Evolución bibliométrica del análisis termodinámico del ciclo Otto en motores urbanos livianos y su impacto en eficiencia energética

Victor Pachacama-Nasimba; Robinson Alay-Romero; Carlos Ulcuango-Moreno; Cristian Alvarez-Veintimilla; Darwin Chele-Sancán

doi:10.37431/conectividad.v7i2.468

Autores/as

Victor Pachacama-Nasimba Universidad Técnica Estatal de Quevedo https://orcid.org/0000-0001-6315-6641
Robinson Alay-Romero Instituto Superior Tecnológico La Maná https://orcid.org/0009-0001-5760-429X
Carlos Ulcuango-Moreno Instituto Superior Tecnológico La Maná https://orcid.org/0000-0002-5657-1449
Cristian Alvarez-Veintimilla Instituto Superior Tecnológico La Maná https://orcid.org/0009-0007-4337-5346
Darwin Chele-Sancán Universidad Internacional del Ecuador https://orcid.org/0000-0001-6405-2713

DOI:

https://doi.org/10.37431/conectividad.v7i2.468

Palabras clave:

Ciclo Otto, Motor de combustión interna, Rendimiento termodinámico, Eficiencia energética, Eficiencia de combustible

Resumen

El transporte terrestre demanda estrategias urgentes de descarbonización, situando la eficiencia de los motores de encendido por chispa como una prioridad tecnológica. Este estudio examina la evolución y estructura intelectual de la literatura sobre el análisis termodinámico del ciclo Otto en vehículos urbanos livianos. Mediante un enfoque bibliométrico mixto basado en 137 artículos de Scopus (2010-2025) y procesado bajo protocolos PRISMA, se integraron técnicas cuantitativas de desempeño con mapeo científico de redes de colaboración y contenido. Los resultados revelan un crecimiento productivo sostenido liderado por Europa y Asia, identificando una transición estructural en los frentes de investigación: el campo ha evolucionado desde la idealización de ciclos estándar hacia modelos termodinámicos irreversibles y de tiempo finito aplicados a la combustión de nuevos vectores energéticos. El análisis de co-ocurrencia demuestra que el hidrógeno y el amoníaco han desplazado a la gasolina como palabras clave centrales vinculadas a la eficiencia exergética. Se concluye que la investigación académica reposiciona al motor Otto no como una tecnología obsoleta, sino como una tecnología de transición necesaria y resiliente para la economía del hidrógeno, aunque se requiere mayor integración con sistemas híbridos para maximizar su sostenibilidad en entornos urbanos complejos

Citas

Ahmadi, M. H., Ahmadi, M. A., Mehrpooya, M., Feidt, M., & Rosen, M. A. (2016). Optimal design of an Otto cycle based on thermal criteria. Mechanics and Industry, 17(1). https://doi.org/10.1051/meca/2015049 DOI: https://doi.org/10.1051/meca/2015049

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007 DOI: https://doi.org/10.1016/j.joi.2017.08.007

Broatch, A., Novella, R., Pastor, J. M., Gomez-Soriano, J., & Senecal, P. K. (2022). Engine optimization using computational fluid dynamics and genetic algorithms. En Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines (pp. 71–101). Elsevier. https://doi.org/10.1016/B978-0-323-88457-0.00004-7 DOI: https://doi.org/10.1016/B978-0-323-88457-0.00004-7

Caton, J. A. (2018). The thermodynamics of internal combustion engines: Examples of insights. Inventions, 3(2), 33. https://doi.org/10.3390/inventions3020033 DOI: https://doi.org/10.3390/inventions3020033

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 DOI: https://doi.org/10.1016/j.jbusres.2021.04.070

European Commission. (2022). Proposal for a regulation on type-approval of motor vehicles with respect to their emissions from light-duty vehicles (Euro 7). European Commission.

Fasulo, G., Bozza, F., Malfi, E., & Teodosio, L. (2021). Development of a 0D multi-zone model for fast and accurate prediction of homogeneous charge compression ignition (HCCI) engine. E3S Web of Conferences, 312. https://doi.org/10.1051/e3sconf/202131207006 DOI: https://doi.org/10.1051/e3sconf/202131207006

Gómez Montoya, J. P. (2025). A thermodynamic principle for engine design: Exergy optimization of spark-ignition engines fueled by hydrogen-enriched biogas based on otto cycle foundations. Applied Thermal Engineering, 280. https://doi.org/10.1016/j.applthermaleng.2025.128376 DOI: https://doi.org/10.1016/j.applthermaleng.2025.128376

Gómez Montoya, J. P., Amell, A. A., & Olsen, D. B. (2022). Phenomenological analysis of the combustion of gaseous fuels to measure energy quality and capacity to produce work in SI engines, part 2. Journal of Engineering for Gas Turbines and Power, 144(5). https://doi.org/10.1115/1.4053941 DOI: https://doi.org/10.1115/1.4052648

Gomez Montoya, J. P., & Olsen, D. B. (2024). A novel theory for designing SI engines based on exergy efficiency, entropy, octane rating, and fuels’ physicochemical properties for Otto cycles. Energy Conversion and Management, 322. https://doi.org/10.1016/j.enconman.2024.119144 DOI: https://doi.org/10.1016/j.enconman.2024.119144

Gong, C., Deng, B., Wang, S., Su, Y., Gao, Q., & Liu, X. (2008). Investigation on firing behavior of the spark-ignition engine fueled with methanol, liquefied petroleum gas (LPG), and methanol/LPG during cold start. Energy and Fuels, 22(6), 3779–3784. https://doi.org/10.1021/ef800471h DOI: https://doi.org/10.1021/ef800471h

Gong, C. M., Li, J., Li, J. K., Li, W. X., Gao, Q., & Liu, X. J. (2011). Effects of ambient temperature on firing behavior and unregulated emissions of spark-ignition methanol and liquefied petroleum gas/methanol engines during cold start. Fuel, 90(1), 19–25. https://doi.org/10.1016/j.fuel.2010.08.012 DOI: https://doi.org/10.1016/j.fuel.2010.08.012

Han, T., Singh, R., Lavoie, G., Wooldridge, M., & Boehman, A. (2020). Multiple injection for improving knock, gaseous and particulate matter emissions in direct injection SI engines. Applied Energy, 262. https://doi.org/10.1016/j.apenergy.2020.114578 DOI: https://doi.org/10.1016/j.apenergy.2020.114578

Heywood, J. B. (1988). Internal combustion engine fundamentals. En Choice Reviews Online (2nd ed., Vol. 26, Número 02). McGraw-Hill Education. https://doi.org/10.5860/choice.26-0943 DOI: https://doi.org/10.5860/CHOICE.26-0943

Hu, Q., Xu, L., & Goodman, E. (2009). Non-even spread NSGA-II and its application to conflicting multi-objective compatible control. 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC’09, 223–230. https://doi.org/10.1145/1543834.1543866 DOI: https://doi.org/10.1145/1543834.1543866

International Energy Agency. (2023). CO2 Emissions in 2022. En CO2 Emissions in 2022. IEA. https://doi.org/10.1787/12ad1e1a-en DOI: https://doi.org/10.1787/12ad1e1a-en

Kosloff, R., & Rezek, Y. (2017). The quantum harmonic otto cycle. Entropy, 19(4). https://doi.org/10.3390/e19040136 DOI: https://doi.org/10.3390/e19040136

Kumar, S., Sharma, P., & Pal, K. (2023). Application of Machine Learning Approach in Internal Combustion Engine: A Comprehensive Review. En K. A., Z. M., S. K.A., & L. H. (Eds.), Lecture Notes in Mechanical Engineering (pp. 165–178). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-8517-1_12 DOI: https://doi.org/10.1007/978-981-19-8517-1_12

Lee, S., Kim, Y., Lee, J., Kim, K., Lee, S., Min, K., & Oh, S. (2023). Energy and exergy analyses of hydrogen-fueled spark ignition engine with various air excess ratios and ignition timings. Fuel, 349. https://doi.org/10.1016/j.fuel.2023.128588 DOI: https://doi.org/10.1016/j.fuel.2023.128588

Li, R., Shari, Z., & Ab Kadir, M. Z. A. (2025). A review on multi-objective optimization of building performance - Insights from bibliometric analysis. Heliyon, 11(4). https://doi.org/10.1016/j.heliyon.2025.e42480 DOI: https://doi.org/10.1016/j.heliyon.2025.e42480

Liu, J., Yu, Q., Cheng, J., Yakubu, A. U., Ye, X., & Xiong, S. (2025). Numerical study of a cold start at the ambient temperature of 243 K on methanol engine with coolant heating. Fuel, 395. https://doi.org/10.1016/j.fuel.2025.135138 DOI: https://doi.org/10.1016/j.fuel.2025.135138

Liu, X., Ji, C., Gao, B., Wang, S., & Yang, J. (2014). A quasi-dimensional model for hydrogen-enriched gasoline engines with a new laminar flame speed expression. En L. H. & Y. J. (Eds.), Energy Procedia (Vol. 61, pp. 327–330). Elsevier Ltd. https://doi.org/10.1016/j.egypro.2014.11.1117 DOI: https://doi.org/10.1016/j.egypro.2014.11.1117

Mashkour, M. A., & Ahmed, A. Y. (2020). Thermodynamic Modeling for Analysing the Performance and Emissions of Spark-Ignition Engines. Journal of Engineering and Sustainable Development, 24(2), 57–79. https://doi.org/10.31272/jeasd.24.2.5 DOI: https://doi.org/10.31272/jeasd.24.2.5

Minango, P., Zambrano, M., Suarez, C. I., & Minango, J. (2026). Deep-Learning-Based Mobile Application for Real-Time Recognition of Cultural Artifacts in Museum Environments. Applied Sciences, 16(9), 4064. https://doi.org/10.3390/app16094064 DOI: https://doi.org/10.3390/app16094064

Moradi, J., Banagar, I., Mehranfar, S., Mahmoudzadeh Andwari, A., Könnö, J., & Gharehghani, A. (2024). Advancing combustion technologies and alternative fuels in hybrid electric vehicles: a pathway to high-efficiency, low-emission propulsion systems. Future Technology, 3(4), 42–54. https://doi.org/10.55670/fpll.futech.3.4.5 DOI: https://doi.org/10.55670/fpll.futech.3.4.5

Patil, G., Pode, G., Diouf, B., & Pode, R. (2024). Sustainable Decarbonization of Road Transport: Policies, Current Status, and Challenges of Electric Vehicles. Sustainability (Switzerland), 16(18), 8058. https://doi.org/10.3390/su16188058 DOI: https://doi.org/10.3390/su16188058

Pedram, A., Kadıoğlu, S. C., Kabakçıoğlu, A., & Müstecaplıoğlu, I. E. (2023). A quantum Otto engine with shortcuts to thermalization and adiabaticity. New Journal of Physics, 25(11). https://doi.org/10.1088/1367-2630/ad0857 DOI: https://doi.org/10.1088/1367-2630/ad0857

Reitz, R. D., Ogawa, H., Payri, R., Fansler, T., Kokjohn, S., Moriyoshi, Y., Agarwal, A. K., Arcoumanis, D., Assanis, D., Bae, C., Boulouchos, K., Canakci, M., Curran, S., Denbratt, I., Gavaises, M., Guenthner, M., Hasse, C., Huang, Z., Ishiyama, T., … Zhao, H. (2020). IJER editorial: The future of the internal combustion engine. International Journal of Engine Research, 21(1), 3–10. https://doi.org/10.1177/1468087419877990 DOI: https://doi.org/10.1177/1468087419877990

Sarkar, P., Khanapuri, V. B., & Tiwari, M. K. (2025). Integrating machine learning with dynamic multi-objective optimization for real-time decision-making. Information Sciences, 690. https://doi.org/10.1016/j.ins.2024.121524 DOI: https://doi.org/10.1016/j.ins.2024.121524

Shi, S. S., Ge, Y. L., & Chen, L. G. (2022). Power density analysis and multi-objective optimization of an irreversible Otto cycle. Zhongguo Kexue Jishu Kexue/Scientia Sinica Technologica, 52(11), 1716–1728. https://doi.org/10.1360/SST-2021-0168 DOI: https://doi.org/10.1360/SST-2021-0168

United Nations. (2021). The Sustainable Development Goals Report 2021. En United Nations publication issued by the Department of Economic and Social Affairs. United Nations. https://digitallibrary.un.org/record/3932350

Wang, Y. (2020). A novel two-zone thermodynamic model for spark-ignition engines based on an idealized thermodynamic process. Energies, 13(15). https://doi.org/10.3390/en13153801 DOI: https://doi.org/10.3390/en13153801

Wang, Y., Li, Q. H., Huang, X. H., & Wu, Q. (2015). LQ/H∞ controller design for aero-engine based on improved NSGA II. Hangkong Dongli Xuebao/Journal of Aerospace Power, 30(4), 985–991. https://doi.org/10.13224/j.cnki.jasp.2015.04.027

World Health Organization. (2023). Ambient (outdoor) air pollution. WHO.

Yan, F., Xu, L., & Wang, Y. (2018). Application of hydrogen enriched natural gas in spark ignition IC engines: from fundamental fuel properties to engine performances and emissions. Renewable and Sustainable Energy Reviews, 82, 1457–1488. https://doi.org/10.1016/j.rser.2017.05.227 DOI: https://doi.org/10.1016/j.rser.2017.05.227

Zhao, J., & Xu, F. (2018). Finite-time thermodynamic modeling and a comparative performance analysis for irreversible Otto, Miller and Atkinson cycles. Entropy, 20(1). https://doi.org/10.3390/e20010075 DOI: https://doi.org/10.3390/e20010075

Zhou, J. Y. (2021). Four Common Deficiencies in the Current Thermodynamics of Internal Combustion Engines. SAE Technical Papers, 2021. https://doi.org/10.4271/2021-01-5098 DOI: https://doi.org/10.4271/2021-01-5098

Zhou, Y., Gainey, B., & Lawler, B. (2020). An ultrafast multi-zone HCCI model with Autoignition, Global reaction and Interpolation (AGI) for achieving comparable accuracy to detailed chemical kinetics models. Combustion and Flame, 221, 487–501. https://doi.org/10.1016/j.combustflame.2020.08.016 DOI: https://doi.org/10.1016/j.combustflame.2020.08.016