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EXPERIMENTAL STUDY ON REFRIGERATION SYSTEM'S PERFORMANCE OF THE REFRIGERATOR TRUCK USING R404A REFRIGERANT

ABSTRACT
A refrigerated system experimental bench using R404A as the refrigerant was built to address the current issues of high compressor discharge temperature and poor refrigeration performance of refrigerated systems for cold storage. The effects of compressor speed and temperature changes within the storage on the main refrigeration performance parameters of the system were studied and analyzed. The results show that when the rotational speed is increased from 2500-4500 rpm under the conditions of 32°C outside and 0°C inside, the highest system exhaust temperature is 84.3°C, which is lower than 90°C, and the maximum system COP is 3.86, and when the compressor speed is increased from 3500 rpm under the conditions of -5°C to 5°C, the system exhaust temperature is lower than 90°C. The COP can reach 2.74, especially at -5°C.
KEYWORDS
PAPER SUBMITTED: 2022-01-10
PAPER REVISED: 2023-03-08
PAPER ACCEPTED: 2023-05-19
PUBLISHED ONLINE: 2024-05-18
DOI REFERENCE: https://doi.org/10.2298/TSCI2403033S
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2024, VOLUME 28, ISSUE Issue 3, PAGES [2033 - 2041]
REFERENCES
  1. Kasahun, A. W., et al., Vaccine Cold Chain Management Practice and Associated Factors Among Health Professionals in Ethiopia: Systematic Review and Meta-Analysis, Journal of Pharmaceutical Policy and Practice, 16 (2023), 1, 55
  2. Adekomaya, O., et al., Sustaining the Shelf Life of Fresh Food in Cold Chain - A Burden on the Environment, Alexandria Engineering Journal, 55 (2016), 2, pp. 1359-1365
  3. Elbel, S., et al., Flash Gas Bypass for Improving the Performance of Transcritical R744 Systems that Use Micro-channel Evaporators, International Journal of Refrigeration, 27 (2004), 7, pp. 724-735
  4. Wang, X., et al., Two-Stage Heat Pump System with Vapor-Injected Scroll Compressor Using R410A as a Refrigerant, International Journal of Refrigeration, 32 (2009), 6, pp. 1442-1451
  5. Cui, S. Q., et al., Experimental Research on the Application of Medium Pressure Air Supplement Technology in Passenger Car Air Conditioners (in Chinese), Thermal Science and Technology, 18 (2019), 5, pp. 417-422
  6. Xu, B., et al., Experimental Investigation of the Performance of Micro-channel Heat Exchangers with a New Type of Fin Under Wet and Frosting Conditions, Applied Thermal Engineering, 89 (2015), pp. 444-458
  7. Kwon, B., et al., High Power Density Air-Cooled Micro-channel Heat Exchanger, International Journal of Heat and Mass Transfer, 118 (2018), Mar., pp. 1276-1283
  8. Ning, J. H., et al., Analysis and Comparison of Cascade Refrigeration Systems with CO2 as the Low-Temperature Cycle Working Fluid (in Chinese), Thermal Science and Technology, 14 (2015), 2, pp. 155-160
  9. Zhang, X. C., et al., Experimental Research on Vapor Jet Quasi-Two-Stage Compression Refrigeration System (in Chinese), Thermal Science and Technology, 18 (2019), 1, pp. 29-34
  10. Dong, H., et al., The Influence of Compressor Frequency on the Performance of Alternate Cooling Cold Storage (in Chinese), Thermal Science and Technology, 20 (2021), 1, pp. 86-91
  11. Wu, Y. P., et al., Performance Study of Solar Jet/Compression Composite Refrigeration Cycle (in Chinese), Thermal Science and Technology, 19 (2020), 5, pp. 503-510
  12. Xiong, T., et al., Research Status and Prospect of Two-Phase Flow Distribution in Micro-channel Heat Exchanger (in Chinese), Journal of Refrigeration, 42 (2021), 1, pp. 23-35
  13. Luo, H. F., Comparison of the Characteristics of R410a, R32, R290, R134a and R404a in Two-Stage Compression Refrigeration Cycle (in Chinese), Refrigeration Technology, 42 (2019), 1, pp. 53-56
  14. He, L. J., et al., Experimental Investigation on the Effect of Equipment Structure on Refrigeration Performance of Combined Magnetic Refrigeration System, Thermal Science, 26 (2022), 5B, pp. 4401-4411
  15. Mohanraj, M., et al., Applications of Artificial Neural Networks for Refrigeration, Air-Conditioning and Heat Pump Systems -A review, Renewable & Sustainable Energy Reviews, 16 (2012), 2, pp. 1340-1358
  16. Wang, S. Q., et al., Skeletal Maturity Recognition Using a Fully Automated System with Convolutional Neural Networks, IEEE Access, 6 (2018), July, pp. 29979-29993
  17. Wu, K., et al., 3D Convolutional Neural Network for Regional Precipitation Nowcasting, Journal of Image and Signal Processing, 7 (2018), 4, pp. 200-212
  18. Kuo, P. H., et al., Novel Fractional-Order Convolutional Neural Network Based Chatter Diagnosis Approach in Turning Process with Chaos Error Mapping, Non-linear Dynamics, 111 (2023), 8, pp. 7547-7564
  19. Kuo, P. H., et al., A Thermal Displacement Prediction System with an Automatic LRGTVAC-PSO Optimized Branch Structured Bidirectional GRU Neural Network, IEEE Sensors Journal, 23 (2023), 12, pp. 12574-12586
  20. Wang, S. Q., et al., An Ensemble-Based Densely-Connected Deep Learning System for Assessment of Skeletal Maturity, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52 (2020), 1, pp. 426-437
  21. Wang, S. Q., et al., Prediction of Myelopathic Level in Cervical Spondylotic Myelopathy Using Diffusion Tensor Imaging, Journal of Magnetic Resonance Imaging, 41 (2015), 6, pp. 1682-1688
  22. Hu, S. Y., et al., Medical Image Reconstruction Using Generative Adversarial Network for Alzheimer Disease Assessment with Class-Imbalance Problem, Proceedings, IEEE 6th International Conference on Computer and Communications (ICCC), Chengdu, China, 2020, pp. 1323-1327

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence