CN111859667B - Modeling method for predicting performance of automobile air conditioner condenser - Google Patents
Modeling method for predicting performance of automobile air conditioner condenser Download PDFInfo
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Abstract
A modeling method for predicting the performance of an automotive air conditioning condenser comprises the following steps: s1: modeling and data calibration are carried out on the condenser according to structural parameters and experimental data of the condenser, a Knoop coefficient of a wind side and a flow resistance coefficient of a refrigerant side are obtained by utilizing an AMESIM calibration program, and if a calibration error is within a set error, the condenser model is used for performance prediction; s2: the inlet temperature and inlet pressure of a refrigerant side and the outlet supercooling degree are given, the inlet air temperature and relative humidity, the air speed and the atmospheric pressure are given to a wind side as model input conditions, and a condenser prediction model is established; s3: and if the performance under other working conditions is predicted, directly changing the input conditions, and calculating according to an internal program of AMESIM software to obtain the predicted condenser performance. A method for effectively guiding engineers to predict the heat exchange and flow resistance performance of a condenser in the development stage.
Description
Technical Field
The invention relates to the field of performance prediction of automobile air conditioner heat exchangers, in particular to a modeling method for predicting the performance of an automobile air conditioner condenser.
Background
The method is characterized in that 2 methods are used for testing and simulating the heat exchange and flow resistance performance of the automobile air conditioner condenser, wherein the steady-state simulation modeling method for the automobile air conditioner heat exchanger mainly comprises centralized parameter modeling, distributed parameter modeling and partition modeling.
The accuracy of centralized parameter modeling is poor, and the method is replaced by the last 2 methods, along with the requirement of rapid and accurate simulation analysis, the defects of the traditional modeling simulation gradually appear, most simulation researches on the automobile air conditioner need to establish physical and mathematical models, and programming software is used for programming complex programs, the method is time-consuming and labor-consuming, the comparison precision of the calculation result and the test is not necessarily high, along with the development of computer technology and the appearance of mature commercial hot fluid simulation software, the simulation of the air conditioning system enters a new stage, and the relatively mature one-dimensional fluid simulation software such as Flowmaster, AMESim and the like is widely applied to the simulation of the automobile air conditioner. The existing method for predicting condenser performance in amesim is to establish a whole set of laboratory-simulated refrigeration control system model, which is large and complex and is not beneficial to rapidly predicting condenser performance. The invention utilizes AMESim to establish a model which can predict and quickly predict the heat exchange and flow resistance performances under different working conditions without establishing a complex refrigeration control system model, and can effectively guide engineers to predict the heat exchange and flow resistance performances of the condenser in the development stage.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a modeling method for predicting the performance of an automobile air conditioner condenser, which has the following specific technical scheme:
a modeling method for predicting the performance of an automobile air conditioner condenser is characterized by comprising the following steps: the method comprises the following steps:
s1: modeling and data calibration are carried out on the condenser according to structural parameters and experimental data of the condenser, a Knoop coefficient of a wind side and a flow resistance coefficient of a refrigerant side are obtained by utilizing an AMESIM calibration program, and if a calibration error is within a set error, the condenser model is used for performance prediction;
s2: the inlet temperature and inlet pressure of a refrigerant side and the outlet supercooling degree are given, the inlet air temperature and relative humidity, the air speed and the atmospheric pressure are given to a wind side as model input conditions, and a condenser prediction model is established;
s3: and if the performance under other working conditions is predicted, directly changing the input conditions, and calculating according to an internal program of AMESIM software to obtain the predicted condenser performance.
Further: the condenser prediction model comprises a condenser model structure (1), the inlet end of the condenser model structure (1) is connected with a pressure and temperature module at the inlet end through an inlet local flow resistance calculation module (2), and the pressure and temperature module at the inlet end respectively acquires an inlet pressure input parameter (4) and an inlet temperature input parameter (5);
an inlet pressure sensor (6) is arranged between the pipeline inlet local flow resistance calculation module (2) and the inlet pressure temperature module (3);
an outlet local flow resistance calculation module (7) is arranged at the outlet end of the condenser model structure (1), and the outlet local flow resistance calculation module (7) is connected with an outlet pressure and temperature module (8);
an outlet temperature sensor (9) is arranged at a water outlet of the condenser model structure (1), and the outlet temperature sensor (9) outputs the outlet temperature of the condenser model structure (1) to a reverse module (10);
the inversion module (10) is used for adding the outlet temperature parameter value and a parameter value of the outlet supercooling value (11) after inversion to obtain a saturation temperature parameter (22);
a refrigerant physical property parameter conversion module (12) is arranged, and the saturation temperature parameter and the dryness parameter are converted by the refrigerant physical property parameter conversion module (12) to obtain a pressure parameter as an outlet condition input parameter of the condenser;
an air inlet of the condenser model structure (1) is connected with an air outlet of the fan model (13), and an air density sensor (14) is arranged at the air inlet of the condenser model structure (1);
an inlet air temperature input parameter (15) is set at a first simulation port of the fan model (13), an atmospheric pressure input parameter (16) is set at a second simulation port of the fan model (13), and a relative humidity input parameter (17) is set at a third simulation port of the fan model (13);
the unit of a fourth simulation port input parameter of the fan model (13) is kg/s, and the unit of a wind speed input parameter (21) is m/s;
the unit conversion is carried out on the wind speed input parameter (21), the fourth simulation port input parameter is that the wind speed input parameter (21) is multiplied by the heat exchange area of the condenser through a heat exchange area multiplication module (19), and a first intermediate value is obtained;
an air density sensor (14) acquires inlet air density parameters of the condenser;
respectively multiplying the inlet air density parameter with a first intermediate value and an air density value through an air density multiplication module (20) to complete unit conversion, and obtaining a fourth simulation port input parameter;
and an air outlet of the condenser model structure (1) provides an air side output parameter (18).
Further: the calibration error is within 5%.
The invention has the beneficial effects that: the AMESim is used for establishing a model which can predict the heat exchange and flow resistance performances under different working conditions rapidly by using less data without establishing a complex refrigeration control system model, and can predict the heat exchange and flow resistance performances under different working conditions rapidly, so that an engineer can be effectively guided to predict the heat exchange and flow resistance performances of the condenser in a development stage.
Drawings
FIG. 1 is a block diagram of a condenser model;
FIG. 2 shows fin setting parameters according to the present invention;
FIG. 3 shows parameters set for the flat tubes of the present invention;
FIG. 4 is test data for test conditions;
FIG. 5 is a graph showing the results of the simulation;
the reference numbers in the figure illustrate that the condenser model structure 1, the inlet local flow resistance calculation module 2, the inlet pressure temperature module 3, the inlet pressure input parameter 4, the inlet temperature input parameter 5, the inlet pressure sensor 6, the outlet local flow resistance calculation module 7, the outlet pressure temperature module 8, the outlet temperature sensor 9, the inversion module 10, the outlet subcooling value 11, the refrigerant physical property parameter conversion module 12, the fan model 13, the air density sensor 14, the inlet air temperature input parameter 15, the atmospheric pressure input parameter 16, the relative humidity input parameter 17, the corrected air speed parameter 18, the heat exchange area multiplication module 19, the air density multiplication module 20, the air speed input parameter 21, the saturation temperature parameter 22, the dryness input parameter 23, the refrigerant type 24, the condenser material parameter 25 and the condenser structure parameter 26.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention.
As shown in fig. 1 to 5: a modeling method for predicting the performance of an automobile air conditioner condenser comprises the following steps:
s1: modeling and data calibration are carried out on the condenser according to structural parameters and experimental data of the condenser, an AMESIM calibration program is utilized to obtain a Knoop coefficient of a wind side and a flow resistance coefficient of a refrigerant side, and if a calibration error is within 5%, the condenser model is used for performance prediction;
s2: the inlet temperature and inlet pressure of a refrigerant side and the outlet supercooling degree are given, the inlet air temperature and relative humidity, the air speed and the atmospheric pressure are given to a wind side as model input conditions, and a condenser prediction model is established;
in an ideal refrigeration Carnot cycle, the condenser does not consider the pressure drop, but the pressure drop must be considered in simulation software, because the pressure drop influences the performance of the heat exchanger, but the outlet pressure is unknown in the prediction, so the principle of the model is that the pressure drop from the saturated liquid state to the supercooled liquid state is not considered, and the pressure in the saturated liquid state is directly input to the outlet pressure.
The cross-sectional flow area of the pipeline is required to be as large as possible, the length of the pipeline is as short as possible, and the pipeline can affect pressure drop, so that errors are large. But also not the elimination of piping, which can cause some condenser predictions to fail. When the simulation is predicted, the problem that the heat exchange amount fluctuates can be solved by increasing the length of the pipeline, whether the pressure drop before and after the pipeline is obviously existed (greater than 1kap) needs to be observed after the pipeline is increased, and if the pressure drop is not obvious, the model is available;
s3: when the performance of the condenser under other working conditions needs to be predicted, the input conditions are directly changed, fig. 4 shows the results of prediction and actual data of the same condenser under other working conditions, and the heat exchange performance and the flow resistance performance are within 5%, which shows that the prediction model can more accurately predict the performance of the condenser.
The condenser prediction model comprises a condenser model structure 1, wherein the inlet end of the condenser model structure 1 is connected with a pressure and temperature module at the inlet end through an inlet local flow resistance calculation module 2, and the pressure and temperature module at the inlet end respectively acquires an inlet pressure input parameter 4 and an inlet temperature input parameter 5;
an inlet pressure sensor 6 is arranged between the pipeline inlet local flow resistance calculation module 2 and the inlet pressure temperature module 3;
an outlet local flow resistance calculation module 7 is arranged at the outlet end of the condenser model structure 1, and the outlet local flow resistance calculation module 7 is connected with an outlet pressure and temperature module 8;
an outlet temperature sensor 9 is arranged at a water outlet of the condenser model structure 1, and the outlet temperature sensor 9 outputs the outlet temperature of the condenser model structure 1 to a reverse module 10;
the inversion module 10 is used for adding the output temperature parameter value and the output undercooling value 11 to a dryness input parameter 23 after inversion to obtain a saturation temperature parameter 22;
a refrigerant physical property parameter conversion module 12 is arranged, and the saturated temperature parameter and the dryness parameter are converted by the refrigerant physical property parameter conversion module 12 to obtain a pressure parameter as an outlet condition input parameter of the condenser;
an air inlet of the condenser model structure 1 is connected with an air outlet of the fan model 13, and an air density sensor 14 is arranged at the air inlet of the condenser model structure 1;
the first simulation port of the fan model 13 is set with an inlet air temperature input parameter 15, the second simulation port of the fan model 13 is set with an atmospheric pressure input parameter 16, and the third simulation port of the fan model 13 is set with a relative humidity input parameter 17;
the unit of the input parameter of the fourth simulation port of the fan model 13 is kg/s, and the unit of the wind speed input parameter 21 is m/s;
the unit conversion is carried out on the wind speed input parameter 21, the fourth simulation port input parameter is that the wind speed input parameter 21 is multiplied by the heat exchange area of the condenser through the heat exchange area multiplication module 19, and a first intermediate value is obtained;
an air density sensor 14 acquires an inlet air density parameter of the condenser;
respectively multiplying the inlet air density parameter with the first intermediate value and the air density value through an air density multiplication module 20 to complete unit conversion, and obtaining a fourth simulation port input parameter;
the air outlet of the condenser model structure 1 provides an air side output parameter 18.
Claims (2)
1. A modeling method for predicting the performance of an automobile air conditioner condenser is characterized by comprising the following steps: the method comprises the following steps:
s1: modeling and data calibration are carried out on the condenser according to structural parameters and experimental data of the condenser, a Knoop coefficient of a wind side and a flow resistance coefficient of a refrigerant side are obtained by utilizing an AMESIM calibration program, and if a calibration error is within a set error, the condenser model is used for performance prediction;
s2: the inlet temperature and inlet pressure of a refrigerant side and the outlet supercooling degree are given, the inlet air temperature and relative humidity, the air speed and the atmospheric pressure are given to a wind side as model input conditions, and a condenser prediction model is established;
s3: if the performance under other working conditions needs to be predicted, directly changing the input condition, and calculating according to an internal program of AMESIM software to obtain the performance of the predicted condenser;
the condenser prediction model comprises a condenser model structure (1), the inlet end of the condenser model structure (1) is connected with a pressure and temperature module at the inlet end through an inlet local flow resistance calculation module (2), and the pressure and temperature module at the inlet end respectively acquires an inlet pressure input parameter (4) and an inlet temperature input parameter (5);
an inlet pressure sensor (6) is arranged between the pipeline inlet local flow resistance calculation module (2) and the inlet pressure temperature module (3);
an outlet local flow resistance calculation module (7) is arranged at the outlet end of the condenser model structure (1), and the outlet local flow resistance calculation module (7) is connected with an outlet pressure and temperature module (8);
an outlet temperature sensor (9) is arranged at a water outlet of the condenser model structure (1), and the outlet temperature sensor (9) outputs the outlet temperature of the condenser model structure (1) to a reverse module (10);
the inversion module (10) is used for adding the outlet temperature parameter value and a parameter value of the outlet supercooling value (11) after inversion to obtain a saturation temperature parameter (22);
a refrigerant physical property parameter conversion module (12) is arranged, and the saturation temperature parameter and the dryness parameter are converted by the refrigerant physical property parameter conversion module (12) to obtain a pressure parameter as an outlet condition input parameter of the condenser;
an air inlet of the condenser model structure (1) is connected with an air outlet of the fan model (13), and an air density sensor (14) is arranged at the air inlet of the condenser model structure (1);
an inlet air temperature input parameter (15) is set at a first simulation port of the fan model (13), an atmospheric pressure input parameter (16) is set at a second simulation port of the fan model (13), and a relative humidity input parameter (17) is set at a third simulation port of the fan model (13);
the unit of a fourth simulation port input parameter of the fan model (13) is kg/s, and the unit of a wind speed input parameter (21) is m/s;
the unit conversion is carried out on the wind speed input parameter (21), the fourth simulation port input parameter is that the wind speed input parameter (21) is multiplied by the heat exchange area of the condenser through a heat exchange area multiplication module (19), and a first intermediate value is obtained;
an air density sensor (14) acquires inlet air density parameters of the condenser;
respectively multiplying the inlet air density parameter with a first intermediate value and an air density value through an air density multiplication module (20) to complete unit conversion, and obtaining a fourth simulation port input parameter;
and an air outlet of the condenser model structure (1) provides an air side output parameter (18).
2. The modeling method for predicting the performance of the condenser of the air conditioner of the automobile as claimed in claim 1, wherein: the calibration error is within 5%.
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