Energy, exergy and environmental assessment of a cascade refrigeration system with internal heat exchanger based on eco-friendly refrigerants

##plugins.themes.academic_pro.article.main##

Malek Hamzaoui
Samir Tiachacht - samir.tiachacht@ummto.dz
Ali Grine
Ahmed Hadiouche

Abstract

Very low-temperature refrigeration is required in several applications, including cryogenics, pharmaceutical preservation, and ultra-low-temperature freezing. However, achieving such conditions with conventional single-stage systems is difficult because of the high compression ratios involved and the resulting energy losses. In this study, two pairs of environmentally friendly refrigerants with low Global Warming Potential (GWP), namely R744/R290 and R744/R152a, were investigated in a laminar refrigeration system equipped with an internal heat exchanger. A comprehensive parametric analysis was conducted to determine the optimal operating conditions for evaporation temperatures from -55°C to -25°C and condensation temperatures from 25°C to 60°C. The Quadratic Interpolation Optimization (QIO) method was used to determine the optimal intermediate temperature, , for enhancing energy efficiency, exergy performance, and environmental sustainability. The results show that, under all condensing conditions, R744/R290 is more advantageous at very low evaporation temperatures from both thermodynamic and environmental perspectives. Meanwhile, R744/R152a provides better overall performance when the evaporation temperature is ≥ -30°C.

Keywords

cascade refrigeration system; COP; environmental analysis; exergy analysis; optimization; TEWI

How to Cite
Hamzaoui, M., Tiachacht, S., Grine, A., & Hadiouche, A. (2026). Energy, exergy and environmental assessment of a cascade refrigeration system with internal heat exchanger based on eco-friendly refrigerants. HCMCOU Journal of Science - Advances in Computational Structures, 16(1), 7–29. https://doi.org/10.46223/HCMCOUJS.acs.en.16.1.80.2026

References

  1. Abdollahzadeh, B., Khodadadi, N., Barshandeh, S., Trojovský, P., Gharehchopogh, F. S., El-kenawy, E.-S. M., Abualigah, L., & Mirjalili, S. (2024). Puma optimizer (PO): A novel metaheuristic optimization algorithm and its application in machine learning. Cluster Computing, 27(4), 5235-5283. https://doi.org/10.1007/s10586-023-04221-5
  2. Adebayo, V., Abid, M., Adedeji, M., Dagbasi, M., & Bamisile, O. (2021). Comparative thermodynamic performance analysis of a cascade refrigeration system with new refrigerants paired with CO2. Applied Thermal Engineering, 184, Article 116286. https://doi.org/10.1016/j.applthermaleng.2020.116286
  3. Bencharif, M., Nesreddine, H., Perez, S. C., Poncet, S., & Zid, S. (2020). The benefit of droplet injection on the performance of an ejector refrigeration cycle working with R245fa. International Journal of Refrigeration, 113, 276-287. https://doi.org/https://doi.org/10.1016/j.ijrefrig.2020.01.020
  4. Bhattacharyya, S., Garai, A., & Sarkar, J. (2009). Thermodynamic analysis and optimization of a novel N2O-CO2 cascade system for refrigeration and heating. International Journal of Refrigeration, 32(5), 1077-1084. https://doi.org/10.1016/j.ijrefrig.2008.09.008
  5. Cabello, R., Sánchez, D., Llopis, R., Catalán, J., Nebot-Andrés, L., & Torrella, E. (2017). Energy evaluation of R152a as drop in replacement for R134a in cascade refrigeration plants. Applied Thermal Engineering, 110, 972-984. https://doi.org/10.1016/j.applthermaleng.2016.09.010
  6. Davoodi, V., Kazemiani-Najafabadi, P., & Amiri Rad, E. (2022). Presenting a power and cascade cooling cycle driven using solar energy and natural gas. Renewable Energy, 186, 802-813. https://doi.org/10.1016/j.renene.2022.01.031
  7. de Paula, C. H., Duarte, W. M., Rocha, T. T. M., de Oliveira, R. N., & Maia, A. A. T. (2020). Optimal design and environmental, energy and exergy analysis of a vapor compression refrigeration system using R290, R1234yf, and R744 as alternatives to replace R134a. International Journal of Refrigeration, 113, 10-20. https://doi.org/10.1016/j.ijrefrig.2020.01.012
  8. Gado, M. G., Megahed, T. F., Ookawara, S., Nada, S., & El-Sharkawy, I. I. (2022). Potential application of cascade adsorption-vapor compression refrigeration system powered by photovoltaic/thermal collectors. Applied Thermal Engineering, 207, Article 118075. https://doi.org/10.1016/j.applthermaleng.2022.118075
  9. Hamzaoui, M., Aidoun, Z., Nesreddine, H., & Tiachacht, S. (2024). Optimisation of a cascade refrigeration system with natural refrigerants, based on nature-inspired algorithms. Arabian Journal for Science and Engineering, 49(5), 7701-7730. https://doi.org/10.1007/s13369-023-08689-6
  10. Hamzaoui, M., Nesreddine, H., Aidoun, Z., & Balistrou, M. (2018). Experimental study of a low grade heat driven ejector cooling system using the working fluid R245fa. International Journal of Refrigeration, 86, 388-400. https://doi.org/10.1016/j.ijrefrig.2017.11.018
  11. Hamzaoui, M., Tiachacht, S., & Hadiouche, A. (2024). Optimization of a three-stage cascade refrigeration system operating with natural refrigerants to produce low temperatures by applying a bio-inspired method. Thermal Science and Engineering Progress, 50, Article 102519. https://doi.org/10.1016/j.tsep.2024.102519
  12. Han, X. H., Wang, Q., Zhu, Z. W., & Chen, G. M. (2007). Cycle performance study on R32/R125/R161 as an alternative refrigerant to R407C. Applied Thermal Engineering, 27(14), 2559-2565. https://doi.org/10.1016/j.applthermaleng.2007.01.034
  13. Houssein, E. H., Oliva, D., Samee, N. A., Mahmoud, N. F., & Emam, M. M. (2023). Liver cancer algorithm: A novel bio-inspired optimizer. Computers in Biology and Medicine, 165, Article 107389. https://doi.org/10.1016/j.compbiomed.2023.107389
  14. Kilicarslan, A., & Hosoz, M. (2010). Energy and irreversibility analysis of a cascade refrigeration system for various refrigerant couples. Energy Conversion and Management, 51(12), 2947-2954. https://doi.org/10.1016/j.enconman.2010.06.037
  15. Kumar, S., Gahlot, P., & Kumar, S. (2024). Energy, exergy and economical analysis of N2O based cascade refrigeration system for ultralow temperature cooling applications using different eco-friendly refrigerants in high temperature cycle. Results in Engineering, 22, Article 102259. https://doi.org/10.1016/j.rineng.2024.102259
  16. Kumar, S., Gahlot, P., & Kumar, S. (2026). Energy, exergy, environmental, and economical (4E) analysis of modified cascade refrigeration cycles for ultra-low temperature cooling applications. Journal of Thermal Analysis and Calorimetry. Advance online publication. https://doi.org/10.1007/s10973-025-15249-7
  17. Lemmon, E. W., Huber, M. L., & McLinden, M. O. (2007). NIST standard reference database 23: Reference fluid thermodynamic and transport properties-REFPROP, version 8.0. National Institute of Standards and Technology.
  18. Liu, X., Li, J., Hou, K., Wang, S., & He, M. (2022). New environment friendly working pairs of dimethyl ether and ionic liquids for absorption refrigeration with high COP. International Journal of Refrigeration, 134, 159-167. https://doi.org/10.1016/j.ijrefrig.2021.11.031
  19. Lizarte, R., Palacios-Lorenzo, M. E., & Marcos, J. D. (2017). Parametric study of a novel organic Rankine cycle combined with a cascade refrigeration cycle (ORC-CRS) using natural refrigerants. Applied Thermal Engineering, 127, 378-389. https://doi.org/10.1016/j.applthermaleng.2017.08.063
  20. Logesh, K., Baskar, S., Azeemudeen, M., Praveen Reddy, B., & Venkata Subba Sai Jayanth, G. (2019). Analysis of cascade vapour refrigeration system with various refrigerants. Materials Today: Proceedings, 18, 4659-4664. https://doi.org/10.1016/j.matpr.2019.07.450
  21. Ma, X., Fang, Y., Dai, Q., He, Z., Yang, J., Liu, J., & Zou, H. (2025). Experimental evaluation of a high temperature cascade heat pump based on refrigerant charge. Case Studies in Thermal Engineering, 73, Article 106573. https://doi.org/10.1016/j.csite.2025.106573
  22. Mirjalili, S. (2015). The Ant Lion optimizer. Advances in Engineering Software, 83, 80-98. https://doi.org/10.1016/j.advengsoft.2015.01.010
  23. Nesreddine, H., Bendaoud, A., Aidoun, Z., Ouzzane, M., & Le Lostec, B. (2015, August 16-22). Experimental investigation of an ejector-compression cascade system activated with low-grade waste heat [Paper presentation]. 24th IIR International Congress of Refrigeration, Yokohama, Japan.
  24. Pektezel, O., & Ozdemir, S. N. (2025). Performance optimization of new generation R290 and R1234yf refrigerants: A response surface methodology approach. Applied Thermal Engineering, 269, Article 125927. https://doi.org/10.1016/j.applthermaleng.2025.125927
  25. Salhi, K., Korichi, M., & Ramadan, K. M. (2018). Thermodynamic and thermo-economic analysis of compression-absorption cascade refrigeration system using low-GWP HFO refrigerant powered by geothermal energy. International Journal of Refrigeration, 94, 214-229. https://doi.org/10.1016/j.ijrefrig.2018.03.017
  26. Sun, Z., Liang, Y., Liu, S., Ji, W., Zang, R., Liang, R., & Guo, Z. (2016). Comparative analysis of thermodynamic performance of a cascade refrigeration system for refrigerant couples R41/R404A and R23/R404A. Applied Energy, 184, 19-25. https://doi.org/10.1016/j.apenergy.2016.10.014
  27. Sun, Z., Wang, Q., Xie, Z., Liu, S., Su, D., & Cui, Q. (2019). Energy and exergy analysis of low GWP refrigerants in cascade refrigeration system. Energy, 170, 1170-1180. https://doi.org/10.1016/j.energy.2018.12.055
  28. Udroiu, C.-M., Giménez-Prades, P., Navarro-Esbrí, J., Barragán-Cervera, Á., & Mota-Babiloni, A. (2025). Experimental evaluation of a two-stage cascade ultra-low temperature refrigeration system with internal heat exchanger using hydrocarbon pair R290/R170 and comparison with HFC baseline. Applied Thermal Engineering, 274, Article 126679. https://doi.org/10.1016/j.applthermaleng.2025.126679
  29. Ye, W., Liu, Y., Yan, Y., Hu, L., Su, M., & Liu, Y. (2026). Performance analysis and enhancement of cascade refrigeration systems through multi-objective grey wolf optimization algorithm. Thermal Science and Engineering Progress, 70, Article 104504. https://doi.org/https://doi.org/10.1016/j.tsep.2026.104504
  30. Zhao, W., Wang, L., Zhang, Z., Mirjalili, S., Khodadadi, N., & Ge, Q. (2023). Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems. Computer Methods in Applied Mechanics and Engineering, 417, Article 116446. https://doi.org/10.1016/j.cma.2023.116446

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)