Load dynamic adjusting method and system for multi-connected fresh air heat pump unit

Abstract

The invention discloses a load dynamic adjusting method and system of a multi-connected fresh air heat pump unit. The method comprises the steps of collecting operation data of each unit through a multi-source sensor, and performing health degree evaluation on each unit to output a health degree score of each unit; based on the health degree score of each unit, obtaining a decision signal corresponding to each unit, and based on a preset mode trigger logic, determining a working mode corresponding to each unit, the working mode including a health driving mode and a periodic rotation mode; and each unit is controlled to execute corresponding operation according to the respective working mode. According to the invention, on one hand, in a health driving mode, the load is dynamically distributed, so that the healthy unit bears more load, load reduction protection is carried out on the unit in a sub-health state, and a maintenance program is started for the unit in a fault early warning state; on the other hand, the health driving mode and the periodic rotation mode are in double-track parallel, and cooperative control is achieved through a priority arbitration mechanism.

Description

Technical Field

[0001] The present invention relates to a load dynamic adjustment method for a multi-connected fresh air heat pump unit and also relates to a corresponding load dynamic adjustment system, belonging to the technical field of air conditioning. Background Art

[0002] Currently, multi-split fresh air heat pump units (hereinafter referred to as units) have become the mainstream form of commercial building air conditioning systems. However, in their most common parallel operation scenario, they have long been constrained by the extensive "fixed load distribution" strategy: regardless of their health, units are rigidly arranged in "shifts" or "primary / standby" modes. As a result, some units are constantly fully loaded or even overloaded, while others are frequently started and stopped. Mechanical wear, insulation aging, and lubricant carbonization accelerate, prematurely extending equipment lifespans. Although IoT sensors have entered engineering applications, they remain at the "post-event" or "single-point threshold" level, unable to achieve real-time optimization based on multi-dimensional health indicators. Gradual faults such as dust accumulation and lubrication degradation still rely on manual inspections and regular cleaning. These cleaning cycles are seriously out of sync with actual contamination levels, further amplifying system risks.

[0003] The above dilemma manifests itself as four interlocking pain points during the unit's "movement process": First, traditional load distribution adopts a static rotation or fixed master-slave mode, switching the host only based on a time period, completely ignoring the actual health differences between devices, resulting in a surge in the failure rate of high-load units and an imbalance in system availability.

[0004] Secondly, overheating protection relies on temperature sensors to trigger instantaneous frequency reduction. Although it can solve the immediate problem, it is powerless to prevent the cumulative thermal damage caused by long-term saturated operation. Insulation aging and lubricant carbonization continue.

[0005] Third, the start-stop control is based on the set temperature difference threshold. Although frequent start-stopping can temporarily reduce energy consumption, it causes the compressor bearings and motor windings to undergo periodic mechanical shocks, causing fatigue cracks to initiate and the life curve to drop sharply.

[0006] Fourth, dust removal maintenance still relies on manual disassembly or scheduled self-cleaning, and the cleaning cycle is mismatched with the pollution rate; dust accumulation has to wait until the heat dissipation efficiency drops to a critical value before maintenance is passively triggered, which increases the risk of shutdown and power outage. Summary of the Invention

[0007] The primary technical problem to be solved by the present invention is to provide a method for dynamically adjusting the load of a multi-connected fresh air heat pump unit.

[0008] Another technical problem to be solved by the present invention is to provide a load dynamic adjustment system for a multi-connected fresh air heat pump unit.

[0009] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: According to a first aspect of an embodiment of the present invention, a method for dynamically adjusting the load of a multi-connected fresh air heat pump unit is provided, comprising the following steps: Collect the operating data of each unit through multi-source sensors; Based on the operating data of each unit, the health score of each unit is calculated using a preset health model; Based on the health score of each unit, the unit status corresponding to each unit is output according to the preset threshold; wherein the unit status includes at least healthy state, sub-healthy state and fault warning state; According to the status of each unit, the decision signal corresponding to each unit is output; For each of the units, determining whether the decision signal meets the conditions for activating the healthy driving mode through a preset mode trigger logic; If the conditions are met, the health drive mode is activated to cause the unit to perform health drive operations and temporarily freeze the recording time of the periodic rotation mode. The health drive operation includes: selecting healthy units to bear the main load, performing load reduction protection on units in sub-healthy states, and starting maintenance procedures for units in fault warning states. If not, determine whether the accumulated running time of the unit has reached the periodic rotation time; if reached, activate the periodic rotation mode so that the unit performs the periodic rotation operation and resets the unit status corresponding to the unit; if not reached, maintain the current status and wait for the next decision signal; wherein, the periodic rotation operation includes: controlling the unit to perform periodic rotation between full load operation, low load operation and shutdown.

[0010] Preferably, the health score is calculated by the following steps: ; Where F is the fatigue coefficient, ; L is the lubrication index, ; D is the dust accumulation index, .

[0011] Preferably, in the healthy driving mode, each unit performs healthy driving operation in the following manner: If the health score of the current unit is not less than the first threshold, the current load is maintained; If the health score of the current unit is less than the first threshold and not less than the second threshold, the load reduction protection is triggered to reduce the load to 30% of the rated power of the current unit; and other available units with a health score not less than the first threshold are found to compensate for the load according to the total load demand of the system. The power of each load-compensated healthy unit shall not exceed 95% of its rated power. If the health score of the current unit is less than the second threshold, it is marked as a fault warning state and the maintenance procedure is started.

[0012] Preferably, the load dynamic adjustment method further includes: Determine whether the dust accumulation index of each unit exceeds the dust accumulation threshold; If it exceeds, the unit will be shut down and the bypass reverse dust removal air valve channel will be started. The redundant air volume generated by the unit running at low load will be pressurized through the Venturi tube and then controlled by the pulse solenoid valve to reversely impact the heat sink of the shut down unit every 30 seconds.

[0013] Preferably, the determining whether the decision signal satisfies the healthy driving mode by using a preset mode triggering logic specifically includes: Based on the decision signal, outputting a first determination result of whether the health score of the unit exceeds a threshold; outputting a second judgment result of whether the degradation rate of the unit exceeds a limit based on the decision signal; outputting a third judgment result of whether a key component of the unit is abnormal based on the decision signal; The final judgment result of whether the unit meets the healthy driving mode is jointly determined based on the first judgment result, the second judgment result and the third judgment result.

[0014] Preferably, the load dynamic adjustment method further includes: Determine whether the multi-connected fresh air heat pump unit has abnormal operating conditions; If an abnormal operating condition exists, an abnormality handling strategy is executed according to the abnormal operating condition.

[0015] Preferably, executing the abnormality handling strategy according to the abnormal operating condition at least includes: When the healthy driving mode and the periodic rotation mode are triggered at the same time, the healthy driving mode is executed first, and the periodic rotation mode is executed after a preset delay; When there is no healthy unit to compensate for the load in the healthy drive mode, the standby unit is started and the alarm program is activated; When there are insufficient healthy units to rotate in the periodic rotation mode, only the units in sub-healthy status will be rotated, and the units in fault warning status will remain unchanged.

[0016] According to a second aspect of an embodiment of the present invention, a load dynamic adjustment system for a multi-connected fresh air heat pump unit is provided, comprising: A data acquisition unit, used to collect operating data of each unit through multi-source sensors; a health assessment unit connected to the data acquisition unit and pre-set with a health model, for calculating a health score of each unit using the health model based on the operating data of the unit; and, based on the health score of each unit, outputting a unit status corresponding to each unit according to a preset threshold; A decision unit, connected to the health assessment unit, configured to output a decision signal corresponding to each unit according to the unit status corresponding to each unit; a mode selection unit connected to the decision unit to determine, for each of the units, whether the decision signal satisfies the healthy drive mode through a preset mode trigger logic; if so, activating the healthy drive mode to cause the unit to perform a healthy drive operation and temporarily freezing the recording time of the periodic rotation mode; if not, determining whether the accumulated operating time of the unit has reached the periodic rotation time; if so, activating the periodic rotation mode to cause the unit to perform a periodic rotation operation and resetting the unit state corresponding to the unit; if not, maintaining the current state and waiting for the next decision signal; An execution unit is connected to the mode selection unit to control each unit to execute the healthy driving operation or the periodic rotation operation.

[0017] According to a third aspect of an embodiment of the present invention, another load dynamic adjustment system for a multi-connected fresh air heat pump unit is provided, comprising a processor and a memory, wherein the processor reads a computer program in the memory to implement the above-mentioned load dynamic adjustment method.

[0018] Compared with the prior art, the present invention has the following technical effects: (1) Dynamic load distribution in health-driven mode. Specifically, by collecting the operating data of each unit, the health status of each unit is evaluated, and then the load is dynamically distributed according to the health score of each unit, so that healthy units bear more load, while units in sub-healthy states are protected by load reduction, and maintenance procedures are initiated for units in fault warning states. In this way, reasonable load distribution is carried out according to the different health status of each unit.

[0019] (2) The health-driven mode (active response) and the periodic rotation mode (preventive scheduling) operate in parallel, achieving coordinated control through a priority arbitration mechanism. Specifically, the order of operation of the two modes is determined by decision signals, and the mode is switched according to changes in the health status of the unit and the unit's operating time. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a method for dynamically adjusting the load of a multi-connected fresh air heat pump unit provided in the first embodiment of the present invention; Figure 2 This is a flow chart for determining the working mode of a unit in the first embodiment of the present invention; Figure 3 This is a flowchart of the execution of the health driving mode in the first embodiment of the present invention; Figure 4 A structural diagram of a load dynamic adjustment system for a multi-connected fresh air heat pump unit provided in a second embodiment of the present invention; Figure 5 This is a structural diagram of a load dynamic adjustment system for a multi-connected fresh air heat pump unit provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0021] The technical content of the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] First embodiment like Figure 1 As shown, a first embodiment of the present invention provides a method for dynamically adjusting the load of a multi-connected fresh air heat pump unit, comprising at least the following steps: S10: Data collection.

[0023] In this embodiment, the operating data of each unit is collected through multi-source sensors. Specifically, key parameters of each unit during operation, such as temperature, pressure, vibration, current, etc., are obtained through various sensors or monitoring modules.

[0024] S20: Perform health assessment on each unit.

[0025] Specifically, the following steps are included: S21: Data preprocessing.

[0026] After the raw data collected in step S10 above enters the data preprocessing stage, the data is cleaned, denoised, formatted and outliers are removed to ensure the accuracy and reliability of subsequent calculation results.

[0027] S22: Parameter calculation.

[0028] After completing data preprocessing, the parameter calculation phase begins. Based on the algorithm model, key operating characteristics are extracted and calculated to provide basic data support for health assessment.

[0029] Specifically, in this embodiment, the parameters to be calculated include at least: fatigue coefficient F, lubrication index L and dust accumulation index D. The calculation method of each parameter is described in detail below: (1) Fatigue coefficient F In this embodiment, the fatigue coefficient The specific design principle is: the number of starts and stops is adjusted to the power of 1.5 to strengthen the penalty for high-frequency starts and stops, and a critical threshold is set for the vibration component to strengthen abnormal warning. Accordingly, the specific calculation formula of the fatigue coefficient F is as follows: ; Among them, Ns represents the cumulative number of starts and stops on the day; N max Indicates the maximum number of times the compressor can start and stop per day (50 times by default, depending on the compressor signal); V rms Indicates the effective value of vibration acceleration; V crit Indicates the vibration threshold.

[0030] (2) Lubrication index L In this embodiment, the lubrication index The specific design principle is: introducing the ambient temperature change benchmark to eliminate interference, and the oil film thickness coefficient directly reflects the physical state of lubrication. Accordingly, the specific calculation formula of the lubrication index L is as follows: ; Where, ΔT O Indicates the oil temperature fluctuation amplitude; ΔT b Indicates the ambient temperature change benchmark; THD indicates the total harmonic distortion rate of current; η oil Indicates the ink thickness coefficient.

[0031] (3) Dust accumulation index D In this embodiment, the dust accumulation index The specific design principle is to use double normalization (heat dissipation temperature difference and dust concentration are both relative to the baseline value) to make the dust accumulation levels of equipment under different environmental conditions comparable. Accordingly, the specific calculation formula for the dust accumulation index D is as follows: ; Where, ΔT h Indicates the measured temperature difference of the heat sink; ΔT O Indicates the clean radiator design temperature difference; C d Indicates the measured dust concentration; C d0 Indicates the local typical dust concentration baseline value.

[0032] S23: Output the health score corresponding to each unit.

[0033] After the required parameter information is extracted according to the above step S22, a health score is performed according to the preset health model, and the current status of the device is quantitatively evaluated by integrating multi-dimensional indicators to output a value representing the health level of the device.

[0034] Specifically, the calculation formula of the health model is as follows: .

[0035] It can be understood that the health score H output by the health model in this embodiment is in the form of a percentage system, that is, H∈(0-100).

[0036] S30: Obtaining the decision signal corresponding to each unit.

[0037] Specifically, after determining the health score corresponding to each unit based on the above step S20, it is necessary to output the unit status corresponding to each unit according to the preset threshold. In this embodiment, the unit status includes at least healthy state, sub-healthy state and fault warning state. Specifically, When the health score H≥80 points, the unit is in a healthy state; when the health score 60≤H<80 points, the unit is in a sub-healthy state; when the health score H<60 points, the unit is in a fault warning state.

[0038] Furthermore, after determining the status of each unit, it is necessary to output the corresponding decision signal for each unit. Specifically, it includes the following: (1) The decision signal is determined by the trigger flag, trigger unit ID, unit degradation type and urgency level.

[0039] (2) The decision signal generation logic is as follows: Receive the current unit's health score H and perform three conditional judgments: ①H<80 (health score is lower than the threshold); ② Health score change rate dH / dt < -5 (health status declines rapidly); ③ Is THD > 10% or V rms >8 (current harmonics or vibration amplitude exceeds the standard); If any of the above conditions is "yes", the system generates a trigger decision signal, which includes: ① Set the trigger flag activate = true; ②Mark the degradation type according to the specific trigger conditions (such as electrical abnormality, mechanical wear, etc.); ③Calculated fault urgency (for subsequent priority sorting); (3) The rules for quantifying the degree of urgency are shown in the following table: It is understood that after completing the trigger judgment and feature marking, the system generates a complete decision signal, including the trigger status, degradation type and emergency level. This decision signal is sent to the arbitration module for fusion judgment with other signals.

[0040] S40: Determine the working mode of each unit.

[0041] After the decision signal corresponding to each unit is output based on the above step S30, refer to Figure 2 As shown, for each unit, it is necessary to use the preset mode trigger logic to determine whether each unit meets the healthy driving mode based on the decision signal corresponding to each unit.

[0042] It is understood that this decision signal is used to determine whether adjustments to the current device operating state are necessary. Upon receiving the decision signal, the system enters the health drive mode activation phase. At this point, the system determines whether the conditions for enabling health drive mode are met based on pre-set health assessment criteria.

[0043] In this embodiment, the three conditions for determining whether the healthy driving mode is activated correspond to the above-mentioned decision signal generation logic. Specifically, whether the healthy driving mode is activated is determined based on the three conditions: (1) Determine whether the health score exceeds the threshold; if H < 80, it means that the unit has exceeded the threshold and entered the fault warning state.

[0044] (2) Determine whether the unit degradation rate exceeds the limit; if dH / dt < -5 minutes / hour, it means that the health of the unit is deteriorating at an accelerated rate.

[0045] (3) Determine whether there are any abnormalities in the key components of the unit; if THD>10% or V rms >8mm / s 2 , it means that the motor or bearing of the unit is about to fail.

[0046] It is understood that after the decision signal is obtained in step S30, the judgment results of the three conditions are determined based on the decision signal. Furthermore, based on the judgment results of the three conditions, a signal is output indicating whether the unit's healthy drive mode is activated. The specific activation conditions are: the health score does not exceed the threshold, the unit degradation rate does not exceed the limit, and there are no abnormalities in the unit's key components (that is, if any of the three judgment conditions are triggered, the healthy drive mode cannot be activated).

[0047] Based on the above judgment logic, the judgment results for the working mode of each unit are as follows: If the judgment result is "yes," meaning the current device status meets the requirements of the health-driven policy, the system will execute health-driven operations. This includes prioritizing healthy devices, restricting or isolating unhealthy devices, and optimizing load distribution to ensure overall system stability and device lifespan. While executing health-driven operations, the system freezes the periodic rotation clock, suspending the existing timed rotation mechanism to prevent fixed-period switching from interfering with the health-driven policy.

[0048] ② If the health drive mode is not activated (i.e., the judgment result is "No"), the system further determines whether the periodic rotation time has arrived. This judgment is based on the rotation cycle parameters set by the system to achieve regular switching between devices, avoiding uneven wear or accelerated aging caused by long-term operation of a single device.

[0049] ③ If the periodic rotation time has arrived, the system will execute the periodic rotation operation, switching the primary and backup devices or adjusting the operating status of each device in a predetermined order to ensure that the load is balanced and the devices are in good operating condition. After the periodic rotation operation is completed, the system will reset the health driver lock state, removing the device lock mechanism that may have been previously imposed by the health driver policy, restoring the system to a state where it can once again accept health driver judgment, thus achieving the unification of dynamic management and flexible scheduling.

[0050] ④ If the cycle rotation time has not yet arrived, the system chooses to maintain the current operating state, does not switch or adjust the equipment, continues to monitor the system status and waits for the next decision signal.

[0051] S50: Execute corresponding operations according to the working mode.

[0052] It can be understood that when it is determined through the above step S40 that the unit meets the healthy driving mode, the corresponding unit activates the healthy driving mode, so that the unit performs the healthy driving operation and temporarily freezes the recording time of the periodic rotation mode.

[0053] Similarly, when it is determined through the above step S40 that the unit meets the periodic rotation mode, the corresponding unit activates the periodic rotation mode, so that the unit performs the periodic rotation operation and resets the unit status corresponding to the unit.

[0054] The following describes in detail the specific working processes of the health-driven mode and the cycle rotation mode: (1) Health-driven model like Figure 3 As shown, in this embodiment, in the health drive mode, for a single unit, different operations are performed according to the changes in the unit health score. The details are as follows: ① If the unit's health score is greater than or equal to 80 points, maintain the current load.

[0055] ② As the unit continues to operate, the unit's health score will gradually decrease. When it drops below 80 points, the load reduction protection is triggered. At this time, the load of the unit is reduced to 30% of its rated power. In addition, it should be understood that when the unit triggers the load reduction protection, load compensation is required by other healthy units to ensure the stable operation of the system. Specifically, by finding units with a health score greater than 80 points, the load is increased proportionally according to the total load demand of the system. The power of each load-compensated healthy unit is no more than 95% of its rated power to avoid overload operation of healthy units.

[0056] ③ As the unit continues to operate, once the unit's health score falls below 60 points, the unit will be marked as a fault warning state and the maintenance procedure will be triggered.

[0057] In addition, in health-driven mode, based on the health score of each unit, in a system with multiple units (N air-conditioning outdoor units, N compressors, etc.) running in parallel, the system intelligently distributes the load based on the health status of the equipment and decides whether maintenance or switching to backup equipment is required. The details are as follows: ① Select high-health units and allocate the main load.

[0058] Units with a health score greater than 80 are selected from the global variables to form a "high-health unit pool" and are given priority to bear the main load (for example, the target allocation ratio can be set to 70% of the total load).

[0059] High-health equipment takes the main load first, improving the stability of the overall system; preventing inefficient or potentially faulty equipment from running at full load for a long time; achieving optimal load distribution and improving energy efficiency.

[0060] ② Screen sub-healthy units and distribute the remaining load.

[0061] Units with health scores between 60 and 80 are screened out to form a "sub-healthy unit pool" to bear secondary loads (for example, the target allocation ratio can be set to 30% of the remaining total load).

[0062] Control the operating intensity of sub-health equipment to prevent further deterioration; make rational use of existing resources without affecting system stability; and create a time window for subsequent maintenance.

[0063] ③Perform mandatory maintenance and standby takeover on fault warning units.

[0064] A traversal of all units reveals that if a unit's health score is ≤60, it is considered a "fault warning" and the following actions are performed: The unit is triggered to enter maintenance mode. Executable actions include automatic cleaning, lubrication system cycling, and component resets. The goal is to prevent sudden failures and restore equipment performance. The corresponding standby unit is activated to take over the load from the original faulty / low-health unit, ensuring business continuity and preventing system downtime due to single points of failure.

[0065] (2) Cycle rotation mode In this embodiment, the "full-load machines, high-frequency machines, and idle machines" are rotated periodically every 72 hours, wherein the fully-loaded machines operate at full load, the high-frequency machines operate at low load, and the idle machines are in a shutdown state.

[0066] For example, suppose an air conditioning system has three devices: Device 1 is a fully loaded unit (operating at full load for extended periods), Device 2 is a high-frequency unit (used for fine-tuning parameters such as air volume, cooling, and heating within a limited range), and Device 3 is an idle unit (not normally used but used for enhanced ventilation, cooling, or heating in special environments). After the rotation, Device 2 becomes a fully loaded unit, transitioning from low-load operation to full-load operation; Device 3 becomes a high-frequency unit, transitioning from idle to low-load operation; and Device 1 becomes a limited unit, transitioning from full-load operation to shutdown.

[0067] In addition, in the above embodiment, preferably, after step S20, the load dynamic adjustment method further includes: S60: Unit self-maintenance.

[0068] Specifically, the system determines whether the dust accumulation index of each chiller exceeds the threshold. If so, the chiller is shut down and the bypass reverse dust removal air valve is activated. This allows the redundant air volume generated by the chillers running at low load to be pressurized through the Venturi tube and then, controlled by a pulse solenoid valve, to flow back to the cooling fins of the idle chiller every 30 seconds. This utilizes the redundant air volume to achieve zero-additional-energy cleaning.

[0069] In addition, in the above embodiment, preferably, it further includes: S70: Execute an abnormality handling strategy according to the abnormal operating condition.

[0070] Specifically, it includes steps S71 to S72: S71: Determine whether the multi-connected fresh air heat pump unit has an abnormal operating condition.

[0071] In this embodiment, the abnormal operating conditions include at least the simultaneous triggering of the healthy driving mode and the periodic rotation mode, the absence of healthy units for load compensation in the healthy driving mode, and insufficient healthy units for rotation in the periodic rotation mode.

[0072] S72: If an abnormal operating condition exists, execute an abnormality handling strategy according to the abnormal operating condition.

[0073] Specifically, when the healthy driving mode and the periodic rotation mode are triggered at the same time, the healthy driving mode is executed first, and the periodic rotation mode is executed after a preset delay time; When there is no healthy unit to compensate for the load in the healthy drive mode, the standby unit is started and the alarm program is activated; When there are insufficient healthy units to rotate in the periodic rotation mode, only the units in sub-healthy status will be rotated, and the units in fault warning status will remain unchanged.

[0074] It is understandable that in this embodiment, only the above three abnormal operating conditions are used as examples to illustrate the abnormality handling strategy. In other embodiments, if other abnormal operating conditions occur, corresponding abnormality handling strategies can also be pre-set to ensure stable operation of the system.

[0075] Second embodiment like Figure 4 As shown, based on the above-mentioned first embodiment, the second embodiment of the present invention provides a load dynamic adjustment system for a multi-connected fresh air heat pump unit, including a data acquisition unit 1, a health assessment unit 2, a decision unit 3, a mode selection unit 4 and an execution unit 5.

[0076] Specifically, in this embodiment, the data acquisition unit 1 includes at least a lubrication sensor, a vibration sensor, and a dust sensor, etc. Thus, the operation data of each unit is collected through multi-source sensors.

[0077] Health assessment unit 2 is connected to data acquisition unit 1 and is pre-configured with a health model. This model calculates the health score of each unit based on the unit's operating data. Once the unit's health score is calculated, the unit's corresponding unit status is output based on a pre-set threshold. This determines whether the unit is in a healthy, subhealthy, or fault warning state.

[0078] The decision unit 3 is connected to the health assessment unit 2 and is used to output a decision signal corresponding to each unit according to the unit status of each unit. It is understood that the logic for generating the decision signal refers to the above step S30 and will not be repeated here.

[0079] Mode selection unit 4 is connected to decision unit 3 to determine, for each unit, whether the decision signal satisfies the healthy drive mode using the preset mode trigger logic. It is understood that the mode selection process for each unit is similar to step S40 described above and will not be repeated here.

[0080] The execution unit 5 is connected to the mode selection unit 4 to control each unit to perform healthy driving operation or periodic rotation operation. It is understood that the mode execution process of each unit refers to the above step S50 and is not repeated here.

[0081] It can be understood that the composition and connection relationship of the above-mentioned module units are only a specific implementation method for realizing the load dynamic adjustment method in the above-mentioned first embodiment. In other embodiments, the composition and connection relationship of each module unit can be adaptively adjusted as needed, and no specific limitation is made here.

[0082] Third embodiment like Figure 5 As shown, based on the above-mentioned method for dynamic load adjustment of a multi-connected fresh air heat pump unit, a third embodiment of the present invention further provides a system for dynamic load adjustment of a multi-connected fresh air heat pump unit. The system includes one or more processors and a memory. The memory is coupled to the processor and is configured to store one or more programs. When the programs are executed by the processor, the processor implements the method for dynamic load adjustment of a multi-connected fresh air heat pump unit described in the above-mentioned embodiment.

[0083] The processor is used to control the overall operation of the dynamic load adjustment system to complete all or part of the steps of the dynamic load adjustment method for the multi-split fresh air heat pump unit. The processor can be a central processing unit (CPU), a graphics processing unit (GPU), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processing (DSP) chip, etc. The memory is used to store various types of data to support the operation of the dynamic load adjustment system. This data may include, for example, instructions for any application or method operating on the dynamic load adjustment system, as well as application-related data. The memory can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, etc.

[0084] In an exemplary embodiment, the load dynamic adjustment system can be implemented by a computer chip or entity, or by a product with certain functions, to implement the above-mentioned method for dynamic load adjustment of a multi-connected fresh air heat pump unit and achieve the same technical effect as the above-mentioned method. A typical embodiment is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, an in-vehicle human-computer interaction device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0085] In another exemplary embodiment, the present invention further provides a computer-readable storage medium comprising program instructions, which, when executed by a processor, implement the steps of the method for dynamic load adjustment of a multi-split fresh air heat pump system described in any of the aforementioned embodiments. For example, the computer-readable storage medium may be the aforementioned memory comprising the program instructions, which may be executed by a processor of a dynamic load adjustment system to implement the method for dynamic load adjustment of a multi-split fresh air heat pump system described above, thereby achieving the same technical effects as the aforementioned method.

[0086] It should be noted that the above embodiments are merely examples, and the technical solutions of the various embodiments may be combined and are all within the scope of protection of the present invention.

[0087] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature identified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0088] The above describes in detail the method and system for dynamic load adjustment of a multi-connected fresh air heat pump unit provided by the present invention. For those skilled in the art, any obvious modification thereof without departing from the essence of the present invention would constitute an infringement of the present invention's patent rights and would incur corresponding legal liability.

Claims

1. A method for dynamically adjusting the load of a multi-connected fresh air heat pump unit, characterized in that The steps include: Collect the operating data of each unit through multi-source sensors; Based on the operating data of each unit, the health score of each unit is calculated using a preset health model; Based on the health score of each unit, the unit status corresponding to each unit is output according to the preset threshold; wherein the unit status includes at least healthy state, sub-healthy state and fault warning state; Output the decision signal corresponding to each unit according to the unit status corresponding to each unit; For each of the units, determining whether the decision signal meets the conditions for activating the healthy driving mode through a preset mode trigger logic; If the conditions are met, the health drive mode is activated to cause the unit to perform health drive operations and temporarily freeze the recording time of the periodic rotation mode. The health drive operation includes: selecting healthy units to bear the main load, performing load reduction protection on units in sub-healthy states, and starting maintenance procedures for units in fault warning states. If not, determine whether the accumulated running time of the unit has reached the periodic rotation time; if reached, activate the periodic rotation mode so that the unit performs the periodic rotation operation and resets the unit status corresponding to the unit; if not reached, maintain the current status and wait for the next decision signal; wherein, the periodic rotation operation includes: controlling the unit to perform periodic rotation between full load operation, low load operation and shutdown.

2. The load dynamic adjustment method according to claim 1, wherein The health score is calculated by the following steps: ； Where F is the fatigue coefficient, ; L is the lubrication index, ; D is the dust accumulation index, .

3. The load dynamic adjustment method according to claim 1, wherein In the healthy driving mode, each unit performs healthy driving operations in the following manner: If the health score of the current unit is not less than the first threshold, the current load is maintained; If the health score of the current unit is less than the first threshold and not less than the second threshold, the load reduction protection is triggered to reduce the load to 30% of the rated power of the current unit; and other available units with a health score not less than the first threshold are found to compensate for the load according to the total load demand of the system. The power of each load-compensated healthy unit shall not exceed 95% of its rated power. If the health score of the current unit is less than the second threshold, it is marked as a fault warning state and the maintenance procedure is started.

4. The load dynamic adjustment method according to claim 2, wherein Also includes: Determine whether the dust accumulation index of each unit exceeds the dust accumulation threshold; If it exceeds, the unit will be shut down and the bypass reverse dust removal air valve channel will be started. The redundant air volume generated by the unit running at low load will be pressurized through the Venturi tube and then controlled by the pulse solenoid valve to reversely impact the heat sink of the shut down unit every 30 seconds.

5. The load dynamic adjustment method according to claim 1, wherein The determining whether the decision signal satisfies the healthy driving mode through the preset mode triggering logic specifically includes: Based on the decision signal, outputting a first determination result of whether the health score of the unit exceeds a threshold; outputting a second judgment result of whether the degradation rate of the unit exceeds a limit based on the decision signal; outputting a third judgment result of whether a key component of the unit is abnormal based on the decision signal; The final judgment result of whether the unit meets the healthy driving mode is jointly determined based on the first judgment result, the second judgment result and the third judgment result.

6. The load dynamic adjustment method according to claim 5, characterized in that Also includes: Determine whether the multi-connected fresh air heat pump unit has abnormal operating conditions; If an abnormal operating condition exists, an abnormality handling strategy is executed according to the abnormal operating condition.

7. The load dynamic adjustment method according to claim 6, characterized in that The executing of the abnormality handling strategy according to the abnormal operating condition at least includes: When the healthy driving mode and the periodic rotation mode are triggered at the same time, the healthy driving mode is executed first, and the periodic rotation mode is executed after a preset delay; When there is no healthy unit to compensate for the load in the healthy drive mode, the standby unit is started and the alarm program is activated; When there are insufficient healthy units to rotate in the periodic rotation mode, only the units in sub-healthy status will be rotated, and the units in fault warning status will remain unchanged.

8. A load dynamic adjustment system for a multi-connected fresh air heat pump unit, used to implement the load dynamic adjustment method according to any one of claims 1 to 7, characterized in that include: A data acquisition unit, used to collect operating data of each unit through multi-source sensors; a health assessment unit connected to the data acquisition unit and pre-set with a health model, for calculating a health score of each unit using the health model based on the operating data of the unit; and, based on the health score of each unit, outputting a unit status corresponding to each unit according to a preset threshold; A decision unit, connected to the health assessment unit, configured to output a decision signal corresponding to each unit according to the unit status corresponding to each unit; a mode selection unit connected to the decision unit to determine, for each of the units, whether the decision signal satisfies a healthy driving mode through a preset mode trigger logic; If the conditions are met, the healthy driving mode is activated to enable the unit to perform healthy driving operations and temporarily freeze the recording time of the periodic rotation mode; If not, determine whether the cumulative running time of the unit has reached the periodic rotation time; If it is reached, the periodic rotation mode is activated to make the unit perform periodic rotation operation and reset the unit status corresponding to the unit; If not, maintain the current state and wait for the next decision signal; An execution unit is connected to the mode selection unit to control each unit to execute the healthy driving operation or the periodic rotation operation.

9. A load dynamic adjustment system for a multi-connected fresh air heat pump unit, characterized in that The system comprises a processor and a memory, wherein the processor reads a computer program in the memory to implement the load dynamic adjustment method according to any one of claims 1 to 7.

Images