A Review on Applications of Fuzzy Logic Control for Refrigeration Systems
Source abstract
Abstract
The use of fuzzy logic controllers in refrigeration and air conditioning systems, RACs, has as main objective to maintain certain thermal and comfort conditions. In this sense, fuzzy controllers have proven to be a viable option for use in RACs due to their ease of implementation and their ability to integrate with other control systems and control improvements, as well as their ability to achieve potential energy savings. In this document, we present a review of the application of fuzzy controls in RACs based on vapor compression technology. Application information is discussed for each type of controller, according to its application in chillers, air conditioning systems, refrigerators, and heat pumps. In addition, this review provides detailed information on controller design, focusing on the potential to achieve energy savings; this design discusses input and output variables, number and type of membership functions, and inference rules. The future perspectives on the use of fuzzy control systems applied to RACs are shown as well. In other words, the information in this document is intended to serve as a guide for the creation of controller designs to be applied to RACs.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Building Energy and Comfort Optimization · Refrigeration and Air Conditioning Technologies · Smart Grid Energy Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Salamanca-Valle de Santiago km 3.5 + 1.8, Salamanca 36885, CP, Mexico
Institute in Mechanical Engineering, Federal University of Itajubá (UNIFEI), Av. BPS, Itajubá 37500903, CEP, Brazil
References (76)
Show source-provided references
1. Dupont, J.L., Domanski, P., Lebrun, P., and Ziegler, P. (2019). The Role of Refrigeration in the Global Economy (2019), 38th Note on Refrigeration Technologies, IIF-IIR.
2. Overview of low GWP mixtures for the replacement of HFC refrigerants: R134a, R404A and R410A Étude des mélanges à faible PRP pour le remplacement des frigorigénes HFC10.1016/j.ijrefrig.2019.11.012 ↗
3. Potential of nanorefrigerant and nanolubricant on energy saving in refrigeration system—A review10.1016/j.rser.2016.11.207 ↗
4. Characterization of cooling loads in the wine industry and novel seasonal indicator for reliable assessment of energy saving through retrofit of chillers10.1016/j.apenergy.2020.114856 ↗
5. Performance improvement and energy consumption reduction in refrigeration systems using phase change material (PCM)10.1016/j.applthermaleng.2018.07.068 ↗
6. A review on expanders and their performance in vapour compression refrigeration systems10.1016/j.ijrefrig.2019.06.019 ↗
7. Thermal performance of skin-type, hot-wall condensers, Part II: Design guidelines for household applications10.1016/j.ijrefrig.2019.11.011 ↗
8. Achieving better energy-efficient air conditioning—A review of technologies and strategies10.1016/j.apenergy.2012.10.037 ↗
9. A review of control methodologies for vapor compression and absorption heat pumps10.1016/j.ijrefrig.2018.08.026 ↗
10. Empirical modeling and robust control of a novel meso-scale vapor compression refigeration system (mVCRS)10.1016/j.ijrefrig.2017.02.027 ↗
11. A hybrid approach to thermal building modelling using a combination of Gaussian processes and grey-box models10.1016/j.enbuild.2018.01.039 ↗
12. Zero Gradient Control for R-744 refrigeration cycles10.1016/j.ijrefrig.2019.05.041 ↗
13. Suboptimal hierarchical control strategy to improve energy efficiency of vapour-compression refrigeration systems10.1016/j.applthermaleng.2017.06.135 ↗
14. Heat current method for analysis and optimization of a refrigeration system for aircraft environmental control system10.1016/j.ijrefrig.2019.06.004 ↗
15. Model-based predictive control for optimal MicroCSP operation integrated with building HVAC systems10.1016/j.enconman.2019.111924 ↗
16. Modelling a ground-coupled heat pump system using adaptive neuro-fuzzy inference systems10.1016/j.ijrefrig.2007.06.007 ↗
17. Temperature control for a vehicle climate chamber using chilled water system10.1016/j.applthermaleng.2016.05.168 ↗
18. Control Techniques in heating, ventilating and air conditioning systems10.3844/jcssp.2008.777.783 ↗
19. Mirinejad, H., Welch, K.C., and Spicer, L. (2012, January 29–31). A review of intelligent control techniques in HVAC systems. Proceedings of the 2012 IEEE Energytech, Cleveland, OH, USA.10.1109/EnergyTech.2012.6304679 ↗
20. Klir, G.J., and Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall PTR.
21. Management Association (2017). Fuzzy Systems: Concepts, Methodologies, Tools, and Applications, IGI Global.10.4018/978-1-5225-1908-9 ↗
22. Membership functions shape and its influence on the dynamical behaviour of fuzzy logic controller10.1080/019697200124865 ↗
23. The Development of Fuzzy Logic Controller (FLC) in Air Conditioning System Using Several Types of Fuzzy Numbers
24. Fuzzy Expert Systems to Control the Heating, Ventilating and Air Conditioning (HVAC) Systems
25. Mathematical Comparison of Defuzzification of Fuzzy Logic Controller for Intelligence Air Conditioning System
26. Barelli, L., Bidini, G., and Arce, R. (2003, January 15–21). Fuzzy logic regulator for the performance improvement and the energy consumption reduction of an industrial chiller. Proceedings of the 2003 ASME International Mechanical Engineering Congress, Washington, DC, USA.10.1115/IMECE2003-41910 ↗
27. Experimental evaluation of fuzzy controllers for the temperature control of the secondary refrigerant in a liquid chiller10.1016/j.jfoodeng.2005.03.061 ↗
28. Energy saving potential of chiller system with fuzzy logic control10.1002/er.1621 ↗
29. Comparison of different controllers for variable speed compressor and electronic expansion valve10.1016/j.ijrefrig.2010.05.005 ↗
30. Yang, Z., Duan, P., Li, Z., and Yang, X. (2015, January 8–10). Self-Adjusting Fuzzy Logic Controller for Refrigeration Systems. Proceedings of the International Conference on Information and Automation, Lijiang, China.10.1109/ICInfA.2015.7279767 ↗
31. Fuzzy control of the compressor speed in a refrigeration plant10.1016/j.ijrefrig.2004.02.004 ↗
32. Becker, M., Oestreich, D., Hasse, H., and Litz, L. (1994, January 24–26). Fuzzy control for temperature and humidity in refrigeration system. Proceedings of the Third IEEE International Conference on Control and Applications, Glasgow, UK.10.1109/CCA.1994.381476 ↗
33. Spiteri, S., Reznik, L., and Vilas-boas, P. (2001, January 2–5). Embedded Fuzzy Control for Reefer Refrigeration Systems. Proceedings of the 2001 IEEE International Fuzzy Systems Conference, Melbourne, Australia.
34. Lea, R.N., Dohmann, E., Prebilsky, W., and Jani, Y. (1996, January 11). An HVAC fuzzy logic zone control system and performance results. Proceedings of the IEEE 5th International Fuzzy Systems, New Orleans, LA, USA.
35. A practical application of fuzzy control for an air-conditioning system10.1016/0888-613X(91)90016-F ↗
36. Piao, Y.-G., Zhang, H.-G., and Zeungnam, B. (1998, January 4–9). A simple fuzzy adaptive control method and application in HVAC. Proceedings of the 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228), Anchorage, AK, USA.
37. Performance evaluation of a combined variable refrigerant volume and cool thermal energy storage system for air conditioning applications10.1016/j.ijrefrig.2017.02.008 ↗
38. A novel proportional-derivative (PD) law based fuzzy logic principles assisted controller for simultaneously controlling indoor temperature and humidity using a direct expansion (DX) air conditioning (A/C) system gulateur assist e pa10.1016/j.ijrefrig.2015.05.011 ↗
39. A novel neural network aided fuzzy logic controller for a variable speed (VS) direct expansion (DX) air conditioning (A/C) system10.1016/j.applthermaleng.2014.12.030 ↗
40. Xiaoqing, Z. (2002). Self-Tuning Fuzzy Controller for Air-Conditioning Systems. [Master’s Thesis, National University of Singapore].
41. Thermal comfort control on multi-room fan coil unit system using LEE-based fuzzy logic10.1016/j.enconman.2004.08.002 ↗
42. Islam, M.S., Sarker, M.S.Z., Rafi, K.A.A., and Othman, M. (December, January 29). Development of a Fuzzy Logic Controller Algorithm for Air-conditioning System. Proceedings of the 2006 IEEE International Conference on Semiconductor Electronics, Kuala Lumpur, Malaysia.10.1109/SMELEC.2006.380753 ↗
43. García Arenas, D. (2010). Control Ambiental Psicométrico Mediante Lógica Difusa. [Bachelor’s Thesis, Universidad Carlos III de Madrid].
44. Energy conservative building air conditioning system controlled and optimized using fuzzy-genetic algorithm10.1016/j.enbuild.2009.11.014 ↗
45. Coupling a neural network temperature predictor and a fuzzy logic controller to perform thermal comfort regulation in an office building10.1016/j.buildenv.2013.10.020 ↗
46. Intelligent Room Temperature Controller System Using MATLAB Fuzzy Logic Toolbox
47. Fuzzy logic-based advanced on-off control for thermal comfort in residential buildings10.1016/j.apenergy.2015.05.119 ↗
48. Lin, L., and Wang, X. (2016, January 28–30). Design for refrigerator evaporator superheat based on direct adaptive fuzzy controller. Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016, Yinchuan, China.10.1109/CCDC.2016.7532131 ↗
49. Fuzzy Logic in HVAC for Human Comfort
50. Modeling, Analysis, and Design of a Fuzzy Logic Controller for an AHU in the S.J. Carew Building at Memorial University
51. Fanger, P.O. (1972). Thermal Comfort: Analysis and Applications in Environmental Engineering, McGraw-Hill.
52. Design of a fuzzy set environment comfort system10.1016/0378-7788(94)00902-V ↗
53. Design of a fuzzy system for living space thermal-comfort regulation10.1016/S0306-2619(00)00065-9 ↗
54. Hamdi, M., and Lachiver, G. (1998, January 4–9). A fuzzy control system based on the human sensation of thermal comfort. Proceedings of the 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence, Anchorage, AK, USA.
55. The control of indoor thermal comfort conditions: Introducing a fuzzy adaptive controller10.1016/j.enbuild.2003.10.004 ↗
56. Ciabattoni, L., Cimini, G., Ferracuti, F., Grisostomi, M., Ippoliti, G., and Pirro, M. (2015, January 11–16). Indoor thermal comfort control through fuzzy logic PMV optimization. Proceedings of the 2015 International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland.10.1109/IJCNN.2015.7280698 ↗
57. Further development of a thermal comfort based fuzzy logic controller for a direct expansion air conditioning system10.1016/j.apenergy.2018.03.045 ↗
58. Davis, L.I., Sieja, T.F., Matteson, R.W., Dage, G.A., and Ames, R. (1994, January 26–29). Fuzzy logic for vehicle climate control. Proceedings of the 1994 IEEE 3rd International Fuzzy Systems Conference, Orlando, FL, USA.
59. Development of fuzzy logic control for vehicle air conditioning system10.12928/telkomnika.v6i2.553 ↗
60. Intelligent energy management control of vehicle air conditioning via look-ahead system10.1016/j.applthermaleng.2011.05.023 ↗
61. Fuzzy-based temperature and humidity control for HVAC of electric vehicle10.1016/j.proeng.2012.07.261 ↗
62. Choi, B.J., Han, S.-W., and Hong, S.-K. (1998, January 7–10). Refrigerator temperature control using fuzzy logic and neural network. Proceedings of the IEEE International Symposium on Industrial Electronics. Proceedings. ISIE’98 (Cat. No.98TH8357), Pretoria, South Africa.
63. The design of intelligent control of a kitchen refrigerator10.1016/S0378-4754(01)00281-6 ↗
64. Rashid, M.M., and Islam, A. (2010, January 11–12). Design and implementation of a fuzzy logic based controller for refrigerating systems. Proceedings of the International Conference on Computer and Communication Engineering (ICCCE’10), Kuala Lumpur, Malaysia.10.1109/ICCCE.2010.5556848 ↗
65. Azam Baleghy, N., and Mousavi Mashhadi, S.K. (2012, January 15–17). Design and implementation fuzzy controller in the frost-free refrigerator by using multivariate regression. Proceedings of the 20th Iranian Conference on Electrical Engineering (ICEE2012), Tehran, Iran.10.1109/IranianCEE.2012.6292470 ↗
66. Arfaoui, J., Feki, E., and Mami, A. (2015, January 24–26). PID and fuzzy logic optimized controller for temperature control in a cavity of refrigeration. Proceedings of the IREC2015 The Sixth International Renewable Energy Congress, Sousse, Tunisia.10.1109/IREC.2015.7110951 ↗
67. Energy optimization of a domestic refrigerator controlled by a fuzzy logic system using the status of the door10.1016/j.ijrefrig.2019.04.025 ↗
68. Capacity control of a heat pump system applying a fuzzy control method10.1016/j.applthermaleng.2011.03.032 ↗
69. Tsai, C.C., Tsai, K.I., and Su, C.T. (2012, January 16–18). Cascaded fuzzy-PID control using PSO-EP algorithm for air source heat pumps. Proceedings of the 2012 International Conference on Fuzzy Theory and Its Applications (iFUZZY2012), Taichung, Taiwan.10.1109/iFUZZY.2012.6409694 ↗
70. Artificial neural networks and adaptive neuro-fuzzy assessments for ground-coupled heat pump system10.1016/j.enbuild.2007.10.002 ↗
71. ANN and ANFIS models for performance evaluation of a vertical ground source heat pump system10.1016/j.eswa.2010.05.074 ↗
72. Lee, S., Jeong, M., Jang, B., Yoo, C., Kim, S., and Park, Y. (1998, January 4). Fuzzy Precompensated PI Controller for A Variable Capacity Heat Pump. Proceedings of the International Conference on Control Applications, Trieste, Italy.
73. Performance prediction of a vapour-compression heat-pump10.1016/j.apenergy.2003.12.013 ↗
74. Simultaneous control of drying temperature and superheat for a closed-loop heat pump dryer10.1016/j.applthermaleng.2015.09.117 ↗
75. Optimization of heat pump using fuzzy logic and genetic algorithm10.1007/s00231-011-0818-4 ↗
76. Multivariable fuzzy control strategy for an experimental chiller system10.1111/jfpe.12071 ↗