UPS system refrigeration optimization control method and device, UPS control equipment and storage medium

Abstract

The invention relates to the technical field of UPS systems, and provides a UPS system refrigeration optimization control method and device, UPS control equipment and a storage medium. The current load of the liquid cooling system can be accurately predicted based on the load state, the internal temperature and the external temperature of the UPS system obtained in real time and the operation states of the liquid cooling system and the air cooling system by using the pre-trained first neural network model, and the current load of the liquid cooling system can be accurately predicted by using the pre-trained second neural network model. The cooling parameters of the liquid cooling system are predicted based on the current load, the internal temperature and the preset refrigeration efficiency factor, and the cooling starting time of the liquid cooling system is determined based on the internal temperature and the actual operation duration of the UPS system, so that the refrigeration equipment is prevented from being started too early or too late, the refrigeration efficiency and the energy-saving effect are further improved, and the user experience is improved. And when the cooling starting time is up, the liquid cooling system is operated based on the predicted cooling parameters, and cooling of the UPS system is realized. The problems of low refrigeration efficiency and high energy consumption in the prior art are solved.

Description

Technical Field

[0001] The present application relates to the technical field of UPS systems, and in particular to a UPS system cooling optimization control method, device, UPS control equipment and storage medium. Background Art

[0002] As an important device for power supply protection in data centers, UPS system is responsible for providing stable power supply when the city power is interrupted to ensure the normal operation of the server group. However, the high-power UPS system will generate a lot of heat during operation. If the heat cannot be dissipated in time and effectively, it will not only reduce the performance of UPS, but also cause various failures and even bring potential safety hazards.

[0003] In the prior art, the cooling control of the UPS system usually turns on and off the cooling equipment based on a fixed temperature threshold or a fixed operating time, and cannot be flexibly adjusted according to the real-time load status of the UPS system, resulting in low cooling efficiency and high energy consumption, and cannot fully meet the heat dissipation requirements of the UPS system. Summary of the invention

[0004] In view of this, the present application provides a UPS system cooling optimization control method, apparatus, UPS control device and storage medium to optimize the cooling control of the UPS system.

[0005] A first aspect of the present application provides a UPS system cooling optimization control method, the method comprising: Obtain the load status, internal temperature, external temperature, and operating status of the liquid cooling system and air cooling system of the UPS system in real time; Using a pre-trained first neural network model, based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system, predict the current load of the liquid cooling system; Using a pre-trained second neural network model, based on the current load, the internal temperature and a preset refrigeration efficiency factor, a cooling parameter of the liquid cooling system is predicted; Determining a cooling start time of the liquid cooling system based on the internal temperature and the actual operating time of the UPS system; When the temperature reduction start time is reached, the liquid cooling system is operated based on the cooling parameters to achieve temperature reduction of the UPS system.

[0006] Optionally, determining the cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system includes: Calculating the temperature rise rate according to the actual operating time; Determining a temperature threshold range, and determining a temperature intermediate value according to the temperature threshold range; comparing the internal temperature with the temperature threshold range and the temperature intermediate value; When the internal temperature is within the temperature threshold range and is less than the middle temperature value, determining a first cooling start time according to a first ratio value of the middle temperature value and the temperature rise rate; When the internal temperature is within the temperature threshold range and greater than the middle temperature value, a second cooling start time is determined according to a second ratio value of the middle temperature value and the temperature rising rate.

[0007] Optionally, determining the temperature threshold range includes: Determine a maximum temperature threshold and a minimum temperature threshold according to the design requirements of the UPS system; generating a simulated operating environment according to the operating environment of the UPS system; Starting the UPS system in the simulated operating environment, and obtaining a first performance of the UPS system after running for a period of time at the highest temperature threshold, and obtaining a second performance of the UPS system after running for a period of time at the lowest temperature threshold; Adjusting the maximum temperature threshold according to the first performance obtained in real time to obtain a target maximum temperature threshold; Adjusting the minimum temperature threshold according to the second performance obtained in real time to obtain a target minimum temperature threshold; The temperature threshold range is obtained according to the target maximum temperature threshold and the target minimum temperature threshold.

[0008] Optionally, the first performance obtained in real time adjusts the maximum temperature threshold to obtain a target maximum temperature threshold, including: Determine whether the first performance obtained in real time is higher than a first performance threshold corresponding to the maximum temperature threshold; When the first performance obtained in real time is higher than the first performance threshold, increasing the maximum temperature threshold to obtain the target maximum temperature threshold; When the first performance obtained in real time is lower than the first performance threshold, the maximum temperature threshold is lowered to obtain the target maximum temperature threshold.

[0009] Optionally, the second performance obtained in real time adjusts the minimum temperature threshold to obtain a target minimum temperature threshold, including: Determine whether the second performance obtained in real time is higher than a second performance threshold corresponding to the minimum temperature threshold; When the second performance obtained in real time is higher than the second performance threshold, lowering the minimum temperature threshold to obtain the target minimum temperature threshold; When the second performance obtained in real time is lower than the second performance threshold, the minimum temperature threshold is increased to obtain the target minimum temperature threshold.

[0010] Optionally, the obtaining of the external temperature includes: Get the instantaneous external temperature at the current moment; Obtaining the average external temperature within a preset time period before the current moment; The external temperature is obtained by performing a weighted average calculation based on the instantaneous external temperature and the mean external temperature.

[0011] Optionally, the external temperature is calculated by the following formula: temperature[t]= α*temperature[t]+ (1 - α) * temperature[t-1]; α is the smoothing coefficient, 0<α<1, temperature[t] is the instantaneous external temperature at the current time t, and temperature[t-1] is the instantaneous external temperature at the time (t-1).

[0012] A second aspect of the present application provides a UPS system cooling optimization control device, the device comprising: A data acquisition module is used to obtain the load status, internal temperature, external temperature, and operating status of the liquid cooling system and the air cooling system of the UPS system in real time; A first prediction module is used to predict the current load of the liquid cooling system based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system by using a pre-trained first neural network model; a second prediction module, configured to predict a cooling parameter of the liquid cooling system based on the current load, the internal temperature and a preset refrigeration efficiency factor by using a pre-trained second neural network model; A time determination module, used to determine a cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system; The temperature reduction processing module is used to operate the liquid cooling system based on the cooling parameters when the temperature reduction start time is reached, so as to achieve temperature reduction of the UPS system.

[0013] A third aspect of the present application provides a UPS control device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the UPS system cooling optimization control method when executing the computer program.

[0014] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the UPS system cooling optimization control method.

[0015] The UPS system cooling optimization control method, device, UPS control device and storage medium provided in the embodiment of the present application can accurately predict the current load of the liquid cooling system based on the load state, internal temperature, external temperature and operating state of the liquid cooling system and air cooling system of the UPS system acquired in real time by using the pre-trained first neural network model, and predict the cooling parameters of the liquid cooling system based on the current load, internal temperature and preset cooling efficiency factor by using the pre-trained second neural network model, and determine the cooling start time of the liquid cooling system based on the internal temperature and the actual operating time of the UPS system to avoid starting the refrigeration equipment too early or too late, thereby further improving the cooling efficiency and energy saving effect, and when the cooling start time is reached, the liquid cooling system is operated based on the predicted cooling parameters to achieve cooling of the UPS system. The present application solves the problems of low cooling efficiency and high energy consumption in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an architecture diagram of a UPS system shown in an embodiment of the present application; Figure 2 is a flow chart of a UPS system cooling optimization control method shown in an embodiment of the present application; Figure 3 is a functional module diagram of a UPS system cooling optimization control device shown in an embodiment of the present application; Figure 4 It is a structural diagram of a UPS control device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0018] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0019] UPS (Uninterruptible Power Supply) system is an indispensable and important equipment in modern data centers, communication base stations and other key facilities. When the main power fails, the UPS system can provide stable power output for the load through its internal battery pack or other backup power supply.

[0020] See also Figure 1 As shown, the UPS system communicates with the liquid cooling system and the air cooling system respectively, and the cooling control of the UPS system is realized through the liquid cooling system and the air cooling system.

[0021] The liquid cooling system uses liquid (such as special coolant) as a heat transfer medium. The coolant is transported to the heat-generating components of the UPS system through a circulating pump. After absorbing the heat, the hot liquid is cooled through a radiator or heat exchanger, thereby achieving efficient cooling of the UPS system.

[0022] The air cooling system uses a fan or blower to blow cold air into the heat dissipation area of ​​the UPS system, exchange heat with the heat-generating components, and then exhaust the hot air to achieve the purpose of cooling.

[0023] The UPS system is connected to the liquid cooling system and the air cooling system through a communication interface (such as RS485, Ethernet, etc.) to achieve data exchange and transmission of control instructions. The UPS system monitors its own temperature, load status and other information in real time, and the liquid cooling system and the air cooling system implement cooling control of the UPS system based on the information, ensuring that the UPS system always provides stable power output and suitable working temperature in a complex and changing working environment.

[0024] The UPS system cooling optimization control method provided in the embodiment of the present invention is executed by a UPS control device, and correspondingly, the UPS system cooling optimization control device runs in the UPS control device.

[0025] Figure 2 The flowchart of the UPS system cooling optimization control method provided by the embodiment of the present invention is as follows. The UPS system cooling optimization control method specifically includes the following steps.

[0026] S21, real-time acquisition of the load status, internal temperature, external temperature, and operating status of the liquid cooling system and the air cooling system of the UPS system.

[0027] The UPS management system or monitoring software can be used to read the output power and current parameters of the power supply in real time, so as to calculate the current load status. The load status reflects the number and power of the equipment currently driven by the UPS power supply, and is an important basis for judging whether the UPS power supply is overloaded or underloaded.

[0028] The UPS power supply is equipped with a temperature sensor, which collects the internal temperature in real time. The internal temperature of the UPS system refers to the working environment temperature inside the power supply. Since the UPS power supply generates heat when working, the internal temperature is a key indicator for evaluating the heat dissipation performance and stability of the UPS power supply.

[0029] A temperature sensor is set in the environment where the UPS power supply is located, and the external temperature sensor is used to collect the external temperature in real time. The external temperature refers to the atmospheric temperature of the environment where the UPS power supply is located.

[0030] The liquid cooling system is used to adjust the internal temperature of the UPS power supply to ensure that it operates within a suitable temperature range. The operating status of the liquid cooling system may include: the flow rate of the coolant, etc. The operating status of the air cooling system may include: the fan speed, etc.

[0031] Real-time acquisition of the UPS system's load status, internal temperature, external temperature, and the operating status of the liquid cooling system and air cooling system can achieve comprehensive monitoring of the UPS system, timely discover potential problems, and ensure the stable operation of the UPS system. At the same time, based on the load status, internal temperature, external temperature, and the operating status of the liquid cooling system and air cooling system, the UPS system can be managed and maintained more finely, extending the service life of the equipment and improving the reliability of the system.

[0032] In an optional embodiment, the acquisition of the external temperature includes: Get the instantaneous external temperature at the current moment; Obtaining the average external temperature within a preset time period before the current moment; The external temperature is obtained by performing a weighted average calculation based on the instantaneous external temperature and the mean external temperature.

[0033] The instantaneous external temperature refers to the actual temperature value measured in the external environment at a specific moment, reflecting the real-time temperature conditions of the external environment at that moment.

[0034] The average external temperature refers to the average value of the external temperature within a preset time period before the current moment. The preset time period can be set according to the actual situation, such as the average temperature in the past hour, day, or week. The average external temperature represents the overall level of the external environment temperature over a period of time.

[0035] A first weight may be pre-assigned to the instantaneous external temperature, and a second weight may be pre-assigned to the mean external temperature. The external temperature may be obtained by performing a weighted average calculation of the instantaneous external temperature, the first weight, the mean external temperature and the second weight.

[0036] Since the instantaneous temperature reflects the real-time temperature condition at the current moment, it may fluctuate due to short-term environmental factors (such as wind, direct sunlight, etc.), while the mean temperature represents the average temperature over a period of time, which is more stable but not real-time enough. Combining the instantaneous external temperature and the mean external temperature, the mean external temperature can smooth out the abnormal values ​​or fluctuations that may exist in the instantaneous external temperature, making the final external temperature more stable, so as to more accurately reflect the actual temperature condition of the environment where the UPS system is located, reduce the errors that may be caused by a single temperature data, and obtain a real-time and stable external temperature value.

[0037] In addition, since temperature data at different time scales are taken into account, the weighted average temperature can better adapt to temperature changes under different environmental conditions and provide a more comprehensive and reliable basis for the cooling strategy of the UPS system.

[0038] In another optional embodiment, the external temperature is calculated by the following formula: temperature[t]= α*temperature[t]+ (1 - α) * temperature[t-1].

[0039] The smoothing coefficient α is a value between 0 and 1, which is used to control the weight distribution between the instantaneous temperature at the current moment and the instantaneous temperature at the previous moment. The larger the smoothing coefficient, the greater the influence of the temperature at the current moment on the final calculation result; conversely, the influence of the temperature at the previous moment is greater.

[0040] temperature[t] is the instantaneous external temperature at the current time t, and temperature[t-1] is the instantaneous external temperature at the previous time (t-1).

[0041] Set the value of the smoothing coefficient α and obtain the instantaneous external temperature temperature[0] at the initial moment. At each moment t, obtain the current instantaneous external temperature temperature[t] in real time through the temperature sensor. Take the weighted average of the instantaneous temperature at the current moment and the temperature at the previous moment to obtain the external temperature value at the current moment. Save the instantaneous external temperature temperature[t] at the current moment t so that it can be used in the calculation at the next moment t+1. Continuously update the calculation results of the external temperature in real time.

[0042] Since the external temperature is calculated based on the instantaneous temperature data obtained in real time, it can reflect the real-time changes in the external ambient temperature. By adjusting the smoothing coefficient, the noise and abnormal values ​​in the instantaneous temperature can be smoothed out, making the calculated external temperature more stable and reliable.

[0043] S22, using a pre-trained first neural network model, based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system, predicting the current load of the liquid cooling system.

[0044] The pre-trained first neural network model refers to a neural network model that has been trained with a large amount of data and has achieved a certain prediction accuracy. The first neural network model can perform complex nonlinear mapping based on the input feature data to output a prediction result.

[0045] The current load refers to the heat load that the liquid cooling system needs to handle under specific conditions, reflecting the working intensity and efficiency of the liquid cooling system.

[0046] The operation data and actual load of the UPS system under various load states, internal temperature, external temperature, and the operation state of the liquid cooling system and the air cooling system can be collected in advance. These data are preprocessed by cleaning and standardization so that they can be used for training the neural network model. The first neural network model is trained using the preprocessed data. By continuously adjusting the parameters and structure of the model, the model can capture the potential connection between the load state, internal temperature, external temperature, and the operation state of the liquid cooling system and the current load based on the input feature data (load state, internal temperature, external temperature, and the operation state of the liquid cooling system and the air cooling system), thereby accurately predicting the current load of the liquid cooling system.

[0047] Real-time acquisition of UPS system operation data and load forecasting can timely reflect changes in system status and provide a basis for timely adjustment of liquid cooling system strategies. The neural network model has strong generalization ability and can adapt to the operation of the UPS system under different environmental conditions, providing strong support for the stable operation of the UPS system. Using the pre-trained first neural network model for prediction can reduce dependence on manual experience, reduce the possibility of human error, and improve the stability and reliability of the prediction.

[0048] S23, using a pre-trained second neural network model, based on the current load, the internal temperature and the preset refrigeration efficiency factor, predicting the cooling parameters of the liquid cooling system. The pre-trained second neural network model is a neural network model that has been trained with a large amount of data and is used to predict the cooling parameters of the liquid cooling system. The second neural network model outputs the predicted cooling parameters based on the current load, the internal temperature and the preset refrigeration efficiency factor as input features.

[0049] The cooling efficiency factor is a preset parameter used to reflect the cooling efficiency of the liquid cooling system.

[0050] Cooling parameters: refers to the parameters that need to be set during the operation of the liquid cooling system, such as fan speed, coolant flow, cooling capacity, etc. These parameters directly determine the cooling effect and energy consumption of the liquid cooling system.

[0051] Real-time acquisition of UPS system operation data and prediction of cooling parameters can timely reflect changes in system status and provide a basis for timely adjustment of liquid cooling system parameters. By optimizing cooling parameters, the cooling efficiency of the liquid cooling system can be improved, unnecessary energy consumption can be reduced, and operating costs can be reduced. Reasonable cooling parameter settings can ensure that the internal temperature of the UPS system is stable within an appropriate range, avoiding equipment failure or performance degradation caused by excessive temperature, thereby improving the stability and reliability of the system.

[0052] S24, determining a cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system.

[0053] The internal temperature data of the UPS system reflects the current thermal status of the UPS system and is an important basis for determining the cooling start time of the liquid cooling system.

[0054] The actual operating time of the UPS system reflects the usage of the UPS system and the possible heat accumulation. Long-term operation may cause the internal temperature to rise, so the liquid cooling system needs to be turned on more frequently to cool down.

[0055] The real-time internal temperature is compared with the set temperature threshold range, and a comprehensive judgment is made based on the actual operating time of the UPS system to determine the cooling start time of the liquid cooling system. The cooling start time can be immediately turned on or within a period of time before the internal temperature reaches a higher threshold, to ensure that the internal temperature of the UPS system is effectively controlled.

[0056] The liquid cooling system is automatically or manually turned on according to the determined cooling start time. At the same time, the internal temperature and other related parameters of the UPS system are continuously monitored to ensure the effective operation of the liquid cooling system and the stable operation of the UPS system.

[0057] Based on the internal temperature and the actual operating time of the UPS system, the cooling start time of the liquid cooling system is dynamically determined to ensure that the UPS system always operates within the appropriate temperature range and improve its operating efficiency and stability.

[0058] In order to improve the accuracy and response speed of the cooling start time of the liquid cooling system, in an optional implementation manner, determining the cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system includes: Calculating the temperature rise rate according to the actual operating time; Determining a temperature threshold range, and determining a temperature intermediate value according to the temperature threshold range; comparing the internal temperature with the temperature threshold range and the temperature intermediate value; When the internal temperature is within the temperature threshold range and is less than the middle temperature value, determining a first cooling start time according to a first ratio value of the middle temperature value and the temperature rise rate; When the internal temperature is within the temperature threshold range and greater than the middle temperature value, a second cooling start time is determined according to a second ratio value of the middle temperature value and the temperature rising rate.

[0059] The temperature rise rate is calculated based on the internal temperature of the UPS system at the beginning, the internal temperature at the current moment, and the actual operating time. The temperature rise rate can reflect the accumulation speed of heat inside the UPS system and is an important basis for predicting future temperature changes and determining the cooling start time.

[0060] The temperature threshold range is set according to the design and operation requirements of the UPS system to ensure that the UPS system will not be damaged due to overheating. The temperature median is the average value of the temperature threshold range.

[0061] The real-time internal temperature is compared with the temperature threshold range and the temperature middle value to determine the current temperature status of the UPS system and whether the liquid cooling system needs to be turned on for cooling.

[0062] When the internal temperature is within the temperature threshold range and is less than the middle temperature value, it means that the internal temperature of the UPS system has risen but is still within the acceptable range and has not yet approached the upper threshold limit. At this time, the first cooling start time can be determined based on the first proportional value of the middle temperature value (for example, a certain percentage of the middle temperature value) and the temperature rise rate. Since the temperature is relatively low, the cooling start time can be relatively late to save energy and extend the service life of the liquid cooling system.

[0063] When the internal temperature is within the temperature threshold range and greater than the middle temperature value, it indicates that the internal temperature of the UPS system is already high and is close to or may exceed the upper threshold value. At this time, the liquid cooling system needs to be turned on as soon as possible to cool down the system to prevent overheating. Therefore, the second cooling start time can be determined based on the second proportional value of the middle temperature value (larger than the first proportional value) and the temperature rise rate. The second cooling start time is earlier than the first cooling start time to ensure that the UPS system can be cooled in time.

[0064] If the internal temperature approaches or exceeds the temperature threshold range, the liquid cooling system should be turned on immediately to protect the UPS system from damage. In an optional embodiment, determining the temperature threshold range includes: Determine a maximum temperature threshold and a minimum temperature threshold according to the design requirements of the UPS system; generating a simulated operating environment according to the operating environment of the UPS system; Starting the UPS system in the simulated operating environment, and obtaining a first performance of the UPS system after running for a period of time at the highest temperature threshold, and obtaining a second performance of the UPS system after running for a period of time at the lowest temperature threshold; Adjusting the maximum temperature threshold according to the first performance obtained in real time to obtain a target maximum temperature threshold; Adjusting the minimum temperature threshold according to the second performance obtained in real time to obtain a target minimum temperature threshold; The temperature threshold range is obtained according to the target maximum temperature threshold and the target minimum temperature threshold.

[0065] According to the design requirements of the UPS system, an initial maximum temperature threshold and an initial minimum temperature threshold are first determined. The initial maximum temperature threshold and the initial minimum temperature threshold are set based on factors such as the heat resistance performance, safety standards, and long-term operation stability of the UPS system.

[0066] Based on the actual operating environment of the UPS system, a simulated operating environment is constructed to reflect factors such as temperature, humidity, airflow, etc. in the real scene as much as possible, so that performance testing can be carried out without affecting the actual system operation.

[0067] In the simulated operation environment, the operating temperature of the UPS system is set to the initial maximum temperature threshold, and it is continuously operated for a period of time (such as several hours or days) to achieve performance testing under the maximum temperature threshold. During the performance test under the maximum temperature threshold, the performance test results of the UPS system are monitored and recorded in real time, including indicators such as output stability, efficiency, and failure rate. The performance test results under the maximum temperature threshold are used as the first performance performance. According to the first performance, the initial maximum temperature threshold is adjusted. If the first performance performance is good and the system operates stably, the maximum temperature threshold can be appropriately increased to increase the operating temperature range of the system; if the first performance degrades or an abnormal situation occurs, the maximum temperature threshold needs to be lowered to ensure the safety of the system.

[0068] In the simulated operating environment, the operating temperature of the UPS system is set to the initial minimum temperature threshold, and a performance test is performed for a period of time to achieve performance testing under the minimum temperature threshold. During the performance test under the minimum temperature threshold, the performance test results of the UPS system are monitored and recorded in real time, including output stability, efficiency, failure rate and other indicators. The performance test results under the minimum temperature threshold are used as the second performance performance. According to the second performance performance, the initial minimum temperature threshold is adjusted. If the system can start and run normally at low temperature and the performance is stable, the minimum temperature threshold can be appropriately lowered to expand the operating temperature range of the system; if it is difficult to start or the performance is reduced, the minimum temperature threshold needs to be increased to avoid problems caused by low temperature.

[0069] The final temperature threshold range is determined based on the adjusted target maximum temperature threshold and target minimum temperature threshold. The temperature threshold range will serve as an important basis for determining the cooling start time in the future, ensuring that the UPS system can operate safely and stably under different temperature conditions. In order to ensure the stable operation of the UPS system in a high temperature environment, the maximum temperature threshold can be adjusted more finely. In an optional embodiment, the first performance obtained in real time adjusts the maximum temperature threshold, and the target maximum temperature threshold includes: Determine whether the first performance obtained in real time is higher than a first performance threshold corresponding to the maximum temperature threshold; When the first performance obtained in real time is higher than the first performance threshold, increasing the maximum temperature threshold to obtain the target maximum temperature threshold; When the first performance obtained in real time is lower than the first performance threshold, the maximum temperature threshold is lowered to obtain the target maximum temperature threshold.

[0070] The first performance threshold is set based on the expected performance of the UPS system in a high temperature environment, and can include key indicators such as output stability, efficiency, and failure rate. These thresholds will serve as a benchmark for evaluating real-time performance.

[0071] In the simulated operation environment, the UPS system is controlled to operate at the maximum temperature threshold for a period of time, and a first performance of the UPS system is obtained in real time during the operation. The first performance obtained in real time is compared with the set first performance threshold to obtain a first comparison result. Based on the first comparison result, the maximum temperature threshold can be adjusted accordingly.

[0072] If the first performance obtained in real time is higher than the first performance threshold corresponding to the maximum temperature threshold, it indicates that the UPS system can still maintain excellent performance at high temperatures, and the maximum temperature threshold can be increased. By gradually increasing the maximum temperature threshold and re-performing the performance test, a new target maximum temperature threshold can be found that can both guarantee performance and expand the working range.

[0073] On the contrary, if the first performance obtained in real time is lower than the first performance threshold, it indicates that the performance of the UPS system may be affected under high temperature, and the maximum temperature threshold needs to be lowered. By lowering the maximum temperature threshold and retesting, it can be ensured that the UPS system will not fail or performance will be degraded due to overheating under high temperature environment.

[0074] The above optional implementation manner, by continuously simulating the actual performance under the maximum temperature threshold and dynamically adjusting the maximum temperature threshold according to the actual performance, can obtain a target maximum temperature threshold that can both ensure the stable performance of the UPS system and adapt to high temperature environments. By making detailed adjustments to the maximum temperature threshold, the upper limit of the operating temperature of the UPS system can be determined more accurately, thereby optimizing its operating efficiency and stability. It not only helps to extend the service life of the UPS system, but also improves the reliability and safety of the entire UPS system. In order to ensure the stable operation of the UPS system in a low temperature environment, the minimum temperature threshold can be adjusted more carefully. In an optional implementation manner, the second performance obtained in real time adjusts the minimum temperature threshold, and the target minimum temperature threshold includes: Determine whether the second performance obtained in real time is higher than a second performance threshold corresponding to the minimum temperature threshold; When the second performance obtained in real time is higher than the second performance threshold, lowering the minimum temperature threshold to obtain the target minimum temperature threshold; When the second performance obtained in real time is lower than the second performance threshold, the minimum temperature threshold is increased to obtain the target minimum temperature threshold.

[0075] The second performance threshold is set based on the expected performance of the UPS system in a low temperature environment, and can include key indicators such as output stability, efficiency, and failure rate. These thresholds will serve as a benchmark for evaluating real-time performance.

[0076] In the simulated operation environment, the UPS system is controlled to operate at the minimum temperature threshold for a period of time, and the second performance of the UPS system is obtained in real time during the operation. The second performance obtained in real time is compared with the set second performance threshold to obtain a second comparison result. Based on the second comparison result, the minimum temperature threshold can be adjusted accordingly.

[0077] If the second performance obtained in real time is higher than the second performance threshold corresponding to the minimum temperature threshold, it indicates that the UPS system operates well under the current minimum temperature threshold and has excellent performance. In this case, the minimum temperature threshold can be lowered to expand the operating range of the UPS system in a low temperature environment. By gradually lowering the minimum temperature threshold and re-performing the performance test, a new target minimum temperature threshold that can both guarantee performance and expand the operating range can be found.

[0078] On the contrary, if the second performance value obtained in real time is lower than the second performance threshold value corresponding to the minimum temperature threshold value, it indicates that the UPS system does not operate well under the current minimum temperature threshold value and the performance may be affected. In this case, the minimum temperature threshold value needs to be increased to avoid the UPS system operating at too low a temperature and causing performance degradation or failure. Similarly, a new target minimum temperature threshold value that is both safe and stable can be found by gradually increasing the minimum temperature threshold value and re-performing the performance test.

[0079] The above optional implementation method, by continuously simulating the actual performance under the minimum temperature threshold and dynamically adjusting the minimum temperature threshold according to the actual performance, can obtain a target minimum temperature threshold that can both ensure the stability of the UPS system performance and adapt to the low temperature environment, which helps to improve the stability and reliability of the UPS system in the low temperature environment, and also helps to optimize the operating efficiency and life of the entire system. Through the above adjustment process.

[0080] S25, when the cooling start time is reached, operating the liquid cooling system based on the cooling parameters to achieve cooling of the UPS system.

[0081] When the cooling start time determined by factors such as the internal temperature, the actual operating time of the UPS system and the temperature threshold range arrives, the UPS system will trigger the cooling operation and start the liquid cooling system based on the predicted cooling parameters, including but not limited to adjusting the fan speed, controlling the flow of coolant, and adjusting the power output of the liquid cooling system.

[0082] During the operation of the liquid cooling system, the UPS system continuously monitors the internal temperature to ensure that the liquid cooling system can dynamically adjust according to real-time temperature changes to achieve the best cooling effect. If the internal temperature is still too high or the cooling effect is not good, you can adjust the cooling parameters or take other measures, such as increasing the operating power of the liquid cooling system or increasing the fan speed.

[0083] When the internal temperature of the UPS system drops below the safe range, for example, below the middle temperature value, the liquid cooling system should be shut down in time to prevent damage to the UPS system or energy waste caused by overcooling.

[0084] In an optional implementation, the UPS system can also be fault-detected in real time, and an alarm can be promptly issued when a fault or abnormality occurs in the liquid cooling system.

[0085] The above optional implementation mode, operating the liquid cooling system based on the cooling parameters, can ensure that the liquid cooling system can meet the cooling requirements of the UPS system during operation without wasting energy or affecting system stability due to overcooling.

[0086] The UPS system cooling optimization control method provided by the embodiment of the present application can obtain the load state, internal temperature, external temperature and the operating state of the liquid cooling system and the air cooling system of the UPS system in real time, so as to fully understand the real-time working state and environmental conditions of the UPS system. By using the pre-trained first neural network model, based on the real-time acquired load state, internal temperature, external temperature and the operating state of the liquid cooling system and the air cooling system, the current load of the liquid cooling system can be accurately predicted. Further, using the pre-trained second neural network model, based on the current load, internal temperature and the preset cooling efficiency factor, the cooling parameters of the liquid cooling system are predicted. The determination of the cooling parameters not only takes into account the real-time load and temperature of the UPS system, but also takes into account the cooling efficiency factor, so that energy consumption can be optimized while meeting the heat dissipation requirements. The cooling parameter prediction method that comprehensively considers multiple factors is helpful to improve the cooling efficiency and reduce energy consumption. Finally, based on the internal temperature and the actual operating time of the UPS system, the cooling start time of the liquid cooling system is determined to avoid starting the refrigeration equipment too early or too late, thereby further improving the cooling efficiency and energy saving effect. When the cooling start time is reached, the liquid cooling system is operated based on the predicted cooling parameters to achieve cooling of the UPS system. Compared with the traditional refrigeration control method based on fixed thresholds or fixed times, the refrigeration control method of the present application based on real-time data and prediction results can ensure that the UPS system can obtain timely and effective heat dissipation under various load states and environmental conditions, ensuring its stable and efficient operation, and solving the problems of low refrigeration efficiency and high energy consumption in the prior art.

[0087] Figure 3 It is a structural diagram of a UPS system cooling optimization control device provided in Embodiment 2 of the present invention.

[0088] In some embodiments, the UPS system cooling optimization control device 30 may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the UPS system cooling optimization control device 30 may be stored in the memory of the UPS control device and executed by at least one processor to perform (see Figure 2 Description) UPS system cooling optimization control function.

[0089] In this embodiment, the UPS system cooling optimization control device 30 can be divided into multiple functional modules according to the functions it performs. The functional modules may include: a data acquisition module 301, a first prediction module 302, a second prediction module 303, a time determination module 304 and a temperature reduction processing module 305. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0090] The data acquisition module 301 is used to acquire the load status, internal temperature, external temperature, and operating status of the liquid cooling system and the air cooling system of the UPS system in real time; The first prediction module 302 is used to predict the current load of the liquid cooling system based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system by using a pre-trained first neural network model; The second prediction module 303 is used to predict the cooling parameters of the liquid cooling system based on the current load, the internal temperature and a preset refrigeration efficiency factor by using a pre-trained second neural network model; The time determination module 304 is used to determine the cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system; The cooling processing module 305 is used to operate the liquid cooling system based on the cooling parameters when the cooling start time is reached, so as to achieve cooling of the UPS system. It should be understood that the various variations and specific embodiments of the UPS system cooling optimization control method provided in the above embodiments are also applicable to the UPS system cooling optimization control device in this embodiment. Through the detailed description of the above UPS system cooling optimization control method, those skilled in the art can clearly know the implementation process of the UPS system cooling optimization control device in this embodiment. For the sake of brevity of the specification, it will not be described in detail here.

[0091] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, all or part of the steps of the UPS system cooling optimization control method are implemented.

[0092] The UPS system cooling optimization control method comprises: obtaining the load status, internal temperature, external temperature and the operating status of the liquid cooling system and the air cooling system of the UPS system in real time; Using a pre-trained first neural network model, based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system, predict the current load of the liquid cooling system; Using a pre-trained second neural network model, based on the current load, the internal temperature and a preset refrigeration efficiency factor, a cooling parameter of the liquid cooling system is predicted; Determining a cooling start time of the liquid cooling system based on the internal temperature and the actual operating time of the UPS system; When the temperature reduction start time is reached, the liquid cooling system is operated based on the cooling parameters to achieve temperature reduction of the UPS system.

[0093] When the computer program is executed by the processor, determining the cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system specifically includes: Calculating the temperature rise rate according to the actual operating time; Determining a temperature threshold range, and determining a temperature intermediate value according to the temperature threshold range; comparing the internal temperature with the temperature threshold range and the temperature intermediate value; When the internal temperature is within the temperature threshold range and is less than the middle temperature value, determining a first cooling start time according to a first ratio value of the middle temperature value and the temperature rise rate; When the internal temperature is within the temperature threshold range and greater than the middle temperature value, a second cooling start time is determined according to a second ratio value of the middle temperature value and the temperature rising rate.

[0094] When the computer program is executed by the processor, the determination of the temperature threshold range is implemented, specifically including: Determine a maximum temperature threshold and a minimum temperature threshold according to the design requirements of the UPS system; generating a simulated operating environment according to the operating environment of the UPS system; Starting the UPS system in the simulated operating environment, and obtaining a first performance of the UPS system after running for a period of time at the highest temperature threshold, and obtaining a second performance of the UPS system after running for a period of time at the lowest temperature threshold; Adjusting the maximum temperature threshold according to the first performance obtained in real time to obtain a target maximum temperature threshold; Adjusting the minimum temperature threshold according to the second performance obtained in real time to obtain a target minimum temperature threshold; The temperature threshold range is obtained according to the target maximum temperature threshold and the target minimum temperature threshold.

[0095] When the computer program is executed by the processor, the first performance obtained in real time is implemented to adjust the maximum temperature threshold to obtain a target maximum temperature threshold, specifically including: Determine whether the first performance obtained in real time is higher than a first performance threshold corresponding to the maximum temperature threshold; When the first performance obtained in real time is higher than the first performance threshold, increasing the maximum temperature threshold to obtain the target maximum temperature threshold; When the first performance obtained in real time is lower than the first performance threshold, the maximum temperature threshold is lowered to obtain the target maximum temperature threshold.

[0096] When the computer program is executed by the processor, the second performance obtained in real time is implemented to adjust the minimum temperature threshold to obtain a target minimum temperature threshold, specifically including: Determine whether the second performance obtained in real time is higher than a second performance threshold corresponding to the minimum temperature threshold; When the second performance obtained in real time is higher than the second performance threshold, lowering the minimum temperature threshold to obtain the target minimum temperature threshold; When the second performance obtained in real time is lower than the second performance threshold, the minimum temperature threshold is increased to obtain the target minimum temperature threshold.

[0097] When the computer program is executed by the processor, the acquisition of the external temperature is realized, specifically including: Get the instantaneous external temperature at the current moment; Obtaining the average external temperature within a preset time period before the current moment; The external temperature is obtained by performing a weighted average calculation based on the instantaneous external temperature and the mean external temperature.

[0098] When the computer program is executed by the processor, the acquisition of the external temperature is realized, specifically including: Calculated by the following formula: temperature[t]= α*temperature[t]+ (1 - α) * temperature[t-1]; α is the smoothing coefficient, 0<α<1, temperature[t] is the instantaneous external temperature at the current time t, and temperature[t-1] is the instantaneous external temperature at the time (t-1).

[0099] See also Figure 4FIG. 4 is a schematic diagram of the structure of a UPS control device provided in Embodiment 3 of the present application. In a preferred embodiment of the present application, the UPS control device 4 includes a memory 4141 , at least one processor 42 and at least one communication bus 43 .

[0100] Those skilled in the art should understand that Figure 4 The structure of the UPS control device shown does not constitute a limitation of the embodiments of the present application, and can be either a bus structure or a star structure. The UPS control device 4 can also include more or less other hardware or software than shown in the figure, or a different component arrangement.

[0101] In some embodiments, the UPS control device 4 is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits, programmable gate arrays, digital processors, and embedded devices. The UPS control device 4 may also include client devices, which include but are not limited to any electronic product that can interact with a client through a keyboard, mouse, remote control, touchpad, or voice control device, such as a personal computer, tablet computer, smart phone, digital camera, etc.

[0102] It should be noted that the UPS control device 4 is only an example, and other existing or future electronic products that are suitable for the present application should also be included in the protection scope of the present application and included here by reference.

[0103] In some embodiments, the memory 41 stores a computer program, and when the computer program is executed by the at least one processor 42, all or part of the steps in the UPS system cooling optimization control method are implemented. The memory 41 includes a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data. Further, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, and the like.

[0104] In some embodiments, the at least one processor 42 is the control core (Control Unit) of the UPS control device 4, and uses various interfaces and lines to connect various components of the entire UPS control device 4, and executes various functions and processes data of the UPS control device 4 by running or executing programs or modules stored in the memory 41, and calling data stored in the memory 41. For example, when the at least one processor 42 executes the computer program stored in the memory, it implements all or part of the steps of the UPS system cooling optimization control method described in the embodiment of the present application; or implements all or part of the functions of the UPS system cooling optimization control device. The at least one processor 42 can be composed of an integrated circuit, for example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits with the same function or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips.

[0105] In some embodiments, the at least one communication bus 43 is configured to realize connection and communication between the memory 41 and the at least one processor 42, etc. Although not shown, the UPS control device 4 may also include a power supply (such as a battery) for powering each component. Preferably, the power supply may be logically connected to the at least one processor 42 through a power management device, so as to realize functions such as management of charging, discharging, and power consumption management through the power management device. The power supply may also include any components such as one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The UPS control device 4 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which are not described in detail here.

[0106] The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a UPS control device (which can be a personal computer, a UPS control device, or a network device, etc.) or a processor to execute part of the method described in each embodiment of the present application.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0108] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Claims

1. A UPS system cooling optimization control method, characterized in that: The method comprises: Obtain the load status, internal temperature, external temperature, and operating status of the liquid cooling system and air cooling system of the UPS system in real time; Using a pre-trained first neural network model, based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system, predict the current load of the liquid cooling system; Using a pre-trained second neural network model, based on the current load, the internal temperature and a preset refrigeration efficiency factor, a cooling parameter of the liquid cooling system is predicted; Determining a cooling start time of the liquid cooling system based on the internal temperature and the actual operating time of the UPS system; When the temperature reduction start time is reached, the liquid cooling system is operated based on the cooling parameters to achieve temperature reduction of the UPS system.

2. The UPS system cooling optimization control method according to claim 1, characterized in that: The step of determining the cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system comprises: Calculating the temperature rise rate according to the actual operating time; Determining a temperature threshold range, and determining a temperature intermediate value according to the temperature threshold range; comparing the internal temperature with the temperature threshold range and the temperature intermediate value; When the internal temperature is within the temperature threshold range and is less than the middle temperature value, determining a first cooling start time according to a first ratio value of the middle temperature value and the temperature rise rate; When the internal temperature is within the temperature threshold range and greater than the middle temperature value, a second cooling start time is determined according to a second ratio value of the middle temperature value and the temperature rising rate.

3. The UPS system cooling optimization control method according to claim 2, characterized in that: Determining the temperature threshold range includes: Determine a maximum temperature threshold and a minimum temperature threshold according to the design requirements of the UPS system; generating a simulated operating environment according to the operating environment of the UPS system; Starting the UPS system in the simulated operating environment, and obtaining a first performance of the UPS system after running for a period of time at the highest temperature threshold, and obtaining a second performance of the UPS system after running for a period of time at the lowest temperature threshold; The maximum temperature threshold is adjusted according to the first performance obtained in real time to obtain a target maximum temperature threshold; Adjusting the minimum temperature threshold according to the second performance obtained in real time to obtain a target minimum temperature threshold; The temperature threshold range is obtained according to the target maximum temperature threshold and the target minimum temperature threshold.

4. The UPS system cooling optimization control method according to claim 3, characterized in that: The first performance obtained in real time adjusts the maximum temperature threshold to obtain a target maximum temperature threshold, which includes: Determine whether the first performance obtained in real time is higher than a first performance threshold corresponding to the maximum temperature threshold; When the first performance obtained in real time is higher than the first performance threshold, increasing the maximum temperature threshold to obtain the target maximum temperature threshold; When the first performance obtained in real time is lower than the first performance threshold, the maximum temperature threshold is lowered to obtain the target maximum temperature threshold.

5. The UPS system cooling optimization control method according to claim 3, characterized in that: The second performance obtained in real time adjusts the minimum temperature threshold to obtain a target minimum temperature threshold, including: Determine whether the second performance obtained in real time is higher than a second performance threshold corresponding to the minimum temperature threshold; When the second performance obtained in real time is higher than the second performance threshold, lowering the minimum temperature threshold to obtain the target minimum temperature threshold; When the second performance obtained in real time is lower than the second performance threshold, the minimum temperature threshold is increased to obtain the target minimum temperature threshold.

6. The UPS system cooling optimization control method according to any one of claims 1 to 5, characterized in that: The acquisition of the external temperature includes: Get the instantaneous external temperature at the current moment; Obtaining the average external temperature within a preset time period before the current moment; The external temperature is obtained by performing a weighted average calculation based on the instantaneous external temperature and the mean external temperature.

7. The UPS system cooling optimization control method according to any one of claims 1 to 5, characterized in that: The external temperature is calculated by the following formula: temperature[t]= α*temperature[t] + (1 - α) * temperature[t-1]; α is the smoothing coefficient, 0 < α < 1, temperature[t] is the instantaneous external temperature at the current time t, and temperature[t-1] is the instantaneous external temperature at the time (t-1).

8. A UPS system cooling optimization control device, characterized in that: The device comprises: A data acquisition module is used to obtain the load status, internal temperature, external temperature, and operating status of the liquid cooling system and the air cooling system of the UPS system in real time; A first prediction module is used to predict the current load of the liquid cooling system based on the load state, the internal temperature, the external temperature, and the operating states of the liquid cooling system and the air cooling system by using a pre-trained first neural network model; a second prediction module, configured to predict a cooling parameter of the liquid cooling system based on the current load, the internal temperature and a preset refrigeration efficiency factor by using a pre-trained second neural network model; A time determination module, used to determine a cooling start time of the liquid cooling system based on the internal temperature and the actual operation time of the UPS system; The temperature reduction processing module is used to operate the liquid cooling system based on the cooling parameters when the temperature reduction start time is reached, so as to achieve temperature reduction of the UPS system.

9. A UPS control device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the UPS system cooling optimization control method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the UPS system cooling optimization control method according to any one of claims 1 to 7 are implemented.

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