are also associated with a large amount of repair work due to late detection of failures.

The fullest use of individual capabilities of rolling stock and ensuring on this basis the high efficiency of rolling stock during operation can be done through the widespread introduction into the technological process of maintenance and repair of diagnosing the technical condition of rolling stock.

To increase the efficiency of the vehicle, use, methods and diagnostic tools have been developed, which are used both during maintenance and repairs, and as an independent technological process. Diagnosis allows to increase the coefficient of readiness and probability of trouble-free operation of vehicles, to reduce the complexity and cost of operation, to increase the maintainability and controllability of vehicles.

Author Biography

V. Shavkun, O.M. Beketov National University of Urban Economy in Kharkiv

PhD, Associate Professor

References

1. Shavkun, V.M. (2018). Perspective directions of development of methods and means of technical diagnostics of electric transport. Municipal economy of cities: Series: Technical sciences and architecture. Scientific and technical Sat, 1, 58–63.
2. Yatsun, M.A., & Yatsun, A.M. (2010). Operation and diagnostics of electric machines and devices. Lviv Polytechnic University, 228.
3. Shavkun, V.M., & Linkov, V.V. (2019). Analysis of modern methods of diagnostics of technical condition of induction motors. Municipal Economy of Cities: Series: Technical Sciences and Architecture. Scientific and technical Sat, Kharkiv, 5, 8–12.
4. Pavlenko, Т.P., Shavkun, V.M., Scurihin, V.I., Lukashova, N.P. (2018). Methodology of determining the parameters of traction electric motor failures when operating trolleybuses. Science and progress of transport. Bulletin of Dnipropetrovsk National University of Railway Transport. Academician V. Lazaryan, 4, 47–59.
5. Pavlenko, T., Shavkun, V., Petrenko, A. (2017). Ways to improve operation reliability of traction electric motors of the rolling stock of electric transport. Eastern-European Journal of Enterpraise Technologies, 5, 22–30.
6. Daleka, V.H., Budnichenko, V.B., Karpushin, E.I. (2014). Technical operation of urban electric transport: textbook. Manual. Kh.:, KhNUMG, 235.
7. Bondarenko, V.G., Kanivska, I.Y., Paramonova, S.M. (2006). Theory of probabilities and mathematical statistics. K. : NTTU "KPI", 125.
8. Ivabotenko, B.A., & Ilyinsky N.F. (1975). Planning an experiment in electromechanics. М .: Energy, 240.
9. Shavkun, V.M. (2014). Diagnosis of traction electric machines of electric transport. East European Journal of Advanced Technologies, 1/7, 48–52.
10. Kolcio, K., & Fesq, L. (2016). Model-based off-nominal state isolation and detection system for autonomous fault management. IEEE Aerospace Conference Proceedings.
11. Krobot, Z., Turo, T., Neumann, V. (2017). Using vehicle data in virtual model for maintenance system support. 6th International Conference on Military Technologies, 171–174.
Published
2021-06-29
How to Cite
ShavkunV. (2021). METHODOLOGY OF CHOOSING PARAMETERS FOR DIAGNOSING ELEMENTS OF URBAN ELECTRIC VEHICLES. Municipal Economy of Cities, 3(163), 138-143. Retrieved from https://khg.kname.edu.ua/index.php/khg/article/view/5794