Air conditioner compressor power consumption prediction method, system, equipment and medium

Abstract

The invention provides an air conditioner compressor power consumption prediction method and system, electronic equipment and a storage medium. The air conditioner compressor power consumption prediction method comprises the steps that the exhaust pressure, the suction pressure, the suction temperature, the exhaust temperature, the displacement and the refrigerant adiabatic index of an air conditioner compressor are obtained; according to the exhaust pressure, the suction pressure, the displacement and the refrigerant adiabatic index, a power factor fitting polynomial is used for calculating the power factor of the air conditioner compressor; according to the exhaust pressure, the suction pressure, the suction temperature, the exhaust temperature and the displacement, the active power of the air conditioner compressor is obtained; and predicting the power consumption of the air conditioner compressor according to the active power and the power factor. When the refrigerant of the compressor is replaced, the power factor does not need to be re-fitted, and only the adiabatic index of the corresponding refrigerant needs to be substituted, so that data dependence is reduced; and physical property parameters can be switched, the model is not adjusted, and the generalization ability and expansibility of the model are improved. Compared with the prior art, under limited data calibration, the model is more visual, coefficients are few, and the thermal management development efficiency and the power consumption prediction accuracy of the whole vehicle can be improved.

Description

Technical Field

[0001] This application relates to the field of air conditioning system technology, and in particular to a method, system, device and medium for predicting the power consumption of an air conditioning compressor. Background Technology

[0002] With the accelerated electrification of automobiles, energy consumption prediction for electric vehicles has become a hot research topic in the industry. As the main energy-consuming component of the vehicle, the accuracy of the air conditioning system's energy consumption prediction directly affects the overall vehicle energy consumption prediction results. The compressor, as a core component of the air conditioning system, is a key element in the energy efficiency assessment and optimization of the air conditioning system, and is of great significance for improving overall vehicle energy efficiency and reducing energy consumption.

[0003] Currently, air conditioner compressor power consumption prediction mainly relies on experimental data fitting or empirical models (such as the industry-common AHRI + coefficient model). These methods require fitting experimental data under different compressor operating conditions to establish the correlation between performance and operating parameters. Under specific operating conditions, this type of method can achieve relatively accurate predictions, but it has obvious limitations: on the one hand, when the operating conditions change significantly, the prediction accuracy drops sharply, and the model's applicability is limited by the coverage of experimental data, resulting in weak generalization ability and insufficient scalability; on the other hand, facing new refrigerants (especially with the current upgrading of environmental protection requirements, the research and application of fifth-generation environmentally friendly refrigerants has become an industry hotspot), existing methods rely on a large amount of experimental data, making it difficult to quickly and accurately predict compressor power consumption under different refrigerant conditions. This not only increases the difficulty of refrigerant selection but also significantly increases the cost of air conditioning system optimization, failing to meet the current development needs of refrigeration technology.

[0004] Therefore, there is an urgent need for a method that can quickly and accurately predict compressor power consumption under different refrigerant conditions. Summary of the Invention

[0005] This application provides a microcontroller software update method, system, and automotive controller to solve the technical problems of weak generalization ability, insufficient scalability, and difficulty in quickly and accurately predicting compressor power consumption when changing refrigerant types in existing compressor power consumption models.

[0006] This application provides a method for predicting the power consumption of an air conditioner compressor, including: Obtain the air conditioner compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index; The power factor of the air conditioning compressor is calculated using a power factor fitting polynomial based on the exhaust pressure, intake pressure, displacement, and refrigerant adiabatic index. The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature and displacement. The power consumption of the air conditioner compressor is predicted based on the active power and the power factor.

[0007] In one optional embodiment of this application, obtaining the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature, and displacement includes: The intake density and exhaust density of the air conditioning compressor are obtained based on the exhaust pressure, intake pressure, intake temperature, and exhaust temperature. The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake density, and exhaust density.

[0008] In one optional embodiment of this application, obtaining the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake density, exhaust density, and displacement includes: The volumetric efficiency of the air conditioning compressor is obtained based on the intake density and exhaust density. Based on the displacement, obtain the volumetric flow rate of the air conditioning compressor; The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake density, exhaust density, volumetric flow rate, and volumetric efficiency.

[0009] In an optional embodiment of this application, the expression for the active power of the air conditioner compressor is: Wo=(1+ρi / ρo) / 2*V*(Pc-Pe)*101 / 3600*ηv Where ρi represents the intake density of the air conditioning compressor, ρo represents the exhaust density of the air conditioning compressor, V represents the volumetric flow rate of the air conditioning compressor, Pc represents the exhaust pressure of the air conditioning compressor, Pe represents the intake pressure of the air conditioning compressor, and ηv represents the volumetric efficiency of the air conditioning compressor.

[0010] In an optional embodiment of this application, the formula for calculating the volumetric flow rate V is: V=D / 1000000*N*60 Where D is the compressor displacement and N is the compressor speed.

[0011] In an optional embodiment of this application, the volumetric efficiency ηv is expressed as: ηv =(-A0*N^2+A1*N+A2)*((ρoo / ρio) / (ρo / ρi)) ^A3 Where N represents the rotational speed of the air conditioning compressor, ρi represents the intake density of the air conditioning compressor, ρo represents the exhaust density of the air conditioning compressor, ρio represents the intake density of the air conditioning compressor under the reference operating condition, ρoo represents the exhaust density of the air conditioning compressor under the reference operating condition, and A0, A1, A2, and A3 are polynomial fitting coefficients.

[0012] In an optional embodiment of this application, the expression for the power factor n is: n=MIN(A4+A5*LN(Pc / Pe)-A6*LN(D)-A7*LN(k), 0.95) Where N represents the speed of the air conditioner compressor, Pc represents the discharge pressure of the air conditioner compressor, Pe represents the suction pressure of the air conditioner compressor, D represents the displacement of the air conditioner compressor, and k represents the refrigerant adiabatic index of the air conditioner compressor.

[0013] In an optional embodiment of this application, the power consumption model expression of the air conditioner compressor is: W = Wo / n Where W represents the power consumption of the air conditioner compressor, Wo represents the active power of the air conditioner compressor, and n represents the power factor of the air conditioner compressor.

[0014] This application also provides an air conditioner compressor power consumption prediction system, including: The data acquisition module is used to acquire the air conditioner compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index. The power factor calculation module is used to calculate the power factor of the air conditioner compressor based on the exhaust pressure, intake pressure, displacement and refrigerant adiabatic index using a power factor fitting polynomial. The active power calculation module is used to obtain the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature and displacement. The power consumption prediction module is used to predict the power consumption of the air conditioner compressor based on the active power and the power factor.

[0015] This application also provides an electronic device, the electronic device comprising: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the electronic device to implement any of the above-described methods for predicting the power consumption of an air conditioner compressor.

[0016] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer's processor, causes the computer to perform any of the above-described methods for predicting the power consumption of an air conditioning compressor.

[0017] This application obtains the discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index of an air conditioning compressor; calculates the power factor of the air conditioning compressor using a power factor fitting polynomial based on the discharge pressure, suction pressure, displacement, and refrigerant adiabatic index; obtains the active power of the air conditioning compressor based on the discharge pressure, suction pressure, suction temperature, discharge temperature, and displacement; and predicts the power consumption of the air conditioning compressor based on the active power and the power factor. This method can predict compressor power consumption based on the compressor's power factor. When the refrigerant type needs to be changed, there is no need to refit the power factor; only the corresponding refrigerant's adiabatic index needs to be input to obtain a new power factor, greatly reducing the dependence on data volume. This application allows for easy switching of different refrigerant properties without adjusting the model, improving the model's generalization ability and scalability. Compared with existing technologies, with limited data calibration, the model is more intuitive, requires fewer coefficients for calibration and learning, greatly improving the development efficiency of vehicle thermal management and the accuracy of vehicle power consumption prediction. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0019] In the attached diagram: Figure 1 This is a flowchart illustrating the air conditioner compressor power consumption prediction method provided in one embodiment of this application; Figure 2 This is a schematic diagram of a module of an air conditioning compressor power consumption prediction system provided in an embodiment of this application; Figure 3 This is a schematic diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0020] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0022] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0023] Figure 1 This is a flowchart of the air conditioner compressor power consumption prediction method of this application. Figure 1 As shown, the air conditioner compressor power consumption prediction method of this application includes the following steps: Step S10: Obtain the air compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index.

[0024] Among them, discharge pressure, suction pressure, suction temperature, and discharge temperature are the basic parameters of compressor operation, which can be obtained through corresponding sensors; displacement is the specification parameter of air conditioning compressor, which is determined by compressor design and manufacturing; refrigerant adiabatic index is a key parameter for measuring the thermodynamic characteristics of refrigerant during the adiabatic process, representing the ratio of the refrigerant's specific heat capacity at constant pressure to its specific heat capacity at constant volume. Its value mainly depends on the molecular structure and physical properties of the refrigerant. For example, the adiabatic index of carbon dioxide can be taken as 1.295, and the adiabatic index of R134a can be taken as 1.14.

[0025] Step S20: Based on the exhaust pressure, intake pressure, displacement, and refrigerant adiabatic index, calculate the power factor of the air conditioning compressor using a power factor fitting polynomial.

[0026] The expression for the power factor n is: n=MIN(A4+A5*LN(Pc / Pe)-A6*LN(D)-A7*LN(k), 0.95) Where Pc represents the discharge pressure of the air conditioner compressor, Pe represents the suction pressure of the air conditioner compressor, D represents the displacement of the air conditioner compressor, k represents the refrigerant adiabatic index of the air conditioner compressor, and A4, A5, A6 and A7 are polynomial fitting coefficients.

[0027] In one specific embodiment, the power factor calculation formula for a compressor is as follows: n=MIN(1.29+0.09*LN(Pc / Pe)-0.08*LN(D)-2.5*LN(k), 0.95).

[0028] Step S30: Obtain the active power of the air conditioning compressor based on the discharge pressure, suction pressure, suction temperature, discharge temperature, and discharge volume. The active power of the air conditioning compressor is the compression work obtained by the refrigerant compressed by the compressor.

[0029] Step S30 may further include: Step S31: Obtain the suction density and discharge density of the air conditioning compressor based on the discharge pressure, suction pressure, suction temperature, and discharge temperature. The suction density and discharge density can be calculated using the gas state equation based on pressure and temperature, or derived from refrigerant property tools based on pressure and temperature, or obtained by consulting the corresponding refrigerant's thermodynamic property table based on pressure and temperature.

[0030] Step S32: Obtain the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake density, exhaust density, and displacement.

[0031] The process of obtaining the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake density, exhaust density, and displacement may further include: Step S321: Obtain the volumetric efficiency of the air conditioning compressor based on the intake density and exhaust density. The expression for the volumetric efficiency ηv is: ηv =(-A0*N^2+A1*N+A2)*((ρoo / ρio) / (ρo / ρi))^A3 Where N represents the air conditioner compressor speed, ρi represents the air conditioner compressor intake density, ρo represents the air conditioner compressor exhaust density, ρio represents the air conditioner compressor intake density under reference operating conditions, ρoo represents the air conditioner compressor exhaust density under reference operating conditions, and A0, A1, A2, and A3 are polynomial fitting coefficients.

[0032] It should be noted that the baseline operating condition (also known as the standard operating condition) of an air conditioning compressor is a standardized operating condition set by the industry for the unified testing and evaluation of compressor performance (such as cooling capacity, power consumption, COP, etc.). The core is to uniformly define key parameters such as evaporation temperature, condensation temperature, suction temperature, and subcooling temperature to avoid the lack of comparability of performance data due to differences in operating conditions.

[0033] In one specific embodiment, the expression for the volumetric efficiency ηv of a compressor is: ηv =(-0.000000004741*N^2+0.000052696442*N+0.754432241452) * ((ρoo / ρio) / (ρo / ρi))^0.05.

[0034] Step S322: Obtain the volumetric flow rate of the air conditioning compressor based on the displacement. The formula for calculating the volumetric flow rate V is: V=D / 1000000*N*60 Where D is the compressor displacement and N is the air conditioner compressor speed.

[0035] Step S323: Obtain the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake density, exhaust density, volumetric flow rate, and volumetric efficiency. The expression for the active power of the air conditioning compressor is: Wo=(1+ρi / ρo) / 2*V*(Pc-Pe)*101 / 3600*ηv Where ρi represents the intake density of the air conditioning compressor, ρo represents the exhaust density of the air conditioning compressor, V represents the volumetric flow rate of the air conditioning compressor, Pc represents the exhaust pressure of the air conditioning compressor, Pe represents the intake pressure of the air conditioning compressor, and ηv represents the volumetric efficiency of the air conditioning compressor.

[0036] Step S40: Based on the active power and the power factor, predict the power consumption of the air conditioner compressor. The power consumption model expression for the air conditioner compressor is: W=Wo / n Where W represents the power consumption of the air conditioner compressor, Wo represents the active power of the air conditioner compressor, and n represents the power factor of the air conditioner compressor.

[0037] The above method can predict compressor power consumption based on the compressor's power factor. When the compressor needs to change the type of refrigerant, there is no need to refit the power factor; only the adiabatic index of the corresponding refrigerant needs to be input to obtain a new power factor, which greatly reduces the dependence on the amount of data. This application can freely switch the physical property parameters of different refrigerants without adjusting the model, which improves the model's generalization ability and scalability. Compared with the prior art, the model is more intuitive under limited data calibration, and fewer coefficients need to be calibrated and learned, which can greatly improve the development efficiency of vehicle thermal management and improve the accuracy of vehicle power consumption prediction.

[0038] Based on the same concept, such as Figure 2 As shown, this application also provides an air conditioner compressor power consumption prediction system 11, which includes a data acquisition module 111, a power factor calculation module 112, an active power calculation module 113, and a power consumption prediction module 114.

[0039] Among them, the data acquisition module 111 is used to acquire the air compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement and refrigerant adiabatic index. The power factor calculation module 112 is used to calculate the power factor of the air conditioner compressor based on the exhaust pressure, intake pressure, displacement and refrigerant adiabatic index using a power factor fitting polynomial. The active power calculation module 113 is used to obtain the active power of the air conditioner compressor based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature and displacement. The power consumption prediction module 114 is used to predict the power consumption of the air conditioner compressor based on the active power and the power factor.

[0040] It should be noted that the air conditioner compressor power consumption prediction system 11 provided in the above embodiments and the air conditioner compressor power consumption prediction method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the air conditioner compressor power consumption prediction system 11 provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0041] like Figure 3 The diagram shown is a structural schematic of an electronic device that implements the power consumption prediction method for air conditioner compressors according to this application.

[0042] The electronic device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as an air conditioner compressor power consumption prediction program.

[0043] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 12 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 1. Furthermore, the memory 12 can include both internal and external storage units of the electronic device 1. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for predicting the power consumption of an air conditioner compressor, but also to temporarily store data that has been output or will be output.

[0044] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the electronic device 1, connecting various components of the electronic device 1 through various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., an air conditioner compressor power consumption prediction program) and calls data stored in the memory 12 to perform various functions and process data of the electronic device 1.

[0045] The processor 13 executes the operating system of the electronic device 1 and various installed applications. The processor 13 executes the applications to implement the steps in the aforementioned air conditioner compressor power consumption prediction method, for example... Figure 1 The steps are shown.

[0046] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for predicting the power consumption of an air conditioner compressor, characterized in that, include: Obtain the air conditioner compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index; The power factor of the air conditioning compressor is calculated using a power factor fitting polynomial based on the exhaust pressure, intake pressure, displacement, and refrigerant adiabatic index. The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature and displacement. The power consumption of the air conditioner compressor is predicted based on the active power and the power factor.

2. The method for predicting the power consumption of an air conditioner compressor according to claim 1, characterized in that, The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature, and displacement, including: The intake density and exhaust density of the air conditioning compressor are obtained based on the exhaust pressure, intake pressure, intake temperature, and exhaust temperature. The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake density, exhaust density, and displacement.

3. The method for predicting the power consumption of an air conditioning compressor according to claim 2, characterized in that, The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake density, exhaust density, and displacement, including: The volumetric efficiency of the air conditioning compressor is obtained based on the intake density and exhaust density. Based on the displacement, obtain the volumetric flow rate of the air conditioning compressor; The active power of the air conditioning compressor is obtained based on the exhaust pressure, intake pressure, intake density, exhaust density, volumetric flow rate, and volumetric efficiency.

4. The method for predicting the power consumption of an air conditioning compressor according to claim 3, characterized in that, The expression for the active power of the air conditioner compressor is: Wo=(1+ρi / ρo) / 2*V*(Pc-Pe)*101 / 3600*ηv Where ρi represents the intake density of the air conditioning compressor, ρo represents the exhaust density of the air conditioning compressor, V represents the volumetric flow rate of the air conditioning compressor, Pc represents the exhaust pressure of the air conditioning compressor, Pe represents the intake pressure of the air conditioning compressor, and ηv represents the volumetric efficiency of the air conditioning compressor.

5. The method for predicting the power consumption of an air conditioning compressor according to claim 3, characterized in that, The expression for the volumetric efficiency ηv is: ηv =(-A0*N^2+A1*N+A2)*((ρoo / ρio) / (ρo / ρi))^A3 Where N represents the rotational speed of the air conditioning compressor, ρi represents the intake density of the air conditioning compressor, ρo represents the exhaust density of the air conditioning compressor, ρio represents the intake density of the air conditioning compressor under the reference operating condition, ρoo represents the exhaust density of the air conditioning compressor under the reference operating condition, and A0, A1, A2, and A3 are polynomial fitting coefficients.

6. The method for predicting the power consumption of an air conditioning compressor according to claim 1, characterized in that, The expression for the power factor n is: n=MIN(A4+A5*LN(Pc / Pe)-A6*LN(D)-A7*LN(k), 0.95) Where Pc represents the discharge pressure of the air conditioning compressor, Pe represents the suction pressure of the air conditioning compressor, D represents the displacement of the air conditioning compressor, and k represents the refrigerant adiabatic index of the air conditioning compressor.

7. The method for predicting the power consumption of an air conditioning compressor according to claim 1, characterized in that, The power consumption model expression for the air conditioner compressor is as follows: W = Wo / n Where W represents the power consumption of the air conditioner compressor, Wo represents the active power of the air conditioner compressor, and n represents the power factor of the air conditioner compressor.

8. An air conditioner compressor power consumption prediction system, characterized in that, include: The data acquisition module is used to acquire the air conditioner compressor's discharge pressure, suction pressure, suction temperature, discharge temperature, displacement, and refrigerant adiabatic index. The power factor calculation module is used to calculate the power factor of the air conditioner compressor based on the exhaust pressure, intake pressure, displacement and refrigerant adiabatic index using a power factor fitting polynomial. The active power calculation module is used to obtain the active power of the air conditioning compressor based on the exhaust pressure, intake pressure, intake temperature, exhaust temperature and displacement. The power consumption prediction module is used to predict the power consumption of the air conditioner compressor based on the active power and the power factor.

9. An electronic device, characterized in that: The electronic device includes: One or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the air conditioning compressor power consumption prediction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by the computer's processor, causes the computer to perform the air conditioner compressor power consumption prediction method according to any one of claims 1 to 7.

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