Comprehensive assessment of technical condition of vehicles during operation based on Harrington’s desirability function

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.298567

Keywords:

Harrington function and desirability criteria, technical condition, vehicle, control parameter

Abstract

The object of research is the process of changing the technical condition of vehicles during their operation. The study solved the problem of comprehensive evaluation of change in the technical condition based on Harrington’s desirability function.

The essence of the results is as follows. A scale of desirability was built and a set of criteria for assessing the technical condition of vehicles was clarified. A general desirability index is proposed as a convolution of partial Harrington desirability functions. When solving the investigated problem, the characteristics and properties of the partial and generalized Harrington’s desirability function and their graphical representation were taken into account.

Using an example of the technical condition of the chassis and braking system of vehicles, a set of controlled parameters was formed. Based on the values of the controlled parameters, the regression equation of the partial Harrington desirability functions was obtained.

The value of the weighting coefficients of each of the criteria was determined and the generalized desirability function was calculated.

As a result of the study, it was established that if the generalized criterion of desirability is D<0.37, then individual nodes, systems, and units of the vehicle are in a pre-accident condition, if 0.37£D£0.63 – in a satisfactory condition, and if D>0.63 – in a good condition and cannot be the cause of a traffic accident.

An applied aspect of the results is the implementation of the technique of comprehensive assessment of the technical condition of the vehicle. This causes an increase in the productivity of the expert (specialist), will shorten the period of the auto technical examination, and improve its quality. The results could be used by insurance companies and investigators, investigators and judges when considering traffic accidents

Author Biographies

Viktor Aulin, Central Ukrainian National Technical University

Doctor of Technical Sciences, Professor

Department of Maintenance and Repair of Machines

Ivan Rogovskii, National University of Life and Environmental Sciences of Ukraine

Doctor of Technical Sciences, Professor

Department of Technical Service and Engineering Management named after M. P. Momotenko

Oleh Lyashuk, Ternopil Ivan Puluj National Technical University

Doctor of Technical Sciences, Professor

Department of Automobiles

Liudmyla Titova, National University of Life and Environmental Sciences of Ukraine

PhD, Associate Professor

Department of Technical Service and Engineering Management named after M. P. Momotenko

Andrii Hrynkiv, Central Ukrainian National Technical University

PhD, Senior Researcher

Department of Maintenance and Repair of Machines

Dmytro Mironov, Ternopil Ivan Puluj National Technical University

PhD, Associate Professor

Department of Automobiles

Mykhailo Volianskyi, National University of Life and Environmental Sciences of Ukraine

PhD, Associate Professor

Department of Agricultural Machines and System Engineering named after Academician P. M. Vasylenko

Roman Rogatynskyi, Ternopil Ivan Puluj National Technical University

Doctor of Technical Sciences, Professor

Department of Automobiles

Oleksiy Solomka, National University of Life and Environmental Sciences of Ukraine

PhD, Associate Professor

Department of Tractors, Cars and Bioenergy Resources

Serhii Lysenko, Central Ukrainian National Technical University

PhD, Associate Professor

Department of Maintenance and Repair of Machines

References

  1. Koteleva, N. I., Korolev, N. A., Zhukovskiy, Y. L. (2021). Identification of the Technical Condition of Induction Motor Groups by the Total Energy Flow. Energies, 14 (20), 6677. https://doi.org/10.3390/en14206677
  2. Parekh, D., Poddar, N., Rajpurkar, A., Chahal, M., Kumar, N., Joshi, G. P., Cho, W. (2022). A Review on Autonomous Vehicles: Progress, Methods and Challenges. Electronics, 11 (14), 2162. https://doi.org/10.3390/electronics11142162
  3. Kondratenko, O. (2020). Assessment of ecological and chemical efficiency of exploitation process of reciprocating ICE of vehicle with consideration of emission of sulphur oxides, benzo(a)pyrene and polycyclic aromatic hydrocarbons. Technogenic and Ecological Safety, 7 (1/2020), 38–50. https://doi.org/10.5281/zenodo.3780076
  4. Hrynkiv, A., Rogovskii, I., Aulin, V., Lysenko, S., Titova, L., Zagurskiy, O., Kolosok, I. (2020). Development of a system for determining the informativeness of the diagnosing parameters for a cylinder­piston group in the diesel engine during operation. Eastern-European Journal of Enterprise Technologies, 3 (5 (105)), 19–29. https://doi.org/10.15587/1729-4061.2020.206073
  5. Prytz, R., Nowaczyk, S., Rögnvaldsson, T., Byttner, S. (2015). Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data. Engineering Applications of Artificial Intelligence, 41, 139–150. https://doi.org/10.1016/j.engappai.2015.02.009
  6. Kondratenko, O. M. (2020). Assessment of fuel and ecological efficiency of exploitation process of reciprocating ICE of power plants with considering of emission of benzo(a)pyrene and polycyclic aromatic hydrocarbons. Internal Combustion Engines, 1, 52–59. https://doi.org/10.20998/0419-8719.2020.1.07
  7. Britton, M. A., Asnaashari, S., Read, G. J. M. (2016). Analysis of train derailment cause and outcome in Victoria, Australia, between 2007 and 2013: Implications for regulation. Journal of Transportation Safety & Security, 9 (1), 45–63. https://doi.org/10.1080/19439962.2015.1088906
  8. Rashidi, E., Parsafard, M., Medal, H., Li, X. (2016). Optimal traffic calming: A mixed-integer bi-level programming model for locating sidewalks and crosswalks in a multimodal transportation network to maximize pedestrians’ safety and network usability. Transportation Research Part E: Logistics and Transportation Review, 91, 33–50. https://doi.org/10.1016/j.tre.2016.03.016
  9. Chen, X., Chen, J. (2020). Optimization of the Impeller Geometry for an Automotive Torque Converter Using Response Surface Methodology and Desirability Function. Open Journal of Applied Sciences, 10 (07), 455–475. https://doi.org/10.4236/ojapps.2020.107032
  10. Padilla-Atondo, J. M., Limon-Romero, J., Perez-Sanchez, A., Tlapa, D., Baez-Lopez, Y., Puente, C., Ontiveros, S. (2021). The Impact of Hydrogen on a Stationary Gasoline-Based Engine through Multi-Response Optimization: A Desirability Function Approach. Sustainability, 13 (3), 1385. https://doi.org/10.3390/su13031385
  11. Vladyslav, R. (2022). Structure of the national police of Ukraine: modern interpretation. Entrepreneurship, Economy and Law, 5, 69–74. https://doi.org/10.32849/2663-5313/2022.5.11
  12. Rolison, J. J., Regev, S., Moutari, S., Feeney, A. (2018). What are the factors that contribute to road accidents? An assessment of law enforcement views, ordinary drivers’ opinions, and road accident records. Accident Analysis & Prevention, 115, 11–24. https://doi.org/10.1016/j.aap.2018.02.025
  13. Heydari, S., Hickford, A., McIlroy, R., Turner, J., Bachani, A. M. (2019). Road Safety in Low-Income Countries: State of Knowledge and Future Directions. Sustainability, 11 (22), 6249. https://doi.org/10.3390/su11226249
  14. Dirnbach, I., Kubjatko, T., Kolla, E., Ondruš, J., Šarić, Ž. (2020). Methodology Designed to Evaluate Accidents at Intersection Crossings with Respect to Forensic Purposes and Transport Sustainability. Sustainability, 12 (5), 1972. https://doi.org/10.3390/su12051972
  15. Gorea, R. K. (2016). Financial impact of road traffic accidents on the society. International Journal of Ethics, Trauma & Victimology, 2 (01), 6–9. https://doi.org/10.18099/ijetv.v2i1.11129
  16. Aulin, V., Hrynkiv, A., Lysenko, S., Rohovskii, I., Chernovol, M., Lyashuk, O., Zamota, T. (2019). Studying truck transmission oils using the method of thermal-oxidative stability during vehicle operation. Eastern-European Journal of Enterprise Technologies, 1 (6 (97)), 6–12. https://doi.org/10.15587/1729-4061.2019.156150
  17. Dela Cruz, O. G., Padilla, J. A., Victoria, A. N. (2021). Managing Road Traffic Accidents: A Review on Its Contributing Factors. IOP Conference Series: Earth and Environmental Science, 822 (1), 012015. https://doi.org/10.1088/1755-1315/822/1/012015
  18. Ahmed, E., Gharavi, H. (2018). Cooperative Vehicular Networking: A Survey. IEEE Transactions on Intelligent Transportation Systems, 19 (3), 996–1014. https://doi.org/10.1109/tits.2018.2795381
  19. Casado-Sanz, N., Guirao, B., Attard, M. (2020). Analysis of the Risk Factors Affecting the Severity of Traffic Accidents on Spanish Crosstown Roads: The Driver’s Perspective. Sustainability, 12 (6), 2237. https://doi.org/10.3390/su12062237
  20. Oladimeji, D., Gupta, K., Kose, N. A., Gundogan, K., Ge, L., Liang, F. (2023). Smart Transportation: An Overview of Technologies and Applications. Sensors, 23 (8), 3880. https://doi.org/10.3390/s23083880
  21. Low, R., Tekler, Z. D., Cheah, L. (2020). Predicting Commercial Vehicle Parking Duration using Generative Adversarial Multiple Imputation Networks. Transportation Research Record: Journal of the Transportation Research Board, 2674 (9), 820–831. https://doi.org/10.1177/0361198120932166
  22. Young, W., Sobhani, A., Lenné, M. G., Sarvi, M. (2014). Simulation of safety: A review of the state of the art in road safety simulation modelling. Accident Analysis & Prevention, 66, 89–103. https://doi.org/10.1016/j.aap.2014.01.008
  23. Slobodyanyuk, M., Gorobchenko, O. (2020). Structural analysis of territorial transport systems based on classification methods. Eastern-European Journal of Enterprise Technologies, 1 (4 (103)), 23–32. https://doi.org/10.15587/1729-4061.2020.194158
  24. Abu Dabous, S., Ibrahim, F., Feroz, S., Alsyouf, I. (2021). Integration of failure mode, effects, and criticality analysis with multi-criteria decision-making in engineering applications: Part I – Manufacturing industry. Engineering Failure Analysis, 122, 105264. https://doi.org/10.1016/j.engfailanal.2021.105264
  25. Radu, P. V., Lewandowski, M., Szelag, A. (2020). On-Board and Wayside Energy Storage Devices Applications in Urban Transport Systems—Case Study Analysis for Power Applications. Energies, 13 (8), 2013. https://doi.org/10.3390/en13082013
Comprehensive assessment of technical condition of vehicles during operation based on Harrington’s desirability function

Downloads

Published

2024-02-28

How to Cite

Aulin, V., Rogovskii, I., Lyashuk, O., Titova, L., Hrynkiv, A., Mironov, D., Volianskyi, M., Rogatynskyi, R., Solomka, O., & Lysenko, S. (2024). Comprehensive assessment of technical condition of vehicles during operation based on Harrington’s desirability function. Eastern-European Journal of Enterprise Technologies, 1(3 (127), 37–46. https://doi.org/10.15587/1729-4061.2024.298567

Issue

Section

Control processes