A method and device for predicting binary vapor-liquid equilibrium

Abstract

The application discloses a binary vapor-liquid equilibrium prediction method and device, and relates to the technical field of chemical engineering, in particular to a binary vapor-liquid equilibrium prediction method and device. The method comprises the following steps: decomposing a gas molecule to be predicted into a plurality of groups; calculating a proportion parameter of each group in the gas molecule to be predicted; calculating a binary interaction parameter according to the proportion parameter; establishing a binary phase diagram according to the binary interaction parameter; and predicting a vapor-liquid equilibrium state according to the binary phase diagram. According to the embodiment of the application, the groups are obtained by decomposing the gas molecule, and the binary interaction parameter is established according to the proportion parameter of the groups, so that the manpower, material resources and time consumed by a large number of experiments for establishing the binary interaction parameter are avoided, and the calculation amount of analyzing the vapor-liquid equilibrium is reduced. In addition, the vapor-liquid equilibrium can be determined more accurately through the binary interaction parameter, the prediction is carried out through analyzing the binary phase diagram, and the accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of phase equilibrium testing technology, and in particular to a binary vapor-liquid phase equilibrium prediction method and apparatus. Background Technology

[0002] Due to environmental constraints, the requirements for refrigerants in refrigeration systems are becoming increasingly stringent. Gas-liquid equilibrium data is used to determine the gas-liquid equilibrium properties of binary gases, reflecting the relationship between the pressure, temperature, and component concentrations of the working fluid. Since the performance of systems using refrigerants is highly dependent on the choice of working fluid, and the design of ORC (Organic Rankine Cycle) and HP (Heat Pump) systems requires knowledge of the thermophysical properties of the working fluid, the predicted results can guide the selection of the working fluid and the system design. Gas-liquid equilibrium data is of great significance for the engineering application and design of refrigerants and is an indispensable part of thermodynamics. Therefore, obtaining this physical property data provides fundamental information for guiding the operation and design of heat pumps and refrigeration systems. Currently, experimental measurement remains the main method for obtaining gas-liquid equilibrium data both domestically and internationally. However, gas-liquid equilibrium measurement requires a significant amount of manpower, resources, and time. At the same time, the pace of new chemical updates is accelerating, and the number of mixtures in the chemical industry is in the tens of thousands. It is impossible to always provide experimental data for every mixture, and experimental data is far from meeting the needs of engineering applications. Existing technologies to address this problem primarily employ molecular dynamics and Monte Carlo simulations. These computer molecular simulations, which study the microscopic properties of a system to derive its macroscopic thermodynamic properties, typically require establishing an accurate molecular force field and incorporating certain assumptions to simplify the computational model. However, molecular models suffer from drawbacks such as high dependence on the molecular force field, high computational cost, and poor accuracy for complex mixed systems. Summary of the Invention

[0003] This invention provides a binary vapor-liquid phase equilibrium prediction method and apparatus to solve the technical problems of large computational load and poor accuracy in the analysis of vapor-liquid phase equilibrium in the prior art.

[0004] To address the aforementioned technical problems, embodiments of the present invention provide a binary vapor-liquid phase equilibrium prediction method, comprising:

[0005] The gas molecules to be predicted are broken down into several groups;

[0006] Calculate the proportion of each group to the gas molecules to be predicted;

[0007] Based on the aforementioned proportional parameters, the binary interaction parameters are calculated.

[0008] Based on the binary interaction parameters, a binary phase diagram is established, and the gas-liquid phase equilibrium state is predicted based on the binary phase diagram.

[0009] This invention obtains functional groups by decomposing gas molecules and establishes binary interaction parameters based on the proportional parameters of these functional groups. This avoids the need to use a large amount of experimental data to establish binary interaction parameters, thus reducing the computational workload of analyzing gas-liquid phase equilibrium. Furthermore, the binary interaction parameters can accurately determine gas-liquid phase equilibrium, and prediction can be made by analyzing binary phase diagrams, thereby improving accuracy.

[0010] Furthermore, the process of decomposing the gas molecules to be predicted into several groups specifically includes:

[0011] Based on the group contribution method for classifying gas molecule structures, the gas molecule to be predicted is decomposed into several groups.

[0012] Further, the calculation of the proportion parameter of each group to the gas molecules to be predicted specifically involves:

[0013] Wherein, the proportional parameter is the α parameter;

[0014] Calculate the α parameter of each group in the gas molecule to be predicted; wherein, 0 ≤ the value of the α parameter ≤ 1, and the sum of the α parameters of the plurality of groups in the gas molecule to be predicted is 1.

[0015] Based on the principle of group division, this invention divides the gas molecules to be predicted into different groups, and obtains the proportion of the groups to be predicted by acquiring the α parameter of the groups. This is used to establish binary interaction parameters and reduce the use of other experimental parameters, thereby reducing the computational load of the analysis.

[0016] Furthermore, the calculation of the binary interaction parameters based on the proportional parameters specifically involves:

[0017] An excess free energy mixing rule is established, and the mixing rule parameters are calculated based on the stated ratio parameters.

[0018] Based on the gas parameters, the cohesion parameters are calculated; wherein, the gas parameters include: critical temperature, critical pressure, and eccentricity factor;

[0019] Based on the mixing rule parameters and the cohesion parameters, binary interaction parameters are established.

[0020] This invention can calculate the binary interaction parameters using only the α parameter, critical temperature, critical pressure, and eccentricity factor, and the calculation accuracy is high. This avoids the use of many experimental parameters, reduces the amount of calculation, and ensures the accuracy of the analysis.

[0021] Furthermore, the establishment of the excess free energy mixing rule and the calculation of the mixing rule parameters based on the ratio parameter are specifically as follows:

[0022] Wherein, the excess free energy mixing rule is the Vanlaar excess free energy mixing rule;

[0023] Based on the PR equation of state and the Vanlaar molar excess free energy model, the Vanlaar excess free energy mixing rule is established.

[0024] Based on the aforementioned proportional parameters, the mixing rule parameters of the Vanlaar excess free energy mixing rule are obtained by solving.

[0025] Furthermore, the expression for the hybrid rule parameter is:

[0026]

[0027] Among them, A kl and B kl Here, Ng is the group interaction parameter, defined by the group contribution method, T is the current calculated temperature, and α is the total number of different groups. ik and α jk Let α be the α parameter for group k occupying molecules i and j, respectively. il and α jl The α parameters represent the occupancy of molecule i and molecule j by group l, respectively.

[0028] Furthermore, the cohesion parameter includes: a first cohesion parameter and a second cohesion parameter;

[0029] The expression for the first cohesive parameter is:

[0030]

[0031] Among them, T c,i P is the critical temperature of the gas to be predicted. c,i m is the critical pressure of the gas to be predicted. i These are adjustable parameters;

[0032] The expression for the second cohesion parameter is:

[0033]

[0034] Furthermore, the expression for the binary interaction parameter is:

[0035]

[0036] Among them, E ij (T) is the parameter of the hybrid rule, a i and aj b is the first cohesion parameter. i and b j This is the second cohesion parameter.

[0037] This invention can calculate the cohesion parameter using only the critical temperature, critical pressure, and eccentricity factor, and establish a binary interaction parameter based on the cohesion parameter and the mixing rule parameter. By using the binary interaction parameter in combination with the binary phase diagram, the gas-liquid phase equilibrium state can be accurately determined, while reducing the collection and use of experimental parameters and reducing the amount of calculation.

[0038] On the other hand, embodiments of the present invention also provide a binary vapor-liquid phase equilibrium prediction device, comprising: a decomposition module, a first calculation module, a second calculation module, and a prediction module;

[0039] The decomposition module is used to decompose the gas molecules to be predicted into several groups;

[0040] The first calculation module is used to calculate the proportion parameter of each group to the gas molecules to be predicted;

[0041] The second calculation module is used to calculate the binary interaction parameters based on the ratio parameters;

[0042] The prediction module is used to establish a binary phase diagram based on the binary interaction parameters, and to predict the gas-liquid phase equilibrium state based on the binary phase diagram.

[0043] Furthermore, the second calculation module includes: a first parameter calculation unit, a second parameter calculation unit, and a parameter establishment unit;

[0044] The first parameter calculation unit is used to establish the excess free energy mixing rule and calculate the mixing rule parameters according to the ratio parameter.

[0045] The second parameter calculation unit is used to calculate the cohesion parameter based on the gas parameters; wherein the gas parameters include: critical temperature, critical pressure, and eccentricity factor;

[0046] The parameter establishment unit is used to establish binary interaction parameters based on the mixing rule parameters and the cohesion parameters.

[0047] This invention obtains functional groups by decomposing gas molecules and establishes binary interaction parameters based on the proportional parameters of these functional groups. This avoids the need to use a large amount of experimental data to establish binary interaction parameters, thus reducing the computational workload of analyzing gas-liquid phase equilibrium. Furthermore, the binary interaction parameters can accurately determine gas-liquid phase equilibrium, and prediction can be made by analyzing binary phase diagrams, thereby improving accuracy. Attached Figure Description

[0048] Figure 1 A schematic flowchart of one embodiment of the binary vapor-liquid phase equilibrium prediction method provided in this invention;

[0049] Figure 2 A schematic flowchart of another embodiment of the binary vapor-liquid phase equilibrium prediction method provided in this invention;

[0050] Figure 3 A schematic flowchart of another embodiment of the binary vapor-liquid phase equilibrium prediction method provided in this invention;

[0051] Figure 4 A schematic diagram of one embodiment of the binary vapor-liquid phase equilibrium prediction device provided in this invention;

[0052] Figure 5 A schematic diagram of another embodiment of the binary vapor-liquid phase equilibrium prediction device provided in this invention;

[0053] Figure 6 A schematic diagram of one embodiment of the binary vapor-liquid phase equilibrium prediction result provided by the present invention;

[0054] Figure 7 This is a schematic diagram of another embodiment of the binary vapor-liquid phase equilibrium prediction results provided in this invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Example 1

[0057] Please refer to Figure 1 The flowchart of one embodiment of the binary vapor-liquid phase equilibrium prediction method provided by the present invention mainly includes steps 101-104, as follows:

[0058] Step 101: Decompose the gas molecules to be predicted into several groups.

[0059] Step 102: Calculate the proportion parameter of each group to the gas molecules to be predicted.

[0060] In this embodiment, the scaling parameter is the α parameter.

[0061] In this embodiment, calculating the proportion parameter of each group to the gas molecule to be predicted specifically involves calculating the α parameter of each group to the gas molecule to be predicted; wherein, 0 ≤ the value of the α parameter ≤ 1, and the sum of the α parameters of the plurality of groups of the gas molecule to be predicted is 1.

[0062] Step 103: Calculate the binary interaction parameters based on the aforementioned proportional parameters.

[0063] Based on the principle of group division, this invention divides the gas molecules to be predicted into different groups, and obtains the proportion of the groups to be predicted by acquiring the α parameter of the groups. This is used to establish binary interaction parameters and reduce the use of other experimental parameters, thereby reducing the computational load of the analysis.

[0064] In this embodiment, the binary interaction parameters are correlated with the group factor formula, which can connect the macroscopic gas-liquid phase equilibrium properties with the microscopic molecular structure. In addition, the binary interaction parameters play an important role in obtaining the overall prediction results. By optimizing the relationship between the binary interaction parameters and the number of groups and the group contribution model, and further weighting and iterating the group coefficients and binary interaction parameters, a more reliable theoretical prediction model can be obtained.

[0065] Step 104: Based on the binary interaction parameters, establish a binary phase diagram, and predict the gas-liquid phase equilibrium state based on the binary phase diagram.

[0066] In this embodiment, after establishing and analyzing the binary phase diagram, the gas-liquid phase equilibrium state of the gas to be predicted can be determined, and the gas-liquid phase equilibrium of the next group of gases to be predicted can be predicted. In addition, after determining the gas-liquid phase equilibrium state of the gas to be predicted, the prediction results can be used to guide the test system in selecting the corresponding working fluid and design method.

[0067] Please refer to Figure 2 This is a schematic flowchart of another embodiment of the binary vapor-liquid phase equilibrium prediction method provided in this invention. Figure 2 and Figure 1 The main difference is that, Figure 2 Including step 201, the details are as follows:

[0068] In this embodiment, step 101 is specifically step 201.

[0069] Step 201: Based on the group division principle of the gas molecule structure in the group contribution method, the gas molecule to be predicted is decomposed into several groups.

[0070] In this embodiment, the several groups that are split off play an important role in obtaining the overall prediction result. By optimizing the relationship between the binary interaction parameters and the number of groups and the group contribution model, and by further weighting and iterating the group coefficients and binary interaction parameters, a more reliable theoretical prediction model can be obtained.

[0071] Please refer to Figure 3 This is a flowchart illustrating another embodiment of the binary vapor-liquid phase equilibrium prediction method provided in this invention. Figure 3 and Figure 1 The main difference is that, Figure 3 Including steps 301-303, as follows:

[0072] Step 301: Establish the excess free energy mixing rule, and calculate the mixing rule parameters according to the ratio parameters.

[0073] In this embodiment, the establishment of the excess free energy mixing rule and the calculation of the mixing rule parameters based on the proportional parameters are specifically as follows: wherein the excess free energy mixing rule is a Vanlaar excess free energy mixing rule; the Vanlaar excess free energy mixing rule is established based on the PR equation of state and the Vanlaar molar excess free energy model; and the mixing rule parameters of the Vanlaar excess free energy mixing rule are obtained by solving based on the proportional parameters.

[0074] In this embodiment, the expression for the hybrid rule parameter is:

[0075]

[0076] Among them, A kl and B kl Here, Ng is the group interaction parameter, defined by the group contribution method, T is the current calculated temperature, and α is the total number of different groups. ik and α jk Let α be the α parameter for group k occupying molecules i and j, respectively. il and α jl The α parameters represent the occupancy of molecule i and molecule j by group l, respectively.

[0077] Step 302: Calculate the cohesion parameters based on the gas parameters; wherein the gas parameters include: critical temperature, critical pressure, and eccentricity factor.

[0078] In this embodiment, the cohesion parameter includes: a first cohesion parameter and a second cohesion parameter.

[0079] In this embodiment, the expression for the first cohesion parameter is:

[0080]

[0081] Among them, T c,i P is the critical temperature of the gas to be predicted. c,i m is the critical pressure of the gas to be predicted. i This is an adjustable parameter.

[0082] In this embodiment, the expression for the second cohesion parameter is:

[0083]

[0084] In this embodiment, given the critical temperature, critical pressure, and eccentricity factor of each binary gas, as well as the group interaction parameters of the groups separated from the binary gas, relatively accurate gas-liquid equilibrium data can be obtained solely through calculation. This significantly reduces the time required to obtain the gas-liquid equilibrium data of binary gases, which previously could only be measured through experimental trial and error. It improves the efficiency of obtaining the gas-liquid equilibrium data of binary gases, saving a significant amount of manpower, material resources, and time to quickly predict the gas-liquid equilibrium data of binary gases.

[0085] Step 303: Establish binary interaction parameters based on the mixing rule parameters and the cohesion parameters.

[0086] In this embodiment, the expression for the binary interaction parameter is:

[0087]

[0088] Among them, E ij (T) is the parameter of the hybrid rule, a i and a j b is the first cohesion parameter. i and b j This is the second cohesion parameter.

[0089] This invention calculates binary interaction parameters using only α parameters, critical temperature, critical pressure, and eccentricity factor, with high accuracy. It avoids the problems of molecular dynamics and Monte Carlo simulations, which heavily rely on molecular force fields and quantum mechanics methods, and suffer from massive computational burdens due to the involvement of electron motion, resulting in poor accuracy for complex mixtures. Furthermore, by predicting the gas-liquid equilibrium data of binary gases using the group contribution method, the computational load in the prediction process is reduced, improving predictive capability and accuracy.

[0090] In another embodiment, R116 refrigerant + R290 refrigerant is used as the gas to be predicted, wherein R116 refrigerant is hexafluoroethane and R290 refrigerant is propane.

[0091] First, the gas molecules to be predicted are decomposed into several groups using the group contribution method. Among them, R116 refrigerant is the first substance, with the structural formula CF3-CF3, containing two first groups -CF3, 0 second groups -CH3 and 1 third group -CH2-, and the total number of groups Ng is 2. R290 refrigerant is the second substance, with the structural formula CH3-CH2-CH3, containing 0 first groups -CF3, 2 second groups -CH3, and 1 third group -CH2-, and the total number of groups Ng is 2+1=3.

[0092] After calculating the number of decomposition groups, the α parameter of each group in the molecule is calculated, where the proportions of the first, second, and third groups in the first substance are: α 11 =2 / 2=1, α 12 =α 13 =0 / 2=0; The proportions of the first, second, and third groups in the second substance are: α 21 =0 / 3=0, α 22 =2 / 3, α 23 =1 / 3.

[0093] After obtaining the α parameter, calculate the mixing rule parameters; the binary interaction parameter k 12 Mixed rule parameters Where α 11 =2 / 2=1, α 12 =α 13 =0 / 2=0, α 21 =0 / 3=0, α 22 =2 / 3, α 23 =1 / 3; A 12 =A 21 =123200000, A 13 =195600000, A 23 =74810000; B 12 =B 21 =133800000, B 13 =199000000, B 23 =165700000; T=303.15K.

[0094] After substituting into the expression, E is calculated. ij (T) = 1.3090 × 10 8 .

[0095] The critical temperature T c,1 =369.95K, critical pressure P c,1 Substituting 4245500Pa and the eccentricity factor ω1 = 0.152 into the expressions for the first and second cohesive parameters, we obtain:

[0096]

[0097]

[0098]

[0099]

[0100] Based on the calculated mixing rule parameters and cohesion parameters, binary interaction parameters are established, where...

[0101]

[0102] Please refer to Figure 6 This is a schematic diagram of one embodiment of the binary vapor-liquid phase equilibrium prediction result provided by the present invention, wherein... Figure 6 The Pxy diagram is for R116 refrigerant + R290 refrigerant.

[0103] Please refer to Figure 7 This is a schematic diagram of another embodiment of the binary vapor-liquid phase equilibrium prediction results provided by the present invention, wherein... Figure 7 The Txy diagram for R116 refrigerant + R290 refrigerant is shown. Analyzing and classifying the binary phase diagram allows for the determination of the gas-liquid phase equilibrium state of the binary gas. From... Figure 6 and Figure 7 It can be seen that R116 refrigerant + R290 refrigerant do not form an azeotrope, which is basically consistent with the experimental value.

[0104] In this embodiment, the predicted results can be used to guide the system in selecting the working fluid and designing the system, as well as to determine which system is suitable for R116 refrigerant + R290 refrigerant based on the actual situation.

[0105] Please refer to Figure 4 This is a schematic diagram of the structure of an embodiment of the binary vapor-liquid phase equilibrium prediction device provided by the present invention, which mainly includes a decomposition module 401, a first calculation module 402, a second calculation module 403, and a prediction module 404.

[0106] In this embodiment, the decomposition module 401 is used to decompose the gas molecules to be predicted into several groups.

[0107] In this embodiment, the decomposition module 401 includes a decomposition unit; the decomposition unit is used to decompose the gas molecule to be predicted into several groups according to the group division principle of the gas molecule structure of the group contribution method.

[0108] The first calculation module 402 is used to calculate the proportion parameter of each group to the gas molecules to be predicted.

[0109] In this embodiment, the first calculation module 402 includes a proportional parameter calculation unit; wherein the proportional parameter is an α parameter; the proportional parameter calculation unit is used to calculate the α parameter of each group in the gas molecule to be predicted; wherein 0 ≤ the value of the α parameter ≤ 1, and the sum of the α parameters of the plurality of groups in the gas molecule to be predicted is 1.

[0110] The second calculation module 403 is used to calculate the binary interaction parameters based on the ratio parameters.

[0111] The prediction module 404 is used to establish a binary phase diagram based on the binary interaction parameters, and to predict the gas-liquid phase equilibrium state based on the binary phase diagram.

[0112] Please refer to Figure 5 This is a schematic diagram of another embodiment of the binary vapor-liquid phase equilibrium prediction device provided in this invention. Figure 5 and Figure 4 The main difference is that, Figure 5 It includes a first parameter calculation unit 501, a second parameter calculation unit 502, and a parameter establishment unit 503.

[0113] In this embodiment, the second calculation module 403 includes a first parameter calculation unit 501, a second parameter calculation unit 502, and a parameter establishment unit 503.

[0114] In this embodiment, the first parameter calculation unit 501 is used to establish the excess free energy mixing rule and calculate the mixing rule parameters according to the ratio parameter.

[0115] In this embodiment, the first parameter calculation unit 501 includes: a rule establishment subunit and a parameter calculation subunit; wherein, the excess free energy mixing rule is a Vanlaar excess free energy mixing rule; the rule establishment subunit is used to establish the Vanlaar excess free energy mixing rule according to the PR equation of state and the Vanlaar molar excess free energy model; the parameter calculation subunit is used to solve for the mixing rule parameters of the Vanlaar excess free energy mixing rule according to the proportional parameters.

[0116] The second parameter calculation unit 502 is used to calculate the cohesion parameter based on the gas parameters; wherein the gas parameters include: critical temperature, critical pressure and eccentricity factor.

[0117] The parameter establishment unit 503 is used to establish binary interaction parameters based on the mixing rule parameters and the cohesion parameters.

[0118] This invention obtains functional groups by decomposing gas molecules and establishes binary interaction parameters based on the proportional parameters of these functional groups. This avoids the need to use a large amount of experimental data to establish binary interaction parameters, thus reducing the computational workload of analyzing gas-liquid phase equilibrium. Furthermore, the binary interaction parameters can accurately determine gas-liquid phase equilibrium, and prediction can be made by analyzing binary phase diagrams, thereby improving accuracy.

[0119] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for predicting binary vapor-liquid phase equilibrium, characterized in that, include: The gas molecules to be predicted are broken down into several groups; Calculate the proportion of each group to the gas molecules to be predicted; Based on the aforementioned proportional parameters, the binary interaction parameters are calculated. Based on the binary interaction parameters, a binary phase diagram is established, and based on the binary phase diagram, the gas-liquid phase equilibrium state is predicted. The binary interaction parameters are calculated based on the proportional parameters, specifically as follows: An excess free energy mixing rule is established, and the mixing rule parameters are calculated based on the stated ratio parameters. Based on the gas parameters, the cohesion parameters are calculated; wherein, the gas parameters include: critical temperature, critical pressure, and eccentricity factor; Based on the mixing rule parameters and the cohesion parameters, establish binary interaction parameters; The establishment of the excess free energy mixing rule, and the calculation of the mixing rule parameters based on the ratio parameter, are specifically as follows: Wherein, the excess free energy mixing rule is the van laar excess free energy mixing rule; Based on the PR equation of state and the van Laar molar excess free energy model, a van Laar excess free energy mixing rule is established. Based on the aforementioned proportional parameters, the mixing rule parameters of the van laar excess free energy mixing rule are obtained by solving. The expression for the binary interaction parameter is: ； in, The parameters of the mixing rules, and The first cohesion parameter, and This is the second cohesion parameter.

2. The binary vapor-liquid phase equilibrium prediction method as described in claim 1, characterized in that, The process of decomposing the gas molecules to be predicted into several groups specifically involves: Based on the group contribution method for classifying gas molecule structures, the gas molecule to be predicted is decomposed into several groups.

3. The binary vapor-liquid phase equilibrium prediction method as described in claim 1, characterized in that, The calculation of the proportion of each group to the gas molecules to be predicted is specifically as follows: Wherein, the proportional parameter is the α parameter; Calculate the α parameter of each group in the gas molecule to be predicted; wherein, 0 ≤ the value of the α parameter ≤ 1, and the sum of the α parameters of the plurality of groups in the gas molecule to be predicted is 1.

4. The binary vapor-liquid phase equilibrium prediction method as described in claim 1, characterized in that, The expression for the hybrid rule parameter is: ； in, and For group interaction parameters, It is the total amount of different groups as defined by the group contribution method. The current calculated temperature, and They are groups occupying molecules and molecules The α parameter, and They are groups occupying molecules and molecules The α parameter.

5. The binary vapor-liquid phase equilibrium prediction method as described in claim 1, characterized in that, The cohesive parameters include: a first cohesive parameter and a second cohesive parameter; The expression for the first cohesive parameter is: ； in, The critical temperature of the gas to be predicted is... The critical pressure of the gas to be predicted, These are adjustable parameters; The expression for the second cohesion parameter is: 。 6. A binary vapor-liquid phase equilibrium prediction device, characterized in that, include: Decomposition module, first calculation module, second calculation module, prediction module; The decomposition module is used to decompose the gas molecules to be predicted into several groups; The first calculation module is used to calculate the proportion parameter of each group to the gas molecules to be predicted; The second calculation module is used to calculate the binary interaction parameters based on the ratio parameters; The prediction module is used to establish a binary phase diagram based on the binary interaction parameters, and to predict the gas-liquid phase equilibrium state based on the binary phase diagram. The second calculation module includes: a first parameter calculation unit, a second parameter calculation unit, and a parameter establishment unit; The first parameter calculation unit is used to establish the excess free energy mixing rule and calculate the mixing rule parameters according to the ratio parameter. The second parameter calculation unit is used to calculate the cohesion parameter based on the gas parameters; wherein the gas parameters include: critical temperature, critical pressure, and eccentricity factor; The parameter establishment unit is used to establish binary interaction parameters based on the mixing rule parameters and the cohesion parameters; The first parameter calculation unit includes a rule establishment subunit and a parameter calculation subunit; wherein, the excess free energy mixing rule is a van Laar excess free energy mixing rule; the rule establishment subunit is used to establish the van Laar excess free energy mixing rule based on the PR equation of state and the van Laar molar excess free energy model; the parameter calculation subunit is used to solve for the mixing rule parameters of the van Laar excess free energy mixing rule based on the proportional parameters; The expression for the binary interaction parameter is: ； in, The parameters of the mixing rules, and The first cohesion parameter, and This is the second cohesion parameter.

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