WO2023050907A1 - 一种转速控制方法、系统、设备及存储介质 - Google Patents

一种转速控制方法、系统、设备及存储介质 Download PDF

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Publication number
WO2023050907A1
WO2023050907A1 PCT/CN2022/099796 CN2022099796W WO2023050907A1 WO 2023050907 A1 WO2023050907 A1 WO 2023050907A1 CN 2022099796 W CN2022099796 W CN 2022099796W WO 2023050907 A1 WO2023050907 A1 WO 2023050907A1
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Prior art keywords
data
oil content
temperature
pressure ratio
pressure
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PCT/CN2022/099796
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English (en)
French (fr)
Inventor
胡磊
夏嵩勇
卢叶红
李长龙
强一博
李永锋
Original Assignee
浙江吉利控股集团有限公司
浙江联控技术有限公司
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Application filed by 浙江吉利控股集团有限公司, 浙江联控技术有限公司 filed Critical 浙江吉利控股集团有限公司
Priority to EP22874304.3A priority Critical patent/EP4354052A1/en
Priority to KR1020247008278A priority patent/KR20240047419A/ko
Publication of WO2023050907A1 publication Critical patent/WO2023050907A1/zh
Priority to US18/585,012 priority patent/US20240191925A1/en

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B49/00—Arrangement or mounting of control or safety devices
    • F25B49/02—Arrangement or mounting of control or safety devices for compression type machines, plants or systems
    • F25B49/022—Compressor control arrangements
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B30/00—Heat pumps
    • F25B30/02—Heat pumps of the compression type
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B31/00—Compressor arrangements
    • F25B31/002—Lubrication
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B41/00—Fluid-circulation arrangements
    • F25B41/20—Disposition of valves, e.g. of on-off valves or flow control valves
    • F25B41/22—Disposition of valves, e.g. of on-off valves or flow control valves between evaporator and compressor
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B41/00—Fluid-circulation arrangements
    • F25B41/30—Expansion means; Dispositions thereof
    • F25B41/31—Expansion valves
    • F25B41/34—Expansion valves with the valve member being actuated by electric means, e.g. by piezoelectric actuators
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2500/00—Problems to be solved
    • F25B2500/16—Lubrication
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2500/00—Problems to be solved
    • F25B2500/18—Optimization, e.g. high integration of refrigeration components
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2600/00—Control issues
    • F25B2600/02—Compressor control
    • F25B2600/025—Compressor control by controlling speed
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2600/00—Control issues
    • F25B2600/02—Compressor control
    • F25B2600/025—Compressor control by controlling speed
    • F25B2600/0253—Compressor control by controlling speed with variable speed
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2700/00—Sensing or detecting of parameters; Sensors therefor
    • F25B2700/19—Pressures
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2700/00—Sensing or detecting of parameters; Sensors therefor
    • F25B2700/19—Pressures
    • F25B2700/193—Pressures of the compressor
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2700/00—Sensing or detecting of parameters; Sensors therefor
    • F25B2700/19—Pressures
    • F25B2700/193—Pressures of the compressor
    • F25B2700/1933—Suction pressures
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2700/00—Sensing or detecting of parameters; Sensors therefor
    • F25B2700/21—Temperatures
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
    • F25B2700/00—Sensing or detecting of parameters; Sensors therefor
    • F25B2700/21—Temperatures
    • F25B2700/2115—Temperatures of a compressor or the drive means therefor
    • F25B2700/21151—Temperatures of a compressor or the drive means therefor at the suction side of the compressor

Definitions

  • the invention relates to the technical field of heat pump system control, in particular to a speed control method, system, equipment and storage medium.
  • the purpose of the present invention is to provide a rotational speed control method, system, equipment and storage medium to improve the technical problem in the prior art that automatic control of the rotational speed of the compressor cannot be performed.
  • the present invention provides a speed control method, which is applied to a heat pump system.
  • the heat pump system includes an electronic flow regulating valve and a compressor, and temperature sensors are arranged on both sides of the electronic flow regulating valve. and a pressure sensor, the speed control method includes:
  • the temperature ratio data and the pressure ratio data are respectively matched with the preset conditions of each pre-trained oil content prediction model, and if the matching is successful, the temperature ratio data and the pressure ratio data are input into the matching obtained Oil content prediction model to obtain predicted oil content data;
  • the rotational speed of the compressor is controlled according to the predicted oil content data.
  • the step of collecting the actual data of the temperature sensor and the pressure sensor, and processing to obtain the temperature ratio data and the pressure ratio data includes:
  • the temperature ratio data and the pressure ratio data are respectively matched with the preset conditions of each pre-trained oil content prediction model, and if the matching is successful, the temperature ratio data Input and match the oil content prediction model obtained with the pressure ratio data, and the steps of obtaining the predicted oil content data include:
  • the step of matching and obtaining a corresponding oil content prediction model according to the temperature ratio data and the pressure ratio data further includes:
  • the temperature ratio data and the pressure ratio data at the same time constitute one sample data.
  • the four types of sample data include:
  • the second type of sample data that conforms to the pressure ratio range but does not conform to the first temperature ratio range;
  • the third type of sample data that does not meet the pressure ratio range but meets the second temperature ratio range;
  • the fourth type of sample data does not conform to the pressure ratio range and the second temperature ratio range.
  • the step of controlling the rotation speed of the compressor according to the predicted oil content data includes:
  • a rotation speed control system is also disclosed, which is applied to a heat pump system.
  • the system includes an electronic flow regulating valve and a compressor. Both sides of the electronic flow regulating valve are provided with temperature sensors and pressure sensors.
  • the speed control system includes:
  • Ratio data acquisition module used to collect the actual data of the temperature sensor and the pressure sensor, and process to obtain temperature ratio data and pressure ratio data;
  • An oil content prediction model acquisition module configured to match and obtain a corresponding oil content prediction model according to the temperature ratio data and the pressure ratio data;
  • a predicted oil content data acquisition module configured to input the temperature ratio data and the pressure ratio data into the matched oil content prediction model to obtain predicted oil content data
  • a rotational speed control module configured to control the rotational speed of the compressor according to the predicted oil content data.
  • a computer device including a processor, the processor is coupled to a memory, the memory stores program instructions, and when the program instructions stored in the memory are executed by the processor, the The speed control method mentioned above.
  • a computer-readable storage medium including a program, which, when running on a computer, causes the computer to execute the above method for controlling the rotational speed.
  • the speed control method, system, equipment, and storage medium obtained four oil content prediction models through a large amount of data training, so that the heat pump system can predict the oil content of the compressor according to the readings of the temperature sensor and the pressure sensor.
  • the quantity is predicted, and further according to the predicted oil content of the compressor, the speed of the compressor is automatically controlled, which realizes the automatic control of the compressor, prevents the oil shortage of the compressor, and improves the safety of the heat pump system.
  • FIG. 1 is a schematic structural diagram of a heat pump system in an embodiment of the present invention.
  • FIG. 2 is a schematic flowchart of an embodiment of the rotational speed control method of the present invention.
  • FIG. 3 is a schematic structural diagram of an embodiment of the rotational speed control system of the present invention.
  • FIG. 4 is a schematic structural diagram of a computer device of the present invention in an embodiment.
  • Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.
  • the present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.
  • the terminology used in the embodiments of the present invention is for describing specific implementations, not for limiting the protection scope of the present invention.
  • the test methods for which specific conditions are not indicated in the following examples are usually in accordance with conventional conditions, or in accordance with the conditions suggested by each manufacturer.
  • a heat pump is a high-efficiency energy-saving device that makes full use of low-grade heat energy.
  • Heat can be spontaneously transferred from a high-temperature object to a low-temperature object, but it cannot be spontaneously carried out in the opposite direction; the working principle of the heat pump is to force heat from a low temperature to
  • the heat pump system includes a compressor 1, a condenser 2, an electronic expansion valve 3, an evaporator 4, a gas-liquid separator 5 and an electronic flow regulating valve 6 arranged in sequence along the flow direction of the refrigerant, and the electronic flow regulating The valve 6 is set on the low-pressure return air side of the compressor 1.
  • the front end of the electronic flow regulating valve 6 is provided with a sensor combination PT2
  • the rear end of the electronic flow regulating valve 6 is provided with a sensor combination PT1.
  • Both the sensor combination PT1 and the sensor combination PT2 include a temperature sensor and a pressure sensor, and in another preferred embodiment, the electronic flow regulating valve 6 can adopt a short throttle tube, an electronic expansion valve or a thermal expansion valve. any kind.
  • FIG. 1 shows a schematic flow chart of a speed control method in this embodiment.
  • the speed control method includes:
  • Step S100 collecting the actual data of sensor combination PT1 and sensor combination PT2, and processing to obtain temperature ratio data and pressure ratio data;
  • Step S100 specifically includes:
  • Step S200 according to the temperature ratio data T2/T1 and the pressure ratio data P2/P1, matching to obtain the corresponding oil content prediction model;
  • step S200 first judge whether the pressure ratio data P2/P1 conforms to the preset pressure ratio range (0, A); when the pressure ratio data P2/P1 conforms to the pressure ratio range (0, A), continue to judge the temperature ratio range Whether T2/T1 conforms to the preset first temperature ratio range (0, B): if yes, match to the corresponding first oil content prediction model; if not, match to the corresponding second oil content prediction model;
  • the pressure ratio range (0, A), the first temperature ratio range (0, B), and the second temperature ratio range (0, C) are determined according to actual conditions.
  • A can be 3
  • B can be 4
  • C can be 3.
  • step S200 also includes a training method for the oil content prediction model, including:
  • the temperature ratio data and the pressure ratio data at the same moment constitute a sample data; according to the pressure ratio range (0, A), the first temperature ratio range (0, B) and the second temperature ratio range (0, C), Classify the sample data to obtain four types of sample data.
  • these four types of sample data include:
  • the third type of sample data that does not conform to the pressure ratio range (0, A) but conforms to the second temperature ratio range (0, C);
  • the fourth type of sample data does not meet the pressure ratio range (0, A) and the second temperature ratio range (0, C).
  • the neural network model used in this embodiment can be a support vector regression model. It should be noted that the present invention does not limit the type of neural network model, and only needs to be able to obtain corresponding predicted oil content data according to the input test set data That's it.
  • step S100 After processing and obtaining actual temperature ratio data T2/T1 and pressure ratio data P2/P1 in step S100, according to the pressure ratio range (0, A), the first temperature ratio range (0, B) and the second temperature ratio range ( 0, C), determine the type of sample data that the actual temperature ratio data T2/T1 and pressure ratio data P2/P1 conform to, and further match to obtain the corresponding oil content prediction model, for example, when the actual temperature ratio data T2/T1 and When the pressure ratio data P2/P1 does not conform to the pressure ratio range (0, A), but conforms to the second temperature ratio range (0, C), the third oil content prediction model is matched.
  • Step S300 input the temperature ratio data T2/T1 and pressure ratio data P2/P1 into the oil content prediction model obtained by matching, and obtain the predicted oil content data;
  • Step S400 controlling the rotation speed of the compressor 1 according to the predicted oil content data.
  • Step S400 specifically includes:
  • oil content range (1, D) is determined according to actual conditions, and in a preferred embodiment, D may be 7.
  • this embodiment also includes a rotational speed control system 100, which is applied to the heat pump system described above, and the rotational speed control system includes:
  • the ratio data acquisition module 110 is used to collect the actual data of the temperature sensor and the pressure sensor in the sensor combination PT1 and the sensor combination PT2, and process and obtain the temperature ratio data and the pressure ratio data;
  • the oil content prediction model acquisition module 120 is used to match and obtain the corresponding oil content prediction model according to the temperature ratio data and the pressure ratio data;
  • the predicted oil content data acquisition module 130 is used to input the temperature ratio data and the pressure ratio data into the matched oil content prediction model to obtain the predicted oil content data;
  • the rotational speed control module 140 is used for controlling the rotational speed of the compressor according to the predicted oil content data.
  • a computer device 200 is also included, including a processor 210.
  • the processor 210 is coupled to a memory 220.
  • the memory 220 stores program instructions. When the program instructions stored in the memory 220 are stored by the processor 210 Implement the upper speed control method when executing.
  • Processor 210 can be a general-purpose processor, including a central processing unit (Central Processing Unit, referred to as CPU), a network processor (Network Processor, referred to as NP), etc.; it can also be a digital signal processor (Digital Signal Processing, referred to as DSP), Application Specific Integrated Circuit (ASIC for short), Field Programmable Gate Array (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components; the memory 220 It may include random access memory (Random Access Memory, RAM for short), and may also include non-volatile memory (Non-Volatile Memory), such as at least one disk memory.
  • CPU Central Processing Unit
  • NP Network Processor
  • DSP Digital Signal Processing
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • the memory 220 It may include random access memory (Random Access Memory, RAM for short), and may also include non-volatile memory (Non-Volatile
  • the memory 220 can also be an internal memory of a random access memory (Random Access Memory, RAM) type, and the processor 210 and the memory 220 can be integrated into one or more independent circuits or hardware, such as: ASIC ( Application Specific Integrated Circuit, ASIC).
  • ASIC Application Specific Integrated Circuit
  • the computer program in the above-mentioned memory 220 may be implemented in the form of a software function unit and sold or used as an independent product, and may be stored in a computer-readable storage medium.
  • the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several
  • the instructions are used to make a computer device (which may be a personal computer, an electronic device, or a network device, etc.) execute all or part of the steps of the methods in various embodiments of the present invention.
  • it also includes a computer-readable storage medium, including a program, which, when running on the computer, causes the computer to execute the above method for controlling the rotational speed.
  • the speed control method, system, equipment, and storage medium obtained four oil content prediction models through a large amount of data training, so that the heat pump system can predict the oil content of the compressor according to the readings of the temperature sensor and the pressure sensor.
  • the quantity is predicted, and further according to the predicted oil content of the compressor, the speed of the compressor is automatically controlled, which realizes the automatic control of the compressor, prevents the oil shortage of the compressor, and improves the safety of the heat pump system. Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial application value.

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  • Control Of Positive-Displacement Pumps (AREA)

Abstract

本发明提供了一种转速控制方法、系统、设备及存储介质，应用于热泵系统，热泵系统包括节流短管和压缩机，节流短管的两侧均设置有温度传感器和压力传感器，转速控制方法包括：采集温度传感器和压力传感器的实际数据，处理得到温度比值数据和压力比值数据，并匹配到对应的含油量预测模型；根据温度比值数据和压力比值数据，得到预测含油量数据；根据预测含油量数据控制压缩机的转速。本发明通过大量的数据训练得到四个含油量预测模型，使得热泵系统能够根据温度传感器、压力传感器的读数进行压缩机含油量的预测，根据预测的压缩机含油量，控制压缩机的转速，实现了压缩机的自动控制，防止压缩机出现缺油情况，提高了热泵系统的安全性。

Description

一种转速控制方法、系统、设备及存储介质 技术领域
本发明涉及热泵系统控制技术领域，特别是涉及一种转速控制方法、系统、设备及存储介质。
背景技术
随着电动汽车的推广，人们对电动汽车空调系统的要求也越来越高，目前常见的电动汽车空调系统多采用热泵系统，其在低温热泵制热模式中，常常会因为环境温度较低而引起低压侧制冷剂的黏度升高，使得热泵系统中压缩机的机油溶解于制冷剂，从而导致压缩机回油困难，甚至可能会因此引发压缩机缺油或损坏的情况。
热泵系统中冷媒的流动速度是改变压缩机含油量的一大因素，在现有技术中，工作人员通常通过目测压缩机实际含油量的方式，进一步做出压缩机转速控制的判断，而通过人力控制压缩机转速来调节压缩机中机油含量的方式不仅会损耗大量的人力、物力，而且压缩机转速的具体控制只能根据工作人员的经验得出，并不一定准确，目前也没有成熟的方法能够实现压缩机转速的自动控制。
综上，现有技术中存在无法进行压缩机转速自动控制的技术问题。
发明内容
鉴于以上现有技术的缺点，本发明的目的在于提供一种转速控制方法、系统、设备及存储介质，以改善现有技术中存在无法进行压缩机转速自动控制的技术问题。
为实现上述目的及其他相关目的，本发明提供一种转速控制方法，应用于热泵系统，所述热泵系统包括电子流量调节阀和压缩机，所述电子流量调节阀的两侧均设置有温度传感器和压力传感器，所述转速控制方法包括：
采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据；
将所述温度比值数据和所述压力比值数据分别与每个预训练的含油量预测模型的预设条件相匹配，匹配成功，则将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据；
根据所述预测含油量数据控制所述压缩机的转速。
在本发明一实施例中，所述采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据的步骤包括：
采集得到所述温度传感器和所述压力传感器的实际数据；
沿着所述热泵系统中冷媒流动的方向，将所述电子流量调节阀前侧的温度传感器的实际数据与后侧的温度传感器的实际数据相除，得到所述温度比值数据；将所述电子流量调节阀前侧的压力传感器的实际数据与后侧的压力传感器的实际数据相除，得到所述压力比值数据。
在本发明一实施例中，所述将所述温度比值数据和所述压力比值数据分别与每个预训练的含油量预测模型的预设条件相匹配，匹配成功，则将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据的步骤包括：
判断所述压力比值数据是否符合预设的压力比值范围；
在所述压力比值数据符合所述压力比值范围时，继续判断所述温度比值范围是否符合预设的第一温度比值范围：若是，则匹配到对应的第一个含油量预测模型；若否，则匹配到对应的第二个含油量预测模型；
在所述压力比值数据不符合所述压力比值范围时，继续判断所述温度比值范围是否符合预设的第二温度比值范围；若是，则匹配到对应的第三个含油量预测模型；若否，则匹配到对应的第四个含油量预测模型；
将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据。
在本发明一实施例中，所述根据所述温度比值数据和所述压力比值数据，匹配得到对应的含油量预测模型的步骤还包括：
采集以往多个时刻下所述温度传感器和所述压力传感器的实际数据，以及所述压缩机的实际含油量数据，并处理得到多组温度比值数据和压力比值数据，作为样本数据；
根据所述压力比值范围、所述第一温度比值范围和所述第二温度比值范围，将所述样本数据进行分类，得到四类样本数据；
针对分类后的每一类样本数据：
将其随机划分为训练集和测试集；
根据所述训练集训练神经网络模型，得到训练好的神经网络模型；
将所述测试集输入训练好的神经网络模型，得到对应的预测含油量数据；当所述预测含油量数据符合所述实际含油量数据的概率达到预设的阈值时，将训练好的神经网络模型确定为最终的含油量预测模型。
在本发明一实施例中，同一时刻下的所述温度比值数据和所述压力比值数据组成一个样本数据。
在本发明一实施例中，四类所述样本数据包括：
符合所述压力比值范围和所述第一温度比值范围的第一类样本数据；
符合所述压力比值范围，不符合所述第一温度比值范围的第二类样本数据；
不符合所述压力比值范围，符合所述第二温度比值范围的第三类样本数据；
不符合所述压力比值范围和所述第二温度比值范围的第四类样本数据。
在本发明一实施例中，所述根据所述预测含油量数据控制所述压缩机的转速的步骤包括：
判断所述预测含油量数据是否符合预设的含油量范围；
若是，则按照一预设的数值提升所述压缩机的转速；若否，则控制所述压缩机的转速不变。
在本实施例中，还公开了一种转速控制系统，应用于热泵系统，所述系统包括电子流量调节阀和压缩机，所述电子流量调节阀的两侧均设置有温度传感器和压力传感器，所述转速控制系统包括：
比值数据采集模块，用于采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据；
含油量预测模型获取模块，用于根据所述温度比值数据和所述压力比值数据，匹配得到对应的含油量预测模型；
预测含油量数据获取模块，用于将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据；
转速控制模块，用于根据所述预测含油量数据控制所述压缩机的转速。
在本实施例中，还公开了一种计算机设备，包括处理器，所述处理器和存储器耦合，所述存储器存储有程序指令，当所述存储器存储的程序指令被所述处理器执行时实现上述转速控制方法。
在本实施例中，还公开了一种计算机可读的存储介质，包括程序，当其在计算机上运行时，使得计算机执行上述转速控制方法。
综上所述，本发明提供的一种转速控制方法、系统、设备及存储介质通过大量的数据训练得到四个含油量预测模型，使得热泵系统能够根据温度传感器、压力传感器的读数进行压缩机含油量的预测，并进一步根据预测的压缩机含油量，自动控制压缩机的转速，实现了压缩机的自动控制，防止压缩机出现缺油情况，提高了热泵系统的安全性。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术 描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1显示为本发明的热泵系统于一实施例中的结构示意图。
图2显示为本发明的转速控制方法于一实施例中的流程示意图。
图3显示为本发明的转速控制系统于一实施例中的结构示意图。
图4显示为本发明的计算机设备于一实施例中的结构示意图。
元件标号说明
1、压缩机；2、冷凝器；3、电子膨胀阀；4、蒸发器；5、气液分离器；6、电子流量调节阀；100、转速控制系统；110、比值数据采集模块；120、含油量预测模型获取模块；130、预测含油量数据获取模块；200、计算机设备；210、处理器；220、存储器。
具体实施方式
以下通过特定的具体实例说明本发明的实施方式，本领域技术人员可由本说明书所揭露的内容轻易地了解本发明的其它优点与功效。本发明还可以通过另外不同的具体实施方式加以实施或应用，本说明书中的各项细节也可以基于不同观点与应用，在没有背离本发明的精神下进行各种修饰或改变。需说明的是，在不冲突的情况下，以下实施例及实施例中的特征可以相互组合。还应当理解，本发明实施例中使用的术语是为了描述特定的具体实施方案，而不是为了限制本发明的保护范围。下列实施例中未注明具体条件的试验方法，通常按照常规条件，或者按照各制造商所建议的条件。
请参阅图1至图4。须知，本说明书附图所绘示的结构、比例、大小等，均仅用以配合说明书所揭示的内容，以供熟悉此技术的人士了解与阅读，并非用以限定本发明可实施的限定条件，故不具技术上的实质意义，任何结构的修饰、比例关系的改变或大小的调整，在不影响本发明所能产生的功效及所能达成的目的下，均应仍落在本发明所揭示的技术内容所能涵盖的范围内。同时，本说明书中所引用的如“上”、“下”、“左”、“右”、“中间”及“一”等的用语，亦仅为便于叙述的明了，而非用以限定本发明可实施的范围，其相对关系的改变或调整，在无实质变更技术内容下，当亦视为本发明可实施的范畴。
当实施例给出数值范围时，应理解，除非本发明另有说明，每个数值范围的两个端点以及两个端点之间任何一个数值均可选用。除非另外定义，本发明中使用的所有技术和科学术语与本技术领域的技术人员对现有技术的掌握及本发明的记载，还可以使用与本发明实施例 中所述的方法、设备、材料相似或等同的现有技术的任何方法、设备和材料来实现本发明。
热泵是一种充分利用低品位热能的高效节能装置，热量可以自发地从高温物体传递到低温物体中去，但不能自发地沿相反方向进行；热泵的工作原理就是以逆循环方式迫使热量从低温物体流向高温物体的机械装置，它仅消耗少量的逆循环净功，就可以得到较大的供热量，可以有效地把难以应用的低品位热能利用起来达到节能目的
请参阅图1，热泵系统包括沿着冷媒的流动方向依次设置的压缩机1，冷凝器2，电子膨胀阀3，蒸发器4，气液分离器5和电子流量调节阀6，且电子流量调节阀6设置在压缩机1的低压回气侧，在本实施例中，电子流量调节阀6的前端设置有传感器组合PT2，电子流量调节阀6的后端设置有传感器组合PT1。
传感器组合PT1和传感器组合PT2均包括有一温度传感器和一压力传感器，且在另一种较优的实施例中，电子流量调节阀6可以采用节流短管、电子膨胀阀或热力膨胀阀中的任意一种。
请参阅图1，显示为本实施例中一种转速控制方法的流程示意图，该转速控制方法包括：
步骤S100、采集传感器组合PT1和传感器组合PT2的实际数据，并处理得到温度比值数据和压力比值数据；
步骤S100具体包括：
采集得到传感器组合PT1和传感器组合PT2中温度传感器和压力传感器的实际数据；
将传感器组合PT2中的温度传感器的实际数据与传感器组合PT1中的温度传感器的实际数据相除，得到温度比值数据T2/T1；将传感器组合PT2中的压力传感器的实际数据与传感器组合PT1中的压力传感器的实际数据相除，得到压力比值数据P2/P1。
步骤S200、根据温度比值数据T2/T1和压力比值数据P2/P1，匹配得到对应的含油量预测模型；
在步骤S200中，首先判断压力比值数据P2/P1是否符合预设的压力比值范围(0，A)；在压力比值数据P2/P1符合压力比值范围(0，A)时，继续判断温度比值范围T2/T1是否符合预设的第一温度比值范围(0，B)：若是，则匹配到对应的第一个含油量预测模型；若否，则匹配到对应的第二个含油量预测模型；
在所述压力比值数据P2/P1不符合压力比值范围(0，A)时，继续判断温度比值范围T2/T1是否符合预设的第二温度比值范围(0，C)；若是，则匹配到对应的第三个含油量预测模型；若否，则匹配到对应的第四个含油量预测模型。
具体的，压力比值范围(0，A)、第一温度比值范围(0，B)、第二温度比值范围(0，C)是 根据实际情况确定的，在一种较优的实施例中，A可以为3，B可以为4，C可以为3。
进一步的，步骤S200中还包括有含油量预测模型的训练方法，包括：
采集以往多个时刻下传感器组合PT1和传感器组合PT2中温度传感器和压力传感器的实际数据，以及压缩机1的实际含油量数据，并处理得到多组温度比值数据和压力比值数据，作为样本数据，其中，同一时刻下的温度比值数据和压力比值数据组成一个样本数据；根据压力比值范围(0，A)、第一温度比值范围(0，B)和第二温度比值范围(0，C)，将样本数据进行分类，得到四类样本数据，具体的，这四类样本数据包括：
符合压力比值范围(0，A)和第一温度比值范围(0，B)和的第一类样本数据；
符合压力比值范围(0，A)，不符合第一温度比值范围(0，B)和的第二类样本数据；
不符合压力比值范围(0，A)，符合第二温度比值范围(0，C)的第三类样本数据；
不符合压力比值范围(0，A)和第二温度比值范围(0，C)的第四类样本数据。
针对分类后的每一类样本数据：将其随机划分为训练集和测试集；根据训练集训练神经网络模型，得到训练好的神经网络模型；将测试集输入训练好的神经网络模型，得到对应的预测含油量数据；当预测含油量数据符合实际含油量数据的概率达到预设的阈值时，将训练好的神经网络模型确定为最终的含油量预测模型。
本实施例中采用神经网络模型可以为支持向量回归模型，需要说明的是，本发明对神经网络模型的种类不做限制，只需能够根据输入的测试集数据，得出相应的预测含油量数据即可。
在本实施例中，最终得到和四类样本数据对应的四种含油量预测模型。
在步骤S100中处理得到实际的温度比值数据T2/T1和压力比值数据P2/P1后，根据压力比值范围(0，A)、第一温度比值范围(0，B)和第二温度比值范围(0，C)，判断得到实际的温度比值数据T2/T1和压力比值数据P2/P1符合的样本数据种类，进一步匹配得到对应的含油量预测模型，例如，当实际的温度比值数据T2/T1和压力比值数据P2/P1不符合压力比值范围(0，A)，但符合第二温度比值范围(0，C)时，匹配得到的是第三种含油量预测模型。
步骤S300、将温度比值数据T2/T1和压力比值数据P2/P1输入匹配得到的含油量预测模型，得到预测含油量数据；
步骤S400、根据预测含油量数据控制压缩机1的转速。
步骤S400具体包括：
判断预测含油量数据是否符合预设的含油量范围(1，D)；
若是，则按照一预设的数值提升压缩机1的转速；若否，则控制压缩机1的转速不变。
具体的，含油量范围(1，D)是根据实际情况确定的，在一种较优的实施例中，D可以为7。
请参阅图3，本实施例还包括一种转速控制系统100，应用于上述的热泵系统，转速控制系统包括：
比值数据采集模块110，用于采集传感器组合PT1和传感器组合PT2中温度传感器和压力传感器的实际数据，并处理得到温度比值数据和压力比值数据；
含油量预测模型获取模块120，用于根据温度比值数据和压力比值数据，匹配得到对应的含油量预测模型；
预测含油量数据获取模块130，用于将温度比值数据和压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据；
转速控制模块140，用于根据预测含油量数据控制压缩机的转速。
请参阅图4，在本实施例中，还包括一种计算机设备200，包括处理器210，处理器210和存储器220耦合，存储器220存储有程序指令，当存储器220存储的程序指令被处理器210执行时实现上转速控制方法。处理器210可以是通用处理器，包括中央处理器(Central Processing Unit，简称CPU)、网络处理器(Network Processor，简称NP)等；还可以是数字信号处理器(Digital Signal Processing，简称DSP)、专用集成电路(Application Specific Integrated Circuit，简称ASIC)、现场可编程门阵列(Field-Programmable Gate Array，简称FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件；所述存储器220可能包含随机存取存储器(Random Access Memory，简称RAM)，也可能还包括非易失性存储器(Non-Volatile Memory)，例如至少一个磁盘存储器。所述存储器220也可以为随机存取存储器(Random Access Memory，RAM)类型的内部存储器，所述处理器210、存储器220可以集成为一个或多个独立的电路或硬件，如：专用集成电路(Application Specific Integrated Circuit，ASIC)。需要说明的是，上述的存储器220中的计算机程序可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，电子设备，或者网络设备等)执行本发明各个实施例方法的全部或部分步骤。
在本实施例中，还包括一种计算机可读的存储介质，包括程序，当其在计算机上运行时，使得计算机执行上述转速控制方法。
综上所述，本发明提供的一种转速控制方法、系统、设备及存储介质通过大量的数据训练得到四个含油量预测模型，使得热泵系统能够根据温度传感器、压力传感器的读数进行压缩机含油量的预测，并进一步根据预测的压缩机含油量，自动控制压缩机的转速，实现了压缩机的自动控制，防止压缩机出现缺油情况，提高了热泵系统的安全性。所以，本发明有效克服了现有技术中的种种缺点而具高度产业利用价值。
上述实施例仅例示性说明本发明的原理及其功效，而非用于限制本发明。任何熟悉此技术的人士皆可在不违背本发明的精神及范畴下，对上述实施例进行修饰或改变。因此，举凡所属技术领域中具有通常知识者在未脱离本发明所揭示的精神与技术思想下所完成的一切等效修饰或改变，仍应由本发明的权利要求所涵盖。

Claims (10)

  1. 一种转速控制方法，其特征在于，应用于热泵系统，所述热泵系统包括电子流量调节阀和压缩机，所述电子流量调节阀的两侧均设置有温度传感器和压力传感器，所述转速控制方法包括：
    采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据；
    将所述温度比值数据和所述压力比值数据分别与每个预训练的含油量预测模型的预设条件相匹配，匹配成功，则将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据；
    根据所述预测含油量数据控制所述压缩机的转速。
  2. 根据权利要求1所述的转速控制方法，其特征在于，所述采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据的步骤包括：
    采集得到所述温度传感器和所述压力传感器的实际数据；
    沿着所述热泵系统中冷媒流动的方向，将所述电子流量调节阀前侧的温度传感器的实际数据与后侧的温度传感器的实际数据相除，得到所述温度比值数据；将所述电子流量调节阀前侧的压力传感器的实际数据与后侧的压力传感器的实际数据相除，得到所述压力比值数据。
  3. 根据权利要求1所述的转速控制方法，其特征在于，所述将所述温度比值数据和所述压力比值数据分别与每个预训练的含油量预测模型的预设条件相匹配，匹配成功，则将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据的步骤包括：
    判断所述压力比值数据是否符合预设的压力比值范围；
    在所述压力比值数据符合所述压力比值范围时，继续判断所述温度比值范围是否符合预设的第一温度比值范围：若是，则匹配到对应的第一个含油量预测模型；若否，则匹配到对应的第二个含油量预测模型；
    在所述压力比值数据不符合所述压力比值范围时，继续判断所述温度比值范围是否符合预设的第二温度比值范围；若是，则匹配到对应的第三个含油量预测模型；若否，则匹配到对应的第四个含油量预测模型；
    将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据。
  4. 根据权利要求3所述的转速控制方法，其特征在于，所述根据所述温度比值数据和所述压力比值数据，匹配得到对应的含油量预测模型的步骤还包括：
    采集以往多个时刻下所述温度传感器和所述压力传感器的实际数据，以及所述压缩机的实际含油量数据，并处理得到多组温度比值数据和压力比值数据，作为样本数据；
    根据所述压力比值范围、所述第一温度比值范围和所述第二温度比值范围，将所述样本数据进行分类，得到四类样本数据；
    针对分类后的每一类样本数据：
    将其随机划分为训练集和测试集；
    根据所述训练集训练神经网络模型，得到训练好的神经网络模型；
    将所述测试集输入训练好的神经网络模型，得到对应的预测含油量数据；当所述预测含油量数据符合所述实际含油量数据的概率达到预设的阈值时，将训练好的神经网络模型确定为最终的含油量预测模型。
  5. 根据权利要求4述的转速控制方法，其特征在于，同一时刻下的所述温度比值数据和所述压力比值数据组成一个样本数据。
  6. 根据权利要求4所述的转速控制方法，其特征在于，四类所述样本数据包括：
    符合所述压力比值范围和所述第一温度比值范围的第一类样本数据；
    符合所述压力比值范围，不符合所述第一温度比值范围的第二类样本数据；
    不符合所述压力比值范围，符合所述第二温度比值范围的第三类样本数据；
    不符合所述压力比值范围和所述第二温度比值范围的第四类样本数据。
  7. 根据权利要求1所述的转速控制方法，其特征在于，所述根据所述预测含油量数据控制所述压缩机的转速的步骤包括：
    判断所述预测含油量数据是否符合预设的含油量范围；
    若是，则按照一预设的数值提升所述压缩机的转速；若否，则控制所述压缩机的转速不变。
  8. 一种转速控制系统，其特征在于，应用于热泵系统，所述系统包括电子流量调节阀和压缩机，所述电子流量调节阀的两侧均设置有温度传感器和压力传感器，所述转速控制系统包括：
    比值数据采集模块，用于采集所述温度传感器和所述压力传感器的实际数据，并处理得到温度比值数据和压力比值数据；
    含油量预测模型获取模块，用于根据所述温度比值数据和所述压力比值数据，匹配得到对应的含油量预测模型；
    预测含油量数据获取模块，用于将所述温度比值数据和所述压力比值数据输入匹配得到的含油量预测模型，得到预测含油量数据；
    转速控制模块，用于根据所述预测含油量数据控制所述压缩机的转速。
  9. 一种计算机设备，其特征在于，包括处理器，所述处理器和存储器耦合，所述存储器存储有程序指令，当所述存储器存储的程序指令被所述处理器执行时实现权利要求1-7中任意一项所述的转速控制方法。
  10. 一种计算机可读的存储介质，其特征在于，包括程序，当其在计算机上运行时，使得计算机执行如权利要求1-7任意一项所述的转速控制方法。
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