A health management method for switching power supplies in parallel operation

Abstract

This invention is used for health management of switching power supplies in parallel operation. By analyzing and comparing internal monitoring information of the parallel switching power supplies, including input voltage, input current, ambient temperature, power supply temperature, output voltage, output current, and other internal monitoring points, this method overcomes the current problem of inaccurate fault diagnosis of switching power supplies in parallel operation, enabling early warning and detection of suspected faults. This power supply health management method monitors and adjusts the operating status of the power supplies in real time, providing functions such as power on / off control, power supply status monitoring, fault protection, and load balancing management. The invention can also be applied to standalone switching power supplies.

Description

Technical Field

[0001] The present invention belongs to the field of power electronics technology, and in particular relates to a health management method for switching power supplies under parallel operation conditions. Background Art

[0002] A switching power supply is a high-frequency power conversion device that converts a voltage level into the voltage or current required by the user through various architectures. Due to its high conversion efficiency, it is widely used to power radar arrays. Parallel connection of multiple switching power supplies to ensure high current is a common power supply topology in power supply design. However, since both the input and output are connected in parallel, simple voltage detection methods make it difficult to distinguish the different operating states of the parallel power supplies. This can delay fault detection, leading to worsening of the problem and increased losses. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to form a real-time data stream by monitoring the internal monitoring points such as the input voltage, input current, ambient temperature, power supply temperature, output voltage, output current of the parallel switching power supply, and analyze the data according to a mathematical model, and report a fault when a deviation in the data is found.

[0004] The present invention provides a method for managing the health of switching power supplies in parallel operation. This method can be used to manage the health of switching power supplies in parallel operation. By analyzing and comparing internal power supply monitoring information, such as input voltage, input current, ambient temperature, power supply temperature, output voltage, output current, and other internal monitoring points, the method overcomes the current problem of inaccurate fault diagnosis of switching power supplies in parallel operation and enables early warning and detection of suspected faults. The power supply health management method provided by the present invention can monitor and adjust the operating status of the power supplies in real time, providing functions such as power on / off control, power supply status monitoring, fault protection, and load balancing management.

[0005] The present invention provides a method for health management of switching power supplies in parallel operation, the method comprising the following steps:

[0006] Step 1: Number and distinguish the parallel power supplies.

[0007] Each number is unique and represents information such as the installation location or installation time, serving as a unique identification code.

[0008] Step 2: The parallel switching power supplies traverse and report their current status in turn.

[0009] The switching power supplies connected in parallel are sequentially traversed and report their current status according to the order of number or other specified order.

[0010] Step 3: After one round of traversal, calculate the health status of each switching power supply.

[0011] After a round of traversal, the degree of deviation of each indicator from the mean and historical value is calculated, and then the hierarchical analysis mathematical model is used to calculate the health status of each switching power supply.

[0012] Step 4: After obtaining the health status of each parallel power supply, dynamically adjust the load size of each component according to the power supply health status to achieve load balancing; when the health status does not meet the safety or reliability indicators, warn of planned maintenance or unplanned maintenance.

[0013] Table 1 Self-monitoring information

[0014] Interface Name Interface Function Internal Monitoring 1 Output voltage Internal Monitoring 2 Input voltage Internal Monitoring 3 Output current Internal Monitoring 4 Input current Internal Monitoring 5 Radiator temperature Internal Monitoring 6 Ambient temperature Internal Monitoring7 …

[0015] Step 5: Repeat steps 3 and 4 until the parallel power system task is completed.

[0016] Preferably, in step 1, the parallel use model is as follows: when z power supplies are used in parallel, the microcomputer number of each power supply should be identified first, and the redundancy should be calculated. Here, the redundancy is Y=z-z0+1, z0 is the minimum number of power supplies required for the system, and Y, z, and z0 are all positive integers. Redundancy greater than or equal to 1 indicates that the parallel system meets the power supply requirements; redundancy greater than 1 indicates that the parallel system can withstand partial power supply failure and shutdown; redundancy less than 1 indicates that the parallel system cannot withstand the current load end requirements. When used in parallel, the parallel system automatically calculates the total current and the average power supply of the power supply components, and realizes load balancing of each power supply component through current sharing hardware circuit or current sharing software.

[0017] Preferably, in step 3, the step of calculating the health status of each switching power supply is specifically as follows:

[0018] Based on the performance indicators obtained from the test system, the power supply health status assessment model is constructed using the fuzzy variable weight analytic hierarchy process.

[0019] Based on the structure and control characteristics of the parallel switching power supply system, the evaluation model is divided into three levels: target level, project level, and indicator level. The indicator level is a sub-level of the project level, and the project level is a sub-level of the target level. The health of each level is determined by the health of its sub-levels. The system health calculation formula is:

[0020]

[0021] Where n is the number of sub-level items, ω and M are the corresponding relevant weights and healthiness, respectively.

[0022] When calculating the health of the indicator layer, it is necessary to first convert the different properties and unit parameters into a unified dimensionless form through the fuzzy dimensionless function. Here, the triangular negative function condition is used:

[0023]

[0024] Where M(x) is the index health degree, A is the health parameter range, the index deviation x = |X - Xe|, X is the actual measured value of the index, Xe is the expected measured value, [x l , x h is the upper and lower evaluation interval of the index.

[0025] Generally, the importance of the voltage weight is the greatest.

[0026] During the actual operation of the system, when the index of a certain module deteriorates significantly, its impact on the system health level will be amplified. For example, when the temperature of a certain power supply is abnormal, the output power of the power supply should be reduced or the power supply should be turned off at this time to avoid damage events.

[0027] At this time, the evaluation system based on constant weights will be difficult to reflect the actual situation of the system, and the evaluation results will be distorted. Therefore, an equilibrium function is introduced to calculate the dynamic weights:

[0028]

[0029] In the formula, W i is the new weight; ω i is the initial weight obtained by expert scoring; a is the variable weight coefficient, and 0 < a ≤ 1. When a = 1, it is the case of constant weights. After obtaining the new weights, the power supply health degree is calculated based on the new weights.

[0030] Preferably, step 4 is specifically as follows:

[0031] When the health level of some power supplies drops and they cannot be used, recalculate the system redundancy; if the redundancy is greater than or equal to 1, evenly distribute the total load demand to the power supply components that are working properly to ensure the safety and reliability of the parallel switching power supply system, and send a warning message; if the redundancy is less than 1, issue a power management command to the load end to ensure that the maximum peak power demand does not exceed the maximum supply capacity of the parallel power supply system, and evenly distribute the load demand to the power supply components that are working properly; if the requirements are still not met, turn off the output and send a warning message.

[0032] The beneficial effects of the present invention are: [[ID=Зб]]

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention overcomes the problem that the voltage measurement under parallel conditions cannot accurately locate the fault point of the switching power supply. By monitoring the input voltage, input current, ambient temperature, power supply temperature, output voltage, output current and other internal monitoring points of each parallel switching power supply, health monitoring and warning of each parallel switching power supply are carried out based on a mathematical model, and at the same time, load management is carried out based on the health status to improve the reliability of the use of the parallel switching power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Power supply self-monitoring working principle block diagram

[0036] Figure 2 Fault judgment model diagram of switching power supply based on hierarchical analysis method

[0037] Figure 3 Power supply parallel management schematic diagram DETAILED DESCRIPTION

[0038] The technical solutions provided by the present invention will be described in detail below with reference to specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention.

[0039] The present invention provides a method for health management of switching power supplies in parallel operation, the method comprising the following steps:

[0040] Step 1: Number and distinguish the parallel power supplies.

[0041] Each number is unique and represents information such as the installation location or installation time, serving as a unique identification code.

[0042] The parallel operation model is as follows: When z power supplies are connected in parallel, each power supply is first identified by its microcomputer number and its redundancy calculated. Here, redundancy is Y = z - z0 + 1, where z0 is the minimum number of power supplies required to meet system requirements. Y, z, and z0 are all positive integers. A redundancy greater than or equal to 1 indicates that the parallel system meets power supply requirements; a redundancy greater than 1 indicates that the parallel system can withstand partial power supply failure and shutdown; a redundancy less than 1 indicates that the parallel system cannot withstand the current load requirements. When used in parallel, the parallel system automatically calculates the total current and the average power supply component power, and balances the load across the power supply components using current-sharing hardware or software.

[0043] Step 2: The parallel switching power supplies traverse and report their current status in turn.

[0044] The switching power supplies connected in parallel are sequentially traversed and report their current status according to the order of number or other specified order.

[0045] Step 3: After one round of traversal, calculate the health status of each switching power supply.

[0046] After a round of traversal, the degree of deviation of each indicator from the mean and historical value is calculated, and then the hierarchical analysis mathematical model is used to calculate the health status of each switching power supply.

[0047] Based on the performance indicators obtained from the test system, the power supply health status assessment model is constructed using the fuzzy variable weight analytic hierarchy process.

[0048] As Figure 2 shown, for the structure and control characteristics of the parallel switching power supply system, the evaluation model is divided into three levels, namely the target layer, the project layer, and the index layer from top to bottom. The index layer is a sub-level of the project layer, and the project layer is a sub-level of the target layer. The health degree of each level is determined by the health degree of its sub-level. The formula for calculating the system health degree is:

[0049]

[0050] where n is the number of sub-level projects, ω and M are the corresponding relevant weights and health degrees respectively.

[0051] When calculating the health degree of the index layer, it is necessary to first convert parameters with different natures and units into a unified dimensionless form through a fuzzy dimensionless function. Here, the triangular negative function condition is adopted:

[0052]

[0053] In the formula, M(x) is the index health degree, A is the health parameter range, the index deviation x = |X - Xe|, X is the actual measured value of the index, Xe is the expected measured value, and [x l , x h is the upper and lower evaluation intervals of the index.

[0054] Generally, the importance of the voltage weight is the greatest.

[0055] During the actual operation of the system, when the index of a certain module deteriorates significantly, its impact on the system health level will be amplified. For example, when the temperature of a certain power supply is abnormal, the output power of the power supply should be reduced or the power supply should be turned off at this time to avoid damage events. At this time, the evaluation system based on constant weights will be difficult to reflect the actual situation of the system, and the evaluation results will be distorted. Therefore, an equilibrium function is introduced to calculate the dynamic weights:

[0056]

[0057] In the formula, W i is the new weight; ω i is the initial weight obtained by expert scoring; a is the variable weight coefficient, and 0 < a ≤ 1. When a = 1, it is the case of constant weights. After obtaining the new weights, calculate the power supply health degree based on the new weights

[0058] Step 4. After obtaining the health states of the parallel power supplies, dynamically adjust the load sizes of each component according to the power supply health conditions to achieve load balancing; when the health state does not meet the safety or reliability index, give an early warning for planned maintenance or unplanned maintenance.

[0059] When the health level of some power supplies degrades and they cannot be used, the system redundancy is recalculated; if the redundancy is greater than or equal to 1, the total load demand is evenly distributed to the normally functioning power components to ensure the safety and reliability of the parallel switching power supply system, and an early warning message is sent; if the redundancy is less than 1, a power management command is issued to the load end to ensure that the maximum peak power demand does not exceed the maximum supply capacity of the parallel power supply system, and the load demand is evenly distributed to the normally functioning power components; if the requirements are still not met, the output is shut down and an early warning message is issued.

[0060] Step 5: Repeat steps 3 and 4 until the parallel power system task is completed.

[0061] The above description is only the best specific implementation method of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or replacements that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

[0062] The contents not described in detail in the specification of the present invention belong to the common knowledge of professionals in this field.

Claims

1. A method for health management of switching power supplies in parallel operation, characterized in that: The steps of this method are as follows: Step 1: Number and distinguish the parallel power supplies; Each number is unique and represents the installation location or installation time information, serving as a unique identification code; Step 2: The parallel switching power supplies traverse and report their current status in turn; The switching power supplies connected in parallel report their current status in sequence according to the numbering order or other specified order; Step 3: After one round of traversal, calculate the health status of each switching power supply; After a round of traversal, the deviation degree of each indicator from the mean and historical value is calculated, and then the health status of each switching power supply is calculated using the hierarchical analysis mathematical model; Step 4: After obtaining the health status of each parallel power supply, dynamically adjust the load size of each component according to the power supply health status to achieve load balancing; if the health status does not meet the safety or reliability indicators, warn of planned maintenance or unplanned maintenance; Step 5: Repeat steps 3 and 4 until the parallel power system task is completed.

2. The method according to claim 1, characterized in that In step 1, the parallel use model is as follows: when z power supplies are used in parallel, the microcomputer number of each power supply should be identified first, and the redundancy should be calculated. Here, the redundancy is Y=z-z0+1, z0 is the minimum number of power supplies required for the system, and Y, z, and z0 are all positive integers; redundancy is greater than or equal to 1, which means that the parallel system meets the power supply requirements; redundancy is greater than 1, which means that the parallel system can withstand partial power supply failure and shutdown; redundancy is less than 1, which means that the parallel system cannot withstand the current load end requirements; when used in parallel, the parallel system automatically calculates the total current and the average power supply of the power supply components, and realizes load balancing of each power supply component through current sharing hardware circuit or current sharing software.

3. The method according to claim 1, characterized in that In step 3, the steps for calculating the health status of each switching power supply are as follows: Based on the performance indicators obtained from the test system, the power supply health status assessment model was constructed using the fuzzy variable weight analytic hierarchy process. According to the structure and control characteristics of the parallel switching power supply system, the evaluation model is divided into three levels: target level, project level, and indicator level from top to bottom. The indicator level is a sub-level of the project level, and the project level is a sub-level of the target level. The health of each level is determined by the health of its sub-levels; the system health calculation formula is: Where n is the number of sub-level items, ω and M are the corresponding related weights and healthiness respectively; When calculating the health of the indicator layer, it is necessary to first convert the different properties and unit parameters into a unified dimensionless form through a fuzzy dimensionless function; here, the triangular negative function condition is used: Where M(x) is the indicator health, A is the health parameter range, indicator deviation x = |X-Xe|, X is the actual measurement value of the indicator, Xe is the expected measurement value, [x l , x h ] is the upper and lower evaluation interval of the indicator; During actual system operation, when a module indicator deteriorates significantly, its impact on the system health level will be magnified; At this time, the evaluation system based on constant weights will be difficult to reflect the actual situation of the system, and the evaluation results will be distorted; therefore, the equilibrium function is introduced to calculate the dynamic weights: In the formula, W i is the new weight; ω i is the initial weight obtained by expert scoring; a is the variable weight coefficient, and 0 < a ≤ 1. When a = 1, it is the case of constant weight. After obtaining the new weight, calculate the power supply health based on the new weight.

4. The method according to claim 1, wherein Step 4 is as follows: When the health level of some power supplies degrades and they cannot be used, the system redundancy is recalculated; if the redundancy is greater than or equal to 1, the total load demand is evenly distributed to the normally functioning power components to ensure the safety and reliability of the parallel switching power supply system, and an early warning message is sent; if the redundancy is less than 1, a power management command is issued to the load end to ensure that the maximum peak power demand does not exceed the maximum supply capacity of the parallel power supply system, and the load demand is evenly distributed to the normally functioning power components; if the requirements are still not met, the output is shut down and an early warning message is issued.

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