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HVAC System Modeling and Control: Vapor Compression System Modeling and Control

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Intelligent Building Control Systems

Part of the book series: Advances in Industrial Control ((AIC))

Abstract

In this chapter, we delve deeper into understanding modeling and control approaches for one of the important subsystems in an intelligent building, the HVAC system. Specifically, Vapor Compression Systems (VCS) are the primary energy systems in building air conditioning, heat pump, and refrigeration systems. We will discuss standard methods for constructing dynamic models of vapor compression systems, and their relative advantages for analysis, design, control design, and fault detection. The principal interests are moving boundary and finite-volume approaches to capture the salient dynamics of two-phase flow heat exchangers. We will present modeling approaches for auxiliary equipment, such as, valves, compressors, fans, dampers, and heating/cooling coils, allowing the reader to understand the construction of typical HVAC system models. We will then highlight limitations of such models and address advanced modeling approaches for challenging transient scenarios. Finally, we give a summary of single-input, single-output control strategies for HVAC system, with simulation and experimental examples to illustrate their effectiveness.

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References

  1. Klepeis N, Nelson W, Ott W, Robinson J, Tsang A, Switzer P, Behar J, Hern S, Engelmann W (2001) The National Human Activity Pattern Survey (NHAPS): A Resource For Assessing Exposure to Environmental Pollutants. J Exposure Anal Environ Epidemiol 11(3):231–252

    Article  Google Scholar 

  2. Sarigiannis D (2013) Combined or Multiple Exposure to Health Stressors in Indoor Built Environments. Tech. Rep, World Health Organization, Regional Office for Europe

    Google Scholar 

  3. Constable G, Somerville B (2003) A century of innovation: twenty engineering achievements that transformed our lives. Joseph Henry Press

    Google Scholar 

  4. Stoecker WF (2000) Industrial refrigeration handbook. McGraw-Hill, New York

    Google Scholar 

  5. Bourdouxhe J-P, Grodent M, Lebrun J (1998) Reference guide for dynamic models of HVAC equipment, ASHRAE, Tech. Rep. Project 738-TRP

    Google Scholar 

  6. Bendapudi S, Braun J (2002) A review of literature on dynamic models of vapor compression equipment ASHRAE, Tech. Rep. Report #4036-5

    Google Scholar 

  7. Ding G-L (2007) Recent developments in simulation techniques for vapour-compression refrigeration systems. Int J Refrig 30(7):1119–1133

    Article  Google Scholar 

  8. Rasmussen B (2011) Dynamic modeling for vapor compression systems - Part I: literature review. HVAC&R Res 18(5):934–955

    Google Scholar 

  9. Li P, Qiao H, Li Y, Seem JE, Winkler J, Li X (2014) Recent advances in dynamic modeling of hvac equipment. part 1: equipment modeling. HVAC&R Res 20(1):136–149

    Article  Google Scholar 

  10. Eborn J (2001) On model libraries for thermo-hydraulic applications, Ph.D. dissertation. Lund University

    Google Scholar 

  11. Rasmussen B, Alleyne A, Musser A (2005) Model-driven system identification of transcritical vapor compression systems. IEEE Trans Control Syst Technol 13(3):444–451

    Article  Google Scholar 

  12. Gruhle WD, Isermann R (1985) Modeling and control of a refrigerant evaporator. ASME J Dyn Syst Meas Control 107(4):235–240

    Article  Google Scholar 

  13. MacArthur JW (1984) Transient heat pump behaviour: a theoretical investigation. Int J Refrig 7(2):123–132

    Article  Google Scholar 

  14. MacArthur JW, Grald EW (1989) Unsteady compressible two-phase flow model for predicting cyclic heat pump performance and a comparison with experimental data. Int J Refrig 12(1):29–41

    Article  Google Scholar 

  15. Bendapudi S, Braun J (2002) Development and validation of a mechanistic, Dynamic model for a vapor compression centrifugal chiller, ASHRAE, Tech. Rep. Report #4036-4

    Google Scholar 

  16. Anand G, Mahajan M, Jain N, Maniam B, Tumas T (2004) e-Thermal: automobile air conditioning module. In: SAE international Society of automotive engineers 2004 world congress, Paper 2004-01-1509

    Google Scholar 

  17. Skaugen G, Svensson M (1998) Dynamic modeling and simulation of a transcritical CO\(_2\) heat pump unit, pp 230–239

    Google Scholar 

  18. Pfafferott T, Schmitz G (2000) Numeric simulation of an integrated CO\(_2\) cooling system. In: Proceedings of the 2000 modelica workshop. Lund, Sweden, pp 89–92

    Google Scholar 

  19. Rigola J, Raush G, Prez-Segarra CD, Oliva A (2005) Numerical simulation and experimental validation of vapour compression refrigeration systems. special emphasis on CO\(_2\) trans-critical cycles. Int J Refrig 28(8):1225–1237

    Article  Google Scholar 

  20. Kapadia RG, Jain S, Agarwal RS (2009) Transient characteristics of split air-conditioning systems using R-22 and R-410A as refrigerants. pp 617–649

    Google Scholar 

  21. Beghi A, Cecchinato L (2009) A simulation environment for dry-expansion evaporators with application to the design of autotuning control algorithms for electronic expansion valves. Int J Refrig 32(7):1765–1775

    Article  Google Scholar 

  22. Kohlenbach P, Ziegler F (2008) A dynamic simulation model for transient absorption chiller performance. Part I: the model. Int J Refrig 31(2):217–225

    Article  Google Scholar 

  23. Kohlenbach P, Ziegler F (2008) A dynamic simulation model for transient absorption chiller performance. Part II: numerical results and experimental verification. Int J Refrig 31(2):226–233

    Google Scholar 

  24. Matsushima H, Fujii T, Komatsu T, Nishiguchi A (2010) Dynamic simulation program with object-oriented formulation for absorption chillers (modelling, verification, and application to triple-effect absorption chiller). Int J Refrig 33(2):259–268

    Article  Google Scholar 

  25. Schicktanz M, Núñez T (2009) Modelling of an adsorption chiller for dynamic system simulation. Int J Refrig 32(4):588–595

    Article  Google Scholar 

  26. Zhou X, Braun JE (2007) A simplified dynamic model for chilled-water cooling and dehumidifying coils-Part 1: development (RP-1194). pp 785–804

    Google Scholar 

  27. Zhou X, Braun JE (2007) A simplified dynamic model for chilled-water cooling and dehumidifying coils-Part 2: experimental validation (RP-1194). pp 805–817

    Google Scholar 

  28. Li P, Li Y, Seem JE (2010) Modelica-based dynamic modeling of a chilled-water cooling coil. HVAC&R Res 16:35–58

    Article  Google Scholar 

  29. Grald EW, MacArthur JW (1992) A moving-boundary formulation for modeling time-dependent two-phase flows. Int J Heat Fluid Flow 13(3):266–272

    Article  Google Scholar 

  30. He XD, Liu S, Asada H (1997) Modeling of vapor compression cycles for multivariable feedback control of HVAC systems. ASME J Dyn Syst Meas Control 119(2):183–191

    Article  MATH  Google Scholar 

  31. Rasmussen BP, Alleyne A (2004) Control-oriented modeling of transcritical vapor compression systems. ASME J Dyn Syst Meas Control 126(1):54–64

    Article  Google Scholar 

  32. Rice C (1987) Effect of void fraction correlation and heat flux assumption on refrigerant charge inventory. ASHRAE Trans 93(1):341–367

    Google Scholar 

  33. Wilson M, Newell T, Chato J (1998) Experimental investigation of void fraction during horizontal flow in larger diater refrigeration applications, Air conditioning and refrigeration center, vol. ACRC TR-140. University of Illinois, Urbana

    Google Scholar 

  34. Wedekind GL, Bhatt BL, Beck BT (1978) A system mean void fraction model for predicting various transient phenomena associated with two-phase evaporating and condensing flows. Int J Multiph Flow 4(1):97–114

    Article  Google Scholar 

  35. Beck BT, Wedekind GL (1981) A generalization of the system mean void fraction model for transient two-phase evaporating flows. ASME J Heat Transf 103(1):81–85

    Article  Google Scholar 

  36. He XD, Asada H, Liu S, Itoh H (1998) Multivariable control of vapor compression systems. HVAC&R Res 4(3):205–230

    Article  Google Scholar 

  37. Bendapudi S, Braun JE, Groll EA (2008) A comparison of moving-boundary and finite-volume formulations for transients in centrifugal chillers. Int J Refrig 31(8):1437–1452

    Article  Google Scholar 

  38. Rasmussen BP, Shenoy B (2011) Dynamic modeling for vapor compression systems, Part II: Simulation tutorial. HVAC&R Res 18(5):956–973

    Google Scholar 

  39. Pangborn H, Alleyne AG, Wu N (2015) A comparison between finite volume and switched moving boundary approaches for dynamic vapor compression system modeling. Int J Refrig 53:101–114

    Article  Google Scholar 

  40. Pettit NBOL, Willatzen M, Ploug-Sorensen L (1998) General dynamic simulation model for evaporators and condensers in refrigeration. part ii: simulation and control of an evaporator. Int J Refrig 21(5):404–414

    Article  Google Scholar 

  41. Willatzen M, Pettit NBOL, Ploug-Sorensen L (1998) General dynamic simulation model for evaporators and condensers in refrigeration. part i: moving-boundary formulation of two-phase flows with heat exchange. Int J Refrig 21(5):398–403

    Article  Google Scholar 

  42. Zhang W-J, Zhang C-L (2006) A generalized moving-boundary model for transient simulation of dry-expansion evaporators under larger disturbances. Int J Refrig 29(7):1119–1127

    Article  Google Scholar 

  43. McKinley T, Alleyne A (2008) An advanced nonlinear switched heat exchanger model for vapor compression cycles using the moving-boundary method. Int J Refrig 31(7):1253–1264

    Article  Google Scholar 

  44. Li B, Alleyne A (2010) A dynamic model of a vapor compression cycle with shut-down and start-up operations. Int J Refrig 33(3):538–552

    Article  Google Scholar 

  45. Cecchinato L, Mancini F (2012) An intrinsically mass conservative switched evaporator model adopting the moving-boundary method. Int J Refrig 35(2):349–364

    Article  Google Scholar 

  46. Bonilla J, Dormido S, Cellier FE (2015) Switching moving boundary models for two-phase flow evaporators and condensers. Commun Nonlinear Sci Numer Simul 20(3):743–768

    Article  MathSciNet  Google Scholar 

  47. Qiao H, Laughman CR, Aute V, Radermacher R (2016) An advanced switching moving boundary heat exchanger model with pressure drop. Int J Refrig 65:154–171

    Article  Google Scholar 

  48. Gordon BW, Liu S, Asada HH (1999) Dynamic modeling of multiple-zone vapor compression cycles using variable order representations. In: Proceedings of the American control conference. IEEE, pp 3765–3769

    Google Scholar 

  49. Eldredge B, Rasmussen B, Alleyne A (2008) Moving-boundary heat exchanger models with variable outlet phase. J Dyn Syst Meas Control 130: 61 003–1–61 003–12

    Google Scholar 

  50. Zhang W-J, Zhang C-L, Ding G-L (2009) On three forms of momentum equation in transient modeling of residential refrigeration systems. Int J Refrig 32(5):938–944

    Article  Google Scholar 

  51. Sheng L, Xiangdong H, Asada H, Itoh H, Nakagawa K (1996) Multivariable control of vapor compression cycles: coordination of compressor and expansion valve. In: Proceedings of the 13th world congress, International federation of automatic control. Chemical process control, mineral, mining, metals, Vol. M. Pergamon. 1997. Oxford, UK, pp 193–8

    Google Scholar 

  52. Jensen JM, Tummescheit H (2002) Moving boundary models for dynamic simulations of two-phase flows. In: Proceedings of the 2nd international modelica conference. pp 235–244

    Google Scholar 

  53. Leducq D, Guilpart J, Trystram G (2003) Low order dynamic model of a vapor compression cycle for process control design. J Food Process Eng 26(1):67–91

    Article  Google Scholar 

  54. Eisenhower B, Runolfsson T (2009) System level modeling of a transcritical vapor compression system for bistability analysis. Nonlinear Dyn 55(1):13–30

    Article  MATH  Google Scholar 

  55. Rodriguez E, Rasmussen B (2015) A nonlinear reduced order modeling method for dynamic two-phase flow heat exchanger simulations. Science and technology for the built environment

    Google Scholar 

  56. Murphy W, Goldschmid V (1985) Cyclic characteristics of a residential air-conditioner - modeling of start-up transient. ASHRAE Trans 91(2A):427–444

    Google Scholar 

  57. García-Valladares O (2007) Numerical simulation of non-adiabatic capillary tubes considering metastable region. part i: mathematical formulation and numerical model. Int J Refrig 30(4):642–653

    Article  Google Scholar 

  58. García-Valladares O (2007) Numerical simulation of non-adiabatic capillary tubes considering metastable region. Part II: experimental validation. Int J Refrig 30(4):654–663

    Google Scholar 

  59. Stoecker WF (1996) Stability of an evaporator-expansion valve control loop. ASHRAE Trans 72(2):4.3.1–4.3.8

    Google Scholar 

  60. Broersen PMT, van der Jagt MFG (1980) Hunting of evaporators controlled by a thermostatic expansion valve. ASME J DynSyst Meas Control 102(2):130–135

    Article  Google Scholar 

  61. Higuchi K, Hayano M (1982) Dynamic characteristics of thermostatic expansion valves. Int J Refrig 5(4):216–220

    Article  Google Scholar 

  62. Yasuda H, Touber S, Machielsen C (1983) Simulation model of a vapor compression refrigeration system. ASHRAE Trans 89(2787):408–42

    Google Scholar 

  63. Najork H (1973) Investigations on the dynamical behavior of evaporators with thermostatic expansion valve. In: Proceedings of the 13th international congress of refrigeration. pp 759–769

    Google Scholar 

  64. Broersen PMT, ten Napel J (1983) Identification of a thermostatic expansion valve. In: Proceedings of the sixth IFAC symposium, vol. 1. Pergamon, pp 415–20

    Google Scholar 

  65. James K, James R (1987) Transient Analysis of Thermostatic Expansion Valves for Refrigeration System Evaporators Using Mathematical Models. Trans Instit Meas Control 9(4):198–205

    Article  Google Scholar 

  66. Ibrahim G (2001) Effect of sudden changes in evaporator external parameters on a refrigeration system with an evaporator controlled by a thermostatic expansion valve. In J Refrig 24(6):566–576

    Article  Google Scholar 

  67. Mithraratne P, Wijeysundera N (2002) An experimental and numerical study of hunting in thermostatic-expansion-valve-controlled evaporators. Int J Refrig 25(7):992–998

    Article  Google Scholar 

  68. Hariharan N, Rasmussen B (2010) Parameter estimation of hvac model with limited sensors. In: Proceedings of the American control conference

    Google Scholar 

  69. Outtagarts A, Haberschill P, Lallemand M (1997) Transient response of an evaporator fed through an electronic expansion valve. Int J Energy Res 21(9):793–807

    Article  Google Scholar 

  70. Finn D, Doyle C (2000) Control and optimization issues associated with algorithm-controlled refrigerant throttling devices. ASHRAE Trans 106(1):524–533

    Google Scholar 

  71. Jain N, Li B, Keir M, Hencey B, Alleyne A (2010) Decentralized feedback structures of a vapor compression cycle system. IEEE Trans Control Syst Technol 18(1):185–193

    Article  Google Scholar 

  72. Pollock D, Yang Z, Wen J (2015) Dryout avoidance control for multi-evaporator vapor compression cycle cooling. Appl Energy 160:266–285

    Article  Google Scholar 

  73. Estrada-Flores S, Cleland D, Cleland A, James R (2003) Simulation of transient behavior in refrigeration plant pressure vessels: mathematical models and experimental validation. Int J Refrig 26(2):170–179

    Article  Google Scholar 

  74. Qiao H, Aute V, Radermacher R (2014) Transient modeling of a flash tank vapor injection heat pump system - part i: model development. Int J Refrig 49:169–182

    Article  Google Scholar 

  75. Rasmussen B, Alleyne A, Musser A (2004) Iterative modeling and identification of a CO\(_2\) air conditioning system. In: Proceedings of the international mechanical engineering congress and exposition, American society of mechanical engineers, Dynamic systems and control division (Publication) DSC, vol. 73. American Society of Mechanical Engineers, New York, NY 10016-5990, United States, pp 813–820

    Google Scholar 

  76. Bendapudi S (2015) Development and evaluation of modeling approaches for transients in centrifugal chillers, Ph.D. dissertation. Purdue University

    Google Scholar 

  77. Haines RW, Hittle DC (2006) Control systems for heating, ventilating, and air conditioning, 6th edn. Springer Science & Business Media

    Google Scholar 

  78. Yamakawa Y, Yamazaki T, Kamimura K, Kurosu S (2010) Compensation of manual reset to offset thermal loads change for PID controller. ASHRAE Trans 116(1):303–315

    Google Scholar 

  79. Price C, Liang S, Rasmussen B (2015) HVAC nonlinearity compensation using cascaded control architectures. ASHRAE Trans 121:217–231

    Google Scholar 

  80. Wisniewski R, Chen L, Larsen LF (2009) Synchronization analysis of the supermarket refrigeration system. In: Proceedings of the 48th conference on decision and control, 2009 held jointly with the 2009 28th Chinese control conference (CDC/CCC). IEEE pp 5562–5567

    Google Scholar 

  81. Wisniewski R, Leth J, Rasmussen JG (2014) Analysis of synchronization in a supermarket refrigeration system. Control Theory Technol 12(2):154–162

    Article  MathSciNet  Google Scholar 

  82. N, A, (2010) ASHRAE Handbook - Refrigeration (SI Edition). American Society of Heating, Refrigerating and Air-Conditioning Engineers Inc, p 2010

    Google Scholar 

  83. Energy Star (2009) A guide to energy-efficient heating and cooling

    Google Scholar 

  84. Ulpiani G, Borgognoni M, Romagnoli A, Di Perna C (2016) Comparing the performance of On/Off, PID, and fuzzy controllers applied to the heating system of an energy-efficient building. Energy Build 116:1–17

    Article  Google Scholar 

  85. Ziegler JG, Nichols NB (1942) Optimum settings for automatic controllers. ASME Trans 64:759–768

    Google Scholar 

  86. Astrom K, Hagglund T (2004) Revisiting the Ziegler-Nichols step response method for PID control. J Process Control 14:635–650

    Article  Google Scholar 

  87. Visioli A (2006) Practical PID control. Springer, Berlin

    Google Scholar 

  88. Lim D, Rasmussen BP, Swaroop D (2009) Selecting PID control gains for nonlinear HVAC&R systems. HVAC&R Res 15(6):991–1019

    Article  Google Scholar 

  89. Kasahara M, Matsuba T, Kuzuu Y, Yamazaki T, Hashimoto Y, Kamimura K, Kurosu S (1999) Design and tuning of robust PID controller for HVAC systems. ASHRAE Trans 105:154–156

    Google Scholar 

  90. Chintala R, Price C, Liang S, Rasmussen B (2015) Identification and elimination of hunting behavior in HVAC systems. ASHRAE Trans 121:294–305

    Google Scholar 

  91. Bi Q, Cai W-J, Wang Q-G, Hang C-C, Lee E-L, Sun Y, Liu K-D, Zhang Y, Zou B (2000) Advanced controller auto-tuning and its application in HVAC systems. Control Eng Pract 8(6):633–644

    Article  Google Scholar 

  92. Bai J, Zhang X (2007) A new adaptive PI controller and its application in HVAC systems. Energy Convers Manag 48(4):1043–1054

    Article  Google Scholar 

  93. Tahersima F, Stoustrup J, Rasmussen H (2013) An analytical solution for stability-performance dilemma of hydronic radiators. Energy Build 64:439–446

    Article  Google Scholar 

  94. Rasmussen B, Alleyne A (2010) Gain scheduled control of an air conditioning system using the Youla parameterization. IEEE Trans Control Syst Technol 18(5):1216–1225

    Article  Google Scholar 

  95. Rentel-Gomez C, Velez-Reyes M (2001) Decoupled control of temperature and relative humidity using a variable-air-volume HVAC system and non-interacting control. In: Proceedings of the 2001 International Conference on Control Applications (CCA). IEEE, pp 1147–1151

    Google Scholar 

  96. Lee J, Hyun Kim D, Edgar T (2005) Static decouplers for control of multivariable processes. AIChE J 51(10):2712–2720

    Article  Google Scholar 

  97. Elliott M, Estrada C, Rasmussen B (2011) Cascaded superheat control with a multiple evaporator refrigeration system. In: Proceedings of the American control conference (ACC). pp 2065–2070

    Google Scholar 

  98. Camacho E, Bordons Alba C (2004) Model predictive control. Advanced textbooks in control and signal processing. Springer, New York

    MATH  Google Scholar 

  99. Afram A, Janabi-Sharifi F (2014) Theory and applications of HVAC control systems - a review of model predictive control (MPC). Build Environ 72:343–355

    Article  Google Scholar 

  100. Siroky J, Oldewurtel F, Cigler J, Privara S (2011) Experimental analysis of model predictive control for an energy efficient building heating system. Appl Energy 88(9):3079–3087

    Article  Google Scholar 

  101. Ma Y, Borrelli F, Hencey B, Coffey B, Bengea S, Haves P (2012) Model predictive control for the operation of building cooling systems. IEEE Trans Control Syst Technol 20(3):796–803

    Article  Google Scholar 

  102. Xu M, Li S, Cai W-J, Lu L (2006) Effects of a GPC-PID control strategy with hierarchical structure for a cooling coil unit. Energy Convers Manag 47(1):132–145

    Article  Google Scholar 

  103. Elliott M, Rasmussen B (2015) Optimal setpoints for HVAC systems via iterative cooperative neighbor communication. J Dyn Syst Meas Control 137(1):011006

    Article  Google Scholar 

  104. Elliott M, Rasmussen B (2013) Decentralized model predictive control of a multi-evaporator air conditioning system. Control Eng Pract 21(12):1665–1677

    Google Scholar 

  105. Jalal R, Rasmussen B (2015) Neighbor-communication distributed model predictive control for coupled and constrained subsystems in networks. In: 2015 American Control Conference (ACC). IEEE, pp 743–749

    Google Scholar 

  106. Monsen J (2015) Part 1: an insider’s guide to valve sizing & selection. Flow Control Mag 21(2)

    Google Scholar 

  107. Headley M (2003) Guidelines for selecting the proper valve characteristics. Valve Mag 15(2)

    Google Scholar 

  108. Singhal A, Salsbury T (2007) Characterization and cancellation of static nonlinearity in HVAC systems. ASHRAE Trans 113(1):391–399

    Google Scholar 

  109. He X-D, Asada HH (2003) A new feedback linearization approach to advanced control of multi-unit HVAC systems. Proc Am Control Conf 3:2311–2316

    Google Scholar 

  110. Guardabassi G, Savaresi S (2001) Approximate linearization via feedback - an overview. Automatica 37(1):1–15

    Article  MathSciNet  MATH  Google Scholar 

  111. Price C, Rasmussen B (2016) Optimal tuning of casacaded control architectures for nonlinear HVAC systems. Sci Technol Built Environ. https://doi.org/10.1080/23744731.2016.1262663

  112. Siemens Global (2011) Texas A&M University: a detailed account of how one university is improving its energy efficiency through effective management and performance contracting, White Paper

    Google Scholar 

  113. Price C, Rasmussen B (2015) Effective tuning of cascaded control loops for nonlinear HVAC systems. In: Proceedings of the 2015 dynamic systems and control conference. ASME

    Google Scholar 

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Authors and Affiliations

  1. Texas A&M University, College Station, TX, USA

    Bryan P. Rasmussen & Christopher Price

  2. University of Illinois Urbana-Champaign, Champaign, IL, USA

    Justin Koeln, Bryan Keating & Andrew Alleyne

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  1. Bryan P. Rasmussen
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  2. Christopher Price
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  3. Justin Koeln
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  4. Bryan Keating
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  5. Andrew Alleyne
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Correspondence to Bryan P. Rasmussen .

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Editors and Affiliations

  1. Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA

    John T. Wen

  2. Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA

    Sandipan Mishra

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Rasmussen, B.P., Price, C., Koeln, J., Keating, B., Alleyne, A. (2018). HVAC System Modeling and Control: Vapor Compression System Modeling and Control. In: Wen, J., Mishra, S. (eds) Intelligent Building Control Systems. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-68462-8_4

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