Control method for preventing frequent start and stop of heat pump based on fuzzy control and frequency gradient

Abstract

The invention provides a heat pump frequent start-stop prevention control method based on fuzzy control and frequency gradual change, and the method comprises the steps: firstly constructing a fuzzy control model through a temperature difference and a change rate thereof, predicting a load change trend, and dynamically adjusting the width of a temperature control dead zone; then, combining the current frequency with a dead zone state to initialize a target frequency, and adopting a nonlinear frequency gradient path to realize smooth adjustment; in the low-frequency operation stage, a low-frequency stability factor is introduced to judge the operation state, time is accumulated only under the stable condition, and short-time frequency increasing oil return protection is triggered; and finally, when the temperature difference is continuously in a dynamic dead zone, the frequency is lower than a safety threshold value, the low-frequency stable time reaches the standard and the oil is not returned, the shutdown operation is executed. The heat pump system is converted from start-stop control to continuous flexible adjustment, the energy efficiency is effectively improved, the comfort is effectively improved, and the service life of equipment is effectively prolonged.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of heat pumps, and particularly relates to a heat pump anti-frequent start-stop control method based on fuzzy control and frequency variation. BACKGROUND

[0002] In modern heat pump systems, the operation control of the compressor is the core problem affecting system stability, energy efficiency and service life. With the dynamic change of building load and the improvement of user comfort requirements, the traditional heat pump control system generally faces the chain problem of "frequent start-stop - insufficient oil return - control precision fluctuation". The existing control methods mainly adopt the PID algorithm with fixed parameters or simple on / off control. When the indoor temperature fluctuates or the terminal load changes frequently, the system will often be frequently started or stopped due to slight temperature difference disturbance, resulting in the compressor being in a high-frequency switching state. This control method not only increases the mechanical impact and current impact of the compressor, but also significantly reduces the energy efficiency of the system. In addition, during the low load operation stage, the compressor often runs at low frequency for a long time. At this time, if there is no reasonable oil return mechanism, the lubricating oil in the system may not be able to fully return to the compressor, which is easy to cause dry friction or cylinder jamming of the compressor. At the same time, in order to balance the heating precision and temperature control comfort, the traditional controller often falls into the dilemma of "narrowing the dead zone to improve the precision" and "widening the dead zone to ensure stability". Once the dead zone parameter is not reasonably set, the system response will be too slow or the compressor will be frequently started and stopped, so that the heat pump unit cannot fully play its variable frequency energy-saving and flexible regulation characteristics. SUMMARY

[0003] The purpose of the present application is to design a heat pump anti-frequent start-stop control method based on fuzzy control and frequency variation, which can realize the improvement of the heat pump compressor from the start-stop control to the continuous flexible control, and significantly prolong the service life of the equipment and improve the overall energy efficiency of the system while ensuring the comfort.

[0004] In order to achieve the above purpose, the present application provides a heat pump anti-frequent start-stop control method based on fuzzy control and frequency variation, which comprises the following steps: Collecting the current indoor temperature and the user set temperature, calculating the temperature difference and the change rate of the temperature difference; Taking the temperature difference and the change rate of the temperature difference as input variables, outputting the load change trend through a fuzzy control model, dynamically adjusting the temperature control dead zone width centered on the user set temperature according to the load change trend, and obtaining the dynamically adjusted temperature control dead zone width; When the absolute value of the temperature difference is less than or equal to the dynamically adjusted temperature control dead zone width, it is determined that the system enters a frequency maintenance mode, and a target frequency is initialized in combination with the current operating frequency of the compressor, the dynamically adjusted temperature control dead zone width, and a change rate thereof; a nonlinear frequency gradual change path is constructed based on a difference between the target frequency and the current operating frequency of the compressor; The compressor frequency is gradually adjusted according to the nonlinear frequency gradual change path, so that the compressor frequency is smoothly transitioned to the target frequency; A low-frequency operating state of the compressor below a safety frequency threshold is monitored, and when a low-frequency stability condition is met and an accumulated operating time reaches a set time limit, a short-time frequency-increasing oil return protection action is triggered; Under the condition that the absolute value of the temperature difference continuously remains within a range defined by the dynamically adjusted temperature control dead zone width, the compressor frequency is lower than a minimum safety frequency, and a low-frequency stable operating time exceeds a preset integral time threshold, a compressor shutdown operation is performed.

[0005] Further, in the fuzzy control model, the temperature difference and the temperature difference change rate are divided into five fuzzy subsets, including negative large, negative small, zero, positive small, and positive large, and a five-level discretized load change trend is output based on a preset fuzzy rule base.

[0006] Further, the dynamically adjusted temperature control dead zone width is adjusted in the following manner: when the predicted load tends to increase, the dead zone width is increased to delay the response, and when the predicted load tends to be stable, the dead zone width is reduced to improve the control sensitivity.

[0007] Further, an inertial memory factor is introduced in the initialization process of the target frequency, which is calculated based on the change rate of the dynamic dead zone width and used to suppress frequency oscillation of the system in a critical state.

[0008] Further, the nonlinear frequency gradual change path is achieved by dynamically reducing the frequency change step size during frequency adjustment, so that the frequency changes faster at the beginning of adjustment, and gradually slows down when approaching the target frequency.

[0009] Further, the monitoring of the low-frequency operating state includes judging whether the operating frequency of the compressor is lower than a preset safety frequency threshold, and integrating and accumulating a low-frequency duration.

[0010] Further, the low-frequency stability condition is determined by a low-frequency stability factor, which is dynamically calculated according to the fluctuation degree of the compressor frequency in the low-frequency region, and only when the frequency fluctuation is stable is the effective low-frequency operating time allowed to be counted.

[0011] Further, the low-frequency stability factor is based on the frequency fluctuation amplitude and fluctuation duration of the compressor during low-frequency operation, and when the frequency fluctuation amplitude is less than a preset tolerance and the duration exceeds a set threshold, it is determined that the low-frequency operation is stable.

[0012] Further, the short-time frequency increase oil return protection action is to forcibly increase the compressor frequency to a preset oil return frequency and maintain for a set time length, and then automatically restore to the original frequency regulation path.

[0013] Further, the non-linear frequency gradual change path is realized in the controller by table lookup method or exponential approximation algorithm to reduce the calculation load of the control system.

[0014] The beneficial technical effects of the present application are at least the following points: To solve the above problems, the present application provides a heat pump anti-frequent start-stop control method based on fuzzy control and frequency gradual change, which establishes a fuzzy control model by using temperature difference and temperature difference change rate, predicts future load change trend and dynamically adjusts temperature control dead zone, so that the system has forward-looking load adaptability, and fundamentally reduces the excessive response caused by sudden load fluctuation. Secondly, based on the prediction result, the gradual change path of the compressor frequency is adjusted in real time, the inertia memory factor and the non-linear buffer curve are introduced, so that the frequency change gradually slows down when approaching the set temperature, thereby avoiding "over-regulation" and "overshoot". Thirdly, the present application designs a low-frequency operation oil return protection mechanism for low-load long-time operation scene, dynamically triggers a short-time frequency increase oil return pulse through comprehensive judgment of low-frequency time, frequency fluctuation stability and operation state, to ensure smooth circulation of compressor lubricating oil. Finally, when the system approaches thermal equilibrium, an intelligent shutdown decision model is built by introducing time integral lag and non-linear stability criterion, and the system can only be shut down when it is long-term stable and the frequency is lower than the safety threshold, thereby avoiding the "critical start-stop oscillation" in traditional control. Through the synergistic effect of fuzzy prediction, dynamic dead zone adjustment, frequency gradual change control, oil return protection and intelligent shutdown judgment, the present application realizes the technical leap of heat pump compressor from start-stop control to continuous flexible control, while ensuring comfort, significantly prolonging equipment life and improving system overall energy efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0015] The present application is further illustrated by the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present application. For ordinary skilled in the art, other drawings can be obtained without creative labor on the basis of the following drawings.

[0016] Figure 1 A flowchart of the heat pump anti-frequent start-stop control method based on fuzzy control and frequency gradual change of the present application. DETAILED DESCRIPTION

[0017] Embodiments of the present application are described in detail below with reference to the attached drawing figures, wherein the same or like component have the same or similar designations. The embodiments described below are presented by way of example only and are not intended to limit the application.

[0018] In one or more embodiments, as shown in Figure 1 a heat pump anti-frequent start-stop control method based on fuzzy control and frequency gradient is disclosed, the method comprising the following: S1: Collect the current indoor temperature and the user set temperature, calculate the temperature difference and the change rate of the temperature difference; take the temperature difference and the change rate of the temperature difference as input variables, output the load change trend through a fuzzy control model, and dynamically adjust the temperature control dead zone width centered on the user set temperature according to the load change trend to obtain the dynamically adjusted temperature control dead zone width; Specifically, this step aims to build a fuzzy control model that can dynamically output the load change trend. This model will provide a prediction basis for the subsequent control strategies of the heat pump system (such as dead zone adjustment, frequency gradient, etc.), avoiding frequent start-stop caused by system response lag or overreaction. This process combines the physical characteristics of the heat pump system in operation to establish an active association between load prediction and control strategies.

[0019] During system operation, first, the current indoor temperature is collected, which is provided by a thermistor temperature sensor installed near the return air inlet of the indoor terminal, with a sampling period of 30 seconds. The user set temperature is input by the wall-mounted temperature controller and transmitted to the main controller through the Modbus protocol. The difference between the two constitutes the temperature difference , reflecting the deviation between the current room actual state and the target temperature. The main controller uses a sliding time window (default 5 minutes) to perform first-order differentiation on to calculate its change rate , representing the speed trend of the current system temperature adjustment process.

[0020] ; wherein, is the difference between the set temperature and the room temperature, used to measure the load size; is the change rate of the temperature difference, used to determine whether the system is rapidly warming up or cooling down.

[0021] These two variables are sent as input to the fuzzy controller, constructing a set of input membership functions covering five fuzzy subsets (negative large, negative small, zero, positive small, positive large). For example, when and When the current room temperature is lower than the set value and the temperature is approaching the target value quickly, the system judges that the load will gradually decrease. and , the system judges that the room temperature is low and the temperature is rising slowly, and expects that the load will increase. The fuzzy rule base is developed by artificial experience and test data, covering the common response mode under temperature control.

[0022] The fuzzy controller outputs a quantitative "load change trend" variable, denoted as , according to the two inputs. The variable is discrete, with a value range of , corresponding to "obvious decrease, slow decrease, stable, slow increase, and obvious increase" respectively. The output of is not only used as the basis for adjusting the subsequent temperature control strategy, but also directly used to adjust the temperature control dead zone width.

[0023] ; wherein represents the adjusted temperature control dead zone width, is the basic dead zone set by the system manufacturer (such as 0.3), is the adjustment coefficient (ranging from 0.1 to 0.2, which needs to be obtained by actual measurement and calibration), is the current load change trend level. This formula embodies a key control strategy: when the predicted load is expected to increase significantly, the system delays the compressor start-stop response by increasing the dead zone, thereby reducing excessive operation; when the load tends to be stable, the dead zone is reduced, enhancing the sensitivity of system regulation.

[0024] For example, if the current prediction result is , which represents that the load will increase rapidly, the dead zone is increased from to ; if , which means the load is stable, the default value is maintained, and no adjustment is needed.

[0025] The output of this step includes two variables: load change trend and dynamic dead zone width . Among them is used to convey the direction of the current system load development, is used as the basis for the subsequent frequency adjustment logic.

[0026] S2: When the absolute value of the temperature difference is less than or equal to the dynamically adjusted temperature control dead zone width, it is determined that the system enters a frequency maintenance mode, and the target frequency is initialized in combination with the current operating frequency of the compressor, the dynamically adjusted temperature control dead zone width and its change rate; a nonlinear frequency gradual change path is constructed based on the difference between the target frequency and the current operating frequency of the compressor; Specifically, the step is to further perform application level execution strategy conversion on the basis of the load change trend and the dynamic dead zone width . The core purpose is to land the prediction result into the temperature control logic and the compressor frequency control strategy, and introduce a gradually changeable frequency adjustment scheme to prevent unnecessary start-stop actions of the compressor in the case of rapid load change or critical stable state, thereby improving the overall stability of the system and the service life of the compressor. Unlike the fixed dead zone and on-off type start-stop strategy used in traditional temperature control, the step adjusts the trigger condition of the "entry control behavior", and proposes a dynamic frequency adjustment initialization method with a gradual buffer zone, thereby constructing a more responsive and flexible compressor braking strategy.

[0027] The two output variables from step one are input: the load change trend and the dynamic dead zone width . The values of the two output variables represent the predicted load fluctuation direction and strength, and the value range is . The larger the value, the faster the load growth, and the more the system needs to respond and release output power in advance; on the contrary, the smaller the value, the smaller the load or the more stable the system needs to enter the anti-start-stop control. is the dead zone width adjusted according to the trend, which will be used by the system instead of the traditional fixed dead zone as the threshold condition for triggering frequency control. The control logic is set as follows: when , the system determines that it is in the temperature control balance zone and no longer directly shuts down, but enters the frequency maintenance mode; when , it indicates that there is still a risk of load gap or overshoot, and enters the active frequency adjustment.

[0028] The first key operation of this step is to calculate the initial value of the target frequency of the compressor in the frequency maintenance mode . If the traditional heat pump system simply reduces the frequency to an empirically set value (such as 20 Hz) when approaching the set temperature, it will result in insufficient adaptability of the system to the load, especially in the case of rapid load dynamic change but small critical value, which is easy to enter "stop-start-stop" oscillation. Therefore, the present scheme proposes a dynamic initialization method considering the current state inertia and load trend of the system, and expresses as a functional relationship between the current frequency of the compressor and the dynamic dead zone, and introduces an inertia factor Memory term of system physical response: ; Where, is the current operating frequency of the compressor, which is fed back by the frequency drive in real time; is the static adjustment coefficient, which regulates the degree of linear influence of the dead zone on the target frequency; is the dynamic dead zone width, which is calculated in the previous step; is the inertial adjustment coefficient (0.2-0.5, calibrated according to the inertia experiment of the device), represents the dead zone change rate, which quantifies the "momentum" trend of the change in system thermal load.

[0029] The design of this formula has two creative features: first, the dynamic calculation of participates in the calculation, which can achieve flexible setting of the maintenance frequency according to the predicted load intensity; second, the term is introduced as a kind of micro-inertial feedback mechanism, which can suppress the frequency oscillation problem after the system enters the critical state. For example, when the load change slows down but the dead zone continues to expand (indicating that the prediction tends to be stable), , at this time will raise to prevent the compressor frequency from being too low; when the load tends to increase and the dead zone shrinks, the term is adjusted in the opposite direction to avoid over-response.

[0030] The second key operation is to provide a nonlinear control surface for the frequency ramping process, constructing a flexible adjustment space. For this purpose, we insert an exponential buffer function between the frequency ramping intervals (e.g. ), so that the frequency decreases faster in the front and slower in the back, preventing control conflicts when the compressor is about to enter the dead zone boundary due to too fast frequency adjustment. The adjustment curve can be described as the compressor frequency adjustment function : ; Here represents the relative time of each adjustment cycle of the controller, is the nonlinear factor of frequency decay, is the control sensitivity parameter (which can be set to 0.3-0.6), which is adjusted according to the controller refresh period and the target temperature control response time. This function is implemented by table lookup or exponential approximation in hardware, without introducing complex calculation burden, but can significantly improve the stability of the control curve.

[0031] This step outputs the following two variables: the initial frequency The target frequency for the compressor's gradual adjustment phase guides the system to enter low-load continuous operation when the temperature approaches the set value; buffer frequency adjustment function. : Compressor frequency adjustment path control function, used to generate a path from the current frequency to... A smooth transition path prevents frequency jumps from causing system control instability.

[0032] S3: The compressor frequency is gradually adjusted according to the nonlinear frequency gradient path to smoothly transition the compressor frequency to the target frequency; the compressor's low-frequency operation status below the safe frequency threshold is monitored, and when the low-frequency stability condition is met and the cumulative operating time reaches the set time limit, a short-term frequency increase oil return protection action is triggered. Specifically, this step follows up on the two key parameters output from the previous stage: the frequency maintenance target value. With buffer frequency adjustment function Based on this, specific frequency control actions are executed, and a "low-frequency operation oil return protection" mechanism strongly relevant to the scenario of this solution is introduced. This step is the part of the actual control layer that directly affects the compressor frequency. Its goal is to maintain a flexible supply of system heat output through a gradual frequency change within the range where the temperature difference is close to the set value but has not yet met the shutdown conditions. In the case of excessively long low-frequency operation, a forced short-term frequency increase is triggered, thereby ensuring that the system compressor's lubrication oil circuit remains unobstructed and avoiding the risk of compressor dry friction, wear, or burnout in the "continuous low frequency - frequent fine-tuning" mode. This control strategy is particularly suitable for typical room types in the scenario set by this solution, such as rooms with frequent opening and closing of doors and windows or rooms with independent logic at the indoor terminal. In these environments, the system frequency is often maintained at a low load state, but due to the unpredictable heat load disturbance, the traditional "low frequency + shutdown" strategy frequently switches, which will seriously reduce the compressor's lifespan. Therefore, the key to this step is to build a mechanism that integrates dynamic adjustment, state perception, and protection control.

[0033] The system first uses the buffer frequency control function from the previous stage. Output the current target frequency The function, defined in step two, is a nonlinear decay model, expressed as follows: ; This frequency value is refreshed in the controller every 2 seconds, replacing the traditional step frequency distribution method, so that the frequency changes from... Smooth transition to To ensure the safety of the control logic and lubrication, we introduced a low-frequency operating time integral mechanism, which monitors the compressor operating at frequencies below a certain safe operating frequency threshold. Cumulative running time at (e.g., 28Hz) and set the system safety low frequency operation limit (eg. 30 minutes). Once the condition is met, the system will trigger a short frequency boost pulse to promote oil return.

[0034] Considering the actual engineering, if simply triggered by time threshold, it may frequently produce "false trigger" phenomenon when the system just enters the low frequency state, especially when the frequency is small amplitude dithering near the low frequency limit, the system frequent frequency boost instead of energy waste. Therefore, this step adds a "low frequency stability factor" to the original trigger logic, which is used to measure the stability of low frequency operation. When the system frequency continues to stabilize in the low frequency area, tends to 1; if the frequency fluctuates near the low frequency limit, tends to 0. The calculation method is: ; ; Where, is the fluctuation suppression coefficient, the value is set according to the experience of the device response time constant, such as . This design combines the "low frequency boost protection" mechanism with the system's stable state perception: when the system runs stably in the low frequency state (the frequency changes smoothly), close to 1, allowing normal timing trigger protection; while in the frequency instability phase (the system is not yet stable or in the transition state), significantly reduced, the system will delay the oil return pulse trigger, effectively avoiding unnecessary frequency boost.

[0035] The oil return pulse trigger judgment formula constructed in this way is as follows: ; In this expression, is the effective low frequency operation time integral, which is only counted when the system low frequency stability is high, ensuring that the frequency boost protection action only occurs when it is really needed. This judgment logic is calculated periodically by the main controller firmware, updated once every refresh period. If the trigger condition is met, the system will force the compressor frequency to be set to (eg. 45Hz), maintain running (eg. 3 minutes), and then automatically fall back to and re-enter curve to continue adjustment.

[0036] This step outputs two variables: the current control period target frequency , determined by or , used for frequency converter frequency driving signal; current cycle oil return protection state flag ​, control whether to perform the frequency increase action.

[0037] S4: Under the condition that the absolute value of the temperature difference continuously meets the dynamically adjusted temperature control dead zone width, the compressor frequency is lower than the minimum safe frequency, the low-frequency stable operation time exceeds the preset integral time threshold, and the current is not in the oil return protection action, perform the compressor shutdown operation.

[0038] Specifically, the compressor frequency set value output in the previous stage and the oil return pulse state flag are used to determine and execute the key control behavior of "whether to shut down". The goal of this step is to prevent the heat pump compressor from frequent start-stop due to small temperature signal fluctuations, especially when the frequency adjustment near the set point tends to be stable, providing a stable, lagging, and controllable shutdown logic for the system. In traditional control, compressor shutdown often only depends on whether the temperature difference falls within the dead zone, but in the application scenario of this solution, the end load fluctuates frequently. If the judgment condition does not introduce a system dynamic lag mechanism, "start-stop oscillation" may occur at the edge of the dead zone. Therefore, this step designs a composite shutdown criterion system based on frequency state, temperature difference trend, and time integration.

[0039] To ensure the realizability of the logic, the control system collects the following operating state quantities every refresh cycle (usually 2 seconds): the current compressor frequency , which is obtained by the controller through the frequency converter feedback, is the target value of the frequency buffer function ; the dynamic dead zone width , which is calculated in step one, is used to define the "non-trigger interval" when the temperature control approaches the set point; the current temperature difference , which is obtained by subtracting the real-time room temperature collected by the return air temperature sensor from the user set temperature ; the temperature difference integral time is an internal variable of the controller. Whenever the condition is met, it starts to accumulate, and if the condition is interrupted, it returns to zero; whether the current is in the oil return pulse process is provided by the variable from the previous step.

[0040] For example, in a typical winter heating condition, assume that the user set temperature , the current room temperature is , which is uploaded to the main controller by the sensor module (NTC thermistor sensor) in ModbusRTU protocol, and the calculated . Assuming that the of the current step is , the temperature difference stable condition is met; the controller counts once every 2 seconds increment. If the current is lower than the set minimum frequency and the past minutes are far beyond the set threshold minutes, and this period , it can be determined that the current meets the shutdown condition.

[0041] To enhance robustness and avoid fluctuations caused by discontinuous control boundaries, this step fuses the above states into a shutdown trend indicator function with a smooth regularization term : ; where the first term measures the normalized square difference between the current frequency and the minimum frequency, and the second term is the square ratio of the temperature difference integral time to the threshold time, is a weight coefficient set when designing the system regulator, and the recommended value is 0.3 to 0.5. The construction of this function has two points: one is to introduce frequency response state buffering through the frequency term to avoid immediate shutdown due to close to the minimum frequency; the other is to introduce a time integral term as a hysteresis factor to ensure that the shutdown behavior can only be triggered in a "stable and sustained" scenario, thereby improving the system's disturbance rejection capability.

[0042] The system takes as the shutdown judgment boundary. When this condition is met and the current is lower than the set minimum frequency , the controller will generate a shutdown command , instructing the frequency converter to stop the compressor from running and clearing the temporary storage states related to frequency regulation (such as buffer function counters, etc.). Otherwise, the current low-frequency running state is maintained, and the system continues to move along the buffering path , waiting for further stabilization of the system state.

[0043] The embodiment of the present application also provides a heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradual change, which comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements steps in the above-mentioned heat pump anti-frequent start-stop control method embodiment based on fuzzy control and frequency gradual change, such as steps S1-S4 in the above-mentioned embodiment. Figure 1 Or, the processor implements the functions of the modules in the above-mentioned system embodiments when executing the computer program.

[0044] The computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient.

[0045] The heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient can be a computing device such as a desktop computer, a notebook computer, a palm computer, and a cloud server. The heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient can also include an input / output device, a network access device, a bus, and the like.

[0046] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASAC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. The general-purpose processor can be a microprocessor or any conventional processor, and the like. The processor is the control center of the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient, and connects all parts of the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient through various interfaces and lines.

[0047] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, etc.; and the data storage area can store data created according to the running of the air conditioner controller, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0048] The modules of the heat pump anti-frequent start-stop control device based on fuzzy control and frequency gradient can be stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of the above-mentioned various method embodiments when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0049] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the program can be stored in a computer readable storage medium, and the program can include the processes of the above-mentioned various method embodiments when executed. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0050] The above is the preferred embodiment of the present application, it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, can also make a number of improvements and refinements, these improvements and refinements are also considered to be within the scope of the present application.

Claims

1. A heat pump anti-frequent start-stop control method based on fuzzy control and frequency gradient, characterized in that, The method comprises: collecting the current indoor temperature and the user set temperature, calculating the temperature difference and the change rate of the temperature difference; using the temperature difference and the change rate of the temperature difference as input variables, outputting the load change trend through a fuzzy control model, and dynamically adjusting the width of the temperature control dead zone centered on the user set temperature according to the load change trend to obtain the dynamically adjusted width of the temperature control dead zone; when the absolute value of the temperature difference is less than or equal to the dynamically adjusted width of the temperature control dead zone, determining that the system enters a frequency maintenance mode, initializing a target frequency in combination with the current operating frequency of the compressor, the dynamically adjusted width of the temperature control dead zone and the change rate thereof, and constructing a nonlinear frequency gradual change path based on the difference between the target frequency and the current operating frequency of the compressor; gradually adjusting the frequency of the compressor according to the nonlinear frequency gradual change path to smoothly transition the frequency of the compressor to the target frequency; monitoring the low-frequency operating state of the compressor below the safety frequency threshold, triggering a short-time frequency-increasing oil return protection action when the low-frequency stability condition is met and the cumulative operating time reaches the set time limit; when the absolute value of the temperature difference continuously stays within the range defined by the dynamically adjusted width of the temperature control dead zone, the frequency of the compressor is lower than the minimum safety frequency, the low-frequency stable operating time exceeds the preset integral time threshold and the current is not in the oil return protection action period, performing a compressor shutdown operation.

2. The method according to claim 1, wherein, In the fuzzy control model, the temperature difference and the change rate of the temperature difference are divided into five fuzzy subsets, including negative large, negative small, zero, positive small and positive large, and five levels of discrete load change trends are output based on a preset fuzzy rule base.

3. The method according to claim 1, wherein the method is characterized by, The dynamically adjusted temperature control dead zone width is: when the predicted load tends to increase, the dead zone width is increased to delay the response, and when the predicted load tends to be stable, the dead zone width is reduced to improve the control sensitivity.

4. The method according to claim 1, wherein, The initialization process of the target frequency introduces an inertial memory factor, which is calculated based on the change rate of the dynamic dead zone width, and is used to suppress the frequency oscillation of the system in the critical state.

5. The method according to claim 1, wherein the method is characterized by, The nonlinear frequency gradual change path is realized by dynamically reducing the frequency change step size during frequency adjustment, so that the frequency changes quickly at the beginning of adjustment, and gradually slows down when approaching the target frequency.

6. The method according to claim 1, wherein the method is characterized by, The monitoring of the low-frequency operating state includes judging whether the operating frequency of the compressor is lower than the preset safety frequency threshold, and integrating and accumulating the low-frequency duration.

7. The method according to claim 1, wherein the method is characterized by, The low-frequency stability condition is determined by a low-frequency stability factor, which is dynamically calculated according to the fluctuation degree of the frequency of the compressor in the low-frequency region, and only when the frequency fluctuation is stable can the effective low-frequency operating time be counted.

8. The method according to claim 7, wherein the method is characterized by, The low-frequency stability factor is based on the frequency fluctuation amplitude and duration of the compressor during low-frequency operation, and when the frequency fluctuation amplitude is less than the preset tolerance and the duration exceeds the set threshold, it is determined that the low-frequency operation is stable.

9. The method according to claim 1, wherein the method is characterized by, The short-time frequency-increasing oil return protection action is to forcibly increase the frequency of the compressor to a preset oil return frequency and maintain it for a set time, and then automatically restore to the original frequency adjustment path.

10. The method according to claim 1, wherein the method is characterized by, The nonlinear frequency gradual change path is realized in the controller by table lookup method or exponential approximation algorithm to reduce the calculation load of the control system.

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