Software and hardware combined exception protection method for starting control circuit

Abstract

The invention relates to the technical field of start-up control circuits, and discloses a software and hardware combined abnormity protection method for a start-up control circuit, which comprises the following steps of: detecting a current effective value in real time through an electric metering chip, reading the current effective value from the electric metering chip by an MCU (Microprogrammed Control Unit), and starting the start-up control circuit according to the read current effective value. The current is compared with a dynamic current threshold determined according to ambient temperature, humidity and equipment operation time. Once the current effective value is detected to exceed a set dynamic current threshold value, the MCU control unit sends a control signal through software logic to turn off the main silicon controlled rectifier so as to cut off a current path, so that damage caused by overlarge current is prevented. According to the method, the safety range under the current working condition can be reflected more accurately, so that a finer and more personalized protection strategy is provided.

Description

Technical Field

[0001] The present application relates to the technical field of startup control circuits, and more specifically, to a software-hardware combined abnormality protection method for startup control circuits. Background Art

[0002] Ensuring the safety and reliability of startup control circuits in modern electrical equipment is crucial. Traditionally, many devices have relied on simple mechanical or electronic protection mechanisms (such as PTC thermistors) to prevent overcurrent conditions. However, with technological advancements and increasingly stringent safety standards, these traditional approaches are gradually becoming increasingly limited.

[0003] First, traditional overcurrent protection measures are often based on fixed threshold settings, meaning they are unable to adapt to varying operating conditions, such as changes in temperature and humidity, as well as the aging or wear of the device itself. In practical applications, this static protection approach can result in insufficient protection in some situations and oversensitivity in others, leading to unnecessary downtime. Furthermore, these protection mechanisms often fail to consider the critical factor of device operating time, making it difficult to provide precise and personalized protection strategies, especially in applications with long periods of continuous operation or frequent starts and stops. Furthermore, most previous current detection methods focus solely on whether the effective current value exceeds a fixed threshold, ignoring other variables that may affect device safety. For example, ambient temperature and humidity can not only directly affect the operating performance of electrical equipment but can also alter the properties of materials in the circuit, indirectly affecting the actual current behavior. Furthermore, since the operating state of a device can vary significantly at different stages, relying solely on a preset current threshold for protection is clearly insufficient to cope with complex real-world operating conditions. Based on this, this application proposes a combined hardware and software abnormality protection method for startup control circuits. Summary of the Invention

[0004] In order to solve the above technical problems, the present application is proposed. The embodiment of the present application provides a software and hardware combined abnormal protection method for starting the control circuit, which uses the electricity metering chip as the core, monitors the effective value of the current in the circuit in real time, and transmits this data to the MCU control unit for analysis and processing. Unlike the previous fixed threshold setting, this method dynamically calculates a more reasonable current threshold based on factors such as ambient temperature, humidity, and the accumulated operating time of the equipment. Such a design enables the system to more accurately reflect the safety range under the current working conditions, thereby providing a more refined and personalized protection strategy.

[0005] According to one aspect of the present application, a software-hardware combined abnormal protection method for a startup control circuit is provided, comprising: detecting the effective value of current in real time through an electricity metering chip; an MCU control unit reading the effective value of current from a current register of the electricity metering chip; the MCU control unit comparing the effective value of current with a dynamic current threshold to obtain a comparison result, wherein the dynamic current threshold is determined based on ambient temperature, ambient humidity, and device operating time; in response to the comparison result being that the effective value of current is greater than or equal to the dynamic current threshold, the MCU control unit sending a control signal through software logic, wherein the control signal is used to shut down a main thyristor to cut off the current path.

[0006] In one possible implementation, the method further includes: detecting a voltage effective value in real time through an electricity metering chip; an MCU control unit reading the voltage effective value from a voltage register of the electricity metering chip; and the MCU control unit determining whether the voltage effective value is within a preset range. If the voltage effective value is not within the preset range, the MCU control unit sends a control signal through software logic, wherein the control signal is used to turn off a main thyristor to cut off a current path.

[0007] In one possible implementation, the determination of the dynamic current threshold includes: the MCU control unit obtains the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment; the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment are input into the regression model to obtain the current threshold adjustment coefficient; the MCU control unit obtains the recent effective current average value and the recent current fluctuation standard deviation; the recent effective current average value and the recent current fluctuation standard deviation are input into the regression model to obtain the current threshold modulation secondary control coefficient; based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold.

[0008] In one possible implementation, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: multiplying the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain the current threshold dynamic adjustment coefficient; multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain the current threshold floating part; adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

[0009] In one possible implementation, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: performing nonlinear cross-correlation probability coupling correction on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain an optimized current threshold adjustment coefficient and an optimized current threshold modulation secondary control coefficient; multiplying the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient to obtain a current threshold dynamic adjustment coefficient; multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain a current threshold floating part; and adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

[0010] In one possible implementation, the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are subjected to nonlinear cross-correlation probability coupling correction to obtain an optimized current threshold adjustment coefficient and an optimized current threshold modulation secondary control coefficient, including: calculating a dynamic probability coupling response value for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient; calculating a cross-correlation disturbance factor for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient; based on the dynamic probability coupling response value and the cross-correlation disturbance factor, subjecting the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to a nonlinear perturbation constraint of cross-correlation probability distribution to obtain a current threshold adjustment disturbance constraint coefficient and a current threshold modulation secondary control disturbance constraint coefficient; calculating a derivative of the dynamic probability coupling response value relative to the cross-correlation disturbance factor, and optimizing the current threshold adjustment disturbance constraint coefficient and the current threshold modulation secondary control disturbance constraint coefficient based on the derivative to obtain the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient.

[0011] In a possible implementation, the electricity metering chip is electrically connected to the MCU control unit, and the main thyristor is electrically connected to the MCU control unit.

[0012] In a possible implementation, the startup control circuit further includes a secondary thyristor electrically connected to the MCU control unit, for controlling the on / off of the startup winding.

[0013] Compared to existing technologies, the combined software and hardware abnormality protection method for the startup control circuit provided in this application uses an electricity metering chip to detect the effective current value in real time. The MCU control unit reads the effective current value from the electricity metering chip and compares it with a dynamic current threshold determined based on ambient temperature, humidity, and device operating time. Once the effective current value exceeds the set dynamic current threshold, the MCU control unit sends a control signal through software logic to shut down the main thyristor to cut off the current path, thereby preventing damage caused by excessive current. This method can more accurately reflect the safety range under current operating conditions, thereby providing a more refined and personalized protection strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other purposes, features, and advantages of the present application will become more apparent through a more detailed description of the embodiments of the present application in conjunction with the accompanying drawings. The accompanying drawings are intended to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0015] Figure 1 The figure illustrates a schematic flow chart of a software-hardware combined abnormality protection method for starting a control circuit according to an embodiment of the present application.

[0016] Figure 2 The figure illustrates a schematic flow chart of determining the dynamic current threshold in the software-hardware combined abnormal protection method for starting a control circuit according to an embodiment of the present application.

[0017] Figure 3 The figure shows a schematic flow chart of adjusting the initial current threshold to obtain the dynamic current threshold in the software-hardware combined abnormal protection method for starting the control circuit according to an embodiment of the present application.

[0018] Figure 4 The figure shows a schematic flow chart of another embodiment of adjusting the initial current threshold to obtain the dynamic current threshold in the software-hardware combined abnormal protection method for starting the control circuit according to an embodiment of the present application.

[0019] Figure 5 The figure shows a schematic principle block diagram of a startup control circuit according to an embodiment of the present application.

[0020] Figure 6 The figure shows a schematic flow chart of another embodiment of a software-hardware combined abnormal protection method for starting a control circuit according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described herein.

[0022] Figure 1 FIG2 shows a schematic flow chart of a software and hardware combined abnormal protection method for starting a control circuit according to an embodiment of the present application. Figure 1 As shown, the present application provides a software and hardware combined abnormal protection method for a startup control circuit, including: S1, real-time detection of the effective value of current through an electricity metering chip; S2, an MCU control unit reads the effective value of current from the current register of the electricity metering chip; S3, the MCU control unit compares the effective value of current with a dynamic current threshold to obtain a comparison result, wherein the dynamic current threshold is determined based on the ambient temperature, ambient humidity and device operating time; S4, in response to the comparison result that the effective value of current is greater than or equal to the dynamic current threshold, the MCU control unit sends a control signal through software logic, wherein the control signal is used to turn off the main thyristor to cut off the current path.

[0023] Specifically, the current RMS value is first detected in real time by the power metering chip. This step is the foundation of the entire protection mechanism. As a high-precision measurement tool, the power metering chip can accurately capture current changes in the circuit, which is crucial for promptly detecting potential anomalies. Next, the MCU control unit reads the current RMS value from the power metering chip's current register. Specifically, the MCU control unit establishes a communication connection with the power metering chip and periodically reads the current data stored in the current register. This design not only ensures the real-time and accuracy of the data but also allows the MCU to react quickly based on this information.

[0024] The MCU control unit then compares the read RMS current value with the dynamic current threshold. This dynamic current threshold is not fixed but is determined based on factors such as ambient temperature, humidity, and device operating time. This feature makes this protection method more intelligent and adaptable. For example, in high-temperature environments, increased resistance can cause increased current, necessitating adjustment of the current threshold to avoid misjudgment. The MCU control unit uses a preset algorithm model to calculate the appropriate dynamic current threshold based on current operating conditions and compares it with the actual measured current value.

[0025] If the comparison indicates that the RMS current is greater than or equal to the dynamic current threshold, the MCU control unit sends a control signal through software logic to shut down the main thyristor, thereby severing the current path. This allows for emergency action to protect the circuit from damage when potential hazards such as overcurrent are detected. The MCU control unit plays a crucial role in this process, not only accurately determining when to trigger the protection mechanism but also ensuring that the control signal reaches the target component quickly and effectively.

[0026] In one embodiment, Figure 2 As shown, the determination of the dynamic current threshold includes: S31, the MCU control unit obtains the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment; S32, the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment are input into the regression model to obtain the current threshold adjustment coefficient; S33, the MCU control unit obtains the recent effective current average value and the recent current fluctuation standard deviation; S34, the recent effective current average value and the recent current fluctuation standard deviation are input into the regression model to obtain the current threshold modulation secondary control coefficient; S35, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold.

[0027] Specifically, the MCU control unit collects real-time temperature and humidity data by connecting to a sensor network and records the cumulative operating time of the device since it was last started. This information helps the system understand potential risk factors under current operating conditions, such as high temperatures that may cause motor overheating or high humidity that may increase the risk of circuit short circuits.

[0028] Next, the MCU control unit inputs the real-time temperature and humidity values, as well as the accumulated device operating time, into a pre-trained regression model to calculate the current threshold adjustment coefficient. This regression model is built based on extensive historical data analysis and is designed to capture the impact of different environmental conditions on the current threshold. For example, if the current ambient temperature is high, the regression model may output a higher current threshold adjustment coefficient, indicating that a higher current can flow without triggering the protection mechanism in this environment, as the motor may exhibit different electrical characteristics due to insufficient cooling. This step ensures that the current threshold can be flexibly adjusted according to actual operating conditions, improving the system's adaptability and reliability.

[0029] At the same time, the MCU also obtains the recent average effective current and the standard deviation of recent current fluctuations. These two indicators reflect the motor's operating status over a recent period and help identify any abnormal behavior or trends. For example, a significant increase in the standard deviation of recent current fluctuations could be an early sign of impending motor failure. The MCU then inputs these current-related statistics into another regression model, which is specifically used to generate a secondary control coefficient for current threshold modulation. This coefficient is primarily used to fine-tune the initial current threshold, taking into account the short-term current trend itself rather than external environmental factors.

[0030] In one embodiment, a multiple linear regression model is used as a basic model to process the real-time temperature value, the real-time humidity value, and the accumulated operating time of the device to estimate the current threshold adjustment coefficient. The multiple linear regression model can be expressed as: ;in, Indicates the current threshold adjustment coefficient, Indicates the real-time temperature value. Indicates the real-time humidity value. Indicates the cumulative running time of the device. It is a model parameter that needs to be trained through historical data.

[0031] The multiple linear regression model is also used as the basic model to calculate the recent effective current average value and the current fluctuation standard deviation The multivariate linear regression model can be expressed as: ;in, represents the secondary control coefficient of current threshold modulation, It is a model parameter and needs to be trained based on actual data.

[0032] In another embodiment, the regression model is a neural network-based multilayer perceptron. Specifically, taking the example of inputting the real-time temperature value, the real-time humidity value, and the accumulated device runtime into a neural network-based multilayer perceptron to obtain the current threshold adjustment coefficient, the neural network will learn the mapping from input features (such as real-time temperature, humidity, and accumulated device runtime) to the output target (i.e., the current threshold adjustment coefficient). First, the input layer is defined to contain three nodes, one corresponding to the real-time temperature value, the other to the real-time humidity value, and the accumulated device runtime. After preprocessing, these input data are fed into the first layer of the neural network, i.e., the hidden layer. The hidden layer can be configured as multiple layers, each containing multiple neurons. In one specific embodiment, the first hidden layer is configured to have 64 neurons. The primary purpose of this layer is to perform preliminary processing of the input data and introduce nonlinear factors through activation functions. The choice of 64 neurons is based on experience, as it generally provides sufficient capacity to capture complex relationships between input features without excessively increasing the computational burden. The second hidden layer is reduced to 32 neurons. Reducing the number of neurons helps refine information and remove unnecessary details while maintaining the ability to learn key patterns. This architectural design simplifies the model without losing important information. The third hidden layer is further reduced to 16 neurons. This layer further condenses the information learned from previous layers to prepare for the final output. A smaller number of neurons helps avoid overfitting and ensures the model performs well even on unseen data. Each neuron performs a weighted summation operation and applies an activation function (such as ReLU or tanh) to introduce nonlinearity, which is crucial for capturing the complex interactions between input variables. The outputs of these hidden layers are then passed to the output layer, which has a single neuron and generates the predicted current threshold adjustment coefficient. Training such a neural network model requires a large historical dataset containing the actual values ​​of the current threshold adjustment coefficient under different environmental conditions. Using a backpropagation algorithm combined with a gradient descent optimization method, the connection weights between each layer in the network are gradually adjusted to ensure that the model output is as close to the actual observed values ​​as possible. Those skilled in the art will appreciate that the input of the recent effective current average and the recent current fluctuation standard deviation into the neural network-based multilayer perceptron to obtain the secondary control coefficients for current threshold modulation can be found in the model setup and training methods described above and will not be further elaborated here.

[0033] Finally, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient obtained in the above two steps, the MCU control unit makes a final adjustment to the initial current threshold, thereby determining the dynamic current threshold. Here, the initial current threshold can be set and adjusted according to actual conditions. In one embodiment, Figure 3As shown, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: S351, multiplying the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain the current threshold dynamic adjustment coefficient; S352, multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain the current threshold floating part; S353, adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

[0034] It can be seen that the current threshold adjustment coefficient is mainly regressed based on macro-environmental factors (the accumulated operating time of the device also belongs to the operating environment factors in the time series dimension), while the current threshold modulation secondary control coefficient is regressed based on the current micro-factors. Therefore, when the two are directly multiplied, there will be a dynamic balance deviation. In other words, the nonlinear cross-correlation probability between the two needs to be coupled and corrected. In other words, before the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are multiplied together, the nonlinear cross-correlation probability coupling correction of the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient needs to be performed.

[0035] Based on this, Figure 4 As shown, in another embodiment, based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: S354, performing nonlinear cross-correlation probability coupling correction on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient; S355, multiplying the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient to obtain the current threshold dynamic adjustment coefficient; S356, multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain the current threshold floating part; S357, adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

[0036] In one embodiment, the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are subjected to nonlinear cross-correlation probability coupling correction to obtain an optimized current threshold adjustment coefficient and an optimized current threshold modulation secondary control coefficient, including: first, calculating a dynamic probability coupling response value for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, where the current threshold adjustment coefficient is set to , and the current threshold modulation secondary control coefficient is , the dynamic probability coupling response is established as: ;in, represents a natural constant, Represents the dynamic probability coupling response value.

[0037] That is, under the condition that the dynamic coupling error converges by the exponential decay characteristic, the current threshold adjustment coefficient is effectively fitted by the coupled deconstruction of the threshold. and the current threshold modulation secondary control coefficient The probability response phase coupling effect.

[0038] Then, a mutual correlation disturbance factor is introduced, that is, the mutual correlation disturbance factor for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient is calculated, which is expressed as: ;in, represents the cross-correlation perturbation factor.

[0039] Next, based on the dynamic probability coupling response value and the cross-correlation disturbance factor, the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are subjected to nonlinear disturbance constraints of cross-correlation probability distribution to obtain the current threshold adjustment disturbance constraint coefficient and the current threshold modulation secondary control disturbance constraint coefficient, which are expressed as: ;in, represents the current threshold adjustment disturbance constraint coefficient, represents the current threshold modulation secondary control disturbance constraint coefficient, Represents the natural index.

[0040] This enables the nonlinear perturbation blocking of the error relative to the dynamic probability coupling response to be achieved under the action of cross-correlation perturbation.

[0041] In this way, the dynamic probability coupling response value can be Relative to the cross-correlation perturbation factor Based on the derivative of , reverse disturbance suppression based on gradient truncation is performed to optimize the current threshold adjustment disturbance constraint coefficient and the current threshold modulation secondary control disturbance constraint coefficient, That is, the derivative of the dynamic probability coupling response value with respect to the cross-correlation disturbance factor is calculated, and based on the derivative, the current threshold adjustment disturbance constraint coefficient and the current threshold modulation secondary control disturbance constraint coefficient are optimized to obtain the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient, which are expressed as: ;in, Indicates the optimized current threshold adjustment coefficient, represents the optimized current threshold modulation secondary control coefficient, represents the derivative of the dynamic probability coupling response value with respect to the cross-correlation disturbance factor.

[0042] in, based on and Expressed as: .

[0043] Thus, by suppressing the propagation of nonlinear disturbance on the coupling link based on gradient truncation, the current threshold adjustment coefficient with dynamic balance deviation is achieved. and the current threshold modulation secondary control coefficient The nonlinear mutual correlation probability coupling between them improves the accuracy of the obtained current threshold dynamic adjustment coefficient when the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are directly multiplied.

[0044] Considering that, in general, the voltage of the power system is kept relatively stable to ensure the normal operation of various electrical devices, the above embodiment uses the real-time voltage as a default value. However, in certain application scenarios, the real-time voltage may vary. Therefore, in another embodiment, the dynamic current threshold is also determined by the real-time voltage of the device. It should be understood that the operating state of electrical equipment is not only affected by ambient temperature, humidity, and operating time, but also directly depends on the state of its supply voltage. Voltage changes can directly affect the operating conditions and power consumption of the device's internal components, thereby affecting the effective value of the current. For example, at lower voltages, to maintain the same power output, the device may need to increase current to compensate, and vice versa. Therefore, taking the real-time voltage of the device into consideration allows for more precise setting of the current threshold, ensuring that even in the presence of voltage fluctuations, an accurate determination of whether there is an overcurrent risk can be made.

[0045] In one embodiment, the electric metering chip is electrically connected to the MCU control unit, the main thyristor is electrically connected to the MCU control unit, and the main thyristor is electrically connected to the main winding. The startup control circuit also includes a secondary thyristor electrically connected to the MCU control unit for controlling the on / off of the startup winding. Here, for ease of understanding, a schematic principle block diagram of the startup control circuit is also provided for the above embodiment, as shown in FIG. Figure 5 shown.

[0046] Furthermore, considering that voltage is one of the key factors affecting the normal operation of motors and other electrical equipment, if the grid voltage exceeds the rated range specified when the equipment is designed, it may cause serious damage to the equipment. Figure 6As shown, in another embodiment, the software and hardware combined abnormal protection method for starting the control circuit further includes: S5, real-time detection of the effective value of the voltage through the electricity metering chip; S6, the MCU control unit reads the effective value of the voltage from the voltage register of the electricity metering chip; S7, the MCU control unit determines whether the effective value of the voltage is within a preset range, and if the effective value of the voltage is not within the preset range, the MCU control unit sends a control signal through software logic, and the control signal is used to turn off the main thyristor to cut off the current path.

[0047] Specifically, first, the effective value of the voltage is detected in real time through the electricity metering chip. This is to capture the changes in the grid voltage in a timely manner, because voltage fluctuations may have a serious impact on motors and other electrical equipment.

[0048] The MCU control unit then reads the RMS voltage value from the voltage register of the electricity metering chip, determines whether the RMS voltage value is within a preset range, and takes action based on the determination. If the RMS voltage value exceeds the preset range, it means that the current operating conditions do not meet safety standards, and the MCU must respond quickly to avoid possible damage. Specifically, the MCU sends a control signal through software logic to shut down the main thyristor, thereby severing the current path. In one specific embodiment, the RMS voltage value is between 200V and 240V. If the grid voltage suddenly rises to 260V, exceeding the maximum voltage limit of the startup control circuit, the MCU control unit recognizes this anomaly and immediately issues a command to disconnect the main thyristor, preventing the high voltage from causing irreversible damage to the motor. This rapid response mechanism not only protects electrical equipment from overvoltage or undervoltage, but also promptly isolates the source of the fault when an abnormal condition occurs, reducing the possibility of accidents.

[0049] In summary, the combined software and hardware abnormality protection method for the startup control circuit provided in this application uses an electricity metering chip to detect the effective current value in real time. The MCU control unit reads the effective current value from the electricity metering chip and compares it with a dynamic current threshold determined based on the ambient temperature, humidity, and device operating time. Once the effective current value is detected to exceed the set dynamic current threshold, the MCU control unit sends a control signal through software logic to shut down the main thyristor to cut off the current path, thereby preventing damage caused by excessive current. This method can more accurately reflect the safety range under current operating conditions, thereby providing a more refined and personalized protection strategy.

[0050] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this application are merely illustrative and not restrictive, and it should not be assumed that these advantages, strengths, and effects are required of each embodiment of this application. In addition, the specific details disclosed above are merely illustrative and facilitating understanding, and are not restrictive. The above details do not limit this application to necessarily being implemented using the above specific details.

[0051] The block diagrams of the devices, devices, equipment, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "include," "comprise," "have," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0052] It should also be noted that in the apparatus, device, and method of the present application, each component or each step can be decomposed and / or recombined, and such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0053] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0054] The above description has been provided for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A software and hardware combined abnormal protection method for starting a control circuit, characterized in that: include: Real-time detection of the effective value of current through the electricity metering chip; The MCU control unit reads the effective value of the current from the current register of the electricity metering chip; The MCU control unit compares the effective current value with a dynamic current threshold to obtain a comparison result, wherein the dynamic current threshold is determined based on the ambient temperature, ambient humidity, and device operating time; in response to the comparison result that the effective current value is greater than or equal to the dynamic current threshold, the MCU control unit sends a control signal through software logic, and the control signal is used to turn off the main thyristor to cut off the current path.

2. The software-hardware combined abnormal protection method for starting a control circuit according to claim 1, characterized in that: Also includes: The effective value of the voltage is detected in real time by the electricity metering chip; the MCU control unit reads the effective value of the voltage from the voltage register of the electricity metering chip; The MCU control unit determines whether the effective value of the voltage is within a preset range, and if the effective value of the voltage is not within the preset range, the MCU control unit sends a control signal through software logic, and the control signal is used to turn off the main thyristor to cut off the current path.

3. The software-hardware combined abnormal protection method for starting a control circuit according to claim 1, characterized in that: The determination of the dynamic current threshold includes: the MCU control unit obtains the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment; the real-time temperature value, the real-time humidity value and the accumulated running time of the equipment are input into the regression model to obtain the current threshold adjustment coefficient; the MCU control unit obtains the recent effective current average value and the recent current fluctuation standard deviation; the recent effective current average value and the recent current fluctuation standard deviation are input into the regression model to obtain the current threshold modulation secondary control coefficient; based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold.

4. The software-hardware combined abnormal protection method for starting a control circuit according to claim 3, characterized in that: Based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: multiplying the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain the current threshold dynamic adjustment coefficient; multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain the current threshold floating part; adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

5. The software-hardware combined abnormal protection method for starting a control circuit according to claim 3, characterized in that: Based on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient, the initial current threshold is adjusted to obtain the dynamic current threshold, including: performing nonlinear cross-correlation probability coupling correction on the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to obtain an optimized current threshold adjustment coefficient and an optimized current threshold modulation secondary control coefficient; multiplying the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient to obtain a current threshold dynamic adjustment coefficient; multiplying the current threshold dynamic adjustment coefficient by the initial current threshold to obtain a current threshold floating part; and adding the current threshold floating part to the initial current threshold to obtain the dynamic current threshold.

6. The software-hardware combined abnormal protection method for starting a control circuit according to claim 5, characterized in that: The current threshold adjustment coefficient and the current threshold modulation secondary control coefficient are subjected to nonlinear cross-correlation probability coupling correction to obtain an optimized current threshold adjustment coefficient and an optimized current threshold modulation secondary control coefficient, including: calculating a dynamic probability coupling response value for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient; calculating a cross-correlation disturbance factor for the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient; based on the dynamic probability coupling response value and the cross-correlation disturbance factor, subjecting the current threshold adjustment coefficient and the current threshold modulation secondary control coefficient to a nonlinear disturbance constraint of cross-correlation probability distribution to obtain a current threshold adjustment disturbance constraint coefficient and a current threshold modulation secondary control disturbance constraint coefficient; calculating a derivative of the dynamic probability coupling response value relative to the cross-correlation disturbance factor, and optimizing the current threshold adjustment disturbance constraint coefficient and the current threshold modulation secondary control disturbance constraint coefficient based on the derivative to obtain the optimized current threshold adjustment coefficient and the optimized current threshold modulation secondary control coefficient.

7. The software-hardware combined abnormal protection method for starting a control circuit according to claim 1, characterized in that: The electricity metering chip is electrically connected to the MCU control unit, and the main thyristor is electrically connected to the MCU control unit.

8. The software-hardware combined abnormal protection method for starting a control circuit according to claim 7, characterized in that: The starting control circuit also includes a secondary thyristor electrically connected to the MCU control unit for controlling the on and off of the starting winding.

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