A method and system for motor start control regulation

Abstract

The present application relates to the motor adjustment technical field, specifically for a kind of motor starting control adjustment method and system, in the present application, real-time acquisition motor operating parameter and estimate real-time load torque estimate value, immediately based on the estimate value synchronous execution dynamic starting voltage regulation and adaptive starting time optimization, voltage regulation is quickly determined optimum starting voltage by inquiring mapping relationship, ensure that output torque accurately matches load demand;Time optimization is then according to the instantaneous change rate of real-time load torque estimate value dynamically adjusts starting duration, to adapt to different working conditions;Finally, combined with the change trend of real-time load torque estimate value generates comprehensive control instruction, so that voltage and time parameter cooperate, jointly realize the beneficial effect that starting process is smooth, energy efficiency is promoted and reliability is enhanced.

Description

Technical Field

[0001] This invention relates to the field of motor regulation technology, specifically to a motor starting control and regulation method and system. Background Technology

[0002] In the field of motor starting control, traditional starting methods typically rely on fixed starting voltage settings or control strategies based on simple timing. While these methods may barely meet basic requirements under relatively stable load conditions, in actual industrial applications, the load torque of a motor often exhibits dynamic characteristics. For example, due to the nonlinearity of the mechanical transmission system, random fluctuations in the workload, or interference from environmental factors, fixed-parameter starting schemes are difficult to adapt effectively. Although some existing technologies attempt to adjust the starting process by monitoring current or speed signals, these methods often suffer from response lag, failing to accurately capture instantaneous changes in load torque in real time. This can easily lead to drawbacks such as excessive starting inrush current, increased mechanical stress, or excessively long starting times.

[0003] Furthermore, traditional startup time settings are mostly based on offline calculations or empirical values, lacking the ability to dynamically respond to real-time load conditions. This can lead to redundant startup time under light load conditions, reducing overall efficiency, or startup failure risk due to insufficient startup time under heavy load scenarios. Another common limitation is that the selection of startup voltage is usually too conservative to ensure startup reliability, but this leads to unnecessary increases in energy consumption and heat accumulation. Although some advanced solutions employ closed-loop control mechanisms, such as designs based on PID controllers, their parameter tuning is complex and their adaptability to nonlinear loads is poor, making it difficult to maintain optimal performance under varying load conditions. Therefore, existing technologies generally suffer from insufficient smoothness in the startup process, low energy efficiency, and poor reliability, urgently requiring an intelligent control method that can sense load changes in real time and dynamically adjust key parameters. Summary of the Invention

[0004] The purpose of this invention is to provide a motor starting control and regulation method and system to solve the problems mentioned in the background art. Specific technical problems include how to synchronously execute dynamic starting voltage regulation and adaptive starting time optimization based on real-time load torque estimates, in order to solve the problems of uneven starting, low efficiency, and poor reliability caused by dynamic changes in load torque during motor starting.

[0005] To achieve the above objectives, one objective of this invention is a motor starting control and adjustment method, comprising the following steps:

[0006] S1. Real-time acquisition of motor operating parameters, including stator voltage, stator current, and rotor speed. By acquiring these key operating parameters in real time, a highly timely data foundation is provided for subsequent precise control. This step solves the problem of failing to perceive instantaneous load changes due to reliance on fixed parameters or lagging signals. Its effect is to ensure that the input information of the entire control system accurately reflects the current dynamic operating state of the motor, creating the preconditions for accurate load torque estimation and adaptive adjustment, thereby preventing control mismatch caused by inaccurate or delayed information from the outset.

[0007] S2. Based on the operating parameters, perform real-time load torque estimation to obtain the real-time load torque estimate. The calculation process for the real-time load torque estimate includes:

[0008] The operating parameters are substituted into a pre-established motor state-space model, and the Luneburg state observer is used for calculation to output a real-time load torque estimate; where:

[0009] The motor state-space model is composed of the motor's voltage equation, motion equation, and torque equation. The voltage equation describes the relationship between the motor's stator voltage, stator current, and rotor speed. The motion equation describes the relationship between the motor's electromagnetic torque, load torque, and rotor speed. The torque equation describes the relationship between the motor's electromagnetic torque and stator current.

[0010] The calculation process of the Luneburg state observer specifically includes:

[0011] The predicted values ​​of state variables are calculated based on the operating parameters and the motor state-space model; the predicted values ​​are compared with the measured values ​​of the sensors to obtain the difference signal; the difference signal is multiplied by the pre-calculated optimal feedback gain matrix to generate the compensation amount, and the predicted state of the motor state-space model is corrected in a closed loop.

[0012] Step S2 utilizes a state-space model based on the physical laws of motors and a Luneburg state observer to perform real-time and accurate estimation of load torque, which cannot be directly measured. Its technical advantage lies in transforming easily measurable electrical parameters (voltage, current) and mechanical parameters (speed) into crucial load torque information that is difficult to obtain directly. Furthermore, it effectively suppresses interference from model errors and measurement noise through a closed-loop correction mechanism, thereby outputting a highly reliable real-time load torque estimate. This step solves the core problem of the unknowable or inaccurate estimation of key state variables (load torque) in the control system, providing a precise basis for subsequent intelligent decision-making.

[0013] S3. Based on the real-time load torque estimate, perform dynamic starting voltage adjustment. The optimal starting voltage is dynamically calculated and output by querying a preset voltage-torque mapping relationship. The calculation process for the optimal starting voltage specifically includes:

[0014] The real-time load torque estimate is compared with the load torque sequence arranged in ascending order in the preset voltage and torque mapping table. The optimal starting voltage is calculated and output using a linear interpolation algorithm.

[0015] Based on real-time load torque estimates, adaptive start-up time optimization is performed synchronously. By analyzing the instantaneous rate of change of the real-time load torque estimates, the duration of the motor start-up process is dynamically adjusted to obtain optimized start-up time parameters. The specific process of generating start-up time parameters includes:

[0016] The instantaneous rate of change is obtained by performing first-order backward difference calculation on the real-time load torque estimate obtained within the continuous control cycle.

[0017] The absolute value of the instantaneous rate of change is compared with a preset positive threshold.

[0018] When the absolute value of the instantaneous rate of change is greater than a positive threshold, the current total duration is increased by a predetermined fixed time increment.

[0019] When the absolute value of the instantaneous rate of change is less than or equal to a positive threshold, the current total duration is reduced by a predetermined fixed time increment.

[0020] During the initialization and operation of the entire startup phase, the total duration after each adjustment is used as the benchmark for the next adjustment, and the final determined total duration is used as the optimized startup time parameter.

[0021] Step S3 is the core of the collaborative optimization based on real-time load torque estimation. Its effect is reflected in two aspects executed simultaneously. On the one hand, dynamic starting voltage adjustment is performed. By querying a preset mapping table and using linear interpolation, the optimal starting voltage that precisely matches the real-time load torque can be quickly determined. This ensures that the motor output torque always matches the load demand, effectively solving the problem of starting shock or insufficient torque caused by improper voltage setting. On the other hand, adaptive starting time optimization is performed. By analyzing the instantaneous rate of change of load torque, the total starting time is dynamically adjusted. When the load changes drastically, the starting process is automatically extended to ensure smoothness, and when the change is gradual, the time is shortened to improve efficiency. The simultaneous execution of these two aspects jointly solves the problems of uneven starting and low energy efficiency caused by the inability of fixed parameter control to adapt to dynamic load changes.

[0022] S4. Based on the optimal starting voltage and starting time parameters, and according to the changing trend of the real-time load torque estimate, generate comprehensive control commands to drive the motor to complete the starting process, wherein:

[0023] The specific trends in the real-time load torque estimate include:

[0024] Set a judgment window that contains a continuous number of preset control cycles;

[0025] Calculate the change in the estimated real-time load torque at the current moment relative to the value at the previous moment, and record the change within the judgment window;

[0026] If all changes recorded in the judgment window are positive, then it is determined to be an increasing trend;

[0027] If all changes recorded in the judgment window are negative, then it is determined to be a decreasing trend;

[0028] If the changes recorded in the judgment window contain both positive and negative values, it is judged as a fluctuation trend.

[0029] The process of generating integrated control commands specifically includes:

[0030] For an increasing trend, a positive offset is added to the optimal startup voltage in the first half of the startup process time axis, and the positive offset is linearly reduced to zero in the second half of the startup process time axis; for a decreasing trend, a negative offset is subtracted from the optimal startup voltage in the first half of the startup process time axis, and the negative offset is linearly reduced to zero in the second half of the startup process time axis; for a fluctuating trend, the output voltage is maintained equal to the optimal startup voltage.

[0031] Step S4 further introduces a forward-looking judgment on the load torque change trend and generates the final integrated control command accordingly. Its technical effect is that it can identify whether the load is in an increasing, decreasing or fluctuating trend, and apply intelligent feedforward compensation to the starting voltage reference for different trends (such as appropriately increasing the voltage in the early stage of an increasing trend to offset the load growth inertia), thereby achieving proactive adaptation to short-term changes in the load rather than passive response. This step effectively solves the problem of late-stage adjustment lag and disruption of smoothness in the starting process that may be caused by sudden changes in load trend, significantly improves the robustness and reliability of the starting process, and ensures that a smooth and efficient torque output can be achieved throughout the optimized starting time.

[0032] The second objective of this invention is to provide a system for a motor starting control and adjustment method, comprising a parameter acquisition module, a load torque estimation module, an adaptive starting optimization module, and a comprehensive control command module, wherein:

[0033] The parameter acquisition module acquires the motor's operating parameters in real time;

[0034] The load torque estimation module performs real-time load torque estimation based on operating parameters to obtain real-time load torque estimates.

[0035] The adaptive start-up optimization module performs dynamic start-up voltage adjustment based on real-time load torque estimation. It dynamically calculates and outputs the optimal start-up voltage by querying the preset voltage-torque mapping relationship.

[0036] The adaptive start-up optimization module performs adaptive start-up time optimization synchronously based on the real-time load torque estimate. It dynamically adjusts the duration of the motor start-up process by analyzing the instantaneous change rate of the real-time load torque estimate, and obtains the optimized start-up time parameters.

[0037] The integrated control command module generates integrated control commands to drive the motor to complete the starting process based on the optimal starting voltage and starting time parameters and the changing trend of the real-time load torque estimate.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] By accurately estimating the load torque in real time, and dynamically adjusting the starting voltage and optimizing the starting time in a synchronous and coordinated manner, the motor can actively adapt to the real-time changes and trends of the load during the starting process. This effectively solves the problems of large starting impact, poor smoothness, high energy consumption and insufficient reliability caused by fixed parameters and lag in traditional methods. It achieves a high degree of unity between smooth starting process, improved energy efficiency and strong adaptability. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the overall method steps of the present invention;

[0041] Figure 2 This is a schematic diagram of the core process of step S3 of the present invention;

[0042] Figure 3 This is a schematic diagram of the overall module flow of the present invention.

[0043] In the diagram: 100, parameter acquisition module; 200, load torque estimation module; 300, adaptive start-up optimization module; 400, integrated control command module. Detailed Implementation

[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] Next, please refer to Figure 1 One of the objectives of this embodiment is to provide a method for controlling and adjusting the starting of a motor.

[0046] The specific steps are as follows:

[0047] S1. Real-time acquisition of motor operating parameters, specifically including:

[0048] The acquired operating parameters mainly include the electrical and mechanical parameters of the motor. Among the electrical parameters, the stator current is the key acquisition target because it directly reflects the trend of the motor's load torque change. At the same time, the stator voltage of the stator winding is also monitored synchronously to calculate the real-time input power of the motor and help determine its operating point. The mechanical parameters are centered on the rotor speed of the motor, which directly reflects the actual operating state of the motor rotor.

[0049] Electrical and mechanical parameters are not acquired independently, but synchronously through a dedicated sensor array deployed on the motor body and drive circuit. For example, current transformers or Hall effect current sensors are used to measure stator current in isolation to ensure safety and accuracy. Photoelectric encoders or magnetoelectric speed sensors are used to capture changes in the rotational speed of the motor shaft in real time. All analog signals output by the sensors are processed by signal conditioning circuits, including filtering to eliminate high-frequency interference and amplification to match the input range of the sampling circuit. Finally, the analog-to-digital converter in the control unit converts the signals into discrete digital signal sequences at a preset high sampling frequency. This combination of hardware and software constitutes the physical basis for data acquisition.

[0050] S2. To achieve dynamic sensing of the motor load status, real-time load torque estimation is performed based on operating parameters to obtain the real-time load torque estimate. The real-time load torque estimate specifically includes:

[0051] The real-time collected operating parameters are used as input and substituted into a pre-established motor state-space model in the control unit. This motor state-space model consists of the motor's voltage equation, motion equation, and torque equation. The voltage equation describes the relationship between the motor stator voltage, stator current, and rotor speed. The motion equation describes the relationship between the motor's electromagnetic torque, load torque, and rotor speed. The torque equation describes the relationship between the motor's electromagnetic torque and stator current.

[0052] The voltage equation is the core of describing the energy exchange relationship in a motor circuit. It is specifically represented by a set of differential equations. This equation establishes a dynamic balance between the input voltage across the stator windings, the stator current flowing through the windings, and the real-time rotational speed of the rotor. It reveals that the stator voltage is mainly used to overcome the induced electromotive force (EMF) generated in the stator windings due to current changes. This EMF is proportional to the rate of change of current. At the same time, the voltage also needs to balance the back EMF generated in the stator windings due to the rotor rotating and cutting magnetic field lines. The magnitude of this back EMF is proportional to the rotor speed. Therefore, this voltage equation completely describes the dynamic process of how the applied voltage drives the current and overcomes the back EMF to establish a rotating magnetic field. It is the theoretical basis for analyzing the electrical dynamic characteristics of a motor.

[0053] The equation of motion is the core of describing the mechanical motion relationship of an electric motor. Its essence is a differential equation based on Newton's second law or the torque balance principle of a rotating system. This equation defines the dynamic relationship between the electromagnetic torque, load torque, and rotor speed acceleration of the motor. The equation shows that part of the electromagnetic torque generated inside the motor is used to counteract the externally applied load torque, and the remainder is converted into a dynamic torque that causes the motor rotor to produce angular acceleration. This dynamic torque is proportional to the rotational inertia of the motor rotor. Therefore, this equation of motion accurately describes the mechanical process of how the electromagnetic torque overcomes the load and drives the rotor to accelerate, closely linking the electrical output of the motor with its mechanical motion state.

[0054] The torque equation is the core algebraic relationship describing the essence of energy conversion in a motor. This equation clearly states that there is a direct proportional relationship between the electromagnetic torque generated inside the motor and the amplitude of the stator current. Under certain magnetic field conditions, the larger the amplitude of the stator current, the greater the electromagnetic torque generated. This equation reveals the fundamental principle of how a motor converts electrical energy (manifested as current) into mechanical energy (manifested as torque), and is a quantitative description of the entire electromechanical energy conversion process. It provides a direct theoretical basis for precisely controlling the motor's output torque by controlling the stator current.

[0055] Subsequently, a deterministic Luneburg state observer is initiated. This observer uses the motor state-space model as its core and performs two parallel calculation processes internally. First, based on the control voltage signal of the electrical parameters in the current input operating parameters and the built-in motor state-space model, it calculates a set of predicted values ​​for motor state variables in real time, including predicted current and predicted speed. Second, it compares the above predicted values ​​with the actual current and speed measured by the sensors in real time. The resulting difference signal is multiplied by a pre-calculated optimal feedback gain matrix to generate a compensation amount used to correct the prediction of the motor state-space model. This compensation amount is fed back to the input of the motor state-space model to perform closed-loop correction of the predicted state of the motor state-space model, so that the state output of the Luneburg state observer's motor state-space model can progressively approximate the actual operating state of the motor.

[0056] In this convergence state, the output value of a state variable in the Luneburg state observer, specifically constructed based on the motor torque equation to characterize the load torque, is a high-precision real-time load torque estimate. The above process can effectively suppress the interference of minor model parameter mismatch and measurement noise, and finally continuously output an estimated signal that can quickly and accurately track the changes in the real load torque.

[0057] Please see Figure 2 S3. Based on the real-time load torque estimate, perform dynamic starting voltage adjustment. This involves dynamically calculating and outputting the optimal starting voltage by querying a preset voltage-torque mapping relationship. Specifically, this includes:

[0058] A voltage-torque mapping table, pre-established and stored in the non-volatile memory of the control unit, is used. This mapping table is obtained during the motor control system design phase through offline characteristic testing of a specific motor. The specific generation method is as follows:

[0059] On the experimental platform, the motor is subjected to a series of known and stable load torques. For each load torque value, the optimal starting voltage value that enables the motor to start smoothly without stalling or overcurrent is tested and recorded, thus forming a set of discrete but complete data pairs from load torque to optimal starting voltage, which are ultimately solidified into this lookup table. In actual operation, after obtaining the real-time estimated load torque value, it is used as the input lookup value and compared with the load torque sequence arranged in ascending order in the mapping table. The specific lookup calculation process uses a deterministic linear interpolation algorithm, as follows:

[0060] First, the table is used to locate the interval where the current load torque estimate is located. This involves identifying two adjacent torque preset points in the table, such that the current load torque estimate is greater than or equal to the torque value of the previous preset point, and less than or equal to the torque value of the next preset point. Next, based on the specific position of the current load torque estimate within this interval, a linear interpolation formula is applied to calculate the corresponding optimal starting voltage value based on the voltage values ​​corresponding to the preset points at both ends of the interval. If the load torque estimate equals a calibration point in the table, the preset voltage value corresponding to that point is directly output. This optimal starting voltage value, calculated in real-time through deterministic table lookup and interpolation algorithms, is directly output to the motor's power drive unit as a given command for the voltage loop, thereby achieving precise and dynamic adjustment of the motor terminal voltage.

[0061] Based on real-time load torque estimates, adaptive start-up time optimization is performed synchronously. By analyzing the instantaneous rate of change of the real-time load torque estimates, the duration of the motor start-up process is dynamically adjusted to obtain optimized start-up time parameters, specifically including:

[0062] Adaptive start-up time optimization is a deterministic predictive adjustment process based on the dynamic characteristics of the load. The core of its technical solution lies in performing differential calculations on the real-time load torque estimate to accurately obtain its instantaneous rate of change, and using this rate of change as the direct basis for adjusting the start-up time. First, numerical differential calculations are performed on the sequence of real-time load torque estimates obtained in multiple consecutive control cycles. A first-order backward difference algorithm is used, that is, the load torque estimate of the current cycle is subtracted from the load torque estimate of the previous cycle, and then divided by the duration of the control cycle, thereby obtaining a quantitative index of the instantaneous rate of change that reflects the speed of load torque change.

[0063] Subsequently, the absolute value of this instantaneous rate of change is compared with a preset, single positive threshold, which is a non-negative constant determined based on the inertia of the motor system and the requirements for smooth start-up. The comparison and adjustment logic is as follows:

[0064] When the absolute value of the instantaneous rate of change is greater than the preset positive threshold, it indicates that the load torque is increasing or decreasing rapidly, which may lead to an unstable start-up. In this case, the start-up extension mechanism will increase the total duration of the start-up process by a predetermined fixed time increment based on the current value. Conversely, when the absolute value of the instantaneous rate of change is less than or equal to the preset positive threshold, it indicates that the load change is within the allowable stable range. In this case, the start-up shortening mechanism will decrease the total duration by a predetermined fixed time increment based on the current value.

[0065] This dynamic adjustment process is executed cyclically throughout the startup phase. Each adjustment is based on a comparison between the latest absolute value of the rate of change and the same threshold. During the initialization and operation of the startup phase, the total duration after each adjustment is used as the benchmark for the next adjustment, and the final determined total duration is used as the optimized startup time parameter. Finally, the system outputs an optimized startup time parameter, determined after multiple iterations of optimization, which serves as the total duration of this startup process. This scheme ensures the accuracy and consistency of the time optimization response through a defined threshold and explicit binary judgment logic.

[0066] S4. Based on the optimal starting voltage and optimized starting time parameters, and according to the changing trend of the real-time load torque estimate, generate comprehensive control commands to drive the motor to complete the starting process, specifically including:

[0067] The generation of integrated control commands is a collaborative decision-making process. It uses the optimal start-up voltage determined in step S3 as the given command reference for the voltage control loop, and uses the optimized start-up time parameters obtained from the adaptive start-up time optimization step in step S4 as the timing framework for the entire start-up phase.

[0068] Within this framework, the changing trend of the real-time load torque estimate is first determined by setting a judgment window, which contains a continuous number of preset control cycles. The change in the real-time load torque estimate at the current moment relative to the value at the previous moment is calculated, and the continuous changes within the judgment window are recorded. If all changes recorded within the judgment window are positive, it is determined to be an increasing trend; if all changes recorded within the judgment window are negative, it is determined to be a decreasing trend; if changes recorded within the judgment window contain both positive and negative values, it is determined to be a fluctuating trend.

[0069] For an increasing trend, in the first half of the startup process time axis, the output voltage value is increased by a positive offset dynamically calculated based on the magnitude of the change, based on the optimal startup voltage reference; in the second half of the startup process time axis, this positive offset is linearly reduced to zero, allowing the output voltage to smoothly return to the optimal startup voltage reference. For a decreasing trend, in the first half of the startup process time axis, the output voltage value is subtracted from the optimal startup voltage reference by a negative offset dynamically calculated based on the magnitude of the change; in the second half of the startup process time axis, this negative offset is linearly reduced to zero. For a fluctuating trend, the output voltage is maintained equal to the optimal startup voltage reference.

[0070] Ultimately, the integrated control command, which combines voltage setting, time constraints, and load trend feedforward, is sent to the motor's power drive unit to precisely control the switching state of the power devices, thereby driving the motor to complete the entire startup process.

[0071] Please see Figure 3 The second objective of this embodiment is to provide a system for a motor starting control and adjustment method, including a parameter acquisition module 100, a load torque estimation module 200, an adaptive starting optimization module 300, and a comprehensive control command module 400, wherein:

[0072] The parameter acquisition module 100 acquires the motor's operating parameters in real time;

[0073] The load torque estimation module 200 performs real-time load torque estimation based on operating parameters to obtain real-time load torque estimation values.

[0074] The adaptive start optimization module 300 performs dynamic start voltage adjustment based on real-time load torque estimation. It dynamically calculates and outputs the optimal start voltage by querying the preset voltage-torque mapping relationship.

[0075] The adaptive start optimization module 300 performs adaptive start time optimization synchronously based on the real-time load torque estimate. It dynamically adjusts the duration of the motor start-up process by analyzing the instantaneous change rate of the real-time load torque estimate, and obtains the optimized start time parameters.

[0076] The integrated control command module 400 generates integrated control commands based on the optimal starting voltage and starting time parameters and the changing trend of the real-time load torque estimate to drive the motor to complete the starting process.

[0077] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling and adjusting the starting of a motor, characterized in that, The methods and steps include the following: S1. Obtain the motor's operating parameters in real time; S2. Based on the operating parameters, perform real-time load torque estimation to obtain the real-time load torque estimate; S3. Based on the real-time load torque estimate, perform dynamic starting voltage adjustment, dynamically calculate and output the optimal starting voltage by querying a preset voltage-torque mapping relationship; the calculation process of the optimal starting voltage specifically includes: The estimated real-time load torque is compared with the load torque sequence arranged in ascending order in the preset voltage and torque mapping table, and the optimal starting voltage is calculated and output using a linear interpolation algorithm. Based on the real-time load torque estimate, adaptive start-up time optimization is performed synchronously. The duration of the motor start-up process is dynamically adjusted by analyzing the instantaneous rate of change of the real-time load torque estimate, resulting in optimized start-up time parameters. The generation process of these start-up time parameters specifically includes: The instantaneous rate of change is obtained by performing first-order backward difference calculation on the real-time load torque estimate obtained within the continuous control cycle. The absolute value of the instantaneous rate of change is compared with a preset positive threshold. When the absolute value of the instantaneous rate of change is greater than the positive threshold, the current total duration is increased by a predetermined fixed time increment. When the absolute value of the instantaneous rate of change is less than or equal to the positive threshold, the current total duration is reduced by a predetermined fixed time increment. During the initialization and operation of the entire startup phase, the total duration after each adjustment is used as the benchmark for the next adjustment, and the final determined total duration is used as the optimized startup time parameter. S4. Based on the optimal starting voltage and starting time parameters, and according to the changing trend of the real-time load torque estimate, generate a comprehensive control command to drive the motor to complete the starting process.

2. The motor starting control and adjustment method according to claim 1, characterized in that, The operating parameters include stator voltage, stator current, and rotor speed.

3. The motor starting control and adjustment method according to claim 1, characterized in that, The calculation process for the real-time load torque estimate specifically includes: The operating parameters are substituted into the pre-established motor state-space model, and the calculation is performed using the Luneburg state observer to output the real-time load torque estimate.

4. The motor starting control and adjustment method according to claim 3, characterized in that, The motor state-space model is composed of the motor's voltage equation, motion equation, and torque equation. The voltage equation describes the relationship between the motor's stator voltage, stator current, and rotor speed. The motion equation describes the relationship between the motor's electromagnetic torque, load torque, and rotor speed. The torque equation describes the relationship between the motor's electromagnetic torque and stator current.

5. The motor starting control and adjustment method according to claim 3, characterized in that, The calculation process of the Lumberjack state observer specifically includes: The predicted values ​​of the state variables are calculated based on the operating parameters and the motor state-space model; the predicted values ​​are compared with the measured values ​​of the sensors to obtain a difference signal; the difference signal is multiplied by the pre-calculated optimal feedback gain matrix to generate a compensation amount, and the predicted state of the motor state-space model is closed-loop corrected.

6. The motor starting control and adjustment method according to claim 1, characterized in that, The feature is that, The specific trends in the real-time load torque estimate include: Set a judgment window that contains a continuous number of preset control cycles; Calculate the change in the estimated real-time load torque at the current moment relative to the value at the previous moment, and record the change within the judgment window; If all changes recorded in the judgment window are positive, then it is determined to be an increasing trend; If all changes recorded in the judgment window are negative, then it is determined to be a decreasing trend; If the changes recorded in the judgment window contain both positive and negative values, it is determined to be a fluctuation trend.

7. The motor starting control and adjustment method according to claim 1, characterized in that, The process of generating the integrated control command specifically includes: For an increasing trend, a positive offset is added to the optimal startup voltage in the first half of the startup process time axis, and the positive offset is linearly reduced to zero in the second half of the startup process time axis; for a decreasing trend, a negative offset is subtracted from the optimal startup voltage in the first half of the startup process time axis, and the negative offset is linearly reduced to zero in the second half of the startup process time axis; for a fluctuating trend, the output voltage is maintained equal to the optimal startup voltage.

8. A system using the motor starting control adjustment method according to any one of claims 1-7, characterized in that, It includes a parameter acquisition module (100), a load torque estimation module (200), an adaptive start-up optimization module (300), and a comprehensive control command module (400), wherein: The parameter acquisition module (100) acquires the motor's operating parameters in real time; The load torque estimation module (200) performs real-time load torque estimation based on the operating parameters to obtain a real-time load torque estimate. The adaptive start-up optimization module (300) performs dynamic start-up voltage adjustment based on the real-time load torque estimate, and dynamically calculates and outputs the optimal start-up voltage by querying the preset voltage-torque mapping relationship; The adaptive start-up optimization module (300) performs adaptive start-up time optimization synchronously based on the real-time load torque estimate. It dynamically adjusts the duration of the motor start-up process by analyzing the instantaneous change rate of the real-time load torque estimate, and obtains the optimized start-up time parameters. The integrated control command module (400) generates integrated control commands to drive the motor to complete the starting process based on the optimal starting voltage and starting time parameters and the changing trend of the real-time load torque estimate.

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