Patent Description:
With the promotion of electric vehicles, people have an increasingly high requirement on air conditioning systems of the electric vehicles. Nowadays, heat pump systems are often used in common air conditioning systems of electric vehicles. In a low-temperature heat pump heating mode of the heat pump system, viscosity of a refrigerant on a low-pressure side is usually increased because of a relatively low ambient temperature, and therefore, engine oil of a compressor in the heat pump system dissolves in the refrigerant, which makes oil return of the compressor difficult, and may even result in oil shortage or damage of the compressor.

A flow speed of the refrigerant in the heat pump system is a major factor that changes oil content of the compressor. In the conventional technology, staff usually visually inspect actual oil content of the compressor to further make a judgement on compressor speed control. In the manner of adjusting the oil content of the compressor by manually controlling a rotation speed of the compressor, a lot of manpower and material resources are consumed, and specific control over the rotation speed of the compressor can be derived based on only experience of the staff, and may be inaccurate. Currently, there is no mature method for implementing automatic control over the rotation speed of the compressor.

<CIT> is discloses an air conditioner, the air conditioner includes a first temperature sensor <NUM> which detects the temperature of refrigerator oil present in a compressor <NUM>, a low-pressure sensor <NUM> which detects the pressure in a refrigerant suction-side pipe 10b, and a control section <NUM> which monitors the refrigerator oil temperature T1 detected by the first temperature sensor <NUM> and a low-pressure saturation temperature T2 calculated from the pressure detected by the low-pressure sensor <NUM>, and controls a flow rate control valve <NUM> of an oil return pipe <NUM>, and the control section <NUM> monitors the refrigerator oil temperature T1 and low-pressure saturation temperature T2 with the flow rate control valve <NUM> open from the beginning of actuation of the compressor <NUM>, and closes the flow rate control valve <NUM> when a temperature difference Δt(=T1-T2) reaches or exceeds a prescribed determination value.

In conclusion, there is a technical problem in the conventional technology that the rotation speed of the compressor cannot be automatically controlled.

In view of the foregoing disadvantages of the conventional technology, the present invention is intended to provide a rotation speed control method, a system, a device, and a storage medium, to solve a technical problem in the conventional technology that automatic control over a rotation speed of a compressor cannot be performed.

To achieve the foregoing and other related objectives, the present invention provides a rotation speed control method, applied to a heat pump system, as defined in claim <NUM>. The heat pump system includes an electronic flow regulating valve and a compressor, the electronic flow regulating valve is disposed on a low-pressure gas return circuit side of the compressor, both sides of the electronic flow regulating valve are provided with a temperature sensor and a pressure sensor, and the rotation speed control method includes:.

In an embodiment of the present invention, the step of collecting the actual data of the temperature sensors and the pressure sensors, and processing to obtain the temperature ratio data and the pressure ratio data includes:.

In an embodiment of the present invention, the step of separately matching the temperature ratio data and the pressure ratio data with the preset conditions of each pre-trained oil content prediction model, and if the matching succeeds, inputting the temperature ratio data and the pressure ratio data into the oil content prediction model obtained through matching, to obtain the predicted oil content data includes:.

In an embodiment of the present invention, the step of obtaining the corresponding oil content prediction model through matching according to the temperature ratio data and the pressure ratio data further includes:.

In an embodiment of the present invention, the temperature ratio data and the pressure ratio data at a same moment constitute one piece of the sample data.

In an embodiment of the present invention, the four types of the sample data include:.

In an embodiment of the present invention, the step of controlling the rotation speed of the compressor according to the predicted oil content data includes:.

In the present invention, a rotation speed control system as defined in claim <NUM> is further disclosed, which is applied to a heat pump system. The system includes an electronic flow regulating valve and a compressor, the electronic flow regulating valve is disposed on a low-pressure gas return circuit side of the compressor, both sides of the electronic flow regulating valve are provided with a temperature sensor and a pressure sensor, and the rotation speed control system includes:.

In the embodiments, a computer device is further disclosed. The computer device includes a processor, the processor is coupled to a memory, and the memory stores program instructions, and when the program instructions stored in the memory are executed by the processor, the foregoing rotation speed control method is implemented.

In the embodiments, a computer-readable storage medium is further disclosed. The computer-readable storage medium includes a program, and when the program runs on a computer, the computer is enabled to perform the foregoing rotation speed control method.

In conclusion, the present invention provides the rotation speed control method and system, the device, and the storage medium, obtains four oil content prediction models through training by using a large amount of data, so that the heat pump system can predict the oil content of the compressor according to the readings of the temperature sensors and the pressure sensors, and further automatically control the rotation speed of the compressor according to the predicted oil content of the compressor, thereby implementing the automatic control over the compressor, preventing the oil shortage of the compressor, and improving the safety of the heat pump system.

To describe the technical solutions in the embodiments of the present invention or in the conventional technology more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the conventional technology. Clearly, the accompanying drawings in the following description merely show some embodiments of the present invention, and a person of ordinary skill in the art can still derive other drawings from these accompanying drawings without creative efforts.

compressor; <NUM>. condenser; <NUM>. electronic expansion valve; <NUM>. evaporator; <NUM>. gas-liquid separator; <NUM>. electronic flow regulating valve; <NUM>. rotation speed control system; <NUM>. ratio data collection module; <NUM>. oil content prediction model obtaining module; <NUM>. predicted oil content data obtaining module; <NUM>. computer device; <NUM>. processor; and <NUM>.

The following describes implementations of the present invention by using specific examples. A person skilled in the art may easily understand other advantages and effects of the present invention based on content disclosed in this specification. The present invention may be further implemented or applied in other different specific implementations. Various details in this specification may also be modified or altered based on different viewpoints and applications. The present invention is solely defined by the appended claims. It should be noted that the following embodiments and features in the embodiments may be mutually combined when there are no conflicts. It should be further understood that terms used in the embodiments of the present invention are used to describe specific implementation solutions, and are not used to limit the protection scope of the present invention. In the following embodiments, test methods not marked with specific conditions are usually performed based on conventional conditions or based on conditions recommended by manufacturers.

References are made to <FIG>. It should be noted that the structure, scale, size, and the like shown in the accompanying drawings of this specification are merely used to cooperate with the content disclosed in the specification for understanding and reading by a person skilled in the art, and are not restrictions for limiting implementation of the present invention, and therefore have no technically substantial significance. Any modification of the structure, change of a proportional relationship or adjustment of the size shall still fall within the scope that can be covered by the technical content disclosed in the present invention, provided that they do not affect the effects that can be generated by the present invention and the purpose that can be achieved by the present invention. In addition, terms such as "upper", "lower", "left", "right", "middle", and "one" that are referred in this specification are merely used for ease of description, and are not intended to limit the scope of implementation of the present invention. A change or an adjustment of a relative relationship thereof also falls within the scope of implementation of the present invention on the premise that the technical content is not substantially changed.

When a value range is provided in an embodiment, it should be understood that unless otherwise stated in the present invention, two endpoints in each value range and any value between the two endpoints each can be selected. Unless otherwise defined, all technical and scientific terms used in the present invention are consistent with mastery of the conventional technology by a person skilled in the art and the descriptions of the present invention, and the present invention may be further implemented by using any method, device, or material in the conventional technology that is similar or equivalent to a method, device, or material described in the embodiments of the present invention.

A heat pump is an efficient energy-saving apparatus that fully uses low-grade heat energy. Heat can be spontaneously transferred from a high-temperature object to a low-temperature object, but cannot be spontaneously transferred in an opposite direction. A working principle of the heat pump is a mechanical apparatus that forces, through reverse circulation, the heat to flow from the low-temperature object to the high-temperature object. The heat pump can obtain a relatively large supply of heat by consuming only a small amount of reverse circulation net work, so that the low-grade heat energy that is difficult to use can be effectively used to save energy.

Referring to <FIG>, a heat pump system includes a compressor <NUM>, a condenser <NUM>, an electronic expansion valve <NUM>, an evaporator <NUM>, a gas-liquid separator <NUM>, and an electronic flow regulating valve <NUM> that are sequentially disposed in a flow direction of a refrigerant. The electronic flow regulating valve <NUM> is disposed on a low-pressure gas return circuit side of the compressor <NUM>. In this embodiment, a sensor combination PT2 is disposed at a front end of the electronic flow regulating valve <NUM>, and a sensor combination PT1 is disposed at a back end of the electronic flow regulating valve <NUM>.

The sensor combination PT1 and the sensor combination PT2 each include a temperature sensor and a pressure sensor. In another preferred embodiment, the electronic flow regulating valve <NUM> may be any one of a throttling short tube, an electronic expansion valve, or a thermal expansion valve.

<FIG> is a schematic flowchart of a rotation speed control method according to the embodiment. The rotation speed control method includes the following steps:
Step S100: Collect actual data of the sensor combination PT1 and the sensor combination PT2, and process them to obtain temperature ratio data and pressure ratio data.

Step S200: Obtain a corresponding oil content prediction model through matching according to the temperature ratio data T2/T1 and the pressure ratio data P2/P1.

In step S200, it is first determined whether the pressure ratio data P2/P1 accord with a preset pressure ratio range (<NUM>, A); when the pressure ratio data P2/P1 accord with the pressure ratio range (<NUM>,A), it is further determined whether the temperature ratio range T2/T1 accord with a preset first temperature ratio range (<NUM>, B); and if yes, a first corresponding oil content prediction model is obtained through matching; or if no, a second corresponding oil content prediction model is obtained through matching.

When the pressure ratio data P2/P1 do not accord with the pressure ratio range (<NUM>,A), it is further determined whether the temperature ratio range T2/T1 accords with a preset second temperature ratio range (<NUM>, C); and if yes, a third corresponding oil content prediction model is obtained through matching; or if no, a fourth corresponding oil content prediction model is obtained through matching.

Specifically, the pressure ratio range (<NUM>, A), the first temperature ratio range (<NUM>, B), and the second temperature ratio range (<NUM>, C) are determined according to the actual situation. In a preferred embodiment, A may be <NUM>, B may be <NUM>, and C may be <NUM>.

Further, step S200 further includes a training method for an oil content prediction model, including:
collecting the actual data of the temperature sensors and the pressure sensors in the sensor combination PT1 and the sensor combination PT2 at a plurality of previous moments and the actual oil content data of the compressor <NUM>, and processing to obtain a plurality of groups of temperature ratio data and pressure ratio data as the sample data, where the temperature ratio data and the pressure ratio data at a same moment constitute one piece of the sample data; and classifying the sample data according to the pressure ratio range (<NUM>,A), the first temperature ratio range (<NUM>, B), and the second temperature ratio range (<NUM>, C), to obtain four types of the sample data. Specifically, the four types of the sample data include:.

For each type of the sample data obtained after the classification, the type of sample data are divided into a training set and a test set; a neural network model is trained according to the training set to obtain a trained neural network model; the test set are input into the trained neural network model to obtain corresponding predicted oil content data; and when a probability that the predicted oil content data conform to the actual oil content data reaches a preset threshold, the trained neural network model is determined as the final oil content prediction model.

In this embodiment, the neural network model as used may be a support vector regression model. It should be noted that the type of the neural network model is not limited in the present invention, it would be ok that the corresponding predicted oil content data may be obtained according to the input test set data.

In this embodiment, four oil content prediction models corresponding to the four types of the sample data are finally obtained.

After the actual temperature ratio data T2/T1 and the pressure ratio data P2/P1 are obtained through the processing in step S100, a sample data type to which the actual temperature ratio data T2/T1 and the pressure ratio data P2/P1 conform is determined according to the pressure ratio range (<NUM>, A), the first temperature ratio range (<NUM>, B), and the second temperature ratio range (<NUM>, C). A corresponding oil content prediction model is further obtained through matching. For example, when the actual temperature ratio data T2/T1 and the pressure ratio data P2/P1 do not accord with the pressure ratio range (<NUM>, A), but accord with the second temperature ratio range (<NUM>, C), the third oil content prediction model is obtained through matching.

Step S300: Input the temperature ratio data T2/T1 and the pressure ratio data P2/P1 into the oil content prediction model obtained through the matching, and obtain the predicted oil content data.

Step S400: Control the rotation speed of the compressor <NUM> according to the predicted oil content data.

Specifically, the oil content range (<NUM>,D) is determined according to the actual situation. In a preferred embodiment, D may be <NUM>.

Referring to <FIG>, in the embodiment may include a rotation speed control system <NUM>, which is applied to the foregoing heat pump system. The rotation speed control system includes:.

Referring to <FIG>, in the embodiments, a computer device <NUM> is further included. The computer device <NUM> includes a processor <NUM>, the processor <NUM> is coupled to a memory <NUM>, the memory <NUM> stores program instructions, and when the program instructions stored in the memory <NUM> are executed by the processor <NUM>, the foregoing rotation speed control method is implemented. The processor <NUM> may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), and the like, or may be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or another programmable logic device, a discrete gate or a transistor logic device, or a discrete hardware component. The memory <NUM> may include a random access memory (RAM), and may further include a non-volatile memory, for example, at least one disk memory. The memory <NUM> may alternatively be an internal memory of a random access memory (RAM) type. The processor <NUM> and the memory <NUM> may be integrated into one or more independent circuits or hardware, for example, an application specific integrated circuit (ASIC). It should be noted that a computer program in the memory <NUM> may be stored in a computer-readable storage medium when being implemented in a form of a software functional unit and sold or used as an independent product. Based on such an understanding, the technical solutions of the present invention essentially, or the part contributing to the conventional technology, or some of the technical solutions may be implemented in a form of a software product. The computer software product is stored in a storage medium, and includes several instructions for instructing a computer device (which may be a personal computer, an electronic device, a network device, or the like) to perform all or some of the steps of the methods in embodiments of the present invention.

In the embodiments, a computer-readable storage medium is further included. The computer-readable storage medium includes a program, and when the program runs on a computer, the computer is enabled to perform the foregoing rotation speed control method.

In conclusion, the rotation speed control method and system, the device, and the storage medium provided in the present invention obtain four oil content prediction models through training by using a large amount of data, so that the heat pump system can predict oil content of the compressor according to readings of the temperature sensors and the pressure sensors, and further automatically control the rotation speed of the compressor according to the predicted oil content of the compressor, thereby implementing the automatic control over the compressor, preventing the oil shortage of the compressor, and improving the safety of the heat pump system. Therefore, the present invention effectively overcomes various disadvantages in the conventional technology and has high industrial utilization value.

Claim 1:
A rotation speed control method, applied to a heat pump system, wherein the heat pump system comprises an electronic flow regulating valve (<NUM>) and a compressor (<NUM>), the electronic flow regulating valve (<NUM>) is disposed on a low-pressure gas return circuit side of the compressor (<NUM>), both sides of the electronic flow regulating valve (<NUM>) are provided with a temperature sensor and a pressure sensor, and the rotation speed control method comprises:
collecting actual data of the temperature sensors and the pressure sensors, and processing to obtain temperature ratio data and pressure ratio data;
separately matching the temperature ratio data and the pressure ratio data with preset conditions of each pre-trained oil content prediction model, and if the matching succeeds, inputting the temperature ratio data and the pressure ratio data into an oil content prediction model obtained through matching, and obtaining predicted oil content data; and
controlling a rotation speed of the compressor (<NUM>) according to the predicted oil content data.