Cooperative control method and system for multi-motor synchronization of a variable pitch system

Abstract

The application discloses a cooperative control method and system for multi-motor synchronization of a variable pitch system. Through online dynamic characteristic identification technology, a precise dynamic model is established for each drive chain with different physical characteristics, thereby understanding the unique inertia and friction characteristics. During emergency braking, instead of issuing a unified command, the model and unified cooperative braking target are used to prospectively calculate individualized feedforward compensation torque for each motor to achieve synchronized deceleration, actively eliminating action inconsistencies caused by physical differences. At the same time, the braking target itself is optimized from a constant step value that can cause impact to a smooth dynamic trajectory with continuous jerk generated based on an S-curve. Through this dual mechanism, the torque change process applied to the transmission chain is smooth and impact-free while ensuring high synchronization of motor deceleration behavior, thereby solving the technical problems of non-synchronized stress and braking impact.

Description

Technical Field

[0001] This application relates to the field of pitch control technology, and more specifically, to a cooperative control method and system for multi-motor synchronization in a pitch system. Background Technology

[0002] As a core component of clean energy, the increasing size and intelligence of wind turbine generators are current major trends in technological development. With the continuous increase in the size and weight of wind turbine blades, traditional single-motor driven pitch systems can no longer meet the demands for rapid and precise adjustment under large inertia loads. Therefore, multi-motor collaborative drive schemes using two or more motors to jointly drive the same pitch gear ring have become standard for large wind turbine generators. The core function of the pitch system is to adjust the blade pitch angle in real time according to wind conditions to optimize wind energy capture efficiency and ensure the safety of the unit through rapid feathering in high wind speeds or emergencies. During this process, all drive motors must maintain a high degree of motion synchronization; otherwise, inconsistencies in motor movement will lead to enormous internal stress on the transmission chain, causing mechanical vibration, accelerated gear wear, and in severe cases, even permanent damage to transmission components, directly threatening the operational safety and service life of the wind turbine.

[0003] In existing technological practices, synchronous control of multiple motors often employs strategies such as master-slave control or cross-coupling control. These methods can compensate for speed or position errors between motors through feedback mechanisms under steady-state or gradually changing operating conditions, thereby maintaining a certain level of synchronization. However, the limitations of existing technologies become apparent when dealing with emergency braking conditions triggered by sudden events such as power grid failures or extreme wind conditions. Emergency braking requires the system to brake at maximum capacity within a very short time, and the controller typically issues a unified and rapid braking command to all motors. This control method implicitly assumes that all drive chains have completely identical physical characteristics. In reality, due to manufacturing tolerances, assembly differences, uneven wear caused by long-term operation, and changes in lubrication conditions, the equivalent moment of inertia and coefficient of friction, among other dynamic parameters, of each motor-gearbox-gear drive chain inevitably differ. This leads to inconsistent actual deceleration responses of each drive chain when receiving the same braking command, resulting in severe asynchronous motion and generating significant internal impact stress at the moment of braking.

[0004] Therefore, an optimized cooperative control scheme for multi-motor synchronization in a pitch system is desired. Summary of the Invention

[0005] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a cooperative control method and system for multi-motor synchronization in a pitch system.

[0006] According to one aspect of this application, a cooperative control method for multi-motor synchronization in a pitch system is provided, comprising: Obtain the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor; The dynamic characteristics of the drive chain are identified online by the real-time values ​​of the cross-axis current and the mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. In response to an external emergency braking trigger signal being true, a cooperative braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration; The feedforward braking torque of each motor is calculated based on the current angular velocity, reference angular deceleration and dynamic parameter set of each drive chain at the moment of triggering. Synchronization error feedback correction is performed on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor. The final command torque of each motor is determined based on the feedforward braking torque and the feedback correction torque of each motor.

[0007] According to another aspect of this application, a cooperative control system for multi-motor synchronization in a pitch system is provided, the system being capable of implementing the above-described method, comprising: The data acquisition module is used to obtain the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor. The drive chain dynamic characteristic identification module is used to identify the dynamic characteristics of the drive chain online by the real-time values ​​of the cross-axis current and the real-time values ​​of the mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. The cooperative braking target setting module is used to set the cooperative braking target based on the current angular velocity of each motor at the moment of triggering in response to the external emergency braking trigger signal being true, so as to obtain the reference angular deceleration. The feedforward compensation braking torque calculation module is used to calculate the feedforward compensation braking torque of each motor based on the current angular velocity, reference angular deceleration and dynamic parameter set of each drive chain at the moment of triggering. The synchronization error feedback correction module is used to perform synchronization error feedback correction on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor. The command torque determination module is used to determine the final command torque of each motor based on the feedforward braking torque and the feedback correction torque of each motor.

[0008] Compared with existing technologies, this application provides a cooperative control method and system for multi-motor synchronization in a pitch system. Through online dynamic characteristic identification technology, it establishes a precise dynamic model for each drive train with different physical characteristics, thereby gaining insight into its unique inertia and frictional characteristics. During emergency braking, instead of issuing a unified command, it proactively calculates personalized feedforward compensation torques for each motor based on this model and a unified cooperative braking target, actively eliminating inconsistencies in action caused by physical differences. Simultaneously, the braking target itself is optimized from a constant step value that would cause shock to a smooth dynamic trajectory with continuous acceleration generated based on an S-curve. Through this dual mechanism, while ensuring high synchronization of the deceleration behavior of each motor, the torque change process applied to the drive train is smooth and shock-free, thus systematically solving the two major technical challenges of asynchronous stress and braking shock. Attached Figure Description

[0009] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0010] Figure 1 This is a flowchart of a cooperative control method for multi-motor synchronization of a pitch system according to an embodiment of this application; Figure 2 This is a schematic diagram of the data flow of a cooperative control method for multi-motor synchronization in a pitch system according to an embodiment of this application; Figure 3 The flowchart illustrates the process of online identification of the dynamic characteristics of the drive chain in the real-time values ​​of the cross-axis current and the real-time values ​​of the mechanical angular velocity of each motor in the coordinated control method for multi-motor synchronization of the pitch system according to the embodiments of this application, so as to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. Figure 4 The flowchart illustrates the cooperative control method for multi-motor synchronization of a pitch system according to an embodiment of this application, which responds to an external emergency braking trigger signal being true by setting a cooperative braking target based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration. Figure 5 This is a block diagram of a multi-motor synchronous cooperative control system for a pitch system according to an embodiment of this application. Detailed Implementation

[0011] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0012] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0013] While this application makes various references to certain modules of the systems according to embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The modules described are merely illustrative, and different aspects of the systems and methods may use different modules.

[0014] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0015] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0016] This application proposes a cooperative control method for multi-motor synchronization in a pitch system, aiming to solve the core technical problem of asynchronous motion and severe mechanical shock caused by inconsistent dynamic characteristics of each drive chain and sudden changes in braking commands during emergency braking of multiple motors in a pitch system. To achieve this goal, this solution implements a precise cooperative control process: First, during normal system operation, the method continuously establishes and updates a unique dynamic model for each motor drive chain through an online identification algorithm, accurately quantifying its equivalent moment of inertia and friction coefficient. When an emergency braking command is triggered, the controller does not immediately issue a harsh stop signal, but instead intelligently plans an S-shaped reference angle deceleration trajectory with smooth acceleration changes based on system constraints, eliminating the shock introduced by sudden command changes at the source. Next, the method uses the previously identified, distinct motor models, combined with the smooth braking trajectory target, to proactively calculate the unique feedforward braking torque required for each motor to achieve synchronous deceleration. Based on this, a parallel feedback correction loop monitors the speed synchronization error during braking in real time and generates compensating torque to cope with model deviations and external disturbances. Ultimately, the precise feedforward torque is combined with the real-time feedback correction torque to form the final command, which is then sent to each motor. This ensures that the entire motor unit can brake quickly and extremely smoothly, just like a rigid whole, thus systematically mitigating the risks of asynchronous stress and impact damage.

[0017] Figure 1 This is a flowchart of a cooperative control method for multi-motor synchronization of a pitch system according to an embodiment of this application. Figure 2 This is a schematic diagram of the data flow in a cooperative control method for multi-motor synchronization of a pitch system according to an embodiment of this application. Figure 1 and Figure 2 As shown, the cooperative control method for multi-motor synchronization of a pitch system according to an embodiment of this application includes the following steps: S100, acquiring the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor. S200, performing online identification of the dynamic characteristics of the drive chain on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain, wherein the dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. S300, in response to an external emergency braking trigger signal being true, setting a cooperative braking target based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration. S400, calculating the feedforward compensation braking torque based on the current angular velocity of each motor, the reference angular deceleration, and the dynamic parameter set of each drive chain at the moment of triggering to obtain the feedforward braking torque of each motor. S500, performing synchronization error feedback correction on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor. S600, determining the final command torque of each motor based on the feedforward braking torque and the feedback correction torque of each motor.

[0018] Specifically, in step S100, the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor are acquired. It should be understood that in a pitch system, the dynamic characteristics of each motor drive train, such as the equivalent moment of inertia and equivalent viscous friction coefficient, objectively differ and dynamically change with the operating state. These characteristics directly determine the actual response of the motor to a given drive command. Without acquiring real-time data reflecting its dynamic behavior, an accurate control model cannot be established. Therefore, in the technical solution of this application, the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor are acquired to provide the necessary and fundamental measurement data for subsequent online identification of the dynamic characteristics of the drive train. This enables the control system to establish accurate and personalized mathematical models for each physically different drive train, laying an indispensable data foundation for calculating precise feedforward compensation torque.

[0019] More specifically, in a particular example of this application, the process of acquiring the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor is executed within the servo driver configured for each motor. First, the driver measures the three-phase or two-phase stator current of the motor in real time using its internal current sensor. The driver's processor performs a coordinate transformation on the measured phase current, specifically a Parker transformation, converting it from the stator stationary coordinate system to a rotating coordinate system oriented by the rotor flux linkage, decomposing it to obtain the quadrature-axis current component directly related to torque; this component is used as the real-time value of the quadrature-axis current. Simultaneously, the driver receives high-resolution rotor position signals from position sensors such as encoders or resolvers mounted on the motor shaft. The processor performs a differential operation between the position data acquired in the current control cycle and the position data from the previous cycle, then divides the resulting difference by a fixed control sampling cycle. The result of this differential operation is the real-time value of the motor's mechanical angular velocity. This data acquisition process is synchronized by the system control clock, ensuring that the acquired real-time values ​​of the quadrature-axis current and mechanical angular velocity precisely correspond to the same moment, forming a valid data pair for subsequent processing.

[0020] Specifically, in step S200, the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor are used for online identification of the drive chain dynamic characteristics to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. It should be understood that simply obtaining the real-time operating data of the motors cannot directly reveal their inherent physical characteristics that determine their dynamic response capabilities. These unknown dynamic parameters, which exhibit individual differences, are the fundamental reason for the asynchronous motion of multiple motors under unified commands. Therefore, in the technical solution of this application, the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor are further used for online identification of the drive chain dynamic characteristics to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient, thereby transforming externally measurable electrical and kinematic quantities into key parameters that can characterize the inherent physical characteristics of the system. In this way, the control system can be moved from the phenomenological level to the physical essence, providing essential, quantified, and adaptively updated dynamic parameters for subsequent model-based precise feedforward control, thereby eliminating the deviation between the control model and the physical reality.

[0021] Figure 3 This document describes a flowchart illustrating the online identification of the dynamic characteristics of the drive train based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor in a multi-motor synchronous cooperative control method for a pitch system according to embodiments of this application. The dynamic parameter set of each drive train includes estimated values ​​of equivalent moment of inertia and equivalent viscous friction coefficient. Figure 3 As shown, step S200 includes: S210, calculating the electromagnetic torque and measured angular acceleration of each motor based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor; and S220, performing least-squares regression on the electromagnetic torque and measured angular acceleration of each motor to obtain estimated values ​​of the equivalent moment of inertia and the equivalent viscous friction coefficient.

[0022] Accordingly, in step S210, the electromagnetic torque and measured angular acceleration of each motor are calculated based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor. It should be understood that the real-time values ​​of the quadrature-axis current and mechanical angular velocity obtained directly from the sensors cannot be directly substituted into the dynamic equations describing the torque-motion relationship of the system; the former is an electrical quantity, and the latter is a kinematic quantity, both needing to be converted into corresponding dynamic quantities. Therefore, in the technical solution of this application, the electromagnetic torque and measured angular acceleration of each motor are further calculated based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor. This transforms the original measurement data from different physical dimensions into standard physical quantities unified within the framework of the dynamic model. This establishes a clear, physically consistent input-output data pair for subsequent least-squares regression, giving the parameter identification process a solid physical meaning and data foundation.

[0023] In a specific example of this application, the calculation of electromagnetic torque and measured angular acceleration is performed in real time by the controller within each control cycle. The process begins with the calculation of electromagnetic torque. Specifically, the controller retrieves the motor's torque constant parameter pre-stored in its non-volatile memory and multiplies this constant by the real-time value of the quadrature-axis current acquired in the current control cycle. The result is then determined as the electromagnetic torque at the current moment. Next, the controller calculates the measured angular acceleration. The controller reads the real-time value of the mechanical angular velocity for the current control cycle and the real-time value of the mechanical angular velocity from the previous control cycle stored in its internal register. The controller subtracts these two angular velocity values ​​to obtain a velocity increment, and then divides this velocity increment by the system's fixed control sampling period. The quotient is then determined as the measured angular acceleration at the current moment. Through this process, the controller generates a set of electromagnetic torque and measured angular acceleration data directly corresponding to the system's dynamic behavior in each cycle.

[0024] Accordingly, in step S220, least squares regression is performed on the electromagnetic torque and measured angular acceleration of each motor to obtain estimated values ​​for the equivalent moment of inertia and the equivalent viscous friction coefficient. It should be understood that since the dynamic model of the drive train is an equation containing multiple variables and two unknown parameters, it cannot be solved by a single measurement, and the measurement process is inevitably accompanied by noise interference. Therefore, a robust mathematical method is needed to extract the parameter values ​​that best represent the true characteristics of the system from the continuous data stream. Thus, in the technical solution of this application, least squares regression is further performed on the electromagnetic torque and measured angular acceleration of each motor to obtain estimated values ​​for the equivalent moment of inertia and the equivalent viscous friction coefficient. This applies a statistically optimal parameter estimation method to solve for the unknown parameters in the dynamic model under conditions of measurement noise and dynamic changes. This ensures that the identified equivalent moment of inertia and viscous friction coefficient have high accuracy and strong robustness, providing a reliable and accurate model foundation for the entire cooperative control strategy.

[0025] In a specific example of this application, the least squares regression process is implemented by executing a recursive least squares algorithm in the controller. First, the controller applies the dynamic equations of the driving chain. Construct a standard linear regression model In this model, the observations Electromagnetic torque defined at the current moment The parameter vector to be identified It is defined as a column vector containing two unknown parameters (estimated equivalent moment of inertia and estimated equivalent viscous friction coefficient), i.e. Data Regression Vector It is then defined as the measured angular acceleration at the current moment. and mechanical angular velocity The column vector formed, i.e. In each control cycle, the algorithm performs one iterative update. The controller first uses the parameter vector updated in the previous cycle. and the current data regression vector Calculate a predicted electromagnetic torque and compare it with the actual measured electromagnetic torque. The prediction error is obtained by comparison. Subsequently, the controller uses the covariance matrix... and data regression vector Calculate a gain vector The gain vector is weighted by the prediction error to form a correction value, which the controller adds to the parameter vector of the previous cycle. This allows us to obtain a more accurate parameter vector for the current period. Finally, the controller updates the covariance matrix as follows: This data is stored for use in the next iteration. Through this recursive approach, the controller continuously and optimally extracts estimates of the equivalent moment of inertia and the equivalent viscous friction coefficient from the continuous data stream.

[0026] Specifically, in step S300, in response to the external emergency braking trigger signal being true, a cooperative braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration. It should be understood that since the external emergency braking trigger signal itself is only a discrete event command, it cannot be directly used as a continuous control basis. Furthermore, without a unified, quantified braking target, the individual motor controllers will be unable to coordinate their actions, inevitably leading to chaos and asynchrony in the braking process. The core flaw of the traditional cooperative braking target generation mechanism is that the reference angular deceleration it generates is a constant value. From a data and algorithm perspective, this means that the target acceleration curve is an instantaneously changing step function, which physically corresponds to a theoretically infinite acceleration generated at the moment of braking start and stop. This abrupt command essentially ignores the inherent physical characteristics of the pitch drive system as a complex rigid-flexible coupled body, namely the elastic deformation and damping characteristics within the system. When such a command containing a huge impact is applied to the actual system, even if the servo system cannot fully reproduce it due to bandwidth limitations, its attempt to follow will trigger a drastic change in driving torque within a very short time. This change can trigger oscillations in the elastic components within the system, causing energy to be released instantaneously in the form of stress concentration in critical components such as gears and bearings, resulting in a strong mechanical impact. This is not only the root cause of fatigue damage and early failure in mechanical systems, but also a manifestation of the technical limitations of the original mechanism in pursuing a single braking time objective, failing to fully consider the inherent relationship between the smoothness of the control process and the mechanical health of the system.

[0027] To address the mechanical shock problem caused by constant deceleration commands, a preferred embodiment of this technical solution proposes a dynamic generation mechanism for reference angular deceleration based on S-shaped acceleration planning. This mechanism, by introducing explicit constraints on acceleration, elevates the braking target from a static numerical value to a dynamic function that evolves smoothly over time, thereby eliminating shock at the braking source. Specifically, in this application's technical solution, in response to a true external emergency braking trigger signal, a coordinated braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain the reference angular deceleration. This transforms a non-quantitative emergency event into a precisely quantified kinematic reference standard that all motor controllers must adhere to. This provides a clear and consistent dynamic performance target for subsequent feedforward torque calculation and feedback correction, ensuring the consistency and coordination of the braking behavior of the entire multi-motor system from the control source.

[0028] Figure 4The flowchart illustrates a method for coordinated control of multi-motor synchronization in a pitch system according to an embodiment of this application. It describes how, in response to an external emergency braking trigger signal being true, a coordinated braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration. (See the flowchart for the method.) Figure 4 As shown, step S300 includes: S310, aggregating and setting braking boundary conditions for the current angular velocity of each motor, the total number of motors, the maximum allowable braking time, and the maximum allowable acceleration of the system at the moment of triggering to obtain the aggregated initial angular velocity of the system, the total braking time for planning, and the maximum acceleration amplitude. S320, calculating key timing parameters of the S-curve for the aggregated initial angular velocity of the system, the total braking time for planning, and the maximum acceleration amplitude to obtain the acceleration / deceleration segment duration and the maximum deceleration amplitude. S330, generating a time-varying reference angular deceleration segment based on the acceleration / deceleration segment duration, the maximum deceleration amplitude, the total braking time for planning, and the current moment in the braking process to obtain a time-varying reference angular deceleration as the reference angular deceleration.

[0029] Accordingly, in step S310, braking boundary conditions are aggregated and constrained for the current angular velocity of each motor, the total number of motors, the maximum allowable braking time, and the maximum allowable jerk of the system at the moment of triggering to obtain the aggregated initial angular velocity of the system, the total braking time for planning, and the maximum jerk amplitude. It should be understood that since the subsequent S-curve trajectory planning algorithm requires a precise and unified mathematical starting point and clear boundaries as input, and the state provided by the system at the moment of triggering braking consists of discrete angular velocities of multiple motors and conceptual system-level safety requirements, the technical solution of this application further aggregates and constrains braking boundary conditions for the current angular velocity of each motor, the total number of motors, the maximum allowable braking time, and the maximum allowable jerk of the system at the moment of triggering to obtain the aggregated initial angular velocity of the system, the total braking time for planning, and the maximum jerk amplitude. This converges the discrete initial states of the system into a single macroscopic initial state, and simultaneously explicitly transforms the abstract mechanical bearing capacity and time requirements into algorithmic constraints that can be directly used for calculation.

[0030] In a specific example of this application, the process is executed in a central controller. First, the process begins with the aggregation of initial angular velocities. The controller captures the real-time angular velocity values ​​of all N motors at the moment of triggering. Perform a summation operation, then divide the sum by the total number of motors N, and calculate the arithmetic mean to obtain a single aggregated initial angular velocity of the system that represents the macroscopic motion state of the entire blade system. .

[0031] Next, the controller sets the constraints. It reads two pre-defined system-level parameters from its parameter configuration area: the first is the maximum permissible braking time, which is directly assigned to the planned total braking time; the second is the system's maximum permissible jerk, representing the upper limit of the impact the drivetrain can withstand, and is directly assigned to the limit jerk amplitude. In this way, the emergency braking problem of a physical system is precisely transformed at the algorithmic level into an optimal control trajectory problem with clear initial conditions and process constraints. This lays a solid data foundation for generating a mechanically friendly, smooth braking curve. The ultimate goal and effect is to ensure that the planned braking curve not only meets the time requirements but also fundamentally respects the system's physical load-bearing limits.

[0032] Accordingly, in step S320, the initial angular velocity of the aggregated system, the total braking time used for planning, and the ultimate acceleration amplitude are calculated using key timing parameters of an S-curve to obtain the duration of the acceleration / deceleration segment and the ultimate deceleration amplitude. It should be understood that since the initial angular velocity, total braking time, and ultimate acceleration amplitude determined in the previous step are only macroscopic constraints, they cannot directly generate a specific, time-evolving smooth acceleration curve. These boundary conditions must be transformed into key parameters that can accurately define the curve's shape, replacing the constant deceleration scheme that could cause impact. Therefore, in the technical solution of this application, the initial angular velocity of the aggregated system, the total braking time used for planning, and the ultimate acceleration amplitude are further calculated using key timing parameters of an S-curve to obtain the duration of the acceleration / deceleration segment and the ultimate deceleration amplitude, thereby solving for the core geometric parameters that constitute the ideal trapezoidal acceleration profile that balances efficiency and smoothness. In this way, the abstract concept of smooth braking can be concretized into two measurable key timing parameters: the duration of the acceleration / deceleration phase and the magnitude of the ultimate deceleration. This allows for the precise identification of a braking path with minimal impact while meeting the total time constraint, thus achieving flexibility and intelligence in the braking process.

[0033] In a specific example of this application, this calculation process, serving as the core algorithm of the entire S-curve planning mechanism, is executed in the central controller. The process first calculates the duration of the acceleration / deceleration phase. The controller substitutes the aggregated initial system angular velocity, the total braking time used for planning, and the ultimate acceleration amplitude determined in the previous step into a pre-defined core solution formula that establishes the inherent mathematical relationship between these three factors. This formula directly analyzes the required duration of the acceleration / deceleration phase in the trapezoidal acceleration profile. Subsequently, the controller calculates the limiting deceleration amplitude. The controller multiplies the acceleration / deceleration duration calculated in the previous step with the limiting jerk amplitude, and calculates the platform height of the trapezoidal profile, i.e., the limiting deceleration amplitude, based on the physical definition of jerk. The initial angular velocity of the aggregated system, the planned total braking time, and the limiting jerk amplitude are then used to calculate the key timing parameters of the S-curve using the following formula:

[0034]

[0035] in, It is the calculated duration of the acceleration / deceleration phase. This is the total braking time used for planning. It is the initial angular velocity of the aggregated system. It is the maximum acceleration amplitude. For the duration of acceleration and deceleration phases, This represents the maximum deceleration amplitude. In this way, the abstract concept of smooth braking can be concretized into the duration of the acceleration / deceleration phase. and the magnitude of the limiting deceleration These two measurable key timing parameters enable the precise identification of a braking path with minimal impact while satisfying the total time constraint, thus achieving flexibility and intelligence in the braking process.

[0036] Accordingly, in step S330, a time-varying reference angular deceleration is generated segmentally based on the acceleration / deceleration phase duration, the maximum deceleration amplitude, the planned total braking time, and the current moment during the braking process to obtain a time-varying reference angular deceleration as the reference angular deceleration. It should be understood that since the acceleration / deceleration phase duration and the maximum deceleration amplitude calculated in the previous step are static timing parameters describing the overall process profile, they cannot themselves serve as dynamic commands executed by the controller in each sampling period. Therefore, in the technical solution of this application, a time-varying reference angular deceleration is further generated segmentally based on the acceleration / deceleration phase duration, the maximum deceleration amplitude, the planned total braking time, and the current moment during the braking process to obtain a time-varying reference angular deceleration as the reference angular deceleration. This transforms the static planning parameters into a continuously changing dynamic command signal that can continuously guide the control system's actions throughout the braking process.

[0037] In a specific example of this application, the execution process involves constructing a piecewise function that evolves over time t. The function is and Using time division points, and To accurately depict a complete trapezoidal acceleration profile for morphological control parameters, this generation process is executed in real-time within each control cycle of the central controller after the emergency braking begins. The controller first starts an internal timer to record the current moment elapsed since the start of braking. In each control cycle, the controller compares the current moment with the time division point calculated in the previous step, i.e., the duration of the acceleration / deceleration phase. Total braking time for planning Subtract the duration of acceleration and deceleration phases The values ​​are compared to determine which of the three braking phases is currently in. This occurs during the first braking phase. Within the time period, i.e., the current time is less than the duration of the acceleration / deceleration phase. The deceleration increases linearly from 0. The controller performs the first stage calculation and sets the maximum acceleration amplitude. The negative value and the current time Multiplying these values ​​yields a linearly increasing deceleration value. If the current moment falls within a uniform deceleration phase after acceleration / deceleration but before deceleration, the controller performs a second-stage calculation, directly setting the limiting deceleration amplitude. The negative value is used as the reference angular deceleration, meaning the deceleration is kept at the limit value. If the current moment is in the final deceleration phase, that is, the last moment before braking ends. During the time period, the controller performs the third stage calculation, smoothly reducing the reference angular deceleration from its limit value to zero using a linear function. The time-varying reference angular deceleration is generated piecewise using the following formula:

[0038] in, It is a time-varying reference angular deceleration that changes with time t. In this way, a non-constant reference angular deceleration value can be directly called by the controller in each sampling period. This time-varying value ensures that the torque actually applied to the system changes smoothly, thereby generating a practical and executable braking target trajectory that is immune to mechanical shocks. This transforms the entire emergency braking process from a brutal abrupt stop into an elegant and efficient precision braking, maximizing the protection of the mechanical components of the drivetrain while completing the braking task.

[0039] The above-described preferred embodiment fundamentally solves the problem of severe mechanical shock caused by the generation of step acceleration commands in the original mechanism. Instead of generating a constant deceleration target, it plans and generates a dynamic reference trajectory with continuous acceleration and a smooth trapezoidal change in acceleration. This results in a smooth S-shaped velocity curve throughout the braking process, ensuring that the application and unloading of driving torque are gradual, completely eliminating the impact at the moment of braking start and stop. Its direct technical effect is a significant reduction in the instantaneous peak stress and vibration experienced by core transmission components such as the pitch system gear ring, gearbox, and bearings under emergency braking conditions. This indirectly achieves the long-term technical goals of extending equipment lifespan, reducing maintenance costs, and improving the overall reliability of the wind turbine generator. This achieves the goal of meeting the rigid safety indicator of emergency braking time requirements while also providing refined protection for the mechanical health of the system, transforming emergency braking from a highly damaging action into a safe, efficient, and equipment-friendly standard control process.

[0040] Specifically, in step S400, feedforward compensation braking torque is calculated based on the current angular velocity, reference angular deceleration, and dynamic parameter set of each drive chain at the moment of triggering to obtain the feedforward braking torque of each motor. It should be understood that since a unified, ideal reference angular deceleration target cannot directly act on motor drive chains with different physical characteristics, if it is not converted into specific execution commands based on the unique dynamic parameter set of each drive chain, then even if the target is smooth, the actual response of each motor will still be asynchronous due to its inherent inertia and friction differences, thus failing to eliminate internal stress. Therefore, in the technical solution of this application, feedforward compensation braking torque is further calculated based on the current angular velocity, reference angular deceleration, and dynamic parameter set of each drive chain at the moment of triggering to obtain the feedforward braking torque of each motor. This allows a unified kinematic target to be accurately and individually reverse-analyzed into the dynamic commands that each motor must apply to achieve this target. In this way, the physical asymmetry between the various drive chains can be proactively and forward-lookingly compensated from the source of control command generation, so that the command received by each motor can just overcome its own inertia and friction, thereby ensuring that all motors can follow the common reference angular deceleration trajectory with high consistency and precision on a macroscopic level.

[0041] More specifically, in a particular example of this application, the calculation of the feedforward compensating braking torque is performed independently by the central controller for each motor in each control cycle of the emergency braking process. This process begins with data acquisition and preparation. In the current control cycle, the controller obtains the unified time-varying reference angular deceleration at that moment from the S-curve generation module; simultaneously, the controller retrieves the latest dynamic parameter set of the i-th drive chain from the online identification module, namely the estimated equivalent moment of inertia and the estimated equivalent viscous friction coefficient; and the controller obtains the real-time mechanical angular velocity of the i-th motor from its servo driver at that moment. Subsequently, the controller performs the synthesis calculation of the feedforward torque. This calculation strictly follows the dynamic model of the drive chain. The controller multiplies the estimated equivalent moment of inertia of the i-th drive chain with the reference angular deceleration at the current moment to obtain the inertial torque component required to achieve the target deceleration; simultaneously, it multiplies the estimated equivalent viscous friction coefficient of the drive chain with the real-time mechanical angular velocity of the motor at the current moment to obtain the friction torque component required to overcome friction at the current speed. Finally, the controller algebraically sums the calculated inertial torque component and friction torque component, and the sum is determined as the feedforward braking torque of the i-th motor in this control cycle, and is used as the output for subsequent control loops.

[0042] Specifically, in step S500, the real-time angular velocity of each motor during braking is corrected for synchronization error to obtain the feedback correction torque for each motor. It should be understood that relying solely on model-based feedforward control cannot fully address residual errors from online parameter identification, unmodeled nonlinear dynamics in the system (such as backlash and Coulomb friction), and unpredictable external load disturbances. These factors can still cause the motors to deviate from the ideal synchronous trajectory during actual motion, resulting in minor synchronization errors. Therefore, in the technical solution of this application, the real-time angular velocity of each motor during braking is further corrected for synchronization error to obtain the feedback correction torque for each motor. This constructs a parallel closed-loop correction mechanism to actively suppress and eliminate any tendency to deviate from the synchronous state in real time. This significantly enhances the robustness and control accuracy of the entire cooperative control system, ensuring that even with imperfect models and external disturbances, the multi-motor system maintains extremely high synchronization performance, forming a functionally equivalent electronic shaft with a rigid connection.

[0043] More specifically, in a concrete example of this application, the synchronization error feedback correction process is executed in parallel by the central controller for all motors during each control cycle of emergency braking. The process first generates a synchronization reference. In the current control cycle, the controller acquires the real-time angular velocities of all N motors, sums these values, and divides them by the total number of motors N to calculate the current system average angular velocity, which is used as a common, dynamic synchronization reference target for all motors. Subsequently, the controller independently calculates the synchronization error for each motor. Specifically, for the i-th motor, the controller subtracts its own real-time angular velocity from the system average angular velocity; the difference is the synchronization error of that motor. Finally, the controller generates a feedback correction torque. The controller inputs the synchronization error of the i-th motor into a PI controller configured for it. The PI controller calculates a correction torque value based on the magnitude and duration of the error, according to its proportional gain and integral gain parameters. The magnitude and direction of this torque value are designed to precisely counteract the disturbance that causes the motor to deviate from the average speed, thereby pulling the motor's speed back to the system average level. The calculated torque is the feedback correction torque of the i-th motor.

[0044] Specifically, in step S600, the final command torque of each motor is determined based on the feedforward braking torque and the feedback correction torque of each motor. It should be understood that since the feedforward braking torque and the feedback correction torque perform different control functions—the former as the dominant, model-based predictive control quantity, and the latter as the auxiliary, real-time correction quantity to cope with unknown disturbances—these two independent control components must be integrated into a single, executable final control command to fully apply to the motor driver. Therefore, in the technical solution of this application, the final command torque of each motor is further determined based on the feedforward braking torque and the feedback correction torque of each motor, thereby seamlessly integrating the forward-looking open-loop command with the responsive closed-loop correction to form a structurally complete and functionally complementary composite control law. This ensures that the final command torque issued to the motor includes both accurate compensation for the known dynamic characteristics of the system and real-time suppression capabilities against model uncertainties and external disturbances, fundamentally guaranteeing that the control system possesses both high-speed responsiveness and high robustness, ultimately achieving ultimate synchronous control accuracy.

[0045] More specifically, in this embodiment, determining the final command torque of each motor based on the feedforward braking torque and the feedback correction torque of each motor includes: adding the feedforward braking torque and the feedback correction torque of each motor to obtain the final command torque of each motor. That is, in a specific example of this application, the determination of the final command torque is performed independently for each motor within each control cycle of the central controller, immediately following the calculation of the feedforward and feedback torques. The core operation of this process is the algebraic summation of the two torque components. In the current control cycle, the controller first retrieves the feedforward braking torque and the feedback correction torque calculated for the i-th motor from its internal data register. Subsequently, the arithmetic logic unit within the controller performs an addition operation on these two values, adding the feedforward braking torque value to the feedback correction torque value. The result of this addition operation is immediately assigned to a final command torque variable, which is determined as the total, final command torque that the i-th motor needs to execute in this control cycle. This final command torque is then transmitted to the current loop of the servo driver as the direct basis for generating the quadrature-axis current command.

[0046] In summary, the cooperative control method for multi-motor synchronization in a pitch system according to the embodiments of this application is explained. It utilizes online dynamic characteristic identification technology to establish accurate dynamic models for each drive train with distinct physical characteristics, thereby gaining insight into its unique inertia and frictional characteristics. During emergency braking, it no longer issues uniform commands but, based on this model and a unified cooperative braking target, proactively calculates personalized feedforward compensation torques for each motor to achieve synchronized deceleration, actively eliminating inconsistencies in action caused by physical differences. Simultaneously, the braking target itself is optimized from a constant step value that would cause impact to a smooth dynamic trajectory with continuous acceleration generated based on an S-curve. Through this dual mechanism, while ensuring high synchronization of the deceleration behavior of each motor, the torque change process applied to the drive train is smooth and impact-free, thus systematically solving the two major technical challenges of asynchronous stress and braking impact.

[0047] Furthermore, a cooperative control system for multi-motor synchronization in a pitch system is also provided.

[0048] Figure 5 This is a block diagram of a multi-motor synchronous cooperative control system for a pitch system according to an embodiment of this application. Figure 5As shown, the multi-motor synchronous cooperative control system 100 of the pitch system according to an embodiment of this application includes: a data acquisition module 110, used to acquire the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor; a drive chain dynamic characteristic identification module 120, used to perform online identification of the drive chain dynamic characteristics based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain, the dynamic parameter set of the drive chain including the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient; and a cooperative braking target setting module 130, used to respond to the external emergency braking trigger signal being true, based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor at the moment of triggering. The current angular velocity is used to set the cooperative braking target to obtain the reference angular deceleration; the feedforward compensation braking torque calculation module 140 is used to calculate the feedforward compensation braking torque of each motor based on the current angular velocity, reference angular deceleration and dynamic parameter set of each drive chain at the moment of triggering to obtain the feedforward braking torque of each motor; the synchronization error feedback correction module 150 is used to perform synchronization error feedback correction on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor; the command torque determination module 160 is used to determine the final command torque of each motor based on the feedforward braking torque and the feedback correction torque of each motor.

[0049] As described above, the cooperative control system 100 for multi-motor synchronization of the pitch system according to the embodiments of this application can be implemented in various wireless terminals, such as servers with cooperative control algorithms for multi-motor synchronization of the pitch system. In one possible implementation, the cooperative control system 100 for multi-motor synchronization of the pitch system according to the embodiments of this application can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the cooperative control system 100 for multi-motor synchronization of the pitch system can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the cooperative control system 100 for multi-motor synchronization of the pitch system can also be one of many hardware modules of the wireless terminal.

[0050] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A cooperative control method for multi-motor synchronization in a pitch system, characterized in that, include: Obtain the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor; The dynamic characteristics of the drive chain are identified online by the real-time values ​​of the cross-axis current and the mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. In response to an external emergency braking trigger signal being true, a cooperative braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration; The feedforward braking torque of each motor is calculated based on the current angular velocity, reference angular deceleration and dynamic parameter set of each drive chain at the moment of triggering. Synchronization error feedback correction is performed on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor. The final command torque of each motor is determined based on the feedforward braking torque and the feedback correction torque of each motor.

2. The cooperative control method for multi-motor synchronization in a pitch system according to claim 1, characterized in that, The dynamic characteristics of the drive train are identified online by analyzing the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive train. The dynamic parameter set of the drive train includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient, including: Based on the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor, the electromagnetic torque and measured angular acceleration of each motor are calculated. Least square regression was performed on the electromagnetic torque and measured angular acceleration of each motor to obtain the estimated values ​​of the equivalent moment of inertia and the equivalent viscous friction coefficient.

3. The cooperative control method for multi-motor synchronization in a pitch system according to claim 1, characterized in that, In response to an external emergency braking trigger signal being true, a coordinated braking target is set based on the current angular velocity of each motor at the moment of triggering to obtain a reference angular deceleration, including: At the moment of triggering, the current angular velocity of each motor, the total number of motors, the maximum allowable braking time, and the maximum allowable acceleration of the system are aggregated and constrained to obtain the aggregated initial angular velocity of the system, the total braking time for planning, and the limit acceleration amplitude. The initial angular velocity of the aggregated system, the total braking time for planning, and the ultimate acceleration amplitude are calculated using key timing parameters of the S-curve to obtain the duration of the acceleration / deceleration segment and the ultimate deceleration amplitude. Based on the duration of the acceleration / deceleration phase, the magnitude of the maximum deceleration, the planned total braking time, and the current moment during the braking process, a time-varying reference angular deceleration is generated in segments to obtain the time-varying reference angular deceleration as the reference angular deceleration.

4. The cooperative control method for multi-motor synchronization in a pitch system according to claim 3, characterized in that, The initial angular velocity, total braking time, and ultimate jerk amplitude of the aggregated system are calculated using key S-curve time-series parameters to obtain the acceleration / deceleration segment duration and ultimate deceleration amplitude. This includes calculating the key S-curve time-series parameters of the aggregated system using the following formula: in, It is the calculated duration of the acceleration / deceleration phase. This is the total braking time used for planning. It is the initial angular velocity of the aggregated system. It is the maximum acceleration amplitude. For the duration of acceleration and deceleration phases, This represents the limiting deceleration amplitude.

5. The cooperative control method for multi-motor synchronization in a pitch system according to claim 4, characterized in that, Based on the acceleration / deceleration phase duration, the maximum deceleration amplitude, the planned total braking time, and the current moment during the braking process, a time-varying reference angular deceleration is generated piecewise to obtain a time-varying reference angular deceleration as the reference angular deceleration. This includes: generating the time-varying reference angular deceleration piecewise using the following formula, where the formula is: in, It is a time-varying reference angular deceleration that changes with time t.

6. The cooperative control method for multi-motor synchronization in a pitch system according to claim 1, characterized in that, Based on the feedforward braking torque and the feedback correction torque of each motor, the final command torque of each motor is determined, including: adding the feedforward braking torque and the feedback correction torque of each motor to obtain the final command torque of each motor.

7. A cooperative control system for multi-motor synchronization in a pitch system, said system being capable of implementing the method described in any one of claims 1-6, characterized in that, include: The data acquisition module is used to obtain the real-time values ​​of the quadrature-axis current and mechanical angular velocity of each motor. The drive chain dynamic characteristic identification module is used to identify the dynamic characteristics of the drive chain online by the real-time values ​​of the cross-axis current and the real-time values ​​of the mechanical angular velocity of each motor to obtain the dynamic parameter set of each drive chain. The dynamic parameter set of the drive chain includes the estimated value of the equivalent moment of inertia and the estimated value of the equivalent viscous friction coefficient. The cooperative braking target setting module is used to set the cooperative braking target based on the current angular velocity of each motor at the moment of triggering in response to the external emergency braking trigger signal being true, so as to obtain the reference angular deceleration. The feedforward compensation braking torque calculation module is used to calculate the feedforward compensation braking torque of each motor based on the current angular velocity, reference angular deceleration and dynamic parameter set of each drive chain at the moment of triggering. The synchronization error feedback correction module is used to perform synchronization error feedback correction on the real-time angular velocity of each motor during braking to obtain the feedback correction torque of each motor. The command torque determination module is used to determine the final command torque of each motor based on the feedforward braking torque and the feedback correction torque of each motor.

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