System for automatically adjusting output energy-saving current through induction load change of synchronous reluctance motor

Abstract

The invention relates to the technical field of motor current regulation, in particular to a synchronous reluctance motor induction load change automatic regulation output energy-saving current system, which comprises a load control unit for selecting a starting mode according to a load condition by monitoring load data of a motor in real time and predicting a change trend of a load; the compensation isolation unit performs sampling and real-time compensation according to the change trend to obtain accurate data; the dynamic protection unit is connected with the compensation isolation unit, and key components are modularly designed, so that the starting stability of the motor is improved, the high efficiency in the running process of the motor is ensured, the impact on a power grid and the motor during starting can be remarkably reduced through a soft starting mode, the service life of the motor is prolonged, and the running stability of the motor is improved. The sampling precision is improved, it is ensured that current adjustment and load control are more accurate, the reliability of the system is greatly improved through an over-current and over-temperature protection mechanism, and equipment damage or shutdown caused by faults is avoided.

Description

Technical Field

[0001] The invention relates to the technical field of motor current regulation, and in particular to a system for automatically regulating output energy-saving current with a synchronous reluctance motor inductive load change. Background Art

[0002] The synchronous reluctance motor is a highly efficient and reliable motor widely used in various industrial and commercial fields. In order to improve its performance when the load changes, it is necessary to design a system that senses the load change and automatically adjusts the output current.

[0003] The patent application number is CN202210995863.1, which states in the specification that "the present invention belongs to the field of motor control application technology, and specifically discloses a synchronous reluctance motor induction load change automatic adjustment output energy-saving current system, including a synchronous reluctance motor, a load and a current automatic adjustment output device, the synchronous reluctance motor is connected to the load and the current automatic adjustment output device respectively, wherein the current automatic adjustment output device includes a frequency sampling module, an induction module, a current loop output module, an SVPWM control module, a synchronous reluctance controller and a current sampling module. The beneficial effects of the present invention are: 1. It has the function of automatically sensing load changes, automatically adjusting the current size, and the motor output is automatically adjusted when it is unloaded. The current is extremely low, and the current is reasonable when the load is light. It essentially controls the current output to save power. Its no-load current is only 1 / 18 of that of the three-phase asynchronous motor, and the useless work is extremely low; 2. It can effectively avoid the phenomenon of rapid load changes, which leads to serious heating of the motor, thereby extending the service life of the synchronous reluctance motor. When the above technology is faced with incomplete matching between the motor and the load, the synchronous reluctance motor will have a transient large overload current at startup, resulting in increased equipment loss and impact on the power grid during the motor startup process. In addition, when the load changes rapidly, the load change has a greater impact on the current output, especially when the load changes extremely quickly, the system's response is not enough to achieve instant adjustment, which leads to overload or overheating of the motor.

[0004] In summary, the development of a system for automatically adjusting the output energy-saving current of a synchronous reluctance motor in response to load changes is still a key issue that needs to be urgently addressed in the field of motor current regulation technology. Summary of the invention

[0005] The purpose of the present invention is to solve the problem in the prior art that when the matching between the motor and the load is incomplete, the synchronous reluctance motor will have a transient large overload current at startup, resulting in increased equipment losses and impact on the power grid during the motor startup process. In addition, when the load changes rapidly, the load change has a greater impact on the current output, especially when the load changes extremely quickly, the system response is not sufficient to achieve instant adjustment, thereby causing the motor to overload or overheat.

[0006] To achieve the above object, the present invention provides a system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change, comprising:

[0007] The load control unit monitors the motor's load data in real time, predicts the load change trend, and selects the start mode based on the load conditions;

[0008] A compensation isolation unit performs sampling and real-time compensation according to the change trend to obtain accurate data;

[0009] The dynamic protection unit is connected to the compensation isolation unit, modularizes the key components, and monitors the motor temperature in real time to obtain temperature data;

[0010] The remote control unit transmits the temperature data and the current output data to an external platform, and dynamically adjusts the current output according to the load data.

[0011] Furthermore, the load control unit comprises:

[0012] A high-precision sampling module monitors the load state of the motor in real time to obtain the load data through a high-precision current sensor and a load detector, and predicts the load change trend according to the load data and automatically adjusts the output current;

[0013] The soft start module classifies the load according to the change trend, obtains the load type, and selects a suitable soft start mode according to the load type.

[0014] Furthermore, the compensating isolation unit comprises:

[0015] A data compensation module, which combines an adaptive filtering algorithm according to the change trend to achieve accurate current sampling to obtain accurate data, and processes the noise and error in the accurate data to obtain processed data;

[0016] The isolation protection module automatically enables the backup motor or switches to the backup circuit when a fault occurs according to the processed data.

[0017] Furthermore, the dynamic protection unit includes:

[0018] Modular redundancy module adopts modular design, so that key components have redundant backup function;

[0019] The dynamic temperature control module monitors the motor temperature in real time through a built-in temperature sensor and intelligently adjusts the current output based on the processed data.

[0020] Furthermore, the remote control unit comprises:

[0021] A remote monitoring module is connected to an external remote monitoring platform via a standard communication protocol to transmit the temperature data and current output data in real time;

[0022] The energy-saving optimization module combines the real-time operating status of the motor with the load data to intelligently reduce the current output when the load data is low.

[0023] Furthermore, the load control unit operation process includes:

[0024] High-precision sampling module, current data is sampled through a high-precision current sensor, and the load detector collects the load change data of the motor in real time. The load detector predicts the load change trend in real time based on the motor speed, load status and environmental conditions, combined with Kalman filtering and machine learning models. According to the load data, environmental conditions and motor working status, the load change trend is calculated, and the expected load value is given. The current output is automatically adjusted through the control algorithm. The current sampling formula is: Where I(s) is the current signal, V(s) is the voltage signal, R(s) is the resistance of the circuit, and the Kalman filter formula is: Where M is the state transfer matrix, Z is the control input matrix, L is the observation matrix, w and b w are process noise and observation noise respectively. The machine learning model formula is: L(s)=y[I(s), z(s), w(s)], where L(s) is the motor load, I(s) is the current, z(s) is the speed, w(s) is the temperature, y(·) is the model obtained through training, and the current regulation formula is: Where A is the current regulation coefficient, p is the bias value, is the load forecast, I out (s) is the current output.

[0025] Furthermore, the load control unit operation process includes:

[0026] The soft start module selects the appropriate start mode such as gradual acceleration and current limiting start according to the real-time start mode request and load data of the motor. For the lighter load data, the low start current mode is selected to gradually increase the motor speed; for the heavier load data, a high starting current is used and the current limiting adjustment is gradually made. During the start process, the current change is monitored in real time, the current output is adjusted, and the load adaptive soft start is realized to gradually reach the set working state. The start formula is gradually accelerated: where y max is the maximum speed, μ is the time constant, I start Is the starting current, current limiting starting formula: I(s)=min[I max ,u start ·L(s)], where Imax is the maximum current at startup, u start is a load-dependent constant.

[0027] Furthermore, the operation process of the compensation isolation unit includes:

[0028] The data compensation module uses an adaptive filtering algorithm to suppress the noise in the change trend, and corrects the error caused by the current sensor error or system drift, and corrects the instantaneous deviation in the change trend in real time, and outputs accurate current data for subsequent current regulation and load control. The state update formula is: Where R j is the Kalman gain, D is the observation matrix, is the predicted value, current compensation formula: I cod (s) = I(s) - ε·∈(s), where ε is the learning rate, ∈(s) is the estimated error, and the noise suppression formula is: Where X fid (s) is the filter time constant, X raw (s) is the current sampling signal including noise z(δ);

[0029] The isolation protection module monitors the processed data in real time. When the current exceeds the limit, the temperature is too high or an abnormality occurs, the protection mechanism is triggered. The fault type is automatically diagnosed and corresponding measures are taken through a multi-level protection strategy. When a fault occurs, the isolation protection module automatically switches to the backup circuit or enables the backup motor. The overcurrent protection formula is: When the current exceeds the set threshold, the overcurrent protection is triggered. The overtemperature protection formula is: Fault overhead =W(s)>W threshold When the motor temperature exceeds the set threshold W threshold , triggering over-temperature protection, fault isolation switching formula: I out =Switch(Fault detected )·I backup , where I backup It is the current of the backup circuit. When a fault occurs, the system will automatically switch to the backup circuit.

[0030] Furthermore, the dynamic protection unit operation process includes:

[0031] Modular redundancy module adopts modular design. Each key component has redundant backup. When the processed data of a module is detected to be abnormal, the system will automatically enable the redundant backup module and report the module failure to the user. The module redundancy switching formula is:

[0032] in It indicates whether module M1 is faulty;

[0033] The dynamic temperature control module monitors the working temperature of the motor in real time. When the motor temperature approaches the preset overheating threshold, the motor temperature is lowered by reducing the current output or starting the external cooling system. When the load is low, the current output is reduced to reduce the heat generation. The temperature and current adjustment formula is: Where W min and W max are the minimum and maximum temperature thresholds, I nominal is the rated current, the cooling system enables the formula:

[0034] D(s)=D(s)-β cool ·[D(s)-D ambient ], where D ambient is the ambient temperature, β cool is the cooling efficiency.

[0035] Furthermore, the remote control unit operation process includes:

[0036] The remote monitoring module transmits the temperature data and current output data to an external monitoring platform through a standard communication protocol. The user can view the operating status of the device through the remote platform and make adjustments as needed. The data transmission formula is: P(s) = Protocol (T(s)), where Protocol represents the communication protocol, T(s) is the real-time data of the device, and P(s) is the external remote platform;

[0037] The energy-saving optimization module dynamically adjusts the current output based on the load data of the motor and the real-time operating status of the motor through fuzzy logic and AI optimization algorithm, and intelligently adjusts the current output when light load or no load. The energy efficiency optimization formula is: I oped (s)=I nominal β(F(s)), where β(F(s)) is the optimal efficiency function under load, F(s) is the motor load, β(F) is the efficiency curve, and I oped (s) is the intelligent optimization current output, load optimization control formula:

[0038] Where F(s) is the load, β target is the target efficiency, I dt (s) is the dynamically adjusted current output.

[0039] Beneficial Effects

[0040] Compared with the known public technology, the technical solution provided by the present invention has the following advantages:

[0041] Beneficial effects:

[0042] The present invention not only helps to improve the smoothness of motor starting, but also ensures the high efficiency during motor operation. The soft starting method can significantly reduce the impact on the power grid and the motor during startup, improve the life and operating stability of the motor, and help to improve the sampling accuracy, ensuring that current regulation and load control are more accurate. The over-current and over-temperature protection mechanisms greatly improve the reliability of the system and avoid equipment damage or shutdown due to faults.

[0043] The present invention greatly improves the reliability and fault tolerance of the system, and is particularly suitable for industrial environments that have high requirements for equipment stability. It avoids damage to the motor due to overheating or a decrease in efficiency, thereby extending the service life of the equipment. It helps users to promptly discover potential problems and remotely adjust the system to avoid equipment shutdown due to failures, thereby improving equipment management efficiency. By automatically adjusting current output, it reduces ineffective motor operation, significantly reduces energy consumption, and improves overall energy efficiency. The remote control function allows users to easily manage multiple devices, reduces operation and maintenance costs, and improves management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a system diagram of the system of the synchronous reluctance motor according to the present invention that automatically adjusts the output energy-saving current by sensing load changes. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0046] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0047] The present invention is further described in detail with reference to the accompanying drawings:

[0048] Example:

[0049] like Figure 1 As shown, the present invention provides a system for automatically adjusting the output energy-saving current of a synchronous reluctance motor inductive load change, comprising: a load control unit, which monitors the load data of the motor in real time, predicts the load change trend, and selects a start mode according to the load condition;

[0050] The load control unit includes:

[0051] A high-precision sampling module monitors the load state of the motor in real time to obtain the load data through a high-precision current sensor and a load detector, and predicts the load change trend according to the load data and automatically adjusts the output current;

[0052] A soft start module, which classifies the load according to the change trend, obtains the load type and selects a suitable soft start mode according to the load type;

[0053] The load control unit operation process includes:

[0054] High-precision sampling module, current data is sampled through a high-precision current sensor, and the load detector collects the load change data of the motor in real time. The load detector predicts the load change trend in real time based on the motor speed, load status and environmental conditions, combined with Kalman filtering and machine learning models. According to the load data, environmental conditions and motor working status, the load change trend is calculated, and the expected load value is given. The current output is automatically adjusted through the control algorithm. The current sampling formula is: Where I(s) is the current signal, V(s) is the voltage signal, R(s) is the resistance of the circuit, and the Kalman filter formula is: Where M is the state transfer matrix, Z is the control input matrix, L is the observation matrix, w and b w are process noise and observation noise respectively. The machine learning model formula is: L(s)=y[I(s), z(s), w(s)], where L(s) is the motor load, I(s) is the current, z(s) is the speed, w(s) is the temperature, y(·) is the model obtained through training, and the current regulation formula is: Where A is the current regulation coefficient, p is the bias value, is the load forecast, I out (s) is the current output;

[0055] The soft start module selects the appropriate start mode such as gradual acceleration and current limiting start according to the real-time start mode request and load data of the motor. For the lighter load data, the low start current mode is selected to gradually increase the motor speed; for the heavier load data, a high starting current is used and the current limiting adjustment is gradually made. During the start process, the current change is monitored in real time, the current output is adjusted, and the load adaptive soft start is realized to gradually reach the set working state. The start formula is gradually accelerated: where y max is the maximum speed, μ is the time constant, I start Is the starting current, current limiting starting formula: I(s)=min[I max ,u start ·L(s)], where I max is the maximum current at startup, u start is a constant related to the load;

[0056] Specifically, the high-precision sampling module monitors the load status of the motor in real time through high-precision current sensors and load detectors, and predicts the load change trend based on the collected load data. The soft start module selects the appropriate start mode based on the real-time start mode request of the motor and the load data. During the startup process, the appropriate starting current mode is selected according to the different characteristics of the load, and the current changes are monitored in real time, and the current output is dynamically adjusted to achieve load-adaptive soft start. This not only helps to improve the smoothness of the motor start-up, but also ensures the high efficiency of the motor during operation. The soft start method can significantly reduce the impact on the power grid and motor during startup, and improve the life and operation stability of the motor.

[0057] A compensation isolation unit performs sampling and real-time compensation according to the change trend to obtain accurate data;

[0058] The compensation isolation unit includes:

[0059] A data compensation module, which combines an adaptive filtering algorithm according to the change trend to achieve accurate current sampling to obtain accurate data, and processes the noise and error in the accurate data to obtain processed data;

[0060] an isolation protection module, which automatically enables a backup motor or switches to a backup circuit in the event of a fault according to the processed data;

[0061] The operation process of the compensation isolation unit includes:

[0062] The data compensation module uses an adaptive filtering algorithm to suppress the noise in the change trend, and corrects the error caused by the current sensor error or system drift, and corrects the instantaneous deviation in the change trend in real time, and outputs accurate current data for subsequent current regulation and load control. The state update formula is: Where R j is the Kalman gain, D is the observation matrix, is the predicted value, current compensation formula: I cod (s) = I(s) - ε·∈(s), where ε is the learning rate, ∈(s) is the estimated error, and the noise suppression formula is: Where X fid (s) is the filter time constant, X raw (s) is the current sampling signal including noise z(δ);

[0063] The isolation protection module monitors the processed data in real time. When the current exceeds the limit, the temperature is too high or an abnormality occurs, the protection mechanism is triggered. The fault type is automatically diagnosed and corresponding measures are taken through a multi-level protection strategy. When a fault occurs, the isolation protection module automatically switches to the backup circuit or enables the backup motor. The overcurrent protection formula is: When the current exceeds the set threshold, the overcurrent protection is triggered. The overtemperature protection formula is: Fault overhead =W(s)>W threshold When the motor temperature exceeds the set threshold W threshold , triggering over-temperature protection, fault isolation switching formula: I out =Switch(Fault detected )·I backup , where I backup It is the current of the backup circuit. When a fault occurs, the system will automatically switch to the backup circuit.

[0064] Specifically, first, the current signal in the changing trend is sampled and compensated in real time through the data compensation module to eliminate the impact caused by current sensor error or system drift, and at the same time, the instantaneous deviation is corrected into accurate current data. The compensated current and temperature data are monitored in real time through the isolation protection module, and the protection mechanism is automatically triggered when over-current or over-temperature abnormalities are detected to avoid damage to the main motor or the power grid, which is conducive to improving the sampling accuracy and ensuring more accurate current regulation and load control. The over-current and over-temperature protection mechanisms greatly improve the reliability of the system and avoid equipment damage or shutdown due to faults.

[0065] The dynamic protection unit is connected to the compensation isolation unit, modularizes the key components, and monitors the motor temperature in real time to obtain temperature data;

[0066] The dynamic protection unit includes:

[0067] Modular redundancy module adopts modular design, so that key components have redundant backup function;

[0068] Dynamic temperature control module, which monitors the motor temperature in real time through a built-in temperature sensor and intelligently adjusts the current output based on the processed data;

[0069] The dynamic protection unit operation process includes:

[0070] Modular redundancy module adopts modular design. Each key component has redundant backup. When the processed data of a module is detected to be abnormal, the system will automatically enable the redundant backup module and report the module failure to the user. The module redundancy switching formula is:

[0071] in It indicates whether module M1 is faulty;

[0072] The dynamic temperature control module monitors the working temperature of the motor in real time. When the motor temperature approaches the preset overheating threshold, the motor temperature is lowered by reducing the current output or starting the external cooling system. When the load is low, the current output is reduced to reduce the heat generation. The temperature and current adjustment formula is: Where W min and W max are the minimum and maximum temperature thresholds, I nominal is the rated current, the cooling system enables the formula:

[0073] D(s)=D(s)-β cool ·[D(s)-D ambient ], where D ambient is the ambient temperature, β cool is the cooling efficiency;

[0074] Specifically, when a failure is detected in a key module in the motor system, such as a current sensor or a temperature sensor, the system will automatically switch to a redundant backup module to ensure that the motor system does not stop running due to a failure in a certain module. The dynamic temperature control module monitors the temperature of the motor in real time and reduces the motor temperature by reducing the current output or starting an external cooling system when the temperature approaches the overheating threshold. When the load is low, the current output is reduced to reduce heat generation, thereby effectively controlling the temperature of the motor. This greatly improves the reliability and fault tolerance of the system, and is especially suitable for industrial environments that have high requirements for equipment stability. It avoids damage to the motor or a decrease in efficiency due to overheating, thereby extending the service life of the equipment.

[0075] A remote control unit transmits the temperature data and current output data to an external platform and dynamically adjusts the current output according to the load data;

[0076] The remote control unit includes:

[0077] A remote monitoring module is connected to an external remote monitoring platform via a standard communication protocol to transmit the temperature data and current output data in real time;

[0078] The energy-saving optimization module combines the real-time running status of the motor with the load data to intelligently reduce the current output when the load data is low;

[0079] The remote control unit operation process includes:

[0080] The remote monitoring module transmits the temperature data and current output data to an external monitoring platform through a standard communication protocol. The user can view the operating status of the device through the remote platform and make adjustments as needed. The data transmission formula is: P(s) = Protocol (T(s)), where Protocol represents the communication protocol, T(s) is the real-time data of the device, and P(s) is the external remote platform;

[0081] The energy-saving optimization module dynamically adjusts the current output based on the load data of the motor and the real-time operating status of the motor through fuzzy logic and AI optimization algorithm, and intelligently adjusts the current output when light load or no load. The energy efficiency optimization formula is: I oped (s)=I nominal β(F(s)), where β(F(s)) is the optimal efficiency function under load, F(s) is the motor load, β(F) is the efficiency curve, and I oped (s) is the intelligent optimization current output, load optimization control formula:

[0082] Where F(s) is the load, β target is the target efficiency, I dt (s) is the dynamic adjustment of current output;

[0083] Specifically, the remote monitoring module transmits the real-time temperature data and current output data of the motor to an external remote platform through standard communication protocols such as Modbus and TCP / IP. Users can view the real-time data of the motor through the external platform and make remote adjustments as needed, such as adjusting the current output and starting the cooling system. The energy-saving optimization module intelligently adjusts the current output according to the real-time load data and working status of the motor. For example, when the load is low, the system will reduce the current output to avoid excessive energy waste. This helps users to detect potential problems in time and adjust the system remotely to avoid equipment shutdown due to faults and improve equipment management efficiency. By automatically adjusting the current output, the ineffective operation of the motor is reduced, energy consumption is significantly reduced, and overall energy efficiency is improved. The remote control function allows users to easily manage multiple devices, reduce operation and maintenance costs, and improve management efficiency.

[0084] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The synchronous reluctance motor automatically adjusts the output energy-saving current system by induction load changes, characterized in that: include: The load control unit monitors the motor's load data in real time, predicts the load change trend, and selects the start mode based on the load conditions; A compensation isolation unit performs sampling and real-time compensation according to the change trend to obtain accurate data; The dynamic protection unit is connected to the compensation isolation unit, modularizes the key components, and monitors the motor temperature in real time to obtain temperature data; The remote control unit transmits the temperature data and the current output data to an external platform, and dynamically adjusts the current output according to the load data.

2. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 1 is characterized in that: The load control unit includes: A high-precision sampling module monitors the load state of the motor in real time to obtain the load data through a high-precision current sensor and a load detector, and predicts the load change trend according to the load data and automatically adjusts the output current; The soft start module classifies the load according to the change trend, obtains the load type, and selects a suitable soft start mode according to the load type.

3. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 2 is characterized in that: The compensation isolation unit includes: A data compensation module, which combines an adaptive filtering algorithm according to the change trend to achieve accurate current sampling to obtain accurate data, and processes the noise and error in the accurate data to obtain processed data; The isolation protection module automatically enables the backup motor or switches to the backup circuit when a fault occurs according to the processed data.

4. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 3 is characterized in that: The dynamic protection unit includes: Modular redundancy module adopts modular design to make key components have redundant backup function; The dynamic temperature control module monitors the motor temperature in real time through a built-in temperature sensor and intelligently adjusts the current output based on the processed data.

5. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 4 is characterized in that: The remote control unit includes: A remote monitoring module is connected to an external remote monitoring platform via a standard communication protocol to transmit the temperature data and current output data in real time; The energy-saving optimization module combines the real-time operating status of the motor with the load data to intelligently reduce the current output when the load data is low.

6. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 5 is characterized in that: The load control unit operation process includes: High-precision sampling module, current data is sampled through a high-precision current sensor, and the load detector collects the load change data of the motor in real time. The load detector predicts the load change trend in real time based on the motor speed, load status and environmental conditions, combined with Kalman filtering and machine learning models. According to the load data, environmental conditions and motor working status, the load change trend is calculated, and the expected load value is given. The current output is automatically adjusted through the control algorithm. The current sampling formula is: Where I(s) is the current signal, V(s) is the voltage signal, R(s) is the resistance of the circuit, and the Kalman filter formula is: Where M is the state transfer matrix, Z is the control input matrix, L is the observation matrix, w and b w are process noise and observation noise respectively. The machine learning model formula is: L(s)=y[I(s), z(s), w(s)], where L(s) is the motor load, I(s) is the current, z(s) is the speed, w(s) is the temperature, y(·) is the model obtained through training, and the current regulation formula is: Where A is the current regulation coefficient, p is the bias value, is the load forecast, I out (s) is the current output.

7. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 6 is characterized in that: The load control unit operation process includes: The soft start module selects the appropriate start mode such as gradual acceleration and current limiting start according to the real-time start mode request and load data of the motor. For the lighter load data, the low start current mode is selected to gradually increase the motor speed; for the heavier load data, a high starting current is used and the current limiting adjustment is gradually made. During the start process, the current change is monitored in real time, the current output is adjusted, and the load adaptive soft start is realized to gradually reach the set working state. The start formula is gradually accelerated: where y max is the maximum speed, μ is the time constant, I start is the starting current, current limiting starting formula: I(s)=min[I max ,u start ·L(s)], where I max is the maximum current at startup, u start is a load-dependent constant.

8. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 7 is characterized in that: The operation process of the compensation isolation unit includes: The data compensation module uses an adaptive filtering algorithm to suppress the noise in the change trend, and corrects the error caused by the current sensor error or system drift, and corrects the instantaneous deviation in the change trend in real time, and outputs accurate current data for subsequent current regulation and load control. The state update formula is: Where R j is the Kalman gain, D is the observation matrix, is the predicted value, current compensation formula: I cod (s) = I(s) - ε·∈(s), where ε is the learning rate, ∈(s) is the estimated error, and the noise suppression formula is: Where X fid (s) is the filtering time constant, X raw (s) is the current sampling signal including noise z(δ); The isolation protection module monitors the processed data in real time. When the current exceeds the limit, the temperature is too high or an abnormality occurs, the protection mechanism is triggered. The fault type is automatically diagnosed and corresponding measures are taken through a multi-level protection strategy. When a fault occurs, the isolation protection module automatically switches to the backup circuit or enables the backup motor. The overcurrent protection formula is: When the current exceeds the set threshold, the overcurrent protection is triggered. The overtemperature protection formula is: Fault overhead =W(s)>W threshold When the motor temperature exceeds the set threshold W threshold , triggering over-temperature protection, fault isolation switching formula: I out =Switch(Fault detected )·I backup , where I backup It is the current of the backup circuit. When a fault occurs, the system will automatically switch to the backup circuit.

9. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 8, characterized in that: The dynamic protection unit operation process includes: Modular redundancy module adopts modular design. Each key component has redundant backup. When the processed data of a module is detected to be abnormal, the system will automatically enable the redundant backup module and report the module failure to the user. The module redundancy switching formula is: in It indicates whether module M1 is faulty; The dynamic temperature control module monitors the working temperature of the motor in real time. When the motor temperature approaches the preset overheating threshold, the motor temperature is lowered by reducing the current output or starting the external cooling system. When the load is low, the current output is reduced to reduce the heat generation. The temperature and current adjustment formula is: Where W min and W max are the minimum and maximum temperature thresholds, I nominal is the rated current, the cooling system enables the formula: D(s)=D(s)-β cool ·[D(s)-D ambient ], where D ambient is the ambient temperature, β cool is the cooling efficiency.

10. The system for automatically adjusting output energy-saving current of a synchronous reluctance motor inductive load change according to claim 9, characterized in that: The remote control unit operation process includes: The remote monitoring module transmits the temperature data and current output data to an external monitoring platform through a standard communication protocol. The user can view the operating status of the device through the remote platform and make adjustments as needed. The data transmission formula is: P(s) = Protocol (T(s)), where Protocol represents the communication protocol, T(s) is the real-time data of the device, and P(s) is the external remote platform; The energy-saving optimization module dynamically adjusts the current output based on the load data of the motor and the real-time operating status of the motor through fuzzy logic and AI optimization algorithm, and intelligently adjusts the current output when light load or no load. The energy efficiency optimization formula is: I oped (s)=I nominal β(F(s)), where β(F(s)) is the optimal efficiency function under load, F(s) is the motor load, β(F) is the efficiency curve, and I oped (s) is the intelligent optimization current output, load optimization control formula: Where F(s) is the load, β target is the target efficiency, I dt (s) is the dynamically adjusted current output.

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