Control method of alternating current and direct current compatible low-voltage electric appliance

Abstract

The invention discloses a control method of an alternating current and direct current compatible low-voltage electric appliance, which relates to the technical field of control of low-voltage electric appliances and comprises the following steps of: dividing circuits of the low-voltage electric appliance and establishing a circuit set; establishing a three-dimensional image according to the circuit set, performing load resource allocation simulation on the three-dimensional image, and obtaining first data of the circuit; according to the first data of the circuit, carrying out necessity category classification on the circuit, wherein the necessity category comprises a necessary circuit and an unnecessary circuit; establishing a resource allocation priority evaluation model based on machine learning according to the first data of the circuit, and obtaining a resource allocation coefficient; and controlling a circuit of the low-voltage electric appliance according to the necessity category, the resource allocation coefficient and a preset electric appliance operation mode so as to control the low-voltage electric appliance. Therefore, reasonable utilization of electric power resources is ensured, benefits of electric appliances are maximized, and the problem that low-voltage electric appliances need more energy consumption or the functions of the electric appliances are limited is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of control of low-voltage electrical appliances, and more specifically, to a control method for an AC / DC compatible low-voltage electrical appliance. Background Art

[0002] In the modern society that is increasingly dependent on electric energy, the performance and quality of low-voltage electrical appliances directly affect the reliability of the power supply system. Therefore, low-voltage electrical appliance testing has become a preliminary guarantee for the use and operation of low-voltage electrical appliances in power systems. As an energy-feeding simulated load device, the low-voltage electrical appliance test solid-state load can more accurately adjust the current and power factor.

[0003] At present, the classic PI current control method is widely used to control the current of solid-state loads. The tracking accuracy of this method is low. Especially when simulating nonlinear loads, the bandwidth of the digital PI controller is limited, and it is difficult to meet the requirements of accuracy and stability at the same time. With the development of digital signal processors (DSP), deadbeat current control has the characteristics of easy implementation and fast dynamic response, but this method has strict requirements and serious dependence on PWM converters and load models. When using deadbeat control, it is easy to cause the control model to be inconsistent with the actual object, resulting in circuit parameter mismatch and control delay problems. At the same time, it will increase the input current harmonics, reduce the accuracy of the power factor on the AC side, and even cause the control system to be unstable as the control action continues to strengthen.

[0004] The Chinese invention patent with the announcement number CN112684225B discloses a solid-state load current control method for low-voltage electrical appliance testing based on deadbeat control, including the following steps: the first step is to collect parameters; the second step is to use a second-order generalized integrator to phase-lock the grid voltage; the third step is to use deadbeat control for the current generating unit; the fourth step is to compensate the inductance error online according to the inductance error compensation formula; the fifth step is to use the compensation parameter h to adjust the AC side current phase of the current generating unit to compensate for the power factor deviation. This method compensates the inductance error online to solve the problem of inductance parameter mismatch in deadbeat control, and solves the problems of poor control effect and low accuracy caused by control delay in traditional deadbeat control; the phase of the AC side current of the current generating unit is adjusted by the compensation parameter, thereby ensuring the accuracy of the power factor during the test.

[0005] The above disclosed technical solutions have at least the following technical problems: Low-voltage appliances require special attention in terms of resource utilization because they usually operate under low voltage conditions. At lower voltages, appliances may not be able to achieve the optimal performance level required by the design. Secondly, the energy consumption of appliances under low voltage conditions is usually higher. In order to maintain normal operation, appliances may need to consume more electricity. However, as the demand for low-voltage appliance functions becomes increasingly complex and rich, the number of low-voltage appliance modules gradually increases, and resource utilization becomes a major problem, often resulting in more energy consumption or limiting the functions of appliances.

[0006] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0007] In order to overcome the above defects of the prior art, an embodiment of the present invention provides a control method for an AC / DC compatible low-voltage electrical appliance, which solves the problems raised in the above background technology by controlling the low-voltage electrical appliance.

[0008] To achieve the above object, the present invention provides the following technical solutions: A control method for an AC / DC compatible low-voltage electrical appliance comprises the following steps: dividing the circuit of the low-voltage electrical appliance to establish a circuit set; establishing a three-dimensional image according to the circuit set, simulating the load resource allocation of the three-dimensional image, and obtaining first circuit data, wherein the first circuit data comprises circuit impact degree data and circuit benefit data; classifying the circuit into necessity categories according to the first circuit data, wherein the necessity categories comprise necessary circuits and non-essential circuits; establishing a resource allocation priority evaluation model based on machine learning according to the first circuit data to obtain a resource allocation coefficient; controlling the circuit of the low-voltage electrical appliance according to the necessity categories combined with the resource allocation coefficient and according to a preset electrical appliance operation mode, thereby achieving control of the low-voltage electrical appliance.

[0009] In a preferred embodiment, the circuit impact degree data includes a fault contribution coefficient and a function importance coefficient; the circuit benefit data includes a cost benefit coefficient.

[0010] In a preferred embodiment, the circuit is classified into a necessity category based on the first circuit data, specifically: the function importance coefficient is compared with a preset necessary circuit threshold, when the function importance coefficient is greater than the necessary circuit threshold, the necessity category is marked as a necessary circuit, otherwise it is marked as a non-essential circuit.

[0011] In a preferred embodiment, the preset appliance operation modes include energy-saving mode, basic mode, and performance mode.

[0012] In a preferred embodiment, the circuits of low-voltage electrical appliances are controlled according to the necessity category combined with the resource allocation coefficient and according to the preset electrical appliance operation mode, specifically: when the electrical appliance operation mode is the energy-saving mode, the x circuits after the necessary circuit ranking table are frequency-reduced, and no power resources are allocated to the circuits on the non-essential circuit ranking table; when the electrical appliance operation mode is the basic mode, the x circuits after the necessary circuit ranking table are frequency-reduced, and power resources are allocated to the first k circuits in the non-essential circuit ranking table; when the electrical appliance operation mode is the performance mode, power resources are normally allocated to all circuits in the necessary circuit ranking table, and power resources are allocated to the first g circuits in the non-essential circuit ranking table.

[0013] In a preferred embodiment, a specific method for obtaining the fault contribution coefficient is as follows: obtaining fault data of low-voltage electrical appliances within a specific time interval; calculating the historical frequency of faults based on the fault data; evaluating the influence coefficient of each fault type on the circuit based on downtime and production losses; calculating the fault contribution coefficient based on statistical analysis in combination with the fault data, the influence coefficient of each fault type on the circuit, and the historical frequency of faults, wherein the fault data includes the processing time required for the fault, the cost required for the fault, the fault occurrence rate of the circuit, the fault resolution rate of the circuit, and the fault duration.

[0014] In a preferred embodiment, the specific method for obtaining the function importance coefficient is as follows: the type of each circuit function and the importance ratio of the circuit function type are obtained through a circuit function type database, and an evaluation model constructed by a Logistic regression analysis method is used to conduct an overall analysis of the importance of the circuit functionality for the circuit function type to obtain the function importance coefficient.

[0015] In a preferred embodiment, the specific method for obtaining the cost-effectiveness coefficient is as follows: Obtain the static power consumption and static current of the static circuit, multiply them to establish a static power consumption model; obtain the dynamic power consumption data of the charging and discharging process when the dynamic circuit is switched, and establish a dynamic power consumption model based on the dynamic power consumption data, wherein the dynamic power consumption data includes load capacitance, clock frequency, and the average switching times of each circuit element during the switching process; obtain the preset electrical operation mode, and establish different benefit models based on different electrical operation modes, wherein the electrical operation modes include energy-saving mode, performance mode, and basic mode; determine the power consumption model according to the characteristics of the circuit itself, and determine the power consumption model according to the electrical operation mode; calculate and obtain the cost-effectiveness coefficient based on the benefit model and the power consumption model.

[0016] The technical effects and advantages of the control method of an AC / DC compatible low-voltage electrical appliance of the present invention are as follows: 1. The present invention realizes efficient control and management of low-voltage electrical appliances by utilizing refined circuit partitioning and resource allocation methods, combined with machine learning and cost-benefit analysis. By establishing a circuit set and a three-dimensional image, simulating the necessity of load resource allocation and classifying circuits, the system can give priority to circuits that have a great impact on functions and performance, and improve the fault tolerance and stability of the system. At the same time, the cost-benefit analysis takes into account the cost and performance improvement of each circuit, ensures the rational use of resources, and maximizes the economic benefits of the system. This technology is expected to play an important role in achieving performance optimization, maximizing resource utilization, improving fault handling priority, and balancing economic cost and benefits.

[0017] 2. The present invention uses machine learning to establish a resource allocation priority evaluation model, and through the calculated resource allocation coefficient, it realizes intelligent control of low-voltage electrical appliances. Combined with the preset electrical appliance operation mode, the system can adopt corresponding control strategies according to the necessity classification and resource allocation coefficient, and dynamically adjust the resource allocation of the circuit to improve the performance, energy saving and stability of the system. This intelligent control strategy not only improves the efficiency and reliability of the system, but also can be flexibly adjusted according to actual conditions to adapt to different working environments and changes in demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a schematic structural diagram of a control method for an AC / DC compatible low-voltage electrical appliance. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Embodiment 1, Figure 1 The present invention provides a control method for an AC / DC compatible low-voltage electrical appliance. S10, dividing the circuits of the low-voltage electrical appliances and establishing a circuit set; S20, establishing a three-dimensional image according to the circuit set, performing load resource allocation simulation on the three-dimensional image, and acquiring first circuit data; S30, classifying the circuit into necessity categories according to the first circuit data, wherein the necessity categories include necessary circuits and non-essential circuits; S40, establishing a resource allocation priority evaluation model based on machine learning according to the first circuit data to obtain a resource allocation coefficient; S50, controlling the circuit of the low-voltage electrical appliance according to the necessity category combined with the resource allocation coefficient and according to the preset electrical appliance operation mode, thereby achieving control of the low-voltage electrical appliance.

[0021] In this embodiment, the circuits of the low-voltage electrical appliances are divided to establish a circuit set; Specifically, dividing the circuit into different parts can achieve refined allocation of resources. According to the characteristics and importance of each part, resources can be allocated in a targeted manner to improve resource utilization efficiency. By dividing the circuit, we can better understand the load conditions and resource requirements of each part, thereby achieving more accurate resource allocation. Dividing the circuit into multiple parts is also to improve the flexibility and scalability of the system, making it easier to customize and expand the system as needed; by dividing the circuit into multiple modules, the system can be designed and configured more flexibly to meet the needs of different users and application scenarios.

[0022] In this embodiment, a three-dimensional image is created according to the circuit set, a load resource allocation simulation is performed on the three-dimensional image, and first circuit data is obtained; It should be noted that the purpose of establishing a three-dimensional image and performing load resource allocation simulation is to optimize the circuit control of low-voltage electrical appliances in order to achieve multiple goals such as performance optimization, maximum resource utilization, load balancing, enhanced safety, energy conservation and environmental protection; by simulating circuit performance under different load conditions, the best circuit resource allocation can be found to ensure stable circuit operation.

[0023] The first circuit data includes circuit impact degree data and circuit benefit data; The circuit impact degree data includes a fault contribution coefficient and a function importance coefficient; the circuit benefit data includes a cost benefit coefficient; The resource allocation priority for fault handling mainly considers the contribution of each circuit to fault handling. By allocating resources to circuits that may fail first, the system can improve fault tolerance and reliability. This means that the focus will be on those circuits that can handle problems quickly and effectively in the event of a fault, ensuring that the system can resume normal operation in a timely manner in the face of a fault, reducing downtime and production losses.

[0024] The fault contribution coefficient has the following advantages in evaluating the resource allocation priority of the circuit and improving the control efficiency of low-voltage electrical appliances: Accuracy: By evaluating the fault contribution coefficient, the importance of each circuit in fault handling can be determined more accurately, thereby allocating resources more effectively; System stability: giving priority to circuits with higher fault contribution helps improve the system's fault tolerance and stability and reduce the impact of faults on system operation; Efficiency improvement: Rationally allocating resources to circuits with higher fault contribution can quickly and effectively handle faults, improve the control efficiency of low-voltage electrical appliances, and reduce system maintenance costs and downtime; Priority determination: Fault contribution coefficient can be used as an important basis for determining the priority of circuit resource allocation, so that resources can be more concentrated on key circuits, improving the reliability and performance of the entire system; Real-time: By real-time monitoring and updating of fault contribution coefficients, resource allocation can be adjusted in a timely manner to maintain efficient operation of the system under different working conditions; Therefore, using the fault contribution coefficient to evaluate the resource allocation priority of the circuit can better improve the control efficiency of low-voltage electrical appliances and ensure the stability and reliability of the system.

[0025] The specific method for obtaining the fault contribution coefficient is as follows: Obtain fault data of low-voltage electrical appliances within a specific time interval; Calculate the historical frequency of faults based on fault data; Evaluate the impact of each fault type on the circuit based on downtime and production loss; The fault contribution coefficient is calculated based on statistical analysis in combination with the fault data, the influence coefficient of each fault type on the circuit, and the historical frequency of the fault. The fault data includes the processing time required for the fault, the cost required for the fault, the fault occurrence rate of the circuit, the fault resolution rate of the circuit, and the fault duration.

[0026] The specific calculation formula of the fault contribution coefficient is as follows:

[0027] In the formula, is the fault contribution coefficient of the jth circuit, is the historical frequency of failure, is the duration of the fault, is the cost required for the i-th failure, is the processing time required for the i-th fault, is the fault resolution rate of the jth circuit, is the failure rate of the jth circuit.

[0028] It can be seen from the calculation formula of the fault contribution coefficient that the larger the performance value of the fault contribution coefficient, the greater the resource allocation priority, and vice versa, the smaller the performance value of the fault contribution coefficient, the smaller the resource allocation priority.

[0029] Prioritizing the allocation of resources to circuits that have a greater impact on system functions and performance is based on their importance and criticality in the system; this means giving priority to those circuits that are critical to the realization of core functions, ensuring that they receive sufficient resource support to maintain their normal operation; in this way, the system can more effectively maintain the stability and reliability of its core functions, thereby improving the performance and operating efficiency of the entire system.

[0030] The function importance coefficient has the following advantages for evaluating the resource allocation priority of the circuit and improving the control efficiency of low-voltage electrical appliances: Accuracy: The function importance coefficient can accurately evaluate the importance of each circuit in the system function and performance, making resource allocation more accurate and effective; Priority determination: Based on the function importance coefficient, the priority of circuit resource allocation can be determined, giving priority to circuits that have a greater impact on system functions and performance, ensuring the normal operation of the core functions of the system; Efficiency improvement: By allocating resources preferentially to circuits with higher functional importance, the operating efficiency and response speed of the system can be improved, thereby improving the control efficiency of low-voltage electrical appliances; System stability: ensuring full support for core functional circuits helps improve system stability and reliability and prevents the occurrence and impact of system failures; Cost-effectiveness: Rationally allocating resources according to the functional importance coefficient can maximize system performance and strike a balance between cost-effectiveness, thereby achieving effective use of resources and economic efficiency of the system; Therefore, the function importance coefficient, as an important basis for evaluating the priority of circuit resource allocation, can improve the control efficiency of low-voltage electrical appliances, ensure the stable operation of the system and maximize cost-effectiveness.

[0031] The specific method for obtaining the function importance coefficient is as follows: The types of various circuit functions and the importance ratios of circuit function types are obtained through the circuit function type database. For the types of circuit functions, an evaluation model constructed by the Logistic regression analysis method is used to conduct an overall analysis of the importance of circuit functionality and obtain the function importance coefficient.

[0032] The specific calculation formula of the function importance coefficient is as follows:

[0033] In the formula is the function importance coefficient, is the type of circuit function; is the regression coefficient of each variable, is the importance ratio of the corresponding circuit function type.

[0034] From the calculation formula of the function importance coefficient, it can be seen that the larger the performance value of the function importance coefficient, the greater the resource allocation priority, and vice versa, the smaller the performance value of the function importance coefficient, the smaller the resource allocation priority.

[0035] Cost-benefit analysis is to evaluate the relationship between the cost of each circuit and its function or performance improvement, and to determine the priority of resource allocation by comparing the cost, maintenance cost and benefits of different circuits. This means that the cost of the circuits and the function or performance improvement they can bring are taken into account in resource allocation, so as to achieve a balance between cost and benefit. Through this analysis, the utilization efficiency of resources can be maximized, ensuring that the cost invested can get a reasonable return and obtaining the maximum benefit in system operation.

[0036] The cost-effectiveness factor has the following advantages for evaluating the resource allocation priority of the circuit and improving the control efficiency of low-voltage electrical appliances: Comprehensiveness: The cost-effectiveness factor can comprehensively consider the cost of each circuit and the function or performance improvement it brings, so as to comprehensively evaluate the priority of resource allocation; Reasonableness: Based on the cost-effectiveness coefficient, a more reasonable resource allocation strategy can be formulated, giving priority to investing resources in electricity that brings higher benefits, thus maximizing the utilization of resources; Economical: By evaluating the cost and benefit of the circuit, we can minimize the cost, improve resource utilization efficiency and maximize economic benefits while ensuring system performance; Risk control: Considering cost-effectiveness can help identify circuits with high costs but limited benefits and reduce their resource allocation priority accordingly, thereby reducing system operation risks; Continuous optimization: As costs and benefits change, the cost-benefit coefficient can be adjusted dynamically to continuously optimize resource allocation and ensure that the system's control efficiency is continuously improved; Therefore, the cost-effectiveness coefficient, as an important basis for evaluating the priority of power resource allocation, can effectively improve the control efficiency of low-voltage electrical appliances and realize the rational allocation of resources, thereby achieving the goal of economical, efficient and stable operation.

[0037] The specific method for obtaining the cost-effectiveness coefficient is as follows: Obtain the static power consumption and static current of the static circuit, and multiply them to establish a static power consumption model; Acquire dynamic power consumption data of the charging and discharging process during dynamic circuit switching, and establish a dynamic power consumption model based on the dynamic power consumption data, wherein the dynamic power consumption data includes load capacitance, clock frequency, and average switching times of each circuit element during the switching process; Acquire preset electrical appliance operation modes, and establish different benefit models based on different electrical appliance operation modes, wherein the electrical appliance operation modes include energy-saving mode, performance mode, and basic mode; Determine the power consumption model according to the characteristics of the circuit itself and determine the power consumption model according to the operation mode of the appliance; The cost-effectiveness coefficient is calculated based on the benefit model and power consumption model.

[0038] The dynamic power consumption model is specifically:

[0039] The static power consumption model is specifically:

[0040] The benefit model of the energy-saving mode is:

[0041] The performance mode benefit model is:

[0042] The basic mode benefit model is:

[0043] The specific calculation formula of the cost-effectiveness coefficient is:

[0044] Where P is the power consumption cost, is the load capacitance, is the circuit voltage, f is the clock frequency, is the average number of switching times of each circuit element during the switching process, is the static current; is the preset standard power consumption, Power consumption in energy-saving mode, Use time for the pattern, For maintenance costs, is the power consumption in performance mode, For performance improvement, is the basic current in basic mode, Usage of basic mode.

[0045] It can be seen from the calculation formula of the cost-effectiveness coefficient that the larger the performance value of the cost-effectiveness coefficient, the greater the priority of resource allocation. Conversely, the smaller the performance value of the cost-effectiveness coefficient, the smaller the priority of resource allocation.

[0046] In this embodiment, the circuits are classified into necessity categories according to the first circuit data, and the necessity categories include necessary circuits and non-essential circuits.

[0047] The function importance coefficient is compared with the preset necessary circuit threshold. When the function importance coefficient is greater than the necessary circuit threshold, the necessity category is marked as a necessary circuit, otherwise it is marked as a non-essential circuit.

[0048] This embodiment achieves efficient control and management of low-voltage electrical appliances by utilizing refined circuit partitioning and resource allocation methods, combined with machine learning and cost-benefit analysis. By establishing a circuit set and a three-dimensional image, simulating the necessity of load resource allocation and classifying circuits, the system can prioritize circuits that have a large impact on function and performance, and improve the system's fault tolerance and stability. At the same time, the cost-benefit analysis takes into account the cost and performance improvement of each circuit, ensuring the rational use of resources and maximizing the economic benefits of the system. This technology is expected to play an important role in achieving performance optimization, maximizing resource utilization, improving fault handling priority, and balancing economic cost benefits.

[0049] Embodiment 2: A resource allocation priority evaluation model is established based on machine learning according to the first circuit data to obtain a resource allocation coefficient.

[0050] Specifically, the calculation formula of the resource allocation coefficient is as follows:

[0051] In the formula, is the resource allocation coefficient of the jth circuit, is the preset proportionality factor of the fault contribution factor, is the preset proportional coefficient of the function importance coefficient, is the preset proportionality factor of the cost-effectiveness factor, is the fault contribution coefficient, is the function importance coefficient, is the cost-effectiveness coefficient.

[0052] In this embodiment, the circuit of the low-voltage electrical appliance is controlled according to the necessity category in combination with the resource allocation coefficient and according to the preset electrical appliance operation mode, thereby achieving control over the low-voltage electrical appliance.

[0053] Specifically, the necessary circuits and non-essential circuits of the low-voltage electrical appliances are sorted in descending order based on the resource allocation coefficients to generate a necessary circuit sorting table and a non-essential circuit sorting table; When the operation mode of the electrical appliance is energy-saving mode, the frequency of the x circuits after the necessary circuit ranking list is reduced, and no power resources are allocated to the circuits on the non-essential circuit ranking list; When the electrical appliance operation mode is the basic mode, the frequency of the x circuits after the necessary circuit ranking table is reduced, and the power resources are allocated to the first k circuits in the non-essential circuit ranking table; When the operation mode of the appliance is the performance mode, power resources are normally allocated to all circuits in the necessary circuit ranking table, and power resources are allocated to the first g circuits in the non-essential circuit ranking table.

[0054] It should be noted that the number of g is determined by the available power, and the maximum available number is taken; k and x are preset values, which are analyzed by the machine learning algorithm.

[0055] This embodiment uses machine learning to establish a resource allocation priority evaluation model, and through the calculated resource allocation coefficient, it realizes intelligent control of low-voltage electrical appliances. Combined with the preset electrical appliance operation mode, the system can adopt corresponding control strategies according to the necessity classification and resource allocation coefficient, and dynamically adjust the resource allocation of the circuit to improve the performance, energy saving and stability of the system. This intelligent control strategy not only improves the efficiency and reliability of the system, but also can be flexibly adjusted according to actual conditions to adapt to different working environments and changes in demand.

[0056] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0057] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0058] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0059] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0060] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0061] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A control method for AC / DC compatible low-voltage electrical appliances, characterized in that: The steps include: Divide the circuits of low-voltage electrical appliances and establish circuit sets; Establishing a three-dimensional image according to the circuit set, performing load resource allocation simulation on the three-dimensional image, and obtaining first circuit data, wherein the first circuit data includes circuit impact degree data and circuit benefit data; Classify the circuit into necessity categories according to the first circuit data, wherein the necessity categories include necessary circuits and non-essential circuits; Establish a resource allocation priority evaluation model based on machine learning according to the first data of the circuit to obtain a resource allocation coefficient; According to the necessity category combined with the resource allocation coefficient and based on the preset electrical operation mode, the circuit of the low-voltage electrical appliance is controlled to achieve control of the low-voltage electrical appliance.

2. The control method of AC / DC compatible low-voltage electrical appliance according to claim 1, characterized in that: The circuit impact degree data includes a fault contribution coefficient and a function importance coefficient; the circuit benefit data includes a cost benefit coefficient.

3. The control method of AC / DC compatible low voltage electrical appliance according to claim 2, characterized in that: The specific method for obtaining the cost-effectiveness coefficient is as follows: Obtain the static power consumption and static current of the static circuit, and multiply them to establish a static power consumption model; Acquire dynamic power consumption data of the charging and discharging process during dynamic circuit switching, and establish a dynamic power consumption model based on the dynamic power consumption data, wherein the dynamic power consumption data includes load capacitance, clock frequency, and average switching times of each circuit element during the switching process; Acquire preset electrical appliance operation modes, and establish different benefit models based on different electrical appliance operation modes, wherein the electrical appliance operation modes include energy-saving mode, performance mode, and basic mode; Determine the power consumption model according to the characteristics of the circuit itself and determine the power consumption model according to the operation mode of the appliance; The cost-effectiveness coefficient is calculated based on the benefit model and power consumption model.

4. The control method of AC / DC compatible low voltage electrical appliance according to claim 3, characterized in that: The specific method for obtaining the function importance coefficient is as follows: Obtain the type of each circuit function and the importance ratio of the circuit function type through the circuit function type database; For the types of circuit functions, the evaluation model constructed by the Logistic regression analysis method is used to conduct an overall analysis of the importance of circuit functionality and obtain the function importance coefficient.

5. The control method of AC / DC compatible low voltage electrical appliance according to claim 4, characterized in that: The specific method for obtaining the fault contribution coefficient is as follows: Obtain fault data of low-voltage electrical appliances within a specific time interval; Calculate the historical frequency of faults based on fault data; Evaluate the impact of each fault type on the circuit based on downtime and production loss; The fault contribution coefficient is calculated based on statistical analysis in combination with the fault data, the influence coefficient of each fault type on the circuit, and the historical frequency of the fault. The fault data includes the processing time required for the fault, the cost required for the fault, the fault occurrence rate of the circuit, the fault resolution rate of the circuit, and the fault duration.

6. The control method of AC / DC compatible low voltage electrical appliance according to claim 5, characterized in that: The circuit is classified into necessity categories according to the first circuit data, specifically: The function importance coefficient is compared with the preset necessary circuit threshold. When the function importance coefficient is greater than the necessary circuit threshold, the necessity category is marked as a necessary circuit, otherwise it is marked as a non-essential circuit.

7. The control method of AC / DC compatible low voltage electrical appliance according to claim 6, characterized in that: The circuit of the low-voltage electrical appliance is controlled according to the necessity category combined with the resource allocation coefficient and the preset electrical appliance operation mode, specifically: When the operation mode of the electrical appliance is energy-saving mode, the frequency of the x circuits after the necessary circuit ranking list is reduced, and no power resources are allocated to the circuits on the non-essential circuit ranking list; When the electrical appliance operation mode is the basic mode, the frequency of the x circuits after the necessary circuit ranking table is reduced, and the power resources are allocated to the first k circuits in the non-essential circuit ranking table; When the operation mode of the appliance is the performance mode, power resources are normally allocated to all circuits in the necessary circuit ranking table, and power resources are allocated to the first g circuits in the non-essential circuit ranking table.

8. The control method of AC / DC compatible low voltage electrical appliance according to claim 7, characterized in that: The specific calculation formula of the fault contribution coefficient is as follows: In the formula, is the fault contribution coefficient of the jth circuit, is the historical frequency of failure, is the duration of the fault, is the cost required for the i-th failure, is the processing time required for the i-th fault, is the fault resolution rate of the jth circuit, is the failure rate of the jth circuit.

9. The control method of AC / DC compatible low voltage electrical appliance according to claim 8, characterized in that: The dynamic power consumption model is specifically: The static power consumption model is specifically: The benefit model of the energy-saving mode is: The performance mode benefit model is: The basic mode benefit model is: The specific calculation formula of the cost-effectiveness coefficient is: Where P is the power consumption cost, is the load capacitance, is the circuit voltage, f is the clock frequency, is the average number of switching times of each circuit element during the switching process, is the static current; is the preset standard power consumption, Power consumption in energy-saving mode, Use time for the pattern, For maintenance costs, is the power consumption in performance mode, For performance improvement, is the basic current in basic mode, Usage of basic mode.

10. The control method of AC / DC compatible low voltage electrical appliance according to claim 9, characterized in that: The calculation formula of the resource allocation coefficient is as follows: In the formula, is the resource allocation coefficient of the jth circuit, is the preset proportionality factor of the fault contribution factor, is the preset proportional coefficient of the function importance coefficient, is the preset proportionality factor of the cost-effectiveness factor, is the fault contribution coefficient, is the function importance coefficient, is the cost-effectiveness coefficient.

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