Análisis de la salud, contaminación y desgaste del lubricante de motor. Caso: Bus Inter aeroportuario.

Authors

DOI:

https://doi.org/10.26423/njb3gs46

Keywords:

monitoreo bajo condición, ingeniería de mantenimiento, tribología, motor encendido por compresión.

Abstract

El estudio se orientó en evaluar en condiciones operativas reales, la salud, la contaminación y el desgaste del aceite de motor de un bus inter aeroportuario; se planteó que, con un monitoreo sistemático y correcciones operacionales, las propiedades del lubricante se mantendrían dentro de límites permisibles. Se aplicó un diseño experimental descriptivo con tres muestreos cada 250 h (0–750 h). Las pruebas de laboratorio analizaron viscosidad (ASTM D445), FTIR para oxidación, sulfatación, nitración y contaminantes (ASTM E2412), ICP para metales y aditivos (ASTM D5185) y agua por Karl Fischer (ASTM D4928), y en el análisis de datos se usaron límites permisibles y criterios estadísticos (ASTM D7720). Los resultados mostraron disminución de viscosidad del 13–14% en relación a la. línea base, en la oxidación se mantuvo en 16; la sulfatación, alta y estable en 21; la nitración, 6–7, todas bajo límites establecidos; a la vez, no se registró ningún contaminante en las muestras. En el caso de las partículas se detectó Fe=3–4 ppm, Al=0–1 ppm y Cu=1 ppm, con Mo=41 ppm por aditivo y descenso controlado de Ca–P–Zn. Se concluye que el aceite mantuvo su capacidad protectora dentro del periodo de medición. Finalmente, el mantenimiento basado en condición es viable lo que permite optimizar el intervalo de cambio del aceite con impacto posibles en costos, confiabilidad y cumplimiento ambiental.

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References

1. RAPOSO, Hugo, FARINHA, José Torres, FONSECA, Inácio and GALAR, Diego. Predicting condition based on oil analysis – A case study. Tribology International. 1 July 2019. Vol. 135, p. 65–74. DOI 10.1016/j.triboint.2019.01.041. DOI: https://doi.org/10.1016/j.triboint.2019.01.041

2. WAKIRU, James M., PINTELON, Liliane, MUCHIRI, Peter N. and CHEMWENO, Peter K. A review on lubricant condition monitoring information analysis for maintenance decision support. Mechanical Systems and Signal Processing. 1 March 2019. Vol. 118, p. 108–132. DOI 10.1016/j.ymssp.2018.08.039. DOI: https://doi.org/10.1016/j.ymssp.2018.08.039

3. ISLAM SAZZAD, Md Rahatul, RAHMAN, Md Mizanur, HASSAN, Tafsirul, AL RIFAT, Abdullah, AL MAMUN, Abdullah, ADIB, Abidur Rahman, MERAZ, Redoy Masum and AHMED, Minhaz. Advancing sustainable lubricating oil management: Re-refining techniques, market insights, innovative enhancements, and conversion to fuel. Heliyon. Online. 30 October 2024. Vol. 10, no. 20, p. e39248. [Accessed 9 June 2025]. DOI 10.1016/J.HELIYON. 2024.E39248. DOI: https://doi.org/10.1016/j.heliyon.2024.e39248

4. HASANNUDDIN, A. K., WIRA, J. Y., SARAH, S., WAN SYAIDATUL AQMA, W. M.N., ABDUL HADI, A. R., HIROFUMI, N., AIZAM, S. A., AIMAN, M. A.B., WATANABE, S., AHMAD, M. I. and AZRIN, M. A. Performance, emissions and lubricant oil analysis of diesel engine running on emulsion fuel. Energy Conversion and Management. 1 June 2016. Vol. 117, p. 548–557. DOI 10.1016/J.ENCONMAN.2016.03.057. DOI: https://doi.org/10.1016/j.enconman.2016.03.057

5. VYAVHARE, Kimaya, BAGI, Sujay, PATEL, Mihir and ASWATH, Pranesh B. Impact of Diesel Engine Oil Additives-Soot Interactions on Physiochemical, Oxidation, and Wear Characteristics of Soot. Energy and Fuels. 16 May 2019. Vol. 33, no. 5, p. 4515–4530. DOI 10.1021/ACS.ENERGYFUELS.8B03841. DOI: https://doi.org/10.1021/acs.energyfuels.8b03841

6. KONTOU, A., SOUTHBY, M., MORGAN, N. and SPIKES, H. A. Influence of Dispersant and ZDDP on Soot Wear. Tribology Letters. 1 December 2018. Vol. 66, no. 4. DOI 10.1007/S11249-018-1115-X. DOI: https://doi.org/10.1007/s11249-018-1115-x

7. KIRKBY, Thomas, SMITH, Joshua J., BERRYMAN, Jacqueline, FOWELL, Mark and REDDYHOFF, Tom. Soot wear mechanisms in heavy-duty diesel engine contacts. Wear. 15 July 2023. Vol. 524–525. DOI 10.1016/j.wear.2023.204733. DOI: https://doi.org/10.1016/j.wear.2023.204733

8. RAPOSO, Hugo, FARINHA, José Torres, FONSECA, Inácio and FERREIRA, L. Andrade. Condition monitoring with prediction based on diesel engine oil analysis: A case study for urban buses. Actuators. 2019. Vol. 8, no. 1. https://doi.org/10.3390/act8010014. DOI: https://doi.org/10.3390/act8010014

9. FERNÁNDEZ-FEAL, M. C., FERNÁNDEZ-FEAL, M. L., SÁNCHEZ-FERNÁNDEZ, L. R. and PÉREZ-PRADO, J. R. Study of Metal Concentration in Lubricating Oil with Predictive Purposes. Current Journal of Applied Science and Technology. Online. 15 June 2018. Vol. 27, no. 6, p. 1–12. [Accessed 17 June 2025]. DOI 10.9734/CJAST/2018/41472. DOI: https://doi.org/10.9734/CJAST/2018/41472

10. OMIYA, Takeru, HANYUDA, Kiyoshi and NAGATOMI, Eiji. Predicting engine oil degradation across diverse vehicles and identifying key factors. Mechanical Systems and Signal Processing. Online. 15 April 2025. Vol. 229, p. 112524. [Accessed 12 June 2025]. DOI 10.1016/J.YMSSP.2025.112524. DOI: https://doi.org/10.1016/j.ymssp.2025.112524

11. CAO, Wei, DONG, Guangneng, XIE, You Bai and PENG, Zhongxiao. Prediction of wear trend of engines via on-line wear debris monitoring. Tribology International. 1 April 2018. Vol. 120, p. 510–519. DOI 10.1016/j.triboint.2018.01.015. DOI: https://doi.org/10.1016/j.triboint.2018.01.015

12. MACIÁN, V., TORMOS, B., OLMEDA, P. and MONTORO, L. Analytical approach to wear rate determination for internal combustion engine condition monitoring based on oil analysis. Tribology International. October 2003. Vol. 36, no. 10, p. 771–776. DOI 10.1016/S0301-679X(03)00060-4. DOI: https://doi.org/10.1016/S0301-679X(03)00060-4

13. VALIŠ, David, ŽÁK, Libor, POKORA, Ondřej and LÁNSKÝ, Petr. Perspective analysis outcomes of selected tribodiagnostic data used as input for condition based maintenance. Reliability Engineering and System Safety. 1 January 2016. Vol. 145, p. 231–242. DOI 10.1016/j.ress.2015.07.026. DOI: https://doi.org/10.1016/j.ress.2015.07.026

14. ASTM INTERNACIONAL. Standard Test Method for Kinematic Viscosity of Transparent and Opaque Liquids and Calculation of Dynamic Viscosity (ASTM D445-24) Online. West Conshohocken, PA : ASTM International, 2024. [Accessed 25 September 2025].

15. KIRKBY, Thomas, PACINO, Andrea, SMITH, Joshua J., FOWELL, Mark, BERRYMAN, Jacqueline, FRENNFELT, Claes, LA ROCCA, Antonino and REDDYHOFF, Tom. Correlating wear with the lubricant properties of heavy-duty diesel engine oils. Tribology International. Online. 1 November 2024. Vol. 199, p. 110018. [Accessed 15 June 2025]. DOI 10.1016/J.TRIBOINT.2024.110018. DOI: https://doi.org/10.1016/j.triboint.2024.110018

16. WEI, Lei, DUAN, Haitao, JIA, Dan, JIN, Yongliang, CHEN, Song, LIU, Lian, LIU, Jianfang, SUN, Xianming and LI, Jian. Motor oil condition evaluation based on on-board diagnostic system. Friction. 1 February 2020. Vol. 8, no. 1, p. 95–106. DOI 10.1007/S40544-018-0248-0. DOI: https://doi.org/10.1007/s40544-018-0248-0

17. SEJKOROVÁ, Marie, HURTOVÁ, Ivana, JILEK, Petr, NOVÁK, Martin and VOLTR, Ondřej. Study of the effect of physicochemical degradation and contamination of motor oils on their lubricity. Coatings. 1 January 2021. Vol. 11, no. 1, p. 1–18. DOI 10.3390/COATINGS11010060. DOI: https://doi.org/10.3390/coatings11010060

18. FURCH, Jan and JELÍNEK, Josef. Design of a tribotechnical diagnostics model for determining the technical condition of an internal combustion engine during its life cycle. Eksploatacja i Niezawodnosc. 2022. Vol. 24, no. 3, p. 437–445. DOI 10.17531/EIN.2022.3.5. DOI: https://doi.org/10.17531/ein.2022.3.5

19. TORMOS, Bernardo, PLA, Benjamín, SÁNCHEZ-MÁRQUEZ, Ramón and CARBALLO, Jose Luis. Explainable AI Using On-Board Diagnostics Data for Urban Buses Maintenance Management: A Study Case. Information 2025, Vol. 16, Page 74. Online. 21 January 2025. Vol. 16, no. 2, p. 74. [Accessed 28 September 2025]. DOI 10.3390/INFO16020074. DOI: https://doi.org/10.3390/info16020074

20. SEJKOROVÁ, Marie, KUČERA, Marián, HURTOVÁ, Ivana and VOLTR, Ondřej. Application of FTIR-ATR spectrometry in conjunction with multivariate regression methods for viscosity prediction of worn-out motor oils. Applied Sciences (Switzerland). 1 May 2021. Vol. 11, no. 9. DOI: 10.3390/APP11093842. DOI: https://doi.org/10.3390/app11093842

21. ANTAMBA GUASGUA, Jaime Fernando, REMACHE CHIMBO 2, Álvaro, VALLEJO, Vanessa and CORRALES, Fabricio. Salud del lubricante y comportamiento de los aditivos en vehículos tipo turismo. Revista Científica y Tecnológica UPSE (RCTU). Online. 7 December 2021. Vol. 8, no. 2, p. 33–39. [Accessed 13 June 2025]. DOI 10.26423/RCTU.V8I2.620. DOI: https://doi.org/10.26423/rctu.v8i2.620

22. TORMOS MARTÍNEZ, Bernardo. Diagnóstico de motores diesel mediante el análisis del aceite usado. Online. Reverte, 2013. ISBN 8429147020. Available from: https://books.google.com/books/about/Diagn%C3%B3stico_de_motores_diesel_mediante.html?hl=es&id=DqJuqL_UzjkCEl

23. IASA. CAT DEO-ULS Online. 2025. [Accessed 25 September 2025]. Available from: https://iasaglobal.com/wp-content/fichas-tecnicas/CAT-DEO-ULS-15W-40-CK-4.pdf

24. ASTM INTERNACIONAL. Guide for Statistically Evaluating Measurand Alarm Limits when Using Oil Analysis to Monitor Equipment and Oil for Fitness and Contamination Online. West Conshohocken, PA : ASTM International, 2021. [Accessed 25 September 2025].

25. MACIÁN, Vicente, TORMOS, Bernardo, RUIZ, Santiago and MIRÓ, Guillermo. Low viscosity engine oils: Study of wear effects and oil key parameters in a heavy duty engine fleet test. Tribology International. Online. 1 February 2016. Vol. 94, p. 240–248. [Accessed 13 June 2025]. DOI 10.1016/J.TRIBOINT.2015.08.028. DOI: https://doi.org/10.1016/j.triboint.2015.08.028

Published

2025-12-26

Issue

Section

Original Articles

How to Cite

Análisis de la salud, contaminación y desgaste del lubricante de motor. Caso: Bus Inter aeroportuario. (2025). UPSE Scientific and Technological Magazine, 12(2), 80-89. https://doi.org/10.26423/njb3gs46