UPS power supply self-diagnostic system based on artificial intelligence

Abstract

This invention relates to the field of intelligent diagnostic technology for UPS power supplies, and more particularly to an artificial intelligence-based UPS power supply self-diagnostic system. The system utilizes a battery pack that can be charged by a rectifier to store electrical energy. A monitoring module monitors the output voltage of the battery pack and the temperature and humidity changes in the battery pack area. An AI analysis module stores historical data monitored by the monitor. A control module divides the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods and monitors the operating status to determine the power supply output characterization parameters. This predicts whether the power supply effect of the battery pack meets predetermined standards and determines whether to activate the energy compensation device. Considering the impact of differences in the temperature and humidity resistance properties of individual cells in the battery pack on power supply efficiency during the operation of the UPS power supply self-diagnostic system, the system adaptively intervenes with the energy compensation device, thereby ensuring the power supply efficiency and battery stability of the UPS power supply self-diagnostic system.

Description

Technical Field

[0001] This invention relates to the field of intelligent diagnostics for UPS power supplies, and more particularly to a UPS power supply self-diagnostic system based on artificial intelligence. Background Technology

[0002] UPS power supplies are indispensable power backup devices for modern electronic equipment, widely used in scenarios with high power reliability requirements. In medical industry UPS power supplies, the battery pack is the key component for storing electrical energy. When the voltage difference between individual cells exceeds 50mV, the capacity of the battery pack will plummet. This means that after a mains power outage, the UPS power supply can only provide power to medical equipment for a significantly shorter period, potentially failing to meet the continuous operation needs of medical equipment in emergency situations, thus posing a serious threat to patient treatment and the normal conduct of medical work.

[0003] Chinese Patent Publication No. CN218040842U discloses a UPS power supply for medical devices, including a device body. First heat dissipation grooves are symmetrically formed on the center of the left and right sides of the device body. Dustproof nets are symmetrically fixed to one side of the two first heat dissipation grooves. A sound insulation board is fixedly connected to the inner wall of the device body. A base is fixedly connected to the center of the bottom of the inner cavity of the sound insulation board. A damping spring is fixedly connected to the top of the base. A support plate is fixedly connected to the top of the damping spring. A movable groove is formed in the center of the top of the support plate. A bidirectional lead screw is installed in the inner cavity of the movable groove. A clamping plate is provided at the top of the bidirectional lead screw. A second heat dissipation groove is formed in the inner cavity of the clamping plate. When in use, the device of this invention can reduce the impact of noise on patients and has a good protective structure, preventing damage to its internal components due to external factors such as handling.

[0004] Chinese Patent Publication No. CN106230102A discloses a UPS switching power supply, including a static switch controller, a power supply device, an intelligent battery pack, an inverter, a transformer, a positive filter AC voltage, and a central controller. The output terminal of the static switch controller is connected to the power supply device. The battery pack, inverter, and transformer are connected together. The inverter is connected to the central controller, and the central controller is connected to the static switch controller. The battery pack includes a step-down voltage regulator unit and a charging unit connected to the output of the step-down voltage regulator unit. The UPS switching power supply provided by this invention meets the power supply needs of communication equipment for AC and DC power, as well as for scenarios where proximity is not feasible.

[0005] However, the following problems still exist in the existing technology:

[0006] The existing technology does not take into account the problem that the individual temperature and humidity resistance properties of the backup UPS battery packs for medical devices vary due to the influence of environmental temperature and humidity factors at different historical periods, which in turn affects the power supply performance of the backup UPS. Summary of the Invention

[0007] To address the aforementioned issues, this invention provides an AI-based UPS power supply self-diagnosis system. This system overcomes the problem in existing technologies that fail to consider the differences in temperature and humidity tolerance of individual backup UPS battery packs due to environmental temperature and humidity factors at different historical periods, which in turn affects the power supply performance of the backup UPS.

[0008] To achieve the above objectives, this invention provides an artificial intelligence-based UPS power supply self-diagnosis system, comprising a static switch, rectifier, inverter, control circuit, charger, and filter, characterized in that it further comprises:

[0009] A battery pack includes a battery bank for charging via a rectifier to store electrical energy, a plurality of individual cells connected to the battery bank for storing electrical energy, and an energy compensation device for changing the charge of each individual cell in the battery bank.

[0010] The monitoring module includes several voltage sensors for monitoring the output voltage of each individual cell in the battery pack, several temperature and humidity sensors for monitoring the temperature and humidity of the battery pack area, and an energy monitoring unit for acquiring the output energy parameters of the battery pack.

[0011] The AI ​​analysis module is connected to the monitoring module and is used to store historical data monitored by the monitoring module. It is used to identify the battery management impact cycle based on the output voltage difference of each individual battery in the battery pack in different historical periods, and to analyze the power supply impact tendency characterization value of the battery pack in different battery management impact cycles based on the changes in the power parameters.

[0012] The control module, connected to the battery assembly, monitoring module, and AI analysis module, is used to classify the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, and to monitor the battery pack operation status based on the classification results, including...

[0013] The power output characterization parameters are determined based on the change in the output power of the battery pack within a predetermined period and the change ratio of temperature and humidity in the battery pack area. Based on the power output characterization parameters, it is predicted whether the power supply effect of the battery pack meets the predetermined standard. Based on the temperature difference in the current battery pack area, it is determined whether the power compensation device should be activated.

[0014] Alternatively, the power compensation device may not be activated.

[0015] Furthermore, the AI ​​analysis module is used to identify battery management impact periods based on the output voltage differences of individual cells in the battery pack over different historical periods.

[0016] Used to calculate the variance of the output voltage difference of each individual cell in the battery pack during each historical period;

[0017] If the variance of a single historical period is greater than a predetermined variance threshold, then the historical period is determined to be a battery management impact period.

[0018] Furthermore, the AI ​​analysis module is used to analyze the power supply impact tendency characterization value of the battery pack corresponding to different battery management impact cycles based on the changes in the electrical energy parameters, including,

[0019] The ratio used to calculate the change in the storage power of the battery pack to a predetermined rate of change threshold is determined as the first data parameter feature;

[0020] The ratio of the average difference between the output voltages of each individual cell to a predetermined difference threshold is determined as the second data parameter feature.

[0021] The sum of the first data parameter feature and the second data parameter feature is used to determine the power supply influence tendency characterization value.

[0022] Furthermore, the control module is used to divide the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, including,

[0023] If the power supply impact tendency characterization value is greater than or equal to the preset impact tendency characterization value, it is determined to be the first impact cycle;

[0024] If the power supply impact tendency characterization value is less than the preset impact tendency characterization value, it is determined to be the second impact cycle.

[0025] Furthermore, the control module monitors the battery pack's operating status based on the partitioning results, including:

[0026] If the division result is the first influence period, then the power output characterization parameters are determined based on the change in the output power of the battery pack and the change ratio of the temperature in the battery pack area within the predetermined period to predict whether the power supply effect of the battery pack meets the predetermined standard, and the power compensation device is activated based on the temperature difference in the current battery pack area.

[0027] If the division result is the second influence period, the power compensation device will not be activated.

[0028] Further, the control module is characterized in that it determines power output characterization parameters based on the change in the output electrical energy of the battery pack within a predetermined period and the proportion of change in temperature and humidity in the battery pack area, including:

[0029] The ratio of the change in the output voltage of the battery pack to a predetermined output voltage change threshold is determined as the first power supply output parameter characteristic.

[0030] The ratio of the change in temperature in the battery pack area to a predetermined temperature change threshold is used to determine the second power supply output parameter characteristic.

[0031] The ratio of the change in humidity in the battery pack area to a predetermined humidity change threshold is used to determine the third power supply output parameter characteristic.

[0032] The sum of the first power supply output parameter feature, the second power supply output parameter feature, and the third power supply output parameter is used to determine the power supply output characterization parameter.

[0033] Furthermore, the control module is used to predict whether the power supply performance of the battery pack meets a predetermined standard based on the power supply output characterization parameters, including:

[0034] If the power output characteristic parameter is less than or equal to the preset power output characteristic parameter, then the predicted power supply effect of the battery pack meets the predetermined standard.

[0035] If the power output characteristic parameter is greater than the preset power output characteristic parameter, the predicted power supply effect of the battery pack does not meet the predetermined standard.

[0036] Furthermore, the control module is used to determine whether to activate the power compensation device based on the temperature difference of the current battery pack area when the predicted power supply effect of the battery pack does not meet the predetermined standard.

[0037] Furthermore, the control module is used to determine whether to activate the power compensation device based on the average temperature difference of individual cells in the current battery pack area, including:

[0038] If the average current temperature difference is less than or equal to the predetermined temperature difference threshold, then the power compensation device is activated.

[0039] If the average current temperature difference is greater than the predetermined temperature difference threshold, then the power compensation device will not be activated.

[0040] Furthermore, it also includes a cooling compensation device for reducing the temperature of the battery pack area. When the control module determines that the power compensation device is not to be used, the cooling compensation device is activated. The cooling effect of the cooling compensation device is proportional to the average temperature difference of the individual cells in the current battery pack area.

[0041] Compared with existing technologies, this invention provides an AI-based UPS power supply self-diagnostic system, including a static switch, rectifier, inverter, control circuit, charger, and filter. It also includes a battery assembly, monitoring module, AI analysis module, and control module. This enables the UPS power supply to switch to battery power mode in a very short time. The battery assembly can be charged through the rectifier to store electrical energy. The battery pack consists of several individual cells. The monitoring module monitors the output voltage of each individual cell, the temperature and humidity changes in the battery pack area, and the output electrical parameters of the battery pack. The AI ​​analysis module stores historical data monitored by the monitor. Furthermore, the control module divides the influence period based on the power supply influence tendency characterization value corresponding to different battery management influence periods, monitors the battery pack operation status, determines the power supply output characterization parameters, and predicts whether the power supply effect of the battery pack meets the predetermined standard, thus determining whether to activate the power compensation device. Considering the impact of the differences in temperature and humidity resistance of each individual cell in the battery pack on power supply efficiency during the operation of the UPS power supply self-diagnostic system, the system adaptively intervenes with the power compensation device, thereby ensuring the power supply efficiency and battery stability of the UPS power supply self-diagnostic system.

[0042] In particular, this invention can accurately obtain the pattern of the battery pack being affected by temperature and humidity in different time periods by identifying the battery management impact cycle. By calculating the variance of the output voltage difference of each individual cell in the battery pack in each historical period, the battery management impact cycle of the historical period can be accurately determined. Moreover, by analyzing the changes in power parameters, the power supply tendency of the battery pack in different battery management impact cycles can be accurately analyzed, thereby improving the efficiency and stability of the battery pack.

[0043] In particular, the present invention can determine the power supply output characterization parameters by measuring the change in the output electrical energy of the battery pack and the ratio of temperature and humidity changes in the battery pack area, thereby improving the accuracy of the power supply effect of the battery pack. The power supply output characterization parameters can be used to predict the power supply effect of the battery pack and to predict in advance whether the power supply performance of the battery pack will decline. This reduces the occurrence of power supply efficiency decline caused by temperature and humidity, and improves the stability and power supply efficiency of the battery pack.

[0044] In particular, the present invention can divide the first and second influence periods by the power supply influence tendency characterization values ​​corresponding to different influence periods, thereby improving the utilization efficiency of the battery pack. Moreover, by determining whether the battery pack is equipped with the power compensation device, the energy utilization efficiency is further improved. Attached Figure Description

[0045] Figure 1 This is a structural block diagram of an AI-based UPS power supply self-diagnosis system according to an embodiment of the present invention.

[0046] Figure 2 This is a logic diagram for identifying the battery management impact cycle in an embodiment of the present invention;

[0047] Figure 3 This is a logic decision diagram for analyzing the power supply influence tendency characterization value of the battery pack under different battery management influence cycles in an embodiment of the present invention.

[0048] Figure 4 This is a logic diagram for dividing the influence cycle based on the power supply influence tendency characterization value in an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0050] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0051] It should be noted that in the description of this invention, the term "connection" should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral connection; it can refer to a mechanical connection or an electrical connection; it can refer to a direct connection or an indirect connection through an intermediate medium; it can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0052] Please see Figure 1 The diagram shown is a structural block diagram of an AI-based UPS power supply self-diagnostic system according to an embodiment of the present invention. The present invention provides an AI-based UPS power supply self-diagnostic system, including a static switch, rectifier, inverter, control circuit, charger, filter, and further comprising:

[0053] A battery pack includes a battery bank for charging via a rectifier to store electrical energy, a plurality of individual cells connected to the battery bank for storing electrical energy, and an energy compensation device for changing the charge of each individual cell in the battery bank.

[0054] The monitoring module includes several voltage sensors for monitoring the output voltage of different individual cells in the battery pack, several temperature sensors for monitoring the temperature of the battery pack area, and an energy monitoring unit for acquiring the output energy parameters of the battery pack.

[0055] The AI ​​analysis module is connected to the monitoring module and is used to store historical data monitored by the monitoring module. It is used to identify the battery management impact cycle based on the output voltage difference of each individual battery in the battery pack in different historical periods, and to analyze the power supply impact tendency characterization value of the battery pack in different battery management impact cycles based on the changes in the power parameters.

[0056] The control module, connected to the battery assembly, monitoring module, and AI analysis module, is used to classify the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, and to monitor the battery pack operation status based on the classification results, including...

[0057] The power supply output characterization parameters are determined based on the change in the output power of the battery pack within a predetermined period and the change ratio of the temperature in the battery pack area. Based on the power supply output characterization parameters, it is predicted whether the power supply effect of the battery pack meets the predetermined standard. Based on the average temperature difference of the individual cells in the current battery pack area, it is determined whether the power compensation device should be activated.

[0058] Alternatively, the power compensation device may not be activated.

[0059] Specifically, the UPS power supply self-diagnostic system of the present invention includes a static switch, a rectifier, an inverter, a control circuit, a charger, and a filter. It also includes a battery pack, a monitoring module, an AI analysis module, and a control module to enable the UPS power supply to switch to battery power mode in a very short time. The battery pack can be charged through the rectifier to store electrical energy. The battery pack consists of several individual cells. The monitoring module monitors the output voltage of each individual cell, the temperature and humidity changes in the battery pack area, and the output electrical energy parameters of the battery pack. The AI ​​analysis module stores historical data monitored by the monitor. Furthermore, the control module divides the influence period based on the power supply influence tendency characterization value corresponding to different battery management influence periods, monitors the battery pack operation status, determines the power supply output characterization parameters, and predicts whether the power supply effect of the battery pack meets the predetermined standard, thereby determining whether to activate the power compensation device. Considering the impact of the differences in the temperature and humidity resistance properties of each individual cell in the battery pack on the power supply efficiency during the operation of the UPS power supply self-diagnostic system, the power compensation device is adaptively intervened to ensure the power supply efficiency and battery stability of the UPS power supply self-diagnostic system.

[0060] Specifically, this invention is applied to a self-diagnostic system for backup UPS power supplies in medical devices. Common UPS power supplies include static switches, rectifiers, inverters, control circuits, chargers, filters, and battery packs containing several individual cells. These individual cells are usually connected in series or in parallel. Due to environmental temperature factors, the temperature and humidity resistance properties of each individual cell vary. Furthermore, in some cases, different individual cells may also have certain differences in energy storage and discharge.

[0061] Specifically, there are no specific limitations on the structure of the monitoring module, AI analysis module, control module and its units, and they can be composed of logic components, including field-programmable processors, computers or microprocessors in computers.

[0062] Specifically, the form of the power compensation device is not limited. It can be a compensation device with a DC / DC conversion circuit or a compensation device with pulse charging. For example, for single cells with low voltage or high internal resistance, the amplitude or width of the pulse can be increased to increase the charging current and speed up the power compensation. Other forms can also be used, which will not be elaborated here.

[0063] Specifically, there are no specific restrictions on the location of the temperature and humidity sensor. The temperature and humidity sensor can be placed in different areas of each individual cell in the battery pack, which will not be elaborated further here.

[0064] Specifically, the power detection unit can be a logical component that acquires information, such as by connecting to the battery management system to obtain relevant parameters, which will not be elaborated further here.

[0065] Please see Figure 2 The above describes a logical decision diagram for identifying the battery management impact cycle in an embodiment of the present invention. The AI ​​analysis module of the present invention is used to identify the battery management impact cycle based on the output voltage difference of each individual cell in the battery pack during different historical periods.

[0066] Used to calculate the variance of the output voltage difference of each individual cell in the battery pack during each historical period;

[0067] If the variance corresponding to a single historical period is less than or equal to a predetermined variance threshold, then the historical period is determined to be a non-affected period for battery management.

[0068] If the variance of a single historical period is greater than a predetermined variance threshold, then the historical period is determined to be a battery management impact period.

[0069] Specifically, the variance threshold is determined based on the average variance of the difference between the output voltage of each individual cell and the mean output voltage obtained over several historical periods, and is set between 1.15 and 1.25 times the average variance.

[0070] Specifically, in order to reflect the monitorability of the output voltage changes of each individual battery cell and its impact on the battery pack, the historical period was selected within the range of [3 min, 6 min].

[0071] Please see Figure 3 As shown, this is a logic decision diagram for analyzing the power supply impact tendency characterization value of the battery pack corresponding to different battery management impact cycles according to an embodiment of the present invention. The AI ​​analysis module of the present invention is used to analyze the power supply impact tendency characterization value of the battery pack corresponding to different battery management impact cycles based on the changes in the power parameters, including,

[0072] The ratio used to calculate the change in the storage power of the battery pack to a predetermined rate of change threshold is determined as the first data parameter feature;

[0073] The ratio of the average difference between the voltages of individual cells to a predetermined difference threshold is determined as the second data parameter feature.

[0074] The sum of the first data parameter feature and the second data parameter feature is used to determine the power supply influence tendency characterization value.

[0075] Specifically, the rate of change of the battery pack's stored power reflects the efficiency of the battery pack in storing electrical energy under different temperature influence cycles. The rate of change threshold is a reference value used to measure whether the degree of this change is significant. In practice, it is set as the average rate of change of electrical energy over several historical periods. By calculating the ratio, the rate of change can be standardized, making it easier to compare and analyze with other characteristics.

[0076] Specifically, the ratio of the difference in output voltage of each individual battery cell to a predetermined difference threshold is similar. The difference in output voltage of each individual battery cell is the difference between the output voltage of each individual battery cell and the predetermined average output voltage of each individual battery cell. Then the differences are added together. The changes of each individual battery cell are also affected by the ambient temperature and humidity. This ratio can reflect the degree of influence of temperature and humidity on the changes in the output voltage of each battery cell.

[0077] Specifically, by adding the first data parameter characteristic and the second data parameter characteristic, a power supply impact tendency characterization value is obtained. This value integrates the impact of multiple parameters, such as changes in storage power and changes in individual battery cells, on different impact cycles, and can comprehensively reflect the battery management impact tendency of the battery pack under specific temperature and humidity influence cycles.

[0078] Specifically, by analyzing the output parameters of the battery pack and individual cells, the impact of ambient temperature and humidity on the battery pack can be assessed more accurately. Different parameters reflect the performance changes of the battery pack from different perspectives. Taking these parameters into account can reduce the limitations of single-parameter assessments and provide more comprehensive and accurate temperature impact assessment results.

[0079] Please see Figure 4 As shown, this is a logic determination diagram for dividing the impact period based on the power supply impact tendency characterization value according to an embodiment of the present invention. The control module of the present invention is used to divide the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, including,

[0080] If the power supply impact tendency characterization value is greater than or equal to the preset impact tendency characterization value, it is determined to be the first impact cycle;

[0081] If the power supply impact tendency characterization value is less than the preset impact tendency characterization value, it is determined to be the second impact cycle.

[0082] Specifically, the preset influence tendency characterization value serves as a key judgment criterion, playing a role in dividing the first influence cycle and the second influence cycle. In implementation, the preset influence tendency characterization value is selected within the range [2.25, 2.35].

[0083] Specifically, when the power supply influence tendency characterization value is greater than or equal to the preset influence tendency characterization value, it is determined to be the first influence period. This indicates that within this period, the influence of each individual battery cell on the battery pack is relatively significant, which may lead to a substantial change in the performance of the battery pack. Preferably, the electrolyte properties of each individual battery cell differ, the electrolyte capacity of each individual battery cell leads to a decrease in charging and discharging efficiency, or rapid changes in ambient temperature and humidity may cause stress changes inside the battery, affecting the lifespan and safety of the battery pack.

[0084] Specifically, if the power supply influence tendency value is less than the preset influence tendency value, it is determined to be the second influence cycle. During this cycle, the impact of each individual battery cell on the battery pack is relatively small, and the performance changes of the battery pack are relatively minor. At this time, the battery pack can operate in a relatively stable state, and performance indicators such as charging and discharging efficiency and lifespan are relatively stable.

[0085] Specifically, the control module monitors the battery pack's operating status based on the partitioning results, including:

[0086] If the division result is the first influence period, then based on the change in the output power of the battery pack and the change ratio of temperature and humidity in the battery pack area within the predetermined period, the power output characterization parameters are determined to predict whether the power supply effect of the battery pack meets the predetermined standard, and the power compensation device is activated based on the temperature difference in the current battery pack area.

[0087] If the division result is the second influence period, the power compensation device will not be activated.

[0088] Specifically, during the first period of influence, individual battery cells have a significant impact on the battery pack. By monitoring changes in temperature and humidity in the battery area, the extent to which changes in external environmental temperature and humidity affect the UPS power supply self-diagnostic system can be understood. Simultaneously, the percentage change in the battery pack's output efficiency reflects the performance changes of the battery pack under different temperature and humidity conditions. Combining these three parameters to determine the power output characterization parameters allows for a more comprehensive assessment of the impact of temperature and humidity on the entire UPS power supply self-diagnostic system.

[0089] Specifically, a sharp rise in temperature in the battery pack area can cause changes in the battery pack's output voltage, thereby affecting its power supply efficiency. By analyzing the changes in temperature, humidity, and the proportion of changes in output power, it is possible to predict whether the battery pack's power supply performance under such drastic temperature and humidity changes meets predetermined standards.

[0090] Specifically, during the first impact period, the cost and benefits of using the power compensation device need to be considered. The power consumption of the power compensation device is a crucial factor; excessive power consumption upon activation could reduce the efficiency of the entire UPS power supply self-diagnostic system. Simultaneously, the temperature of the current battery pack area needs to be considered. If the temperature difference in the battery pack area is small, activating the power compensation device may be necessary to reduce power loss due to temperature variations.

[0091] Specifically, if the temperature difference in the battery area is large, it is considered that the charging of the power compensation device will cause the ambient temperature to rise faster. Therefore, the power compensation device may not be activated, and other measures may be taken, such as activating the cooling compensation device, to reduce the impact of temperature on the system.

[0092] Specifically, the control module is used to determine power output characterization parameters based on the change in the output electrical energy of the battery pack within a predetermined period and the proportion of temperature change in the battery pack area, including:

[0093] The ratio of the change in the output voltage of the battery pack to a predetermined output voltage change threshold is determined as the first power supply output parameter characteristic.

[0094] The ratio of the change in temperature in the battery pack area to a predetermined temperature change threshold is used to determine the second power supply output parameter characteristic.

[0095] The ratio of the change in humidity in the battery pack area to a predetermined humidity change threshold is used to determine the third power supply output parameter characteristic.

[0096] The sum of the first power supply output parameter feature, the second power supply output parameter feature, and the third power supply output parameter is used to determine the power supply output characterization parameter.

[0097] For the predetermined output voltage change threshold, the output voltage change threshold in this embodiment is set based on the average value of the average voltage change of the battery pack over a historical period, and is set to be between 0.45 times and 0.55 times the average value of the average voltage change.

[0098] The temperature variation of the battery pack area is set based on the average temperature of the battery pack over a historical period, and is set between 0.55 and 0.65 times the average temperature.

[0099] The amount of change in humidity in the battery area is set based on the average humidity of the battery over a historical period, and is set between 0.5 and 0.8 times the average humidity.

[0100] Specifically, the change in the output voltage of the battery pack reflects the performance change of the energy storage battery pack under different temperature and humidity conditions.

[0101] Specifically, the power supply output characteristic is obtained by adding the first, second, and third power supply output characteristic. This parameter comprehensively considers the impact of changes in battery pack temperature and humidity and changes in battery pack output voltage on the entire UPS power supply self-diagnostic system.

[0102] Specifically, the control module is used to predict whether the power supply performance of the battery pack meets a predetermined standard based on the power supply output characterization parameters, including:

[0103] If the power output characteristic parameter is less than or equal to the preset power output characteristic parameter, then the predicted power supply effect of the battery pack meets the predetermined standard.

[0104] If the power output characteristic parameter is greater than the preset power output characteristic parameter, the predicted power supply effect of the battery pack does not meet the predetermined standard.

[0105] Specifically, the preset power supply performance parameters, serving as key reference values ​​for judging whether the power supply effect of the battery pack meets the predetermined standards, are determined comprehensively based on factors such as the design performance of the battery pack, historical operating data, and the system's requirements for power supply performance. Preferably, a value that can classify whether the power supply performance meets the standards is determined through extensive analysis of the power supply performance of similar battery packs under different temperature and humidity environments.

[0106] Specifically, the control module is used to determine whether to activate the power compensation device based on the average temperature difference of individual cells in the current battery pack area when the predicted power supply effect of the battery pack does not meet the predetermined standard.

[0107] Specifically, in a UPS power supply self-diagnostic system, when the predicted power supply performance of the battery bank does not meet predetermined standards, measures are considered to improve the situation. Power compensation devices are one possible solution, but they also generate heat. Therefore, a comprehensive evaluation of power compensation devices is necessary.

[0108] Specifically, the control module is used to determine whether to activate the power compensation device based on the average temperature difference of individual cells in the current battery pack area, including:

[0109] If the average current temperature difference is less than or equal to the predetermined temperature difference threshold, then the power compensation device is activated.

[0110] If the average current temperature difference is greater than the predetermined temperature difference threshold, then the power compensation device will not be activated.

[0111] Specifically, it also includes a cooling compensation device for reducing the temperature of the battery pack area. When the control module determines that the power compensation device should not be used, it activates the cooling compensation device. The cooling effect of the cooling compensation device is proportional to the average temperature difference of the individual cells in the current battery pack area.

[0112] There are no restrictions on the form of the cooling compensation device; it can be fan cooling or other forms of cooling, which will not be elaborated here.

[0113] Specifically, it also includes a display unit connected to the monitoring module, capable of displaying the data monitored by the module in real time. This is crucial for the operation and management of the UPS power supply self-diagnostic system. Preferably, users can use the display unit to monitor key parameters such as the battery pack's output voltage and storage power, temperature, and humidity at any time. In practical applications, operators can intuitively see the current status of the system, promptly detect abnormalities, and take appropriate measures.

[0114] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A UPS power supply self-diagnostic system based on artificial intelligence, comprising a static switch, rectifier, inverter, control circuit, charger, and filter, characterized in that, Also includes: A battery pack includes a battery bank for charging via a rectifier to store electrical energy, a plurality of individual cells connected to the battery bank for storing electrical energy, and an energy compensation device for changing the charge of each individual cell in the battery bank. The monitoring module includes several voltage sensors for monitoring the output voltage of each individual cell in the battery pack, several temperature and humidity sensors for monitoring the temperature and humidity of the battery pack area, and an energy monitoring unit for acquiring the output energy parameters of the battery pack. The AI ​​analysis module is connected to the monitoring module and is used to store historical data monitored by the monitoring module. It is used to identify the battery management impact cycle based on the output voltage difference of each individual battery in the battery pack in different historical periods, and to analyze the power supply impact tendency characterization value of the battery pack in different battery management impact cycles based on the changes in the power parameters. Among them, the ratio of the change in the storage power of the battery pack to a predetermined rate of change threshold is determined as the first data parameter feature; The ratio of the average difference between the output voltages of each individual cell to a predetermined difference threshold is determined as the second data parameter feature. The sum of the first data parameter feature and the second data parameter feature is used to determine the power supply influence tendency characterization value; Used to calculate the variance of the output voltage difference of each individual cell in the battery pack during each historical period; If the variance corresponding to a single historical period is greater than a predetermined variance threshold, then the historical period is determined to be a battery management impact period. The control module, connected to the battery assembly, monitoring module, and AI analysis module, is used to classify the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, and to monitor the battery pack operation status based on the classification results, including... The power supply output characterization parameters are determined based on the change in the output power of the battery pack within a predetermined period and the change ratio of temperature and humidity in the battery pack area. Based on the power supply output characterization parameters, it is predicted whether the power supply effect of the battery pack meets the predetermined standard. When it is predicted that the power supply effect of the battery pack does not meet the predetermined standard, it is determined whether to activate the power compensation device based on the temperature difference value of the current battery pack area. Alternatively, the power compensation device may not be activated; The control module is used to determine whether to activate the power compensation device based on the average temperature difference of individual cells in the current battery pack area, including: If the average current temperature difference is less than or equal to the predetermined temperature difference threshold, then the power compensation device is activated. If the average current temperature difference is greater than the predetermined temperature difference threshold, then the power compensation device will not be activated.

2. The UPS power supply self-diagnosis system based on artificial intelligence according to claim 1, characterized in that, The control module is used to divide the impact period based on the power supply impact tendency characterization value corresponding to different battery management impact periods, including, If the power supply impact tendency characterization value is greater than or equal to the preset impact tendency characterization value, it is determined to be the first impact cycle; If the power supply impact tendency characterization value is less than the preset impact tendency characterization value, it is determined to be the second impact cycle.

3. The UPS power supply self-diagnostic system based on artificial intelligence according to claim 2, characterized in that, The control module monitors the battery pack's operating status based on the partitioning results, including: If the division result is the first influence period, then the power output characterization parameters are determined based on the change in the output power of the battery pack and the change ratio of the temperature in the battery pack area within the predetermined period to predict whether the power supply effect of the battery pack meets the predetermined standard, and the power compensation device is activated based on the temperature difference in the current battery pack area. If the division result is the second influence period, the power compensation device will not be activated.

4. The UPS power supply self-diagnostic system based on artificial intelligence according to claim 1, characterized in that, The control module is used to determine power output characterization parameters based on the change in the output electrical energy of the battery pack within a predetermined period and the proportion of change in temperature and humidity in the battery pack area, including: The ratio of the change in the output voltage of the battery pack to a predetermined output voltage change threshold is determined as the first power supply output parameter characteristic. The ratio of the change in temperature in the battery pack area to a predetermined temperature change threshold is determined as the second power supply output parameter characteristic. The ratio of the change in humidity in the battery pack area to a predetermined humidity change threshold is used to determine the third power supply output parameter characteristic. The sum of the first power supply output parameter feature, the second power supply output parameter feature, and the third power supply output parameter is used to determine the power supply output characterization parameter.

5. The UPS power supply self-diagnostic system based on artificial intelligence according to claim 4, characterized in that, The control module is used to predict whether the power supply performance of the battery pack meets a predetermined standard based on the power supply output characterization parameters, including: If the power output characteristic parameter is less than or equal to the preset power output characteristic parameter, then the predicted power supply effect of the battery pack meets the predetermined standard. If the power output characteristic parameter is greater than the preset power output characteristic parameter, the predicted power supply effect of the battery pack does not meet the predetermined standard.

6. The UPS power supply self-diagnostic system based on artificial intelligence according to claim 5, characterized in that, The control module is used to determine whether to activate the power compensation device based on the temperature difference in the current battery pack area when the predicted power supply effect of the battery pack does not meet the predetermined standard.

7. The UPS power supply self-diagnostic system based on artificial intelligence according to claim 6, characterized in that, It also includes a cooling compensation device for reducing the temperature of the battery pack area. When the control module determines that the power compensation device should not be used, the cooling compensation device is activated. The cooling effect of the cooling compensation device is proportional to the average temperature difference of the individual cells in the current battery pack area.

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