Drexel University
Mechanical Engineering Department
A Senior Design Proposal Titled:
Binary Refrigerant Refrigerator
Project 25
MEM491
Samuel Beccaria
Abhinav Duggal
Mathew Smith
Xiaoyi Zhu
November 24, 2014
Advisory: Bakthier Farouk
Abstract
The objective of the project is to design, build and test an optimized domestic vapor compression refrigerator that uses a binary refrigerant mixture instead of the more traditional single component refrigerant refrigerators. The temperature glide effect (a range of saturation temperature for a specific saturation pressure) allows for temperature changes during the constant pressure boiling, which occurs in binary refrigerant refrigeration cycles. This changing temperature offers potential energy/efficiency advantages for household refrigeration, because they typically have two different evaporator temperatures for the fridge and freezer. Optimization algorithms will be implemented to choose the specific combination of the mixture components for maximizing the COP of the refrigeration system. Stakeholders for this project include consumers, as well as appliance manufacturers and the environment, because the refrigerant mixture conserves energy while also reducing harmful emissions. The refrigerants for the binary system are selected based on review and using analytical data to generate concentration plots and calculate the temperature glide for different combinations. Based on the analytical data developed in MATLAB, experimental tests will be performed with various refrigerant concentrations in a real household refrigerator/freezer, and the required energy will be measured to determine the mass fractions that produce the highest COP. The experimental procedure will entail a refrigerator that has been charged with the selected refrigerant mixture which will be run with thermocouples placed on the inside. Once the temperature and energy data is collected, the COP will be calculated from those values and compared with the analytical COP results.
Table of Contents
Abstract 2
1. Introduction 4
1.1. Background 4
1.2. Stakeholders and Needs 5
1.3. Problem Statement 5
2. Methods 6
2.1. Reverse Rankine Cycle 6
2.2. Thermophysical Properties of Binary Mixtures 6
2.3. Optimization Methods 7
2.3.1. Objective Function 7
2.3.2. Constraint Equations 7
3. Design Description 8
3.1. Sliding Temperatures 8
3.2. Refrigeration Systems 8
3.3. Experimental Design and Construction of Binary Refrigerant System 8
4. Context and Impacts 10
4.1. Economic Analysis 10
4.2. Environmental Impact Analysis 10
4.3. Social Impact Analysis 10
4.4. Ethical Analysis 11
5. Project Management 11
5.1. Team Organization 11
5.2. Schedule and Milestones 11
5.2.1. Fall Term: Proposal Preparation 11
5.2.2. Winter Term: Optimized System Development 11
5.2.3. Spring Term: Testing and Data Collection 12
5.3. Project Budget 12
4 Thermocouples Garland 4518817 12
Power Meter Energy Monitor 12
Total 12
6. Discussions and Alternative Concepts 12
6.1. Binary Refrigerant Selection 12
6.1.1. Alternative to Binary Refrigerant Mixture 13
6.2. Thermodynamic System Selection 13
6.2.1. Alternative to Refrigeration System 13
6.3. Mathematical Modeling with MATLAB 14
6.3.1. Alternative to Optimization Process 14
7. Summary and Conclusion 14
7.1. Optimized Design 14
7.2. Construction of Experimental Apparatus 14
7.3. Testing of Experimental Apparatus 14
8. Proposed Task 14
9. References 15
10. Appendices 17
10.1. Appendix A: Supplementary Material to Methods 17
10.2. Appendix B: Analysis of Lorenz-Meutzner Cycle 19
10.3. Appendix C: Isentropic Work of Compressor and Related MATLab code 20
10.4. Appendix D: Justification of Refrigerant Mixture Tables 26
1. Introduction
1.1. Background
Refrigerators that currently exist in the home employ a single refrigerant as the working fluid. The working fluid through a refrigerator has to meet a certain set of safety and thermophysical requirements. The best refrigerant to use would have low toxicity, low flammability, a high heat of vaporization, a small specific heat and specific volume and low ozone depletion and global warming potentials. Unfortunately single refrigerants are often very friendly to the environment but have very poor thermophysical properties, or have excellent thermophysical properties but have a high potential to harm the environment. There is a work around to this by the use of a binary refrigerant [2].
A binary refrigerant experiences one or two states, liquid, vapor or liquid-vapor, dependent upon the pressure and temperature of the system and the saturation pressure of the refrigerants in mixture. In most cases this allows for a temperature glide effect (a range of saturation temperature for a given saturation pressure) that allows the freezer temperature to be reached at a much lower pressure [14]. Additionally, by mixing refrigerants with varying pros and cons, i.e. mixing a refrigerant with poor thermophysical properties that does little harm to the environment and refrigerant with excellent thermophysical properties that does a lot of harm to the environment, the harm to the environment can be minimized while still seeing gains in the COP [15].
Currently, refrigerators use a single refrigerant as their working fluid called HFC-134a (1,1,1,2-Tetrafluoroethane), which does not deplete the ozone layer and has good thermophysical properties. However R134a has high GWP (global warming potential) of 1300. The Kyoto Protocol of the United Nations Framework Convention on Climate Change (UNFCCC) calls for reductions in emissions of six categories of greenhouse gases, including hydrofluorocarbons (HFCs) used as refrigerants. From the environmental, economic, social and ethical aspects, it is urgent to find a good alternative option for HFC refrigerant [21].
Household refrigerators are identified as the most energy consuming appliance of all household appliances. It has been proposed that a mixture of refrigerants can offset the energy consumption of household refrigerators while providing an environmentally friendly alternative to HFC-134a. The reason for using binary refrigerants is that binary refrigerants can be tailored to meet a specific temperature requirement, -18°C in the freezer, while simultaneously lowering the power output to reach that temperature. It is also possible to control the properties such as toxicity, flammability, oil miscibility by manipulating the composition. Most importantly, using a binary mixture as the working fluid increases the COP of the system, allowing for greater energy efficiency [21].
1.2. Stakeholders and Needs
The stakeholders of this project include homeowners, supermarkets, facility owners and vendors. Their needs must be considered and implemented into the design of the binary refrigerant to create a successful product.
Once the binary refrigerant mixture has been found through optimization and testing methods, homeowners can use the binary refrigerants in their household refrigerators, which can improve the energy efficient thus saving the money. The same applies to other stakeholders.
1.3. Problem Statement
The objective of the project is to design, build and test a domestic vapor compression refrigerator that uses a binary refrigerant mixture instead of the more traditional single component refrigerant refrigerators.
2. Methods
The optimization of the binary refrigerant system will yield an optimized design that will be used in the building and testing phase of this project. With the optimization algorithm, made in MATLAB, the optimal mixture of refrigerants that yield the maximum COP of the system will be found. Thus the completion of this project rests upon the understanding of refrigeration systems, the thermodynamic properties of mixtures and how the working fluid behaves within a refrigeration system. This understanding will be established analytically in order to use the optimization algorithm. Once the refrigeration system is represented analytically, the optimization algorithm, in this case the method of Lagrange multipliers, will be used to generate the optimized design of the refrigerant mixtures that yields the maximum COP. The optimization of the refrigerant mixtures that yield the maximum COP will be done via simulation in MATLAB.
2.1. Reverse Rankine Cycle
The refrigeration system can be modeled as a simple vapor-compression cycle. The vapor-compression cycle, or the Reverse Rankine cycle, consists of four components, a compressor, condenser, throttling valve and evaporator. The states 1, 2, 3 and 4, are the evaporator outlet, compressor outlet, condenser outlet and throttling valve outlet respectively. The entirety of this process for a single refrigerant can be shown in the T-s diagram in Figure 4 in Appendix A [23].
The compression process is assumed to be adiabatic and isentropic. The working fluid enters the compressor from state 1 as a saturated vapor and leaves the compressor in state 2 as a superheated vapor. From state 2 the working fluid enters the condenser, where it is condensed from a superheated vapor to saturated liquid in state 3. The saturated liquid in state 3 enters the throttling valve where the saturated liquid is turned into a saturated liquid-vapor mixture of quality, x in state 4. The working fluid from state 4 feeds into the evaporator, where the temperature of the working fluid is constant through the evaporator and the saturated liquid-vapor mixture is returned to a saturated vapor at state 1 [23].
Another important factor to note is that the pressure is constant over the evaporator and the condenser. If the pressures are known for each, then the temperatures at state 3, state 4 and state 1 can be found. As well, since the compression process from state 1 to state 2 is isentropic, if the entropy at state 1 is known then the temperature of the superheated vapor can be found. Having these concepts in mind allows for the setup of the analysis of this system to maximize for the COP [19],[20],[23].
2.2. Thermophysical Properties of Binary Mixtures
The equations of states of the system become more complex when a binary refrigerant mixture is used as the working fluid. To grasp this concept the properties of a binary mixture of any two fluids must be explored. A binary refrigerant is a refrigerant that is a mixture of two refrigerants. The thermophysical properties of a binary mixture of fluids are dependent upon the refrigerants saturation temperatures and pressures [6]. If the saturation temperatures or pressures of two fluids are similar then the mixture will be azeotropic. This means that the fluids behave as if they were one fluid when undergoing changes in state from saturated vapor to saturated liquid and vice versa. However if the two fluids vary widely in their saturation temperatures or pressures, this will result in a zeotropic mixture. A zeotropic mixture experiences a dome, where at certain temperatures the mixture will be a combination of liquid and vapor of each component.
To illustrate the difference between azeotropic and zeotropic mixtures, Figures 5 and 6 in Appendix A demonstrate the vapor-liquid equilibrium graphs of a binary mixture of refrigerants, R143A/R125 and R152A/R125 respectively.
2.3. Optimization Methods
Finally, given the thermal system and the working fluid, the Lagrange multiplier method will be utilized in the optimization process. The optimization process outputs the refrigerant mixture that, when run through the cycle, will produce the maximum COP.
The Lagrange multiplier method is a mathematical model to solve a system of linear or nonlinear equations simultaneously. The main components of the method are detailed in Appendix A.
2.3.1. Objective Function
In order to optimize the refrigerant mixture that gives the optimal design COP the Lagrange multiplier method is used by finding an objective function. The objective function to be optimized, in this case the COP as a function of temperature, mass flow rate, and the refrigeration load, must be created, and is shown in EQ 1.
COP=Qlmc1-T1T2 / (1)Where c is a constant, m is the mass flow rate, Ql is the heat taken in by the working fluid through the evaporator, and T1 and T2 are the temperatures at states 1 and 2 respectively. Ql is a given property based off of the type of refrigerator and the constant c can be found using the method in Appendix C.
2.3.2. Constraint Equations
An additional part to deriving the optimal design requires a set of constraint equations to be made. The constraint equations represent physical aspects of the system that restrict the relationship between the variables in the objective function to a specific value. The relations that are made in the constraint equations are often derived from the actual system to be optimized. However to avoid having a system that is overly constrained the number of constraint equations should be less than the number of variables in the objective function. Additionally between the constraint equations every variable in the objective function should be represented. The set of constraint equations for the system to be optimized can be represented in EQ. 2.
ϕ1=fx1,x2,…,xn=0⋮
ϕm=fx1,x2,…,xn=0 / (2)
Where ϕ is the constraint equation that the objective function is subject to, n is the number of variables in the objective function and m is the number of constraint equations. It is important to note that m < n. The rest of the optimization procedure to achieve the optimal design is detailed in Appendix A.
3. Design Description
The aim of this project is to design, build and test an optimized domestic vapor compression refrigerator that uses a binary refrigerant mixture instead of the more traditional single component refrigerant refrigerators. The concept for this project came from several papers by Wilbert F. Stoecker, who investigated the potential benefits of refrigerant mixtures analytically and experimentally to develop the energy savings from thermodynamic concepts; the benefit of using a binary mixture of refrigerants instead of a single working fluid comes from the effect of “sliding temperatures”.
3.1. Sliding Temperatures
Sliding temperatures, or “temperature glides”, occur in a refrigeration cycle when the fluid components have different boiling points [15]. When using a single refrigerant, a constant pressure boiling process takes place at constant temperature; in contrast, a binary mixture experiences an increase in temperature when boiling at constant pressure. Additionally, the temperature increases when heating the subcooled liquid and superheating the vapor. Thermodynamically, the energy savings potential is achieved by matching the refrigerants’ sliding temperatures with the cooled space (the fridge/freezer compartment, air) or the fluid used to cool the condenser; this allows for a higher evaporating temperature and a lower condensing pressure, which in turn increases the cycle efficiency.
3.2. Refrigeration Systems
For a refrigeration cycle, a measure of efficiency is the Coefficient of Performance (COP). COP is defined as the ratio of the heat removed from the cooled space to the required work input for the cycle (the work of the compressor). The heat removed from the cooled space is, Q, is expressed in a per-unit-time basis, and is also called the “Refrigeration Effect”. Similarly, the compressor work input is expressed in a per-unit-time basis, and is termed the compressor power. There are various refrigeration cycles used in application and theoretical analysis, the most common being the reverse Rankine cycle, the Carnot cycle, and the Lorenz-Meutzner cycle [26].